004 Datenverarbeitung; Informatik
Refine
Has Fulltext
- yes (362) (remove)
Year of publication
Document Type
- Monograph/Edited Volume (154)
- Doctoral Thesis (124)
- Postprint (49)
- Conference Proceeding (15)
- Article (8)
- Master's Thesis (8)
- Bachelor Thesis (1)
- Habilitation Thesis (1)
- Moving Images (1)
- Preprint (1)
Language
- English (286)
- German (74)
- Multiple languages (2)
Is part of the Bibliography
- yes (362) (remove)
Keywords
- machine learning (13)
- answer set programming (11)
- Hasso-Plattner-Institut (10)
- cloud computing (10)
- Cloud Computing (9)
- Hasso Plattner Institute (9)
- Forschungskolleg (8)
- Klausurtagung (8)
- Maschinelles Lernen (8)
- Service-oriented Systems Engineering (8)
- Forschungsprojekte (7)
- Future SOC Lab (7)
- In-Memory Technologie (7)
- Modellierung (7)
- Multicore Architekturen (7)
- maschinelles Lernen (7)
- openHPI (7)
- Datenintegration (6)
- E-Learning (6)
- Machine Learning (6)
- Prozessmodellierung (6)
- Smalltalk (6)
- Visualisierung (6)
- cloud (6)
- Antwortmengenprogrammierung (5)
- Geschäftsprozessmanagement (5)
- Identitätsmanagement (5)
- Informatik (5)
- Ph.D. retreat (5)
- Verifikation (5)
- cyber-physical systems (5)
- digital education (5)
- multicore architectures (5)
- quantitative analysis (5)
- research projects (5)
- service-oriented systems engineering (5)
- verification (5)
- visualization (5)
- Digitalisierung (4)
- In-Memory technology (4)
- Informatikdidaktik (4)
- Infrastruktur (4)
- MOOCs (4)
- Research School (4)
- Sicherheit (4)
- Virtualisierung (4)
- business process management (4)
- digitale Bildung (4)
- digitalization (4)
- higher education (4)
- identity management (4)
- nested graph conditions (4)
- privacy (4)
- probabilistic timed systems (4)
- qualitative Analyse (4)
- qualitative analysis (4)
- quantitative Analyse (4)
- research school (4)
- security (4)
- virtual machines (4)
- 3D visualization (3)
- Algorithmen (3)
- Answer Set Programming (3)
- Betriebssysteme (3)
- Bildverarbeitung (3)
- CityGML (3)
- Cloud (3)
- Computer Networks (3)
- Computernetzwerke (3)
- Datenbank (3)
- Datenschutz (3)
- Design Thinking (3)
- Graphtransformationen (3)
- IPv4 (3)
- IPv6 (3)
- Informationsextraktion (3)
- Infrastructure (3)
- Innovation (3)
- Internet Protocol (3)
- Künstliche Intelligenz (3)
- Laufzeitmodelle (3)
- Lively Kernel (3)
- MOOC (3)
- Model Synchronisation (3)
- Model Transformation (3)
- Model-Driven Engineering (3)
- Modeling (3)
- Network Politics (3)
- Netzpolitik (3)
- Online-Lernen (3)
- Onlinekurs (3)
- Ph.D. Retreat (3)
- Privacy (3)
- Process Modeling (3)
- Semantic Web (3)
- Tele-Lab (3)
- Tele-Teaching (3)
- Tripel-Graph-Grammatik (3)
- Virtuelle Maschinen (3)
- Vorhersage (3)
- Werkzeuge (3)
- artifical intelligence (3)
- blockchain (3)
- conference (3)
- data integration (3)
- data profiling (3)
- geospatial data (3)
- graph transformation (3)
- graph transformation systems (3)
- image processing (3)
- künstliche Intelligenz (3)
- model (3)
- modellgetriebene Entwicklung (3)
- models (3)
- non-photorealistic rendering (3)
- operating systems (3)
- outlier detection (3)
- process mining (3)
- programming (3)
- smart contracts (3)
- systems biology (3)
- tele-TASK (3)
- virtualization (3)
- virtuelle Maschinen (3)
- 3D-Geovisualisierung (2)
- 3D-Punktwolken (2)
- 3D-Stadtmodelle (2)
- 3D-Visualisierung (2)
- ACINQ (2)
- ASIC (2)
- AUTOSAR (2)
- Abstraktion (2)
- Algorithmic Game Theory (2)
- Algorithmische Spieltheorie (2)
- Algorithms (2)
- Anomalieerkennung (2)
- Assessment (2)
- Assoziationsregeln (2)
- Asynchrone Schaltung (2)
- Australian securities exchange (2)
- BCCC (2)
- BPM (2)
- BPMN (2)
- BTC (2)
- BitShares (2)
- Bitcoin Core (2)
- Blockchain Auth (2)
- Blockchain-Konsortium R3 (2)
- Blockkette (2)
- Blockstack (2)
- Blockstack ID (2)
- Blumix-Plattform (2)
- Blöcke (2)
- Bounded Model Checking (2)
- Byzantine Agreement (2)
- CSC (2)
- Classification (2)
- Cloud-Sicherheit (2)
- Cloud-Speicher (2)
- Code (2)
- Colored Coins (2)
- Computergrafik (2)
- Computersicherheit (2)
- DAO (2)
- DPoS (2)
- Data Integration (2)
- Data Modeling (2)
- Data Profiling (2)
- Datenanalyse (2)
- Datenaufbereitung (2)
- Datenbanken (2)
- Datenbanksysteme (2)
- Datenmodellierung (2)
- Datenqualität (2)
- Delegated Proof-of-Stake (2)
- Didaktik (2)
- Distributed Proof-of-Research (2)
- Duplikaterkennung (2)
- E-Wallet (2)
- ECDSA (2)
- EEG (2)
- Echtzeit (2)
- Echtzeit-Rendering (2)
- Eris (2)
- Ether (2)
- Ethereum (2)
- European Bioinformatics Institute (2)
- European Union (2)
- Europäische Union (2)
- Evolution (2)
- Exploration (2)
- FMC (2)
- Federated Byzantine Agreement (2)
- Fehlertoleranz (2)
- FollowMyVote (2)
- Fork (2)
- Formale Verifikation (2)
- GPU (2)
- Game Dynamics (2)
- Geodaten (2)
- Graphentransformationssysteme (2)
- Graphtransformationssysteme (2)
- Gridcoin (2)
- HCI (2)
- HPI Schul-Cloud (2)
- Hard Fork (2)
- Hashed Timelock Contracts (2)
- Hauptspeicherdatenbank (2)
- Hochschuldidaktik (2)
- ICA (2)
- IT-Infrastruktur (2)
- IT-infrastructure (2)
- Identität (2)
- In-Memory (2)
- Informatikstudium (2)
- Internet (2)
- Internet Service Provider (2)
- Internet der Dinge (2)
- Internet of Things (2)
- IoT (2)
- Japanese Blockchain Consortium (2)
- Japanisches Blockchain-Konsortium (2)
- Java (2)
- Kette (2)
- Klassifikation (2)
- Knowledge Representation and Reasoning (2)
- Kollaborationen (2)
- Konferenz (2)
- Konsensalgorithmus (2)
- Konsensprotokoll (2)
- Lightning Network (2)
- Link-Entdeckung (2)
- Live-Programmierung (2)
- Lock-Time-Parameter (2)
- MERLOT (2)
- Megamodell (2)
- Micropayment-Kanäle (2)
- Microsoft Azur (2)
- Middleware (2)
- Model Synchronization (2)
- Modell (2)
- Modellprüfung (2)
- Mustererkennung (2)
- NASDAQ (2)
- NameID (2)
- Namecoin (2)
- Navigation (2)
- Off-Chain-Transaktionen (2)
- Onename (2)
- Online Course (2)
- Online-Learning (2)
- Ontologie (2)
- OpenBazaar (2)
- Oracles (2)
- Orphan Block (2)
- P2P (2)
- Patterns (2)
- Peer-to-Peer Netz (2)
- Peercoin (2)
- PoB (2)
- PoS (2)
- PoW (2)
- Preis der Anarchie (2)
- Price of Anarchy (2)
- Privatsphäre (2)
- Process (2)
- Process Mining (2)
- Programmieren (2)
- Programmierung (2)
- Proof-of-Burn (2)
- Proof-of-Stake (2)
- Proof-of-Work (2)
- Prozess (2)
- Python (2)
- Ressourcenoptimierung (2)
- Ripple (2)
- SCP (2)
- SHA (2)
- SPV (2)
- STG decomposition (2)
- STG-Dekomposition (2)
- Schule (2)
- Schwierigkeitsgrad (2)
- Service-Oriented Architecture (2)
- Service-Orientierte Architekturen (2)
- Simplified Payment Verification (2)
- Skalierbarkeit der Blockchain (2)
- Slock.it (2)
- Soft Fork (2)
- Softwarearchitektur (2)
- Steemit (2)
- Stellar Consensus Protocol (2)
- Storj (2)
- Studie (2)
- SysML (2)
- Systemstruktur (2)
- Temporallogik (2)
- Texturen (2)
- The Bitfury Group (2)
- The DAO (2)
- Timed Automata (2)
- Transaktion (2)
- Two-Way-Peg (2)
- Unspent Transaction Output (2)
- User Experience (2)
- VM (2)
- Verhalten (2)
- Verlässlichkeit (2)
- Versionsverwaltung (2)
- Verträge (2)
- Virtual Reality (2)
- Watson IoT (2)
- Zielvorgabe (2)
- Zookos Dreieck (2)
- Zookos triangle (2)
- abstraction (2)
- adaptive Systeme (2)
- adaptive systems (2)
- algorithms (2)
- altchain (2)
- alternative chain (2)
- anomaly detection (2)
- atomic swap (2)
- batch processing (2)
- bidirectional payment channels (2)
- big data services (2)
- bitcoins (2)
- blockchain consortium (2)
- blockchain-übergreifend (2)
- blocks (2)
- blumix platform (2)
- bounded model checking (2)
- business processes (2)
- causal discovery (2)
- causal structure learning (2)
- chain (2)
- clustering (2)
- code (2)
- computer graphics (2)
- computer vision (2)
- confirmation period (2)
- consensus algorithm (2)
- consensus protocol (2)
- contest period (2)
- continuous integration (2)
- contracts (2)
- cross-chain (2)
- cyber-physische Systeme (2)
- data (2)
- data preparation (2)
- database systems (2)
- debugging (2)
- decentralized autonomous organization (2)
- deep learning (2)
- dependability (2)
- dezentrale autonome Organisation (2)
- didactics (2)
- difficulty (2)
- difficulty target (2)
- digital enlightenment (2)
- digital learning platform (2)
- digital sovereignty (2)
- digitale Aufklärung (2)
- digitale Lernplattform (2)
- digitale Souveränität (2)
- direct manipulation (2)
- doppelter Hashwert (2)
- double hashing (2)
- e-learning (2)
- education (2)
- fault tolerance (2)
- federated voting (2)
- functional dependencies (2)
- funktionale Abhängigkeiten (2)
- geovisualization (2)
- graph constraints (2)
- hashrate (2)
- human computer interaction (2)
- identity (2)
- in-memory technology (2)
- inclusion dependencies (2)
- incremental graph pattern matching (2)
- index selection (2)
- informatics (2)
- information extraction (2)
- innovation (2)
- intelligente Verträge (2)
- inter-chain (2)
- intrusion detection (2)
- k-inductive invariant checking (2)
- kausale Entdeckung (2)
- kausales Strukturlernen (2)
- kontinuierliche Integration (2)
- lebenslanges Lernen (2)
- ledger assets (2)
- lifelong learning (2)
- live programming (2)
- liveness (2)
- maschinelles Sehen (2)
- merged mining (2)
- merkle root (2)
- micropayment (2)
- micropayment channels (2)
- miner (2)
- mining (2)
- mining hardware (2)
- minting (2)
- mobile (2)
- mobile mapping (2)
- model checking (2)
- model transformation (2)
- model-driven engineering (2)
- modeling (2)
- navigation (2)
- nonce (2)
- off-chain transaction (2)
- peer-to-peer network (2)
- pegged sidechains (2)
- prediction (2)
- probabilistische gezeitete Systeme (2)
- probabilistische zeitgesteuerte Systeme (2)
- propositional satisfiability (2)
- quorum slices (2)
- real-time (2)
- real-time systems (2)
- rootstock (2)
- runtime models (2)
- scalability of blockchain (2)
- scarce tokens (2)
- schema discovery (2)
- search (2)
- self-sovereign identity (2)
- service-oriented systems (2)
- sidechain (2)
- simulation (2)
- smalltalk (2)
- social media (2)
- software engineering (2)
- solver (2)
- synchronization (2)
- systems of systems (2)
- textures (2)
- tiefes Lernen (2)
- timed automata (2)
- tools (2)
- transaction (2)
- triple graph grammars (2)
- typed attributed graphs (2)
- user experience (2)
- user interaction (2)
- verschachtelte Graphbedingungen (2)
- version control (2)
- virtual 3D city models (2)
- virtuelle 3D-Stadtmodelle (2)
- wearables (2)
- "Big Data"-Dienste (1)
- 'Peer To Peer' (1)
- 0-day (1)
- 3D Computer Grafik (1)
- 3D Computer Graphics (1)
- 3D Drucken (1)
- 3D Linsen (1)
- 3D Point Clouds (1)
- 3D Semiotik (1)
- 3D Visualisierung (1)
- 3D city model (1)
- 3D city models (1)
- 3D computer graphics (1)
- 3D geovisualisation (1)
- 3D geovisualization (1)
- 3D lenses (1)
- 3D point cloud (1)
- 3D point clouds (1)
- 3D portrayal (1)
- 3D printing (1)
- 3D semiotics (1)
- 3D-Punktwolke (1)
- 3D-Rendering (1)
- 3D-Stadtmodell (1)
- 3DCityDB (1)
- 3d city models (1)
- 47A52 (1)
- 65R20 (1)
- 65R32 (1)
- 78A46 (1)
- ADFS (1)
- APT (1)
- Abbrecherquote (1)
- Abhängigkeiten (1)
- Abstraktion von Geschäftsprozessmodellen (1)
- Accepting Grammars (1)
- Ackerschmalwand (1)
- Active Directory Federation Services (1)
- Active Evaluation (1)
- Advanced Persistent Threats (1)
- Adversarial Learning (1)
- Agile (1)
- Agilität (1)
- Aktive Evaluierung (1)
- Aktivitäten (1)
- Akzeptierende Grammatiken (1)
- Algorithmenablaufplanung (1)
- Algorithmenkonfiguration (1)
- Algorithmenselektion (1)
- Alignment (1)
- Ambiguity (1)
- Ambiguität (1)
- Analog-zu-Digital-Konvertierung (1)
- Analyse (1)
- Anfrageoptimierung (1)
- Anfragesprache (1)
- Angewandte Spieltheorie (1)
- Angriffe (1)
- Angriffserkennung (1)
- Anisotroper Kuwahara Filter (1)
- Anleitung (1)
- Antwortmengen Programmierung (1)
- Anwendungsvirtualisierung (1)
- Application Server (1)
- Applied Game Theory (1)
- Apriori (1)
- Arabidopsis thaliana (1)
- Architektur (1)
- Architekturadaptation (1)
- Archivanalyse (1)
- Artem Erkomaishvili (1)
- Artificial Intelligence (1)
- Arzt-Patient-Beziehung (1)
- Aspect-oriented Programming (1)
- Aspektorientierte Softwareentwicklung (1)
- Association Rule Mining (1)
- Asynchronous circuit (1)
- Attribut-Merge-Prozess (1)
- Attribute Merge Process (1)
- Attributsicherung (1)
- Aufzählung (1)
- Augmented Reality (1)
- Augmented reality (1)
- Ausbildung (1)
- Ausführung von Modellen (1)
- Ausführungssemantiken (1)
- Ausreissererkennung (1)
- Ausreißererkennung (1)
- Auswirkungen (1)
- Authentifizierung (1)
- Authorization (1)
- Autismus (1)
- Autorisierung (1)
- BCH (1)
- BCI (1)
- BSS (1)
- Bachelorstudierende der Informatik (1)
- Bahnwesen (1)
- Bank (1)
- Basic Service (1)
- Basic Storage Anbieter (1)
- Batchprozesse (1)
- Batchverarbeitung (1)
- Baumweite (1)
- Bayes'sche Netze (1)
- Bayesian networks (1)
- Bedingte Inklusionsabhängigkeiten (1)
- Bedrohungserkennung (1)
- Behavior (1)
- Behavior change (1)
- Behaviour Analysis (1)
- Benutzerinteraktion (1)
- Benutzeroberfläche (1)
- Berührungseingaben (1)
- Beschränkungen und Abhängigkeiten (1)
- Betrachtungsebenen (1)
- Beweistheorie (1)
- Bibliometrics (1)
- Big Data (1)
- Bilddatenanalyse (1)
- Bildung (1)
- Binäres Entscheidungsdiagramm (1)
- Bioacoustics (1)
- Bioakustik (1)
- Biocomputing (1)
- Bioelektrisches Signal (1)
- Bioinformatik (1)
- Biometrie (1)
- Bisimulation (1)
- Bitcoin (1)
- Blockchain (1)
- Blockchains (1)
- Blockheizkraftwerke (1)
- Boolean constraint solver (1)
- Bounded Backward Model Checking (1)
- Brain Computer Interface (1)
- Business Process Management (1)
- Business Process Models (1)
- CEP (1)
- CSCW (1)
- Cactus (1)
- Carrera Digital D132 (1)
- Case Management (1)
- Change Management (1)
- Choreographien (1)
- Citymodel (1)
- Cloud Datenzentren (1)
- Clusteranalyse (1)
- Clustering (1)
- Codierung (1)
- Common Spatial Pattern (1)
- Complementary Circuits (1)
- Compliance (1)
- Composition (1)
- Compound Values (1)
- Computation Tree Logic (1)
- Computational Complexity (1)
- Computational Hardness (1)
- Computational Photography (1)
- Computer Science (1)
- Computer Science Education (1)
- Computergestützes Training (1)
- Computing (1)
- Conceptual (1)
- Conditional Inclusion Dependency (1)
- Conformance Überprüfung (1)
- Constraint (1)
- Constraint Solving (1)
- Constraint-Programmierung (1)
- Constraints (1)
- Constructive solid geometry (1)
- Context-oriented Programming (1)
- Contracts (1)
- Controlled Derivations (1)
- Controller-Resynthese (1)
- Covariate Shift (1)
- Creative (1)
- Crime mapping (1)
- Cyber-Physical Systems (1)
- Cyber-Physical-Systeme (1)
- Cyber-Sicherheit (1)
- Cyber-physical-systems (1)
- Cyber-physikalische Systeme (1)
- DBMS (1)
- DDoS (1)
- DNA (1)
- DNA computing (1)
- DNS (1)
- DPLL (1)
- Data Dependency (1)
- Data Quality (1)
- Data Structure Optimization (1)
- Data Warehouse (1)
- Data-Mining (1)
- Data-Science (1)
- Database (1)
- Database Cost Model (1)
- Databases (1)
- Dateistruktur (1)
- Daten (1)
- Datenabhängigkeiten (1)
- Datenabhängigkeiten-Entdeckung (1)
- Datenbank-Kostenmodell (1)
- Datenextraktion (1)
- Datenflusskorrektheit (1)
- Datenkorrektheit (1)
- Datenmodelle (1)
- Datenobjekte (1)
- Datenreinigung (1)
- Datensatz (1)
- Datenschutz-sicherer Einsatz in der Schule (1)
- Datensicht (1)
- Datenstrukturoptimierung (1)
- Datensynthese (1)
- Datentransformation (1)
- Datenvertraulichkeit (1)
- Datenvisualisierung (1)
- Datenzustände (1)
- Deadline-Verbreitung (1)
- Debugging (1)
- Deduction (1)
- Deep Learning (1)
- Defining characteristics of physical computing (1)
- Dekubitus (1)
- Delphi study (1)
- Delphine (1)
- Dempster-Shafer-Theorie (1)
- Dempster–Shafer theory (1)
- Denkweise (1)
- Description Logics (1)
- Design-Forschung (1)
- Deskriptive Logik (1)
- Deurema Modellierungssprache (1)
- Diagonalisierung (1)
- Didaktik der Informatik (1)
- Didaktische Konzepte (1)
- Dienstkomposition (1)
- Dienstplattform (1)
- Differential Privacy (1)
- Differenz von Gauss Filtern (1)
- Digital Engineering (1)
- Digital Game Based Learning (1)
- Digitale Transformation (1)
- Digitalstrategie (1)
- Direkte Manipulation (1)
- Discrimination Networks (1)
- Distributed Computing (1)
- Distributed-Ledger-Technologie (DLT) (1)
- Diversität (1)
- Dolphins (1)
- Domänenspezifische Modellierung (1)
- Dreidimensionale Computergraphik (1)
- Dubletten (1)
- Duplicate Detection (1)
- Dynamic Programming (1)
- Dynamic Type System (1)
- Dynamische Programmierung (1)
- Dynamische Rekonfiguration (1)
- Dynamische Typ Systeme (1)
- EHR (1)
- EPA (1)
- Echtzeitanwendung (1)
- Echtzeitsysteme (1)
- Economics (1)
- Effizienz (1)
- Einbruchserkennung (1)
- Eingabegenauigkeit (1)
- Eingebettete Systeme (1)
- Eisenbahnnetz (1)
- Electronic and spintronic devices (1)
- Elektroencephalographie (1)
- Elektronische Patientenakte (1)
- Emotionen (1)
- Emotionsforschung (1)
- Empfehlungen (1)
- Endpunktsicherheit (1)
- Energieeffizienz (1)
- Energiesparen (1)
- Enterprise Search (1)
- Entscheidungsbäume (1)
- Entscheidungsfindung (1)
- Entscheidungsmanagement (1)
- Entscheidungsmodelle (1)
- Entwicklungswerkzeuge (1)
- Entwurf (1)
- Entwurfsmuster (1)
- Entwurfsmuster für SOA-Sicherheit (1)
- Entwurfsraumexploration (1)
- Equilibrium logic (1)
- Ereignisabstraktion (1)
- Ereignisse (1)
- Erfahrungsbericht (1)
- Erfüllbarkeit einer Formel der Aussagenlogik (1)
- Erfüllbarkeitsanalyse (1)
- Erfüllbarkeitsproblem (1)
- Erkennen von Meta-Daten (1)
- Erkennung von Metadaten (1)
- Error Estimation (1)
- Error-Detection Circuits (1)
- Erweiterte Realität (1)
- Escherichia-coli (1)
- Evaluation (1)
- Evidenztheorie (1)
- Evolution in MDE (1)
- Execution Semantics (1)
- Exponential Time Hypothesis (1)
- Exponentialzeit Hypothese (1)
- Extract-Transform-Load (ETL) (1)
- FIDO (1)
- FMC-QE (1)
- FOSS (1)
- FPGA (1)
- FRP (1)
- Fallmanagement (1)
- Fallstudie (1)
- Feature Combination (1)
- Feedback (1)
- Feedback Loop Modellierung (1)
- Feedback Loops (1)
- Fehlende Daten (1)
- Fehlererkennung (1)
- Fehlerinjektion (1)
- Fehlerkorrektur (1)
- Fehlerschätzung (1)
- Fehlersuche (1)
- Fehlvorstellung (1)
- Fernerkundung (1)
- Fertigung (1)
- Fintech (1)
- Flussgesteuerter Bilateraler Filter (1)
- Focus+Context Visualization (1)
- Fokus-&-Kontext Visualisierung (1)
- Formeln der quantifizierten Aussagenlogik (1)
- Fredholm complexes (1)
- Functional Lenses (1)
- Fundamental Modeling Concepts (1)
- Fußgängernavigation (1)
- GIS (1)
- GPU acceleration (1)
- GPU-Beschleunigung (1)
- Game-based learning (1)
- Gaussian process state-space models (1)
- Gaussian processes (1)
- Gauß-Prozess Zustandsraummodelle (1)
- Gauß-Prozesse (1)
- Gebäudemodelle (1)
- Gehirn-Computer-Schnittstelle (1)
- Geländemodelle (1)
- Generalisierung (1)
- Generalized Discrimination Networks (1)
- Geometrieerzeugung (1)
- Georgian chant (1)
- Georgische liturgische Gesänge (1)
- Geovisualisierung (1)
- German schools (1)
- Geschäftsanwendungen (1)
- Geschäftsprozessarchitekturen (1)
- Geschäftsprozesse (1)
- Geschäftsprozessmodelle (1)
- Gesetze (1)
- Gesichtsausdruck (1)
- Gesteuerte Ableitungen (1)
- Gewinnung benannter Entitäten (1)
- GitHub (1)
- Gleichheit (1)
- Globus (1)
- GraalVM (1)
- Grammar Systems (1)
- Grammatikalische Inferenz (1)
- Grammatiksysteme (1)
- Graph-Constraints (1)
- Graph-Mining (1)
- Graph-basierte Suche (1)
- Graph-basiertes Ranking (1)
- Graphableitung (1)
- Graphbedingungen (1)
- Graphdatenbanken (1)
- Graphfärbung (1)
- Graphreparatur (1)
- Graphtransformation (1)
- Grid (1)
- Grid Computing (1)
- Gruppierung von Prozessinstanzen (1)
- HDI (1)
- HENSHIN (1)
- HPI Forschung (1)
- HPI research (1)
- Hardware-Software-Co-Design (1)
- Hasserkennung (1)
- Hasso-Plattner-Institute (1)
- Hauptkomponentenanalyse (1)
- Hauptspeicher Technologie (1)
- Heterogenität (1)
- Heuristiken (1)
- High-Level Synthesis (1)
- Hochschullehre (1)
- Hochschulsystem (1)
- Homomorphe Verschlüsselung (1)
- Hyrise (1)
- Häkeln (1)
- I/O-effiziente Algorithmen (1)
- IBM 360 (1)
- ICT (1)
- ICT competencies (1)
- IDS (1)
- ISSEP (1)
- IT security (1)
- IT-Security (1)
- IT-Sicherheit (1)
- Ideation (1)
- Ideenfindung (1)
- Identity Management (1)
- Impact (1)
- Implementation in Organizations (1)
- Implementierung in Organisationen (1)
- In-Memory Database (1)
- In-Memory Datenbank (1)
- In-Memory-Datenbank (1)
- Index (1)
- Index Structures (1)
- Indexauswahl (1)
- Indexstrukturen (1)
- Individuen (1)
- Infinite State (1)
- Informatics (1)
- Informatics Education (1)
- Informatik-Studiengänge (1)
- Informatiksystem (1)
- Informatikunterricht (1)
- Informatikvoraussetzungen (1)
- Information Extraction (1)
- Information Systems (1)
- Information Transfer Rate (1)
- Informationssysteme (1)
- Informatische Kompetenzen (1)
- Inklusionsabhängigkeit (1)
- Inklusionsabhängigkeiten (1)
- Inkonsistenz (1)
- Inkrementelle Graphmustersuche (1)
- Innovationsmanagement (1)
- Innovationsmethode (1)
- Input Validation (1)
- Integration (1)
- Interactive Rendering (1)
- Interactive system (1)
- Interaktionsmodel (1)
- Interaktionsmodellierung (1)
- Interaktionstechniken (1)
- Interaktives Rendering (1)
- Interaktives System (1)
- Interdisciplinary Teams (1)
- Interface design (1)
- Internet Security (1)
- Internet-Sicherheit (1)
- Interpreter (1)
- Interval Timed Automata (1)
- Intuition (1)
- Invariant-Checking (1)
- Invarianten (1)
- Invariants (1)
- JCop (1)
- JSP (1)
- Java 2 Enterprise Edition (1)
- Java Virtual Machine (1)
- Karten (1)
- Kartografisches Design (1)
- Kausalität (1)
- Kern-PCA (1)
- Kernmethoden (1)
- Key Competencies (1)
- Klassifikator-Kalibrierung (1)
- Klassifizierung (1)
- Kommunikation (1)
- Kompetenz (1)
- Kompetenzen (1)
- Komplexität (1)
- Komplexität der Berechnung (1)
- Komplexitätsbewältigung (1)
- Komplexitätstheorie (1)
- Komposition (1)
- Konnektionskalkül (1)
- Konsensprotokolle (1)
- Konsistenzrestauration (1)
- Konzeptionell (1)
- Kreativität (1)
- Kundenverhalten (1)
- Kunstanalyse (1)
- Kybernetik (1)
- LEGO Mindstorms EV3 (1)
- LOD (1)
- Landmarken (1)
- Laser Cutten (1)
- Laserscanning (1)
- Lastverteilung (1)
- Laufzeitanalyse (1)
- Laufzeitverhalten (1)
- Leadership (1)
- Learning Analytics (1)
- Lebendigkeit (1)
- Lebenslanges Lernen (1)
- Lefschetz number (1)
- Leftmost Derivations (1)
- Lehrer (1)
- Leistungsmodelle von virtuellen Maschinen (1)
- Leistungsvorhersage (1)
- Lernsoftware (1)
- LiDAR (1)
- Link Discovery (1)
- Linked Data (1)
- Linked Open Data (1)
- Linksableitungen (1)
- Live-Migration (1)
- Liveness (1)
- Logic Programming (1)
- Logics (1)
- Logiksynthese (1)
- Lower Bounds (1)
- Lösungsraum (1)
- MDE Ansatz (1)
- MDE settings (1)
- MEG (1)
- Machine-Learning (1)
- Machinelles Lernen (1)
- Magnetoencephalographie (1)
- Malware (1)
- Management (1)
- Marktübersicht (1)
- Maschinen (1)
- Matrizen-Eigenwertaufgabe (1)
- Measurement (1)
- Megamodel (1)
- Megamodels (1)
- Mehr-Faktor-Authentifizierung (1)
- Mehrfamilienhäuser (1)
- Mehrkernsysteme (1)
- Mehrklassen-Klassifikation (1)
- Mensch-Computer-Interaktion (1)
- Messung (1)
- Metacrate (1)
- Metadata Discovery (1)
- Metadaten (1)
- Metadatenentdeckung (1)
- Metadatenqualität (1)
- Metamodell (1)
- Metaverse (1)
- Migration (1)
- Mindset (1)
- Mischmodelle (1)
- Mischung <Signalverarbeitung> (1)
- Mobil (1)
- Mobile Application Development (1)
- Mobile Mapping (1)
- Mobile-Mapping (1)
- Mobiles Lernen (1)
- Mobilgeräte (1)
- Model Based Engineering (1)
- Model Checking (1)
- Model Consistency (1)
- Model Driven Architecture (1)
- Model Execution (1)
- Model Management (1)
- Model-driven SOA Security (1)
- Modeling Languages (1)
- Modell Management (1)
- Modell-driven Security (1)
- Modell-getriebene SOA-Sicherheit (1)
- Modell-getriebene Sicherheit (1)
- Modell-getriebene Softwareentwicklung (1)
- Modellbasiert (1)
- Modelle mit mehreren Versionen (1)
- Modellerzeugung (1)
- Modellgetrieben (1)
- Modellgetriebene Architektur (1)
- Modellgetriebene Entwicklung (1)
- Modellgetriebene Softwareentwicklung (1)
- Modellierungssprachen (1)
- Modellkonsistenz (1)
- Modellreparatur (1)
- Modelltransformation (1)
- Modelltransformationen (1)
- Models at Runtime (1)
- Molekulare Bioinformatik (1)
- Monitoring (1)
- Morphic (1)
- Multi Task Learning (1)
- Multi-Class (1)
- Multi-Instanzen (1)
- Multi-Task-Lernen (1)
- Multicore architectures (1)
- Multidisciplinary Teams (1)
- Multiprocessor (1)
- Multiprozessor (1)
- Muster (1)
- Musterabgleich (1)
- N-of-1 trial (1)
- NUI (1)
- Nash Equilibrium (1)
- Nebenläufigkeit (1)
- Nested Graph Conditions (1)
- Network Creation Game (1)
- Netzneutralität (1)
- Netzwerke (1)
- Netzwerkprotokolle (1)
- Neuronales Netz (1)
- New On-Line Error-Detection Methode (1)
- Newspeak (1)
- Next Generation Network (1)
- Nicht-photorealistisches Rendering (1)
- Nichtfotorealistische Bildsynthese (1)
- Non-photorealistic Rendering (1)
- Nutzerinteraktion (1)
- Nutzungsinteresse (1)
- OAuth (1)
- Object Constraint Programming (1)
- Object-Oriented Programming (1)
- Objects (1)
- Objekt-Constraint Programmierung (1)
- Objekt-Orientiertes Programmieren (1)
- Objekt-orientiertes Programmieren mit Constraints (1)
- Objekte (1)
- Objektive Schwierigkeit (1)
- Objektlebenszyklus-Synchronisation (1)
- Omega (1)
- Online Learning Environments (1)
- Onlinelehre (1)
- Ontologies (1)
- Ontology (1)
- Open Source (1)
- OpenID Connect (1)
- Optimierungen (1)
- Optimierungsproblem (1)
- Optimization (1)
- Organisationsveränderung (1)
- PAVM (1)
- PRISM Modell-Checker (1)
- PRISM model checker (1)
- PTCTL (1)
- Parallel Programming (1)
- Parallele Datenverarbeitung (1)
- Paralleles Rechnen (1)
- Parallelrechner (1)
- Parameterized Complexity (1)
- Parametrisierte Komplexität (1)
- Parsing (1)
- Patientenermündigung (1)
- Pattern Matching (1)
- Pattern Recognition (1)
- Peer-to-Peer-Netz ; GRID computing ; Zuverlässigkeit ; Web Services ; Betriebsmittelverwaltung ; Migration (1)
- Performance Prediction (1)
- Personal Data (1)
- Petri net Mapping (1)
- Petri net mapping (1)
- Petrinetz (1)
- Planing (1)
- Plattform-Ökosysteme (1)
- Platzierung (1)
- Policy Enforcement (1)
- Polymerase Chain Reaction Experiment (1)
- Posenabschätzung (1)
- PostGIS (1)
- Pre-RS Traceability (1)
- Prediction Game (1)
- Predictive Models (1)
- Problem Solving (1)
- Probleme in der Studie (1)
- Problemlösen (1)
- Problemlösung (1)
- Process Enactment (1)
- Process Modelling (1)
- Process modeling (1)
- Professoren (1)
- Prognosen (1)
- Programmierabstraktionen (1)
- Programmiererlebnis (1)
- Programmierkonzepte (1)
- Programmierwerkzeuge (1)
- Programming Languages (1)
- Proof Theory (1)
- Propagation von Aktivitätsinstanzzuständen (1)
- Prototyping (1)
- Prozess Verbesserung (1)
- Prozess- und Datenintegration (1)
- Prozessarchitektur (1)
- Prozessausführung (1)
- Prozessautomatisierung (1)
- Prozesse (1)
- Prozesserhebung (1)
- Prozessinstanz (1)
- Prozessmodell (1)
- Prozessmodelle (1)
- Prozessmodellsuche (1)
- Prozessoren (1)
- Prozessverfeinerung (1)
- Prädiktionsspiel (1)
- Präferenzen (1)
- Präsentation (1)
- Psychotherapie (1)
- Quanten-Computing (1)
- Quantified Boolean Formula (QBF) (1)
- Quantitative Analysen (1)
- Quantitative Modeling (1)
- Quantitative Modellierung (1)
- Query (1)
- Query-Optimierung (1)
- Queuing Theory (1)
- RDF (1)
- RL (1)
- RT_PREEMT patch (1)
- RT_PREEMT-Patch (1)
- Real-Time Rendering (1)
- Realzeitsysteme (1)
- Reconfigurable (1)
- Regressionstests (1)
- Rekonfiguration (1)
- Rendering (1)
- Reparatur (1)
- Research Projects (1)
- Ressourcenmanagement (1)
- Reverse Engineering (1)
- Ruby (1)
- Runtime Binding (1)
- Runtime-monitoring (1)
- SAT (1)
- SCED (1)
- SIEM (1)
- SMT (1)
- SOA (1)
- SOA Security (1)
- SOA Security Pattern (1)
- SOA Sicherheit (1)
- SQL (1)
- SSO (1)
- SWIRL (1)
- Sammlungsdatentypen (1)
- Sample Selection Bias (1)
- Satisfiability (1)
- Savanne (1)
- Scene graph systems (1)
- Schelling Process (1)
- Schelling Prozess (1)
- Schelling Segregation (1)
- Schema-Entdeckung (1)
- Schemaentdeckung (1)
- Schlüsselkompetenzen (1)
- Schlüsselentdeckung (1)
- Schlüsselkompetenzen (1)
- Schriftartgestaltung (1)
- Schriftrendering (1)
- Scrollytelling (1)
- Search Algorithms (1)
- Second Life (1)
- Secure Digital Identities (1)
- Secure Enterprise SOA (1)
- Security Modelling (1)
- Segmentierung (1)
- Selbst-Adaptive Software (1)
- Selektionsbias (1)
- Self-Adaptive Software (1)
- Self-Checking Circuits (1)
- Self-Regulated Learning (1)
- Semantic Search (1)
- Semantik Web (1)
- Semantische Suche (1)
- Semiconductors (1)
- Sequenzeigenschaften (1)
- Sequenzen von s/t-Pattern (1)
- Serialisierung (1)
- Service Creation (1)
- Service Delivery Platform (1)
- Service Provider (1)
- Service convergence (1)
- Service-oriented Architectures (1)
- Service-orientierte Systeme (1)
- Service-orientierte Systme (1)
- Shader (1)
- Sichere Digitale Identitäten (1)
- Sicherheitsanalyse (1)
- Sicherheitsmodellierung (1)
- Signal Processing (1)
- Signalflankengraph (SFG oder STG) (1)
- Signalquellentrennung (1)
- Signaltrennung (1)
- Similarity Measures (1)
- Similarity Search (1)
- Simulation (1)
- Simultane Diagonalisierung (1)
- Single Sign On (1)
- Single Trial Analysis (1)
- Single-Sign-On (1)
- Situationsbewusstsein (1)
- Skelettberechnung (1)
- Skript-Entwicklungsumgebungen (1)
- Skriptsprachen (1)
- SoaML (1)
- Software (1)
- Software Engineering (1)
- Software architecture (1)
- Software-Evolution (1)
- Software-Testen (1)
- Software/Hardware Co-Design (1)
- Softwareanalyse (1)
- Softwareentwicklung (1)
- Softwareproduktlinien (1)
- Softwaretechnik (1)
- Softwaretests (1)
- Softwarevisualisierung (1)
- Softwarewartung (1)
- Solution Space (1)
- Soziale Medien (1)
- Sozialen Medien (1)
- Spaltenlayout (1)
- Spam (1)
- Spam Filtering (1)
- Spam-Erkennung (1)
- Spam-Filter (1)
- Spam-Filtering (1)
- Spatio-Spectral Filter (1)
- Spawning (1)
- Speicheroptimierungen (1)
- Spezifikation von gezeiteten Graph Transformationen (1)
- Spieldynamik (1)
- Spieldynamiken (1)
- Sprachdesign (1)
- Sprachlernen im Limes (1)
- Sprachspezifikation (1)
- Squeak (1)
- Squeak/Smalltalk (1)
- Stadtmodell (1)
- Standardisierung (1)
- Standards (1)
- Statistical Tests (1)
- Statistikprogramm R (1)
- Statistische Tests (1)
- Stilisierung (1)
- Structuring (1)
- Strukturierung (1)
- Studentenerwartungen (1)
- Studentenhaltungen (1)
- Studentenjobs (1)
- Studienabbrecher (1)
- Studiendauer (1)
- Suche (1)
- Suchtberatung und -therapie (1)
- Suchverfahren (1)
- Synchronisation (1)
- Synonyme (1)
- Synthese (1)
- System Biologie (1)
- System of Systems (1)
- System structure (1)
- Systematics (1)
- Systembiologie (1)
- Systeme von Systemen (1)
- Systementwurf (1)
- Systems of Systems (1)
- Systemsoftware (1)
- Szenengraph (1)
- TPTP (1)
- Tableaumethode (1)
- Taxonomy (1)
- Telekommunikation (1)
- Telemedizin (1)
- Temporal Logic (1)
- Temporäre Anbindung (1)
- Terminologische Logik (1)
- Test (1)
- Testen (1)
- Testergebnisse (1)
- Testpriorisierungs (1)
- Texterkennung (1)
- Textklassifikation (1)
- Theoretische Informatik (1)
- Theoretischen Vorlesungen (1)
- Threshold Cryptography (1)
- Time Augmented Petri Nets (1)
- Tool (1)
- Tools (1)
- Traceability (1)
- Tracking (1)
- Trajektorien (1)
- Transaktionen (1)
- Transformation (1)
- Transformationsebene (1)
- Transformationssequenzen (1)
- Travis CI (1)
- Treewidth (1)
- Tripel-Graph-Grammatiken (1)
- Triple Graph Grammar (1)
- Triple Graph Grammars (1)
- Triple-Graph-Grammatiken (1)
- Trust Management (1)
- UX (1)
- Unabhängige Komponentenanalyse (1)
- Unbegrenzter Zustandsraum (1)
- Universität Bagdad (1)
- Universität Potsdam (1)
- Universitätseinstellungen (1)
- Untere Schranken (1)
- Unterricht mit digitalen Medien (1)
- Unveränderlichkeit (1)
- Unvollständigkeit (1)
- Usage Interest (1)
- VM Integration (1)
- VUCA-World (1)
- Verbindungsnetzwerke (1)
- Verbundwerte (1)
- Verhaltensabstraktion (1)
- Verhaltensanalyse (1)
- Verhaltensbewahrung (1)
- Verhaltensverfeinerung (1)
- Verhaltensänderung (1)
- Verhaltensäquivalenz (1)
- Verification (1)
- Verletzung Auflösung (1)
- Verletzung Erklärung (1)
- Versionierung (1)
- Verteiltes Rechnen (1)
- Verteilungsalgorithmen (1)
- Verteilungsalgorithmus (1)
- Verteilungsunterschied (1)
- Vertrauen (1)
- Verwaltung von Rechenzentren (1)
- Verzögerungs-Verbreitung (1)
- Veränderungsanalyse (1)
- Violation Explanation (1)
- Violation Resolution (1)
- Virtual Desktop Infrastructure (1)
- Virtual Machines (1)
- Virtual machines (1)
- Virtuelle Maschine (1)
- Virtuelle Realität (1)
- Virtuelles 3D Stadtmodell (1)
- Visualisierungskonzept-Exploration (1)
- Visualization (1)
- Vorhersagemodelle (1)
- Wahrnehmung (1)
- Wahrnehmung von Arousal (1)
- Wahrnehmungsunterschiede (1)
- Warteschlangentheorie (1)
- Wartung von Graphdatenbanksichten (1)
- Wearable (1)
- Web Services (1)
- Web Sites (1)
- Web applications (1)
- Web of Data (1)
- Web-Anwendungen (1)
- Web-Based Rendering (1)
- Webbasiertes Rendering (1)
- Webseite (1)
- Well-structuredness (1)
- Werkzeugbau (1)
- Wertschöpfungskooperation (1)
- Wicked Problems (1)
- Wikipedia (1)
- Wirtschaftsinformatik (1)
- Wissensrepräsentation und -verarbeitung (1)
- Wissensrepräsentation und Schlussfolgerung (1)
- Wohlstrukturiertheit (1)
- Wolke (1)
- Workflow (1)
- Wüstenbildung (1)
- YouTube (1)
- ZQSA (1)
- ZQSAT (1)
- Zeitbehaftete Petri Netze (1)
- Zero-Suppressed Binary Decision Diagram (ZDD) (1)
- Zugriffskontrolle (1)
- Zuverlässigkeitsanalyse (1)
- access control (1)
- action language (1)
- activity instance state propagation (1)
- adaptiv (1)
- adaptive (1)
- addiction care (1)
- adoption (1)
- advanced persistent threat (1)
- advanced threats (1)
- aerosol size distribution (1)
- agil (1)
- algorithm (1)
- algorithm configuration (1)
- algorithm schedules (1)
- algorithm scheduling (1)
- algorithm selection (1)
- analog-to-digital conversion (1)
- analysis (1)
- animated PCA (1)
- animierte PCA (1)
- anisotropic Kuwahara filter (1)
- answer (1)
- answer set (1)
- anxiety (1)
- app (1)
- application virtualization (1)
- approximate joint diagonalization (1)
- apriori (1)
- apt (1)
- architectural adaptation (1)
- architecture (1)
- archive analysis (1)
- argument mining (1)
- argumentation structure (1)
- arithmethische Prozeduren (1)
- arithmetic procedures (1)
- arousal perception (1)
- art analysis (1)
- artificial intelligence (1)
- asset management (1)
- association rule mining (1)
- asynchronous circuit (1)
- attribute assurance (1)
- augmented reality (1)
- ausführbare Semantiken (1)
- authentication (1)
- authorship attribution (1)
- automatic theorem prover (1)
- automatisierter Theorembeweiser (1)
- automotive electronics (1)
- autonomous (1)
- balance analysis (1)
- bank (1)
- basic cloud storage services (1)
- behavior preservation (1)
- behavioral abstraction (1)
- behavioral equivalenc (1)
- behavioral refinement (1)
- behavioral specification (1)
- behaviour (1)
- behaviourally correct learning (1)
- benutzergenerierte Inhalte (1)
- beschreibende Feldstudie (1)
- bibliometric analysis (1)
- bidirectional optimality theory (1)
- bild (1)
- bildbasiertes Rendering (1)
- bio-computing (1)
- bioinformatics (1)
- biological network (1)
- biological network model (1)
- biological networks (1)
- biometrics (1)
- bisimulation (1)
- bitcoin (1)
- blind source separation (1)
- bounded backward model checking (1)
- bpm (1)
- building models (1)
- business informatics (1)
- business process architecture (1)
- business process architectures (1)
- business process model abstraction (1)
- business process modeling (1)
- bystander (1)
- cartographic design (1)
- case study (1)
- categories (1)
- causal AI (1)
- causal reasoning (1)
- causality (1)
- change detection (1)
- change management (1)
- changing the study field (1)
- changing the university (1)
- choreographies (1)
- circuits (1)
- citation analysis (1)
- classes of logic programs (1)
- classification (1)
- classifier calibration (1)
- clause elimination (1)
- cleansing (1)
- cloud datacenter (1)
- cloud security (1)
- cloud storage (1)
- cluster-analysis (1)
- co-citation analysis (1)
- co-occurrence analysis (1)
- code generation (1)
- cogeneration units (1)
- coherence-enhancing filtering (1)
- collaboration (1)
- collaborations (1)
- collection types (1)
- communication (1)
- competencies (1)
- complex optimization (1)
- complexity (1)
- composite service (1)
- compositional analysis (1)
- computational biology (1)
- computational ethnomusicology (1)
- computational methods (1)
- computational photography (1)
- computational thinking (1)
- computer science (1)
- computer science education (1)
- computer science education (CSE) (1)
- computer security (1)
- computer-aided design (1)
- computer-mediated therapy (1)
- computergestützte Methoden (1)
- computergestützte Musikethnologie (1)
- computervermittelte Therapie (1)
- computing (1)
- confidentiality (1)
- confluence (1)
- conformance analysis (1)
- conformance checking (1)
- connection calculus (1)
- consensus protocols (1)
- consistency (1)
- consistency restoration (1)
- consistent learning (1)
- constraint (1)
- constraint programming (1)
- constraints (1)
- consumer behavior (1)
- continuous testing (1)
- control resynthesis (1)
- controlled experiment (1)
- convolutional neural networks (1)
- corpus study (1)
- couple reaction (1)
- coupling relationship (1)
- course timetabling (1)
- crochet (1)
- cultural heritage (1)
- cyber-physikalische Systeme (1)
- cyberbullying (1)
- cybersecurity (1)
- data center management (1)
- data analytics (1)
- data center management (1)
- data correctness checking (1)
- data dependencies (1)
- data extraction (1)
- data flow correctness (1)
- data in business processes (1)
- data mining (1)
- data modeling (1)
- data models (1)
- data objects (1)
- data quality (1)
- data science (1)
- data security (1)
- data set (1)
- data states (1)
- data synthesis (1)
- data view (1)
- data visualization (1)
- data wrangling (1)
- data-driven (1)
- database (1)
- database optimization (1)
- database technology (1)
- datengetrieben (1)
- dbms (1)
- deadline propagation (1)
- decentral identities (1)
- decision management (1)
- decision mining (1)
- decision models (1)
- decision trees (1)
- decubitus (1)
- deduplication (1)
- deep Gaussian processes (1)
- deferred choice (1)
- definiteness (1)
- delay propagation (1)
- demografische Informationen (1)
- demographic information (1)
- dependable computing (1)
- dependencies (1)
- dependency discovery (1)
- depression (1)
- depressive symptoms (1)
- desertification (1)
- design (1)
- design research (1)
- design space exploration (1)
- design thinking (1)
- deurema modeling language (1)
- development tools (1)
- dezentrale Identitäten (1)
- diagnosis (1)
- difference of Gaussians (1)
- differential gene expression (1)
- differential privacy (1)
- diffusion (1)
- digital health (1)
- digital interventions (1)
- digital picture archive (1)
- digital strategy (1)
- digital transformation (1)
- digital unterstützter Unterricht (1)
- digital whiteboard (1)
- digitale Hochschullehre (1)
- digitale Infrastruktur für den Schulunterricht (1)
- digitales Bildarchiv (1)
- digitales Whiteboard (1)
- digitally-enabled pedagogies (1)
- dimensional (1)
- direkte Manipulation (1)
- discrete-event model (1)
- discrimination networks (1)
- diskretes Ereignismodell (1)
- distributed computation (1)
- distributed performance monitoring (1)
- distributed systems (1)
- distribution algorithm (1)
- doctor-patient relationship (1)
- domain-specific modeling (1)
- dropout (1)
- duplicate detection (1)
- dynamic (1)
- dynamic typing (1)
- dynamic classification (1)
- dynamic consolidation (1)
- dynamic programming languages (1)
- dynamic reconfiguration (1)
- dynamic systems (1)
- dynamisch (1)
- dynamische Klassifikation (1)
- dynamische Programmiersprachen (1)
- dynamische Sprachen (1)
- dynamische Systeme (1)
- dynamische Umsortierung (1)
- e-Learning (1)
- educational systems (1)
- educational timetabling (1)
- efficiency (1)
- eindeutig (1)
- eingebettete Systeme (1)
- electrical muscle stimulation (1)
- electronic health record (1)
- electronic tool integration (1)
- elektrische Muskelstimulation (1)
- elliptic complexes (1)
- email spam detection (1)
- embedded systems (1)
- embedded-systems (1)
- emotion (1)
- emotion representation (1)
- emotion research (1)
- empathy (1)
- endpoint security (1)
- energy efficiency (1)
- energy savings (1)
- enterprise search (1)
- entity alignment (1)
- entity resolution (1)
- enumeration (1)
- epistemic logic programs (1)
- epistemic specifications (1)
- equality (1)
- erfahrbare Medien (1)
- error correction (1)
- error detection (1)
- erzeugende gegnerische Netzwerke (1)
- evaluation (1)
- event abstraction (1)
- events (1)
- evidence theory (1)
- evolution (1)
- evolution in MDE (1)
- evolving systems (1)
- executable semantics (1)
- experience (1)
- experience report (1)
- explicit negation (1)
- exploration (1)
- exploratives Programmieren (1)
- exploratory programming (1)
- extend (1)
- external memory algorithms (1)
- fMRI (1)
- face tracking (1)
- facial expression (1)
- fatty acid amide hydrolase (1)
- fault injection (1)
- feedback loop modeling (1)
- feedback loops (1)
- fehlende Daten (1)
- file structure (1)
- flow-based bilateral filter (1)
- font engineering (1)
- font rendering (1)
- forecasts (1)
- formal framework (1)
- formal semantics (1)
- formal verification (1)
- formal verification methods (1)
- formale Verifikation (1)
- formales Framework (1)
- formalism (1)
- fortschrittliche Angriffe (1)
- freie Daten (1)
- freie Software (1)
- functional dependency (1)
- functional lenses (1)
- functional programming (1)
- funktionale Abhängigkeit (1)
- funktionale Programmierung (1)
- future SOC lab (1)
- ganzheitlich (1)
- ganzzahlige lineare Optimierung (1)
- gefaltete neuronale Netze (1)
- gemischte Daten (1)
- gender (1)
- gene expression matrix (1)
- general education in computer science (1)
- generalization (1)
- generalized discrimination networks (1)
- generative adversarial networks (1)
- genome annotation (1)
- geometry generation (1)
- geovirtual environments (1)
- geovirtuelle Umgebungen (1)
- geschichtsbewusste Laufzeit-Modelle (1)
- gesture (1)
- getypte Attributierte Graphen (1)
- global constraints (1)
- global model management (1)
- globale Constraints (1)
- globales Modellmanagement (1)
- grammar inference (1)
- grammars (1)
- graph clustering (1)
- graph databases (1)
- graph inference (1)
- graph mining (1)
- graph queries (1)
- graph repair (1)
- graph transformations (1)
- graph-based ranking (1)
- graph-transformations (1)
- hardware-software-codesign (1)
- hate speech detection (1)
- heterogeneous computing (1)
- heterogeneous tissue (1)
- heterogenes Rechnen (1)
- heuristics (1)
- history-aware runtime models (1)
- holistic (1)
- homogeneous cell population (1)
- homomorphic encryption (1)
- human-centered (1)
- hybrid graph-transformation-systems (1)
- hybrid systems (1)
- hybride Graph-Transformations-Systeme (1)
- hyrise (1)
- image (1)
- image data analysis (1)
- image stylization (1)
- image-based rendering (1)
- imdb (1)
- immediacy (1)
- immutable values (1)
- in-memory (1)
- in-memory database (1)
- inclusion dependency (1)
- incompleteness (1)
- inconsistency (1)
- incremental graph query evaluation (1)
- incumbent (1)
- independent component analysis (1)
- index (1)
- individual effects (1)
- individuals (1)
- inductive invariant checking (1)
- induktives Invariant Checking (1)
- inference (1)
- informal and formal learning (1)
- informatische Allgemeinbildung (1)
- infrastructure (1)
- inkrementelle Ausführung von Graphanfragen (1)
- inkrementelles Graph Pattern Matching (1)
- innovation capabilities (1)
- innovation management (1)
- input accuracy (1)
- integer linear programming (1)
- integral equation (1)
- integrated development environments (1)
- integrierte Entwicklungsumgebungen (1)
- interaction (1)
- interaction modeling (1)
- interaction techniques (1)
- interactive media (1)
- interactive simulation (1)
- interactive technologies (1)
- interaktive Medien (1)
- interconnect (1)
- interdisziplinäre Teams (1)
- interface (1)
- interpreters (1)
- interval probabilistic timed systems (1)
- interval probabilistische zeitgesteuerte Systeme (1)
- interval timed automata (1)
- intuition (1)
- intuitive Benutzeroberflächen (1)
- intuitive interfaces (1)
- invariant checking (1)
- inverse ill-posed problem (1)
- inverse scattering (1)
- iterative regularization (1)
- job shop scheduling (1)
- juridical recording (1)
- k-Induktion (1)
- k-induction (1)
- k-inductive invariants (1)
- k-induktive Invarianten (1)
- k-induktive Invariantenprüfung (1)
- k-induktives Invariant-Checking (1)
- kausale KI (1)
- kausale Schlussfolgerung (1)
- kernel PCA (1)
- kernel methods (1)
- key competences in physical computing (1)
- key competencies (1)
- key discovery (1)
- knowledge discovery (1)
- kompositionale Analyse (1)
- konsistentes Lernen (1)
- kontinuierliches Testen (1)
- kontrolliertes Experiment (1)
- konvergente Dienste (1)
- kulturelles Erbe (1)
- landmarks (1)
- language design (1)
- language learning in the limit (1)
- language specification (1)
- laser remote sensing (1)
- laserscanning (1)
- law (1)
- leadership (1)
- leanCoP (1)
- lebenszentriert (1)
- left recursion (1)
- level-replacement systems (1)
- life-centered (1)
- linear code (1)
- linear programming problem (1)
- linearer Code (1)
- link discovery (1)
- live migration (1)
- lively kernel (1)
- load balancing (1)
- location-based (1)
- logic (1)
- logic programming (1)
- logic synthesis (1)
- logical signaling networks (1)
- logische Ergänzung (1)
- logische Programmierung (1)
- logische Signalnetzwerke (1)
- longitudinal (1)
- loop formulas (1)
- machines (1)
- main memory computing (1)
- malware detection (1)
- management (1)
- manufacturing (1)
- many-core (1)
- map reduce (1)
- map/reduce (1)
- maps (1)
- market study (1)
- maschinelle Verarbeitung natürlicher Sprache (1)
- maschninelles Lernen (1)
- medical (1)
- medical documentation (1)
- medizinisch (1)
- medizinische Dokumentation (1)
- mehrdimensionale Belangtrennung (1)
- mehrsprachige Ausführungsumgebungen (1)
- memory (1)
- memory optimization (1)
- menschenzentriert (1)
- meta model (1)
- meta-programming (1)
- metabolic network (1)
- metabolite profile (1)
- metacrate (1)
- metadata (1)
- metadata detection (1)
- metadata discovery (1)
- metadata quality (1)
- method comparision (1)
- metric temporal logic (1)
- metric termporal graph logic (1)
- metrisch temporale Graph Logic (1)
- metrische Temporallogik (1)
- microcredential (1)
- microdissection (1)
- middleware (1)
- misconception (1)
- missing data (1)
- mixed data (1)
- mixture models (1)
- mmdb (1)
- mobile application (1)
- mobile devices (1)
- mobile learning (1)
- mobile technologies and apps (1)
- model generation (1)
- model repair (1)
- model-based (1)
- model-based prototyping (1)
- model-driven (1)
- model-driven architecture (1)
- model-driven software engineering (1)
- modellgetriebene Softwaretechnik (1)
- modelling (1)
- molecular network (1)
- molecular networks (1)
- molekulare Netzwerke (1)
- monetary incentive delay task (1)
- monitoring (1)
- morphic (1)
- multi core data processing (1)
- multi factor authentication (1)
- multi-class classification (1)
- multi-core (1)
- multi-dimensional separation of concerns (1)
- multi-instances (1)
- multi-version models (1)
- multi-family residential buildings (1)
- multidisziplinäre Teams (1)
- musical scales (1)
- musikalische Tonleitern (1)
- mutual information (1)
- named entity mining (1)
- natural language processing (1)
- nested application conditions (1)
- nested expressions (1)
- network protocols (1)
- networks-on-chip (1)
- neue Online-Fehlererkennungsmethode (1)
- neural networks (1)
- news media (1)
- nicht-parametrische bedingte Unabhängigkeitstests (1)
- nichtlineare ICA (1)
- nichtlineare PCA (NLPCA) (1)
- nichtlineare Projektionen (1)
- non-monotonic reasoning (1)
- non-parametric conditional independence testing (1)
- nonlinear ICA (1)
- nonlinear PCA (NLPCA) (1)
- nonlinear projections (1)
- novelty detection (1)
- nvm (1)
- object life cycle synchronization (1)
- object-constraint programming (1)
- object-oriented programming (1)
- objective difficulty (1)
- objektorientiertes Programmieren (1)
- omega (1)
- on-chip (1)
- online course (1)
- online course creation (1)
- online course design (1)
- online-learning (1)
- open source (1)
- open source software (1)
- optical character recognition (1)
- optimizations (1)
- oracles (1)
- order dependencies (1)
- organisational evolution (1)
- organizational change (1)
- orts-basiert (1)
- overcomplete ICA (1)
- packrat parsing (1)
- paper prototyping (1)
- parallel (1)
- parallel and sequential independence (1)
- parallel computing (1)
- parallel execution (1)
- parallel processing (1)
- parallel solving (1)
- parallele Verarbeitung (1)
- parallele und Sequentielle Unabhängigkeit (1)
- paralleles Lösen (1)
- paralleles Rechnen (1)
- parsing (1)
- parsing expression grammars (1)
- partial application conditions (1)
- partial correlation (1)
- partial replication (1)
- partielle Anwendungsbedingungen (1)
- partielle Replikation (1)
- pathways (1)
- patient empowerment (1)
- pattern recognition (1)
- pedestrian navigation (1)
- perception (1)
- perception differences (1)
- performance models of virtual machines (1)
- periodic tasks (1)
- periodische Aufgaben (1)
- persönliche Informationen (1)
- petri net (1)
- physical computing tools (1)
- placement (1)
- platform ecosystems (1)
- platypus (1)
- policy evaluation (1)
- polyglot execution environments (1)
- polyglot programming (1)
- polyglottes Programmieren (1)
- portfolio-based solving (1)
- pose estimation (1)
- preference handling (1)
- preferences (1)
- presentation (1)
- prime pair (1)
- primer pair design (1)
- priorities (1)
- probabilistic machine learning (1)
- probabilistic timed automata (1)
- probabilistische zeitbehaftete Automaten (1)
- probabilistisches maschinelles Lernen (1)
- process (1)
- process and data integration (1)
- process automation (1)
- process elicitation (1)
- process improvement (1)
- process instance (1)
- process instance grouping (1)
- process model (1)
- process model search (1)
- process modeling languages (1)
- process modelling (1)
- process models (1)
- process refinement (1)
- processor hardware (1)
- production planning and control (1)
- professors (1)
- profiling (1)
- programming abstraction (1)
- programming experience (1)
- programming tools (1)
- programs (1)
- prototyping (1)
- psychotherapy (1)
- public cloud storage services (1)
- qualitative model (1)
- qualitatives Modell (1)
- quantification protocol (1)
- quantile normalization (1)
- quantum computing (1)
- query optimization (1)
- querying (1)
- railway network (1)
- railways (1)
- rapid prototyping (1)
- raum-zeitlich (1)
- raumbezogene Straftatenanalyse (1)
- reactive (1)
- reaktive Programmierung (1)
- real-time application (1)
- real-time rendering (1)
- rechnerunterstütztes Konstruieren (1)
- recognition (1)
- recommendation (1)
- reconfigurable systems (1)
- reconfiguration (1)
- reconstruction (1)
- regression testing (1)
- regulatory networks (1)
- reinforcement learning (1)
- rekonfigurierbar (1)
- relational model transformation (1)
- relationale Modelltransformationen (1)
- reliability assessment (1)
- remote sensing (1)
- repair (1)
- requirements engineering (1)
- resource management (1)
- resource optimization (1)
- rest service (1)
- reverse engineering (1)
- reversible reaction (1)
- reward system (1)
- robust ICA (1)
- robuste ICA (1)
- runtime adaptations (1)
- runtime behavior (1)
- runtime monitoring (1)
- räumliche Geodaten (1)
- s/t-pattern sequences (1)
- sat (1)
- satisfiabilitiy solving (1)
- savanna (1)
- scheduling (1)
- school (1)
- schwach überwachtes maschinelles Lernen (1)
- scm (1)
- scripting environments (1)
- scripting languages (1)
- scrollytelling (1)
- security analytics (1)
- segmentation (1)
- selbst-souveräne Identitäten (1)
- selbstbestimmte Identitäten (1)
- selbstprüfende Schaltungen (1)
- selection (1)
- self-adaptive software (1)
- self-driving (1)
- semantic classification (1)
- semantic web services (1)
- semantics preservation (1)
- semantische Klassifizierung (1)
- semantisches Netz (1)
- sequence properties (1)
- serialization (1)
- series (1)
- serverseitiges 3D-Rendering (1)
- serverside 3D rendering (1)
- service mediation (1)
- service orchestration (1)
- service-oriented architectures (1)
- serviceorientierte Architekturen (1)
- sets (1)
- shader (1)
- signal transition graph (1)
- significant edge (1)
- similarity (1)
- single-case experimental design (1)
- situational awareness (1)
- skeletonization (1)
- small talk (1)
- smartphone (1)
- social network analysis (1)
- societal effects (1)
- software (1)
- software analysis (1)
- software architecture (1)
- software development (1)
- software evolution (1)
- software maintenance (1)
- software product lines (1)
- software testing (1)
- software tests (1)
- software visualization (1)
- software/hardware co-design (1)
- spatio-temporal (1)
- spatio-temporal sensor data (1)
- specific prime pair (1)
- specification of timed graph transformations (1)
- speed independence (1)
- speed independent (1)
- squeak (1)
- stable model semantics (1)
- standardization (1)
- standards (1)
- stark verhaltenskorrekt sperrend (1)
- static analysis (1)
- static source-code analysis (1)
- statische Analyse (1)
- statische Quellcodeanalyse (1)
- statistics program R (1)
- stochastic Petri nets (1)
- stochastische Petri Netze (1)
- strong and uniform equivalence (1)
- strongly behaviourally correct locking (1)
- structured output prediction (1)
- strukturierte Vorhersage (1)
- study (1)
- study problems (1)
- stylization (1)
- symbolic analysis (1)
- symbolic graphs (1)
- symbolische Analyse (1)
- symbolische Graphen (1)
- synonym discovery (1)
- system of systems (1)
- systematic literature review (1)
- systems (1)
- systems software (1)
- t.BPM (1)
- tabellarische Dateien (1)
- tableau method (1)
- tabular data (1)
- tangible media (1)
- taxonomy (1)
- teacher training (1)
- teachers (1)
- tele-lab (1)
- tele-teaching (1)
- telemedicine (1)
- temporal graph queries (1)
- temporal logic (1)
- temporale Graphanfragen (1)
- temporary binding (1)
- terrain models (1)
- test (1)
- test case prioritization (1)
- test results (1)
- testing (1)
- text based classification methods (1)
- text classification (1)
- threat detection (1)
- threshold cryptography (1)
- tiefe Gauß-Prozesse (1)
- tiering (1)
- tool building (1)
- topics (1)
- touch input (1)
- tptp (1)
- traditional Georgian music (1)
- traditionelle Georgische Musik (1)
- traditionelle Unternehmen (1)
- trajectories (1)
- transduction (1)
- transformation (1)
- transformation level (1)
- transformation sequences (1)
- trust (1)
- tutorial section (1)
- typed graph transformation systems (1)
- typisierte attributierte Graphen (1)
- unferring cellular networks (1)
- unfounded sets (1)
- unique (1)
- unique column combinations (1)
- unsupervised (1)
- user-generated content (1)
- value co-creation (1)
- variables (1)
- variation (1)
- variational inference (1)
- variationelle Inferenz (1)
- ventral striatum (1)
- verhaltenskorrektes Lernen (1)
- verifiable credentials (1)
- verschachtelte Anwednungsbedingungen (1)
- verschachtelte Anwendungsbedingungen (1)
- versioning (1)
- verteilte Berechnung (1)
- verteilte Datenbanken (1)
- verteilte Leistungsüberwachung (1)
- verzwickte Probleme (1)
- view maintenance (1)
- virtual (1)
- virtual 3D city model (1)
- virtual desktop infrastructure (1)
- virtual machine (1)
- virtual mobility (1)
- virtual reality (1)
- virtualisierte IT-Infrastruktur (1)
- virtuell (1)
- virtuelle Realität (1)
- visual language (1)
- visual languages (1)
- visualization concept exploration (1)
- visuelle Sprache (1)
- visuelle Sprachen (1)
- weak supervision (1)
- web application (1)
- web services (1)
- web-applications (1)
- web-based development (1)
- web-based development environment (1)
- web-basierte Entwicklungsumgebung (1)
- webbasierte Entwicklung (1)
- word order freezing (1)
- workflow patterns (1)
- zero-day (1)
- zuverlässige Datenverarbeitung (1)
- zuverlässigen Datenverarbeitung (1)
- Ähnlichkeit (1)
- Ähnlichkeitsmaße (1)
- Ähnlichkeitssuche (1)
- Übereinstimmungsanalyse (1)
- Überwachung (1)
- öffentliche Cloud Speicherdienste (1)
- überbestimmte ICA (1)
- überprüfbare Nachweise (1)
Institute
- Hasso-Plattner-Institut für Digital Engineering gGmbH (147)
- Institut für Informatik und Computational Science (96)
- Hasso-Plattner-Institut für Digital Engineering GmbH (79)
- Mathematisch-Naturwissenschaftliche Fakultät (23)
- Extern (14)
- Digital Engineering Fakultät (7)
- Wirtschaftswissenschaften (7)
- Institut für Umweltwissenschaften und Geographie (5)
- Institut für Physik und Astronomie (4)
- Department Linguistik (2)
Knowledge about causal structures is crucial for decision support in various domains. For example, in discrete manufacturing, identifying the root causes of failures and quality deviations that interrupt the highly automated production process requires causal structural knowledge. However, in practice, root cause analysis is usually built upon individual expert knowledge about associative relationships. But, "correlation does not imply causation", and misinterpreting associations often leads to incorrect conclusions. Recent developments in methods for causal discovery from observational data have opened the opportunity for a data-driven examination. Despite its potential for data-driven decision support, omnipresent challenges impede causal discovery in real-world scenarios. In this thesis, we make a threefold contribution to improving causal discovery in practice.
(1) The growing interest in causal discovery has led to a broad spectrum of methods with specific assumptions on the data and various implementations. Hence, application in practice requires careful consideration of existing methods, which becomes laborious when dealing with various parameters, assumptions, and implementations in different programming languages. Additionally, evaluation is challenging due to the lack of ground truth in practice and limited benchmark data that reflect real-world data characteristics.
To address these issues, we present a platform-independent modular pipeline for causal discovery and a ground truth framework for synthetic data generation that provides comprehensive evaluation opportunities, e.g., to examine the accuracy of causal discovery methods in case of inappropriate assumptions.
(2) Applying constraint-based methods for causal discovery requires selecting a conditional independence (CI) test, which is particularly challenging in mixed discrete-continuous data omnipresent in many real-world scenarios. In this context, inappropriate assumptions on the data or the commonly applied discretization of continuous variables reduce the accuracy of CI decisions, leading to incorrect causal structures.
Therefore, we contribute a non-parametric CI test leveraging k-nearest neighbors methods and prove its statistical validity and power in mixed discrete-continuous data, as well as the asymptotic consistency when used in constraint-based causal discovery. An extensive evaluation of synthetic and real-world data shows that the proposed CI test outperforms state-of-the-art approaches in the accuracy of CI testing and causal discovery, particularly in settings with low sample sizes.
(3) To show the applicability and opportunities of causal discovery in practice, we examine our contributions in real-world discrete manufacturing use cases. For example, we showcase how causal structural knowledge helps to understand unforeseen production downtimes or adds decision support in case of failures and quality deviations in automotive body shop assembly lines.
Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality.
Algorithmic management
(2022)
Column-oriented database systems can efficiently process transactional and analytical queries on a single node. However, increasing or peak analytical loads can quickly saturate single-node database systems. Then, a common scale-out option is using a database cluster with a single primary node for transaction processing and read-only replicas. Using (the naive) full replication, queries are distributed among nodes independently of the accessed data. This approach is relatively expensive because all nodes must store all data and apply all data modifications caused by inserts, deletes, or updates.
In contrast to full replication, partial replication is a more cost-efficient implementation: Instead of duplicating all data to all replica nodes, partial replicas store only a subset of the data while being able to process a large workload share. Besides lower storage costs, partial replicas enable (i) better scaling because replicas must potentially synchronize only subsets of the data modifications and thus have more capacity for read-only queries and (ii) better elasticity because replicas have to load less data and can be set up faster. However, splitting the overall workload evenly among the replica nodes while optimizing the data allocation is a challenging assignment problem.
The calculation of optimized data allocations in a partially replicated database cluster can be modeled using integer linear programming (ILP). ILP is a common approach for solving assignment problems, also in the context of database systems. Because ILP is not scalable, existing approaches (also for calculating partial allocations) often fall back to simple (e.g., greedy) heuristics for larger problem instances. Simple heuristics may work well but can lose optimization potential.
In this thesis, we present optimal and ILP-based heuristic programming models for calculating data fragment allocations for partially replicated database clusters. Using ILP, we are flexible to extend our models to (i) consider data modifications and reallocations and (ii) increase the robustness of allocations to compensate for node failures and workload uncertainty. We evaluate our approaches for TPC-H, TPC-DS, and a real-world accounting workload and compare the results to state-of-the-art allocation approaches. Our evaluations show significant improvements for varied allocation’s properties: Compared to existing approaches, we can, for example, (i) almost halve the amount of allocated data, (ii) improve the throughput in case of node failures and workload uncertainty while using even less memory, (iii) halve the costs of data modifications, and (iv) reallocate less than 90% of data when adding a node to the cluster. Importantly, we can calculate the corresponding ILP-based heuristic solutions within a few seconds. Finally, we demonstrate that the ideas of our ILP-based heuristics are also applicable to the index selection problem.
Viper
(2021)
Key-value stores (KVSs) have found wide application in modern software systems. For persistence, their data resides in slow secondary storage, which requires KVSs to employ various techniques to increase their read and write performance from and to the underlying medium. Emerging persistent memory (PMem) technologies offer data persistence at close-to-DRAM speed, making them a promising alternative to classical disk-based storage. However, simply drop-in replacing existing storage with PMem does not yield good results, as block-based access behaves differently in PMem than on disk and ignores PMem's byte addressability, layout, and unique performance characteristics. In this paper, we propose three PMem-specific access patterns and implement them in a hybrid PMem-DRAM KVS called Viper. We employ a DRAM-based hash index and a PMem-aware storage layout to utilize the random-write speed of DRAM and efficient sequential-write performance PMem. Our evaluation shows that Viper significantly outperforms existing KVSs for core KVS operations while providing full data persistence. Moreover, Viper outperforms existing PMem-only, hybrid, and disk-based KVSs by 4-18x for write workloads, while matching or surpassing their get performance.
To manage tabular data files and leverage their content in a given downstream task, practitioners often design and execute complex transformation pipelines to prepare them. The complexity of such pipelines stems from different factors, including the nature of the preparation tasks, often exploratory or ad-hoc to specific datasets; the large repertory of tools, algorithms, and frameworks that practitioners need to master; and the volume, variety, and velocity of the files to be prepared. Metadata plays a fundamental role in reducing this complexity: characterizing a file assists end users in the design of data preprocessing pipelines, and furthermore paves the way for suggestion, automation, and optimization of data preparation tasks.
Previous research in the areas of data profiling, data integration, and data cleaning, has focused on extracting and characterizing metadata regarding the content of tabular data files, i.e., about the records and attributes of tables. Content metadata are useful for the latter stages of a preprocessing pipeline, e.g., error correction, duplicate detection, or value normalization, but they require a properly formed tabular input. Therefore, these metadata are not relevant for the early stages of a preparation pipeline, i.e., to correctly parse tables out of files. In this dissertation, we turn our focus to what we call the structure of a tabular data file, i.e., the set of characters within a file that do not represent data values but are required to parse and understand the content of the file. We provide three different approaches to represent file structure, an explicit representation based on context-free grammars; an implicit representation based on file-wise similarity; and a learned representation based on machine learning.
In our first contribution, we use the grammar-based representation to characterize a set of over 3000 real-world csv files and identify multiple structural issues that let files deviate from the csv standard, e.g., by having inconsistent delimiters or containing multiple tables. We leverage our learnings about real-world files and propose Pollock, a benchmark to test how well systems parse csv files that have a non-standard structure, without any previous preparation. We report on our experiments on using Pollock to evaluate the performance of 16 real-world data management systems.
Following, we characterize the structure of files implicitly, by defining a measure of structural similarity for file pairs. We design a novel algorithm to compute this measure, which is based on a graph representation of the files' content. We leverage this algorithm and propose Mondrian, a graphical system to assist users in identifying layout templates in a dataset, classes of files that have the same structure, and therefore can be prepared by applying the same preparation pipeline.
Finally, we introduce MaGRiTTE, a novel architecture that uses self-supervised learning to automatically learn structural representations of files in the form of vectorial embeddings at three different levels: cell level, row level, and file level. We experiment with the application of structural embeddings for several tasks, namely dialect detection, row classification, and data preparation efforts estimation.
Our experimental results show that structural metadata, either identified explicitly on parsing grammars, derived implicitly as file-wise similarity, or learned with the help of machine learning architectures, is fundamental to automate several tasks, to scale up preparation to large quantities of files, and to provide repeatable preparation pipelines.
Advancements in computer vision techniques driven by machine learning have facilitated robust and efficient estimation of attributes such as depth, optical flow, albedo, and shading. To encapsulate all such underlying properties associated with images and videos, we evolve the concept of intrinsic images towards intrinsic attributes. Further, rapid hardware growth in the form of high-quality smartphone cameras, readily available depth sensors, mobile GPUs, or dedicated neural processing units have made image and video processing pervasive. In this thesis, we explore the synergies between the above two advancements and propose novel image and video processing techniques and systems based on them. To begin with, we investigate intrinsic image decomposition approaches and analyze how they can be implemented on mobile devices. We propose an approach that considers not only diffuse reflection but also specular reflection; it allows us to decompose an image into specularity, albedo, and shading on a resource constrained system (e.g., smartphones or tablets) using the depth data provided by the built-in depth sensors. In addition, we explore how on-device depth data can further be used to add an immersive dimension to 2D photos, e.g., showcasing parallax effects via 3D photography. In this regard, we develop a novel system for interactive 3D photo generation and stylization on mobile devices. Further, we investigate how adaptive manipulation of baseline-albedo (i.e., chromaticity) can be used for efficient visual enhancement under low-lighting conditions. The proposed technique allows for interactive editing of enhancement settings while achieving improved quality and performance. We analyze the inherent optical flow and temporal noise as intrinsic properties of a video. We further propose two new techniques for applying the above intrinsic attributes for the purpose of consistent video filtering. To this end, we investigate how to remove temporal inconsistencies perceived as flickering artifacts. One of the techniques does not require costly optical flow estimation, while both provide interactive consistency control. Using intrinsic attributes for image and video processing enables new solutions for mobile devices – a pervasive visual computing device – and will facilitate novel applications for Augmented Reality (AR), 3D photography, and video stylization. The proposed low-light enhancement techniques can also improve the accuracy of high-level computer vision tasks (e.g., face detection) under low-light conditions. Finally, our approach for consistent video filtering can extend a wide range of image-based processing for videos.
BCH Codes mit kombinierter Korrektur und Erkennung In dieser Arbeit wird auf Grundlage des BCH Codes untersucht, wie eine Fehlerkorrektur mit einer Erkennung höherer Fehleranzahlen kombiniert werden kann. Mit dem Verfahren der 1-Bit Korrektur mit zusätzlicher Erkennung höherer Fehler wurde ein Ansatz entwickelt, welcher die Erkennung zusätzlicher Fehler durch das parallele Lösen einfacher Gleichungen der Form s_x = s_1^x durchführt. Die Anzahl dieser Gleichungen ist linear zu der Anzahl der zu überprüfenden höheren Fehler.
In dieser Arbeit wurde zusätzlich für bis zu 4-Bit Korrekturen mit zusätzlicher Erkennung höherer Fehler ein weiterer allgemeiner Ansatz vorgestellt. Dabei werden parallel für alle korrigierbaren Fehleranzahlen spekulative Fehlerkorrekturen durchgeführt. Aus den bestimmten Fehlerstellen werden spekulative Syndromkomponenten erzeugt, durch welche die Fehlerstellen bestätigt und höhere erkennbare Fehleranzahlen ausgeschlossen werden können. Die vorgestellten Ansätze unterscheiden sich von dem in entwickelten Ansatz, bei welchem die Anzahl der Fehlerstellen durch die Berechnung von Determinanten in absteigender Reihenfolge berechnet wird, bis die erste Determinante 0 bildet. Bei dem bekannten Verfahren ist durch die Berechnung der Determinanten eine faktorielle Anzahl an Berechnungen in Relation zu der Anzahl zu überprüfender Fehler durchzuführen. Im Vergleich zu dem bekannten sequentiellen Verfahrens nach Berlekamp Massey besitzen die Berechnungen im vorgestellten Ansatz simple Gleichungen und können parallel durchgeführt werden.Bei dem bekannten Verfahren zur parallelen Korrektur von 4-Bit Fehlern ist eine Gleichung vierten Grades im GF(2^m) zu lösen. Dies erfolgt, indem eine Hilfsgleichung dritten Grades und vier Gleichungen zweiten Grades parallel gelöst werden. In der vorliegenden Arbeit wurde gezeigt, dass sich eine Gleichung zweiten Grades einsparen lässt, wodurch sich eine Vereinfachung der Hardware bei einer parallelen Realisierung der 4-Bit Korrektur ergibt. Die erzielten Ergebnisse wurden durch umfangreiche Simulationen in Software und Hardwareimplementierungen überprüft.
This technical report presents the results of student projects which were prepared during the lecture “Operating Systems II” offered by the “Operating Systems and Middleware” group at HPI in the Summer term of 2020. The lecture covered ad- vanced aspects of operating system implementation and architecture on topics such as Virtualization, File Systems and Input/Output Systems. In addition to attending the lecture, the participating students were encouraged to gather practical experience by completing a project on a closely related topic over the course of the semester. The results of 10 selected exceptional projects are covered in this report.
The students have completed hands-on projects on the topics of Operating System Design Concepts and Implementation, Hardware/Software Co-Design, Reverse Engineering, Quantum Computing, Static Source-Code Analysis, Operating Systems History, Application Binary Formats and more. It should be recognized that over the course of the semester all of these projects have achieved outstanding results which went far beyond the scope and the expec- tations of the lecture, and we would like to thank all participating students for their commitment and their effort in completing their respective projects, as well as their work on compiling this report.
Digital technology offers significant political, economic, and societal opportunities. At the same time, the notion of digital sovereignty has become a leitmotif in German discourse: the state’s capacity to assume its responsibilities and safeguard society’s – and individuals’ – ability to shape the digital transformation in a self-determined way. The education sector is exemplary for the challenge faced by Germany, and indeed Europe, of harnessing the benefits of digital technology while navigating concerns around sovereignty. It encompasses education as a core public good, a rapidly growing field of business, and growing pools of highly sensitive personal data. The report describes pathways to mitigating the tension between digitalization and sovereignty at three different levels – state, economy, and individual – through the lens of concrete technical projects in the education sector: the HPI Schul-Cloud (state sovereignty), the MERLOT data spaces (economic sovereignty), and the openHPI platform (individual sovereignty).
The Security Operations Center (SOC) represents a specialized unit responsible for managing security within enterprises. To aid in its responsibilities, the SOC relies heavily on a Security Information and Event Management (SIEM) system that functions as a centralized repository for all security-related data, providing a comprehensive view of the organization's security posture. Due to the ability to offer such insights, SIEMS are considered indispensable tools facilitating SOC functions, such as monitoring, threat detection, and incident response.
Despite advancements in big data architectures and analytics, most SIEMs fall short of keeping pace. Architecturally, they function merely as log search engines, lacking the support for distributed large-scale analytics. Analytically, they rely on rule-based correlation, neglecting the adoption of more advanced data science and machine learning techniques.
This thesis first proposes a blueprint for next-generation SIEM systems that emphasize distributed processing and multi-layered storage to enable data mining at a big data scale. Next, with the architectural support, it introduces two data mining approaches for advanced threat detection as part of SOC operations.
First, a novel graph mining technique that formulates threat detection within the SIEM system as a large-scale graph mining and inference problem, built on the principles of guilt-by-association and exempt-by-reputation. The approach entails the construction of a Heterogeneous Information Network (HIN) that models shared characteristics and associations among entities extracted from SIEM-related events/logs. Thereon, a novel graph-based inference algorithm is used to infer a node's maliciousness score based on its associations with other entities in the HIN. Second, an innovative outlier detection technique that imitates a SOC analyst's reasoning process to find anomalies/outliers. The approach emphasizes explainability and simplicity, achieved by combining the output of simple context-aware univariate submodels that calculate an outlier score for each entry.
Both approaches were tested in academic and real-world settings, demonstrating high performance when compared to other algorithms as well as practicality alongside a large enterprise's SIEM system.
This thesis establishes the foundation for next-generation SIEM systems that can enhance today's SOCs and facilitate the transition from human-centric to data-driven security operations.
Eine übliche Erzählung verknüpft lange Studienzeiten und hohe Abbrecherquoten im Informatikstudium zum einen mit der sehr gut bezahlten Nebentätigkeit von Studierenden in der Informatikbranche, die deutlich studienzeitverlängernd sei; zum anderen werde wegen des hohen Bedarfs an Informatikern ein formeller Studienabschluss von den Studierenden häufig als entbehrlich betrachtet und eine Karriere in der Informatikbranche ohne abgeschlossenes Studium begonnen. In dieser Studie, durchgeführt an der Universität Potsdam, untersuchen wir, wie viele Informatikstudierende neben dem Studium innerhalb und außerhalb der Informatikbranche arbeiten, welche Erwartungen sie neben der Bezahlung damit verbinden und wie sich die Tätigkeit auf ihr Studium und ihre spätere berufliche Perspektive auswirkt. Aus aktuellem Anlass interessieren uns auch die Auswirkungen der Covid-19-Pandemie auf die Arbeitstätigkeiten der Informatikstudierenden.
Die Fachtagungen HDI (Hochschuldidaktik Informatik) beschäftigen sich mit den unterschiedlichen Aspekten informatischer Bildung im Hochschulbereich. Neben den allgemeinen Themen wie verschiedenen Lehr- und Lernformen, dem Einsatz von Informatiksystemen in der Hochschullehre oder Fragen der Gewinnung von geeigneten Studierenden, deren Kompetenzerwerb oder auch der Betreuung der Studierenden widmet sich die HDI immer auch einem Schwerpunktthema.
Im Jahr 2021 war dies die Berücksichtigung von Diversität in der Lehre. Diskutiert wurden beispielsweise die Einbeziehung von besonderen fachlichen und überfachlichen Kompetenzen Studierender, der Unterstützung von Durchlässigkeit aus nichtakademischen Berufen, aber auch die Gestaltung inklusiver Lehr- und Lernszenarios, Aspekte des Lebenslangen Lernens oder sich an die Diversität von Studierenden adaptierte oder adaptierende Lehrsysteme.
Dieser Band enthält ausgewählte Beiträge der 9. Fachtagung 2021, die in besonderer Weise die Konferenz und die dort diskutierten Themen repräsentieren.
In this bachelor’s thesis I implement the automatic theorem prover nanoCoP-Ω. This system is the result of porting arithmetic and equality handling procedures first introduced in the automatic theorem prover with arithmetic leanCoP-Ω into the similar system nanoCoP 2.0. To understand these procedures, I first introduce the mathematical background to both automatic theorem proving and arithmetic expressions. I present the predecessor projects leanCoP, nanoCoP and leanCoP-Ω, out of which nanCoP-Ω was developed. This is followed by an extensive description of the concepts the non-clausal connection calculus needed to be extended by, to allow for proving arithmetic expressions and equalities, as well as of their implementation into nanoCoP-Ω. An extensive comparison between both the runtimes and the number of solved problems of the systems nanoCoP-Ω and leanCoP-Ω was made. I come to the conclusion, that nanoCoP-Ω is considerably faster than leanCoP-Ω for small problems, though less well suited for larger problems. Additionally, I was able to construct a non-theorem that nanoCoP-Ω generates a false proof for. I discuss how this pressing issue could be resolved, as well as some possible optimizations and expansions of the system.
Digitale Technologien bieten erhebliche politische, wirtschaftliche und gesellschaftliche Chancen. Zugleich ist der Begriff digitale Souveränität zu einem Leitmotiv im deutschen Diskurs über digitale Technologien geworden: das heißt, die Fähigkeit des Staates, seine Verantwortung wahrzunehmen und die Befähigung der Gesellschaft – und des Einzelnen – sicherzustellen, die digitale Transformation selbstbestimmt zu gestalten. Exemplarisch für die Herausforderung in Deutschland und Europa, die Vorteile digitaler Technologien zu nutzen und gleichzeitig Souveränitätsbedenken zu berücksichtigen, steht der Bildungssektor. Er umfasst Bildung als zentrales öffentliches Gut, ein schnell aufkommendes Geschäftsfeld und wachsende Bestände an hochsensiblen personenbezogenen Daten. Davon ausgehend beschreibt der Bericht Wege zur Entschärfung des Spannungsverhältnisses zwischen Digitalisierung und Souveränität auf drei verschiedenen Ebenen – Staat, Wirtschaft und Individuum – anhand konkreter technischer Projekte im Bildungsbereich: die HPI Schul-Cloud (staatliche Souveränität), die MERLOT-Datenräume (wirtschaftliche Souveränität) und die openHPI-Plattform (individuelle Souveränität).
In model-driven engineering, the adaptation of large software systems with dynamic structure is enabled by architectural runtime models. Such a model represents an abstract state of the system as a graph of interacting components. Every relevant change in the system is mirrored in the model and triggers an evaluation of model queries, which search the model for structural patterns that should be adapted. This thesis focuses on a type of runtime models where the expressiveness of the model and model queries is extended to capture past changes and their timing. These history-aware models and temporal queries enable more informed decision-making during adaptation, as they support the formulation of requirements on the evolution of the pattern that should be adapted. However, evaluating temporal queries during adaptation poses significant challenges. First, it implies the capability to specify and evaluate requirements on the structure, as well as the ordering and timing in which structural changes occur. Then, query answers have to reflect that the history-aware model represents the architecture of a system whose execution may be ongoing, and thus answers may depend on future changes. Finally, query evaluation needs to be adequately fast and memory-efficient despite the increasing size of the history---especially for models that are altered by numerous, rapid changes.
The thesis presents a query language and a querying approach for the specification and evaluation of temporal queries. These contributions aim to cope with the challenges of evaluating temporal queries at runtime, a prerequisite for history-aware architectural monitoring and adaptation which has not been systematically treated by prior model-based solutions. The distinguishing features of our contributions are: the specification of queries based on a temporal logic which encodes structural patterns as graphs; the provision of formally precise query answers which account for timing constraints and ongoing executions; the incremental evaluation which avoids the re-computation of query answers after each change; and the option to discard history that is no longer relevant to queries. The query evaluation searches the model for occurrences of a pattern whose evolution satisfies a temporal logic formula. Therefore, besides model-driven engineering, another related research community is runtime verification. The approach differs from prior logic-based runtime verification solutions by supporting the representation and querying of structure via graphs and graph queries, respectively, which is more efficient for queries with complex patterns. We present a prototypical implementation of the approach and measure its speed and memory consumption in monitoring and adaptation scenarios from two application domains, with executions of an increasing size. We assess scalability by a comparison to the state-of-the-art from both related research communities. The implementation yields promising results, which pave the way for sophisticated history-aware self-adaptation solutions and indicate that the approach constitutes a highly effective technique for runtime monitoring on an architectural level.
Most machine learning methods provide only point estimates when being queried to predict on new data. This is problematic when the data is corrupted by noise, e.g. from imperfect measurements, or when the queried data point is very different to the data that the machine learning model has been trained with. Probabilistic modelling in machine learning naturally equips predictions with corresponding uncertainty estimates which allows a practitioner to incorporate information about measurement noise into the modelling process and to know when not to trust the predictions. A well-understood, flexible probabilistic framework is provided by Gaussian processes that are ideal as building blocks of probabilistic models. They lend themself naturally to the problem of regression, i.e., being given a set of inputs and corresponding observations and then predicting likely observations for new unseen inputs, and can also be adapted to many more machine learning tasks. However, exactly inferring the optimal parameters of such a Gaussian process model (in a computationally tractable manner) is only possible for regression tasks in small data regimes. Otherwise, approximate inference methods are needed, the most prominent of which is variational inference.
In this dissertation we study models that are composed of Gaussian processes embedded in other models in order to make those more flexible and/or probabilistic. The first example are deep Gaussian processes which can be thought of as a small network of Gaussian processes and which can be employed for flexible regression. The second model class that we study are Gaussian process state-space models. These can be used for time-series modelling, i.e., the task of being given a stream of data ordered by time and then predicting future observations. For both model classes the state-of-the-art approaches offer a trade-off between expressive models and computational properties (e.g. speed or convergence properties) and mostly employ variational inference. Our goal is to improve inference in both models by first getting a deep understanding of the existing methods and then, based on this, to design better inference methods. We achieve this by either exploring the existing trade-offs or by providing general improvements applicable to multiple methods.
We first provide an extensive background, introducing Gaussian processes and their sparse (approximate and efficient) variants. We continue with a description of the models under consideration in this thesis, deep Gaussian processes and Gaussian process state-space models, including detailed derivations and a theoretical comparison of existing methods.
Then we start analysing deep Gaussian processes more closely: Trading off the properties (good optimisation versus expressivity) of state-of-the-art methods in this field, we propose a new variational inference based approach. We then demonstrate experimentally that our new algorithm leads to better calibrated uncertainty estimates than existing methods.
Next, we turn our attention to Gaussian process state-space models, where we closely analyse the theoretical properties of existing methods.The understanding gained in this process leads us to propose a new inference scheme for general Gaussian process state-space models that incorporates effects on multiple time scales. This method is more efficient than previous approaches for long timeseries and outperforms its comparison partners on data sets in which effects on multiple time scales (fast and slowly varying dynamics) are present.
Finally, we propose a new inference approach for Gaussian process state-space models that trades off the properties of state-of-the-art methods in this field. By combining variational inference with another approximate inference method, the Laplace approximation, we design an efficient algorithm that outperforms its comparison partners since it achieves better calibrated uncertainties.
Residential segregation is a widespread phenomenon that can be observed in almost every major city. In these urban areas, residents with different ethnical or socioeconomic backgrounds tend to form homogeneous clusters. In Schelling’s classical segregation model two types of agents are placed on a grid. An agent is content with its location if the fraction of its neighbors, which have the same type as the agent, is at least 𝜏, for some 0 < 𝜏 ≤ 1. Discontent agents simply swap their location with a randomly chosen other discontent agent or jump to a random empty location. The model gives a coherent explanation of how clusters can form even if all agents are tolerant, i.e., if they agree to live in mixed neighborhoods. For segregation to occur, all it needs is a slight bias towards agents preferring similar neighbors.
Although the model is well studied, previous research focused on a random process point of view. However, it is more realistic to assume instead that the agents strategically choose where to live. We close this gap by introducing and analyzing game-theoretic models of Schelling segregation, where rational agents strategically choose their locations.
As the first step, we introduce and analyze a generalized game-theoretic model that allows more than two agent types and more general underlying graphs modeling the residential area. We introduce different versions of Swap and Jump Schelling Games. Swap Schelling Games assume that every vertex of the underlying graph serving as a residential area is occupied by an agent and pairs of discontent agents can swap their locations, i.e., their occupied vertices, to increase their utility. In contrast, for the Jump Schelling Game, we assume that there exist empty vertices in the graph and agents can jump to these vacant vertices if this increases their utility. We show that the number of agent types as well as the structure of underlying graph heavily influence the dynamic properties and the tractability of finding an optimal strategy profile.
As a second step, we significantly deepen these investigations for the swap version with 𝜏 = 1 by studying the influence of the underlying topology modeling the residential area on the existence of equilibria, the Price of Anarchy, and the dynamic properties. Moreover, we restrict the movement of agents locally. As a main takeaway, we find that both aspects influence the existence and the quality of stable states.
Furthermore, also for the swap model, we follow sociological surveys and study, asking the same core game-theoretic questions, non-monotone singlepeaked utility functions instead of monotone ones, i.e., utility functions that are not monotone in the fraction of same-type neighbors. Our results clearly show that moving from monotone to non-monotone utilities yields novel structural properties and different results in terms of existence and quality of stable states.
In the last part, we introduce an agent-based saturated open-city variant, the Flip Schelling Process, in which agents, based on the predominant type in their neighborhood, decide whether to change their types. We provide a general framework for analyzing the influence of the underlying topology on residential segregation and investigate the probability that an edge is monochrome, i.e., that both incident vertices have the same type, on random geometric and Erdős–Rényi graphs. For random geometric graphs, we prove the existence of a constant c > 0 such that the expected fraction of monochrome edges after the Flip Schelling Process is at least 1/2 + c. For Erdős–Rényi graphs, we show the expected fraction of monochrome edges after the Flip Schelling Process is at most 1/2 + o(1).
Today, point clouds are among the most important categories of spatial data, as they constitute digital 3D models of the as-is reality that can be created at unprecedented speed and precision. However, their unique properties, i.e., lack of structure, order, or connectivity information, necessitate specialized data structures and algorithms to leverage their full precision. In particular, this holds true for the interactive visualization of point clouds, which requires to balance hardware limitations regarding GPU memory and bandwidth against a naturally high susceptibility to visual artifacts.
This thesis focuses on concepts, techniques, and implementations of robust, scalable, and portable 3D visualization systems for massive point clouds. To that end, a number of rendering, visualization, and interaction techniques are introduced, that extend several basic strategies to decouple rendering efforts and data management: First, a novel visualization technique that facilitates context-aware filtering, highlighting, and interaction within point cloud depictions. Second, hardware-specific optimization techniques that improve rendering performance and image quality in an increasingly diversified hardware landscape. Third, natural and artificial locomotion techniques for nausea-free exploration in the context of state-of-the-art virtual reality devices. Fourth, a framework for web-based rendering that enables collaborative exploration of point clouds across device ecosystems and facilitates the integration into established workflows and software systems.
In cooperation with partners from industry and academia, the practicability and robustness of the presented techniques are showcased via several case studies using representative application scenarios and point cloud data sets. In summary, the work shows that the interactive visualization of point clouds can be implemented by a multi-tier software architecture with a number of domain-independent, generic system components that rely on optimization strategies specific to large point clouds. It demonstrates the feasibility of interactive, scalable point cloud visualization as a key component for distributed IT solutions that operate with spatial digital twins, providing arguments in favor of using point clouds as a universal type of spatial base data usable directly for visualization purposes.
Proceedings of the HPI Research School on Service-oriented Systems Engineering 2020 Fall Retreat
(2021)
Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application.
Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns.
The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.
Learning the causal structures from observational data is an omnipresent challenge in data science. The amount of observational data available to Causal Structure Learning (CSL) algorithms is increasing as data is collected at high frequency from many data sources nowadays. While processing more data generally yields higher accuracy in CSL, the concomitant increase in the runtime of CSL algorithms hinders their widespread adoption in practice. CSL is a parallelizable problem. Existing parallel CSL algorithms address execution on multi-core Central Processing Units (CPUs) with dozens of compute cores. However, modern computing systems are often heterogeneous and equipped with Graphics Processing Units (GPUs) to accelerate computations. Typically, these GPUs provide several thousand compute cores for massively parallel data processing.
To shorten the runtime of CSL algorithms, we design efficient execution strategies that leverage the parallel processing power of GPUs. Particularly, we derive GPU-accelerated variants of a well-known constraint-based CSL method, the PC algorithm, as it allows choosing a statistical Conditional Independence test (CI test) appropriate to the observational data characteristics.
Our two main contributions are: (1) to reflect differences in the CI tests, we design three GPU-based variants of the PC algorithm tailored to CI tests that handle data with the following characteristics. We develop one variant for data assuming the Gaussian distribution model, one for discrete data, and another for mixed discrete-continuous data and data with non-linear relationships. Each variant is optimized for the appropriate CI test leveraging GPU hardware properties, such as shared or thread-local memory. Our GPU-accelerated variants outperform state-of-the-art parallel CPU-based algorithms by factors of up to 93.4× for data assuming the Gaussian distribution model, up to 54.3× for discrete data, up to 240× for continuous data with non-linear relationships and up to 655× for mixed discrete-continuous data. However, the proposed GPU-based variants are limited to datasets that fit into a single GPU’s memory. (2) To overcome this shortcoming, we develop approaches to scale our GPU-based variants beyond a single GPU’s memory capacity. For example, we design an out-of-core GPU variant that employs explicit memory management to process arbitrary-sized datasets. Runtime measurements on a large gene expression dataset reveal that our out-of-core GPU variant is 364 times faster than a parallel CPU-based CSL algorithm. Overall, our proposed GPU-accelerated variants speed up CSL in numerous settings to foster CSL’s adoption in practice and research.
Decubitus is one of the most relevant diseases in nursing and the most expensive to treat. It is caused by sustained pressure on tissue, so it particularly affects bed-bound patients. This work lays a foundation for pressure mattress-based decubitus prophylaxis by implementing a solution to the single-frame 2D Human Pose Estimation problem.
For this, methods of Deep Learning are employed. Two approaches are examined, a coarse-to-fine Convolutional Neural Network for direct regression of joint coordinates and a U-Net for the derivation of probability distribution heatmaps.
We conclude that training our models on a combined dataset of the publicly available Bodies at Rest and SLP data yields the best results. Furthermore, various preprocessing techniques are investigated, and a hyperparameter optimization is performed to discover an improved model architecture.
Another finding indicates that the heatmap-based approach outperforms direct regression.
This model achieves a mean per-joint position error of 9.11 cm for the Bodies at Rest data and 7.43 cm for the SLP data.
We find that it generalizes well on data from mattresses other than those seen during training but has difficulties detecting the arms correctly.
Additionally, we give a brief overview of the medical data annotation tool annoto we developed in the bachelor project and furthermore conclude that the Scrum framework and agile practices enhanced our development workflow.
RailChain
(2023)
The RailChain project designed, implemented, and experimentally evaluated a juridical recorder that is based on a distributed consensus protocol. That juridical blockchain recorder has been realized as distributed ledger on board the advanced TrainLab (ICE-TD 605 017) of Deutsche Bahn.
For the project, a consortium consisting of DB Systel, Siemens, Siemens Mobility, the Hasso Plattner Institute for Digital Engineering, Technische Universität Braunschweig, TÜV Rheinland InterTraffic, and Spherity has been formed. These partners not only concentrated competencies in railway operation, computer science, regulation, and approval, but also combined experiences from industry, research from academia, and enthusiasm from startups.
Distributed ledger technologies (DLTs) define distributed databases and express a digital protocol for transactions between business partners without the need for a trusted intermediary. The implementation of a blockchain with real-time requirements for the local network of a railway system (e.g., interlocking or train) allows to log data in the distributed system verifiably in real-time. For this, railway-specific assumptions can be leveraged to make modifications to standard blockchains protocols.
EULYNX and OCORA (Open CCS On-board Reference Architecture) are parts of a future European reference architecture for control command and signalling (CCS, Reference CCS Architecture – RCA). Both architectural concepts outline heterogeneous IT systems with components from multiple manufacturers. Such systems introduce novel challenges for the approved and safety-relevant CCS of railways which were considered neither for road-side nor for on-board systems so far. Logging implementations, such as the common juridical recorder on vehicles, can no longer be realized as a central component of a single manufacturer. All centralized approaches are in question.
The research project RailChain is funded by the mFUND program and gives practical evidence that distributed consensus protocols are a proper means to immutably (for legal purposes) store state information of many system components from multiple manufacturers. The results of RailChain have been published, prototypically implemented, and experimentally evaluated in large-scale field tests on the advanced TrainLab. At the same time, the project showed how RailChain can be integrated into the road-side and on-board architecture given by OCORA and EULYNX.
Logged data can now be analysed sooner and also their trustworthiness is being increased. This enables, e.g., auditable predictive maintenance, because it is ensured that data is authentic and unmodified at any point in time.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2018. Selected projects have presented their results on April 17th and November 14th 2017 at the Future SOC Lab Day events.
In this thesis, we investigate language learning in the formalisation of Gold [Gol67]. Here, a learner, being successively presented all information of a target language, conjectures which language it believes to be shown. Once these hypotheses converge syntactically to a correct explanation of the target language, the learning is considered successful. Fittingly, this is termed explanatory learning. To model learning strategies, we impose restrictions on the hypotheses made, for example requiring the conjectures to follow a monotonic behaviour. This way, we can study the impact a certain restriction has on learning.
Recently, the literature shifted towards map charting. Here, various seemingly unrelated restrictions are contrasted, unveiling interesting relations between them. The results are then depicted in maps. For explanatory learning, the literature already provides maps of common restrictions for various forms of data presentation.
In the case of behaviourally correct learning, where the learners are required to converge semantically instead of syntactically, the same restrictions as in explanatory learning have been investigated. However, a similarly complete picture regarding their interaction has not been presented yet.
In this thesis, we transfer the map charting approach to behaviourally correct learning. In particular, we complete the partial results from the literature for many well-studied restrictions and provide full maps for behaviourally correct learning with different types of data presentation. We also study properties of learners assessed important in the literature. We are interested whether learners are consistent, that is, whether their conjectures include the data they are built on. While learners cannot be assumed consistent in explanatory learning, the opposite is the case in behaviourally correct learning. Even further, it is known that learners following different restrictions may be assumed consistent. We contribute to the literature by showing that this is the case for all studied restrictions.
We also investigate mathematically interesting properties of learners. In particular, we are interested in whether learning under a given restriction may be done with strongly Bc-locking learners. Such learners are of particular value as they allow to apply simulation arguments when, for example, comparing two learning paradigms to each other. The literature gives a rich ground on when learners may be assumed strongly Bc-locking, which we complete for all studied restrictions.
The amount of data stored in databases and the complexity of database workloads are ever- increasing. Database management systems (DBMSs) offer many configuration options, such as index creation or unique constraints, which must be adapted to the specific instance to efficiently process large volumes of data. Currently, such database optimization is complicated, manual work performed by highly skilled database administrators (DBAs). In cloud scenarios, manual database optimization even becomes infeasible: it exceeds the abilities of the best DBAs due to the enormous number of deployed DBMS instances (some providers maintain millions of instances), missing domain knowledge resulting from data privacy requirements, and the complexity of the configuration tasks.
Therefore, we investigate how to automate the configuration of DBMSs efficiently with the help of unsupervised database optimization. While there are numerous configuration options, in this thesis, we focus on automatic index selection and the use of data dependencies, such as functional dependencies, for query optimization. Both aspects have an extensive performance impact and complement each other by approaching unsupervised database optimization from different perspectives.
Our contributions are as follows: (1) we survey automated state-of-the-art index selection algorithms regarding various criteria, e.g., their support for index interaction. We contribute an extensible platform for evaluating the performance of such algorithms with industry-standard datasets and workloads. The platform is well-received by the community and has led to follow-up research. With our platform, we derive the strengths and weaknesses of the investigated algorithms. We conclude that existing solutions often have scalability issues and cannot quickly determine (near-)optimal solutions for large problem instances. (2) To overcome these limitations, we present two new algorithms. Extend determines (near-)optimal solutions with an iterative heuristic. It identifies the best index configurations for the evaluated benchmarks. Its selection runtimes are up to 10 times lower compared with other near-optimal approaches. SWIRL is based on reinforcement learning and delivers solutions instantly. These solutions perform within 3 % of the optimal ones. Extend and SWIRL are available as open-source implementations.
(3) Our index selection efforts are complemented by a mechanism that analyzes workloads to determine data dependencies for query optimization in an unsupervised fashion. We describe and classify 58 query optimization techniques based on functional, order, and inclusion dependencies as well as on unique column combinations. The unsupervised mechanism and three optimization techniques are implemented in our open-source research DBMS Hyrise. Our approach reduces the Join Order Benchmark’s runtime by 26 % and accelerates some TPC-DS queries by up to 58 times.
Additionally, we have developed a cockpit for unsupervised database optimization that allows interactive experiments to build confidence in such automated techniques. In summary, our contributions improve the performance of DBMSs, support DBAs in their work, and enable them to contribute their time to other, less arduous tasks.
Pictures are a medium that helps make the past tangible and preserve memories. Without context, they are not able to do so. Pictures are brought to life by their associated stories. However, the older pictures become, the fewer contemporary witnesses can tell these stories.
Especially for large, analog picture archives, knowledge and memories are spread over many people. This creates several challenges: First, the pictures must be digitized to save them from decaying and make them available to the public. Since a simple listing of all the pictures is confusing, the pictures should be structured accessibly. Second, known information that makes the stories vivid needs to be added to the pictures. Users should get the opportunity to contribute their knowledge and memories. To make this usable for all interested parties, even for older, less technophile generations, the interface should be intuitive and error-tolerant.
The resulting requirements are not covered in their entirety by any existing software solution without losing the intuitive interface or the scalability of the system.
Therefore, we have developed our digital picture archive within the scope of a bachelor project in cooperation with the Bad Harzburg-Stiftung. For the implementation of this web application, we use the UI framework React in the frontend, which communicates via a GraphQL interface with the Content Management System Strapi in the backend. The use of this system enables our project partner to create an efficient process from scanning analog pictures to presenting them to visitors in an organized and annotated way. To customize the solution for both picture delivery and information contribution for our target group, we designed prototypes and evaluated them with people from Bad Harzburg. This helped us gain valuable insights into our system’s usability and future challenges as well as requirements.
Our web application is already being used daily by our project partner. During the project, we still came up with numerous ideas for additional features to further support the exchange of knowledge.
Accurately solving classification problems nowadays is likely to be the most relevant machine learning task. Binary classification separating two classes only is algorithmically simpler but has fewer potential applications as many real-world problems are multi-class. On the reverse, separating only a subset of classes simplifies the classification task. Even though existing multi-class machine learning algorithms are very flexible regarding the number of classes, they assume that the target set Y is fixed and cannot be restricted once the training is finished. On the other hand, existing state-of-the-art production environments are becoming increasingly interconnected with the advance of Industry 4.0 and related technologies such that additional information can simplify the respective classification problems. In light of this, the main aim of this thesis is to introduce dynamic classification that generalizes multi-class classification such that the target class set can be restricted arbitrarily to a non-empty class subset M of Y at any time between two consecutive predictions.
This task is solved by a combination of two algorithmic approaches. First, classifier calibration, which transforms predictions into posterior probability estimates that are intended to be well calibrated. The analysis provided focuses on monotonic calibration and in particular corrects wrong statements that appeared in the literature. It also reveals that bin-based evaluation metrics, which became popular in recent years, are unjustified and should not be used at all. Next, the validity of Platt scaling, which is the most relevant parametric calibration approach, is analyzed in depth. In particular, its optimality for classifier predictions distributed according to four different families of probability distributions as well its equivalence with Beta calibration up to a sigmoidal preprocessing are proven. For non-monotonic calibration, extended variants on kernel density estimation and the ensemble method EKDE are introduced. Finally, the calibration techniques are evaluated using a simulation study with complete information as well as on a selection of 46 real-world data sets.
Building on this, classifier calibration is applied as part of decomposition-based classification that aims to reduce multi-class problems to simpler (usually binary) prediction tasks. For the involved fusing step performed at prediction time, a new approach based on evidence theory is presented that uses classifier calibration to model mass functions. This allows the analysis of decomposition-based classification against a strictly formal background and to prove closed-form equations for the overall combinations. Furthermore, the same formalism leads to a consistent integration of dynamic class information, yielding a theoretically justified and computationally tractable dynamic classification model. The insights gained from this modeling are combined with pairwise coupling, which is one of the most relevant reduction-based classification approaches, such that all individual predictions are combined with a weight. This not only generalizes existing works on pairwise coupling but also enables the integration of dynamic class information.
Lastly, a thorough empirical study is performed that compares all newly introduced approaches to existing state-of-the-art techniques. For this, evaluation metrics for dynamic classification are introduced that depend on corresponding sampling strategies. Thereafter, these are applied during a three-part evaluation. First, support vector machines and random forests are applied on 26 data sets from the UCI Machine Learning Repository. Second, two state-of-the-art deep neural networks are evaluated on five benchmark data sets from a relatively recent reference work. Here, computationally feasible strategies to apply the presented algorithms in combination with large-scale models are particularly relevant because a naive application is computationally intractable. Finally, reference data from a real-world process allowing the inclusion of dynamic class information are collected and evaluated. The results show that in combination with support vector machines and random forests, pairwise coupling approaches yield the best results, while in combination with deep neural networks, differences between the different approaches are mostly small to negligible. Most importantly, all results empirically confirm that dynamic classification succeeds in improving the respective prediction accuracies. Therefore, it is crucial to pass dynamic class information in respective applications, which requires an appropriate digital infrastructure.
Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.
Defining the metaverse
(2023)
The term Metaverse is emerging as a result of the late push by multinational technology conglomerates and a recent surge of interest in Web 3.0, Blockchain, NFT, and Cryptocurrencies. From a scientific point of view, there is no definite consensus on what the Metaverse will be like. This paper collects, analyzes, and synthesizes scientific definitions and the accompanying major characteristics of the Metaverse using the methodology of a Systematic Literature Review (SLR). Two revised definitions for the Metaverse are presented, both condensing the key attributes, where the first one is rather simplistic holistic describing “a three-dimensional online environment in which users represented by avatars interact with each other in virtual spaces decoupled from the real physical world”. In contrast, the second definition is specified in a more detailed manner in the paper and further discussed. These comprehensive definitions offer specialized and general scholars an application within and beyond the scientific context of the system science, information system science, computer science, and business informatics, by also introducing open research challenges. Furthermore, an outlook on the social, economic, and technical implications is given, and the preconditions that are necessary for a successful implementation are discussed.
Like conventional software projects, projects in model-driven software engineering require adequate management of multiple versions of development artifacts, importantly allowing living with temporary inconsistencies. In the case of model-driven software engineering, employed versioning approaches also have to handle situations where different artifacts, that is, different models, are linked via automatic model transformations.
In this report, we propose a technique for jointly handling the transformation of multiple versions of a source model into corresponding versions of a target model, which enables the use of a more compact representation that may afford improved execution time of both the transformation and further analysis operations. Our approach is based on the well-known formalism of triple graph grammars and a previously introduced encoding of model version histories called multi-version models. In addition to showing the correctness of our approach with respect to the standard semantics of triple graph grammars, we conduct an empirical evaluation that demonstrates the potential benefit regarding execution time performance.
Modular and incremental global model management with extended generalized discrimination networks
(2023)
Complex projects developed under the model-driven engineering paradigm nowadays often involve several interrelated models, which are automatically processed via a multitude of model operations. Modular and incremental construction and execution of such networks of models and model operations are required to accommodate efficient development with potentially large-scale models. The underlying problem is also called Global Model Management.
In this report, we propose an approach to modular and incremental Global Model Management via an extension to the existing technique of Generalized Discrimination Networks (GDNs). In addition to further generalizing the notion of query operations employed in GDNs, we adapt the previously query-only mechanism to operations with side effects to integrate model transformation and model synchronization. We provide incremental algorithms for the execution of the resulting extended Generalized Discrimination Networks (eGDNs), as well as a prototypical implementation for a number of example eGDN operations.
Based on this prototypical implementation, we experiment with an application scenario from the software development domain to empirically evaluate our approach with respect to scalability and conceptually demonstrate its applicability in a typical scenario. Initial results confirm that the presented approach can indeed be employed to realize efficient Global Model Management in the considered scenario.
Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene- based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for mis- sense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood- ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use it to interpret associations and identify potential novel gain of function variants in PIEZO1. Our results show the benefits of investigating different functional mechanisms when performing rare-variant association tests, and demonstrate pervasive rare-variant contribution to biomarker variability.
In the last two decades, process mining has developed from a niche
discipline to a significant research area with considerable impact on academia and industry. Process mining enables organisations to identify the running business processes from historical execution data. The first requirement of any process mining technique is an event log, an artifact that represents concrete business process executions in the form of sequence of events. These logs can be extracted from the organization's information systems and are used by process experts to retrieve deep insights from the organization's running processes. Considering the events pertaining to such logs, the process models can be automatically discovered and enhanced or annotated with performance-related information. Besides behavioral information, event logs contain domain specific data, albeit implicitly. However, such data are usually overlooked and, thus, not utilized to their full potential.
Within the process mining area, we address in this thesis the research gap of discovering, from event logs, the contextual information that cannot be captured by applying existing process mining techniques. Within this research gap, we identify four key problems and tackle them by looking at an event log from different angles. First, we address the problem of deriving an event log in the absence of a proper database access and domain knowledge. The second problem is related to the under-utilization of the implicit domain knowledge present in an event log that can increase the understandability of the discovered process model. Next, there is a lack of a holistic representation of the historical data manipulation at the process model level of abstraction. Last but not least, each process model presumes to be independent of other process models when discovered from an event log, thus, ignoring possible data dependencies between processes within an organization.
For each of the problems mentioned above, this thesis proposes a dedicated method. The first method provides a solution to extract an event log only from the transactions performed on the database that are stored in the form of redo logs. The second method deals with discovering the underlying data model that is implicitly embedded in the event log, thus, complementing the discovered process model with important domain knowledge information. The third method captures, on the process model level, how the data affects the running process instances. Lastly, the fourth method is about the discovery of the relations between business processes (i.e., how they exchange data) from a set of event logs and explicitly representing such complex interdependencies in a business process architecture.
All the methods introduced in this thesis are implemented as a prototype and their feasibility is proven by being applied on real-life event logs.
The highly structured nature of the educational sector demands effective policy mechanisms close to the needs of the field. That is why evidence-based policy making, endorsed by the European Commission under Erasmus+ Key Action 3, aims to make an alignment between the domains of policy and practice. Against this background, this article addresses two issues: First, that there is a vertical gap in the translation of higher-level policies to local strategies and regulations. Second, that there is a horizontal gap between educational domains regarding the policy awareness of individual players. This was analyzed in quantitative and qualitative studies with domain experts from the fields of virtual mobility and teacher training. From our findings, we argue that the combination of both gaps puts the academic bridge from secondary to tertiary education at risk, including the associated knowledge proficiency levels. We discuss the role of digitalization in the academic bridge by asking the question: which value does the involved stakeholders expect from educational policies? As a theoretical basis, we rely on the model of value co-creation for and by stakeholders. We describe the used instruments along with the obtained results and proposed benefits. Moreover, we reflect on the methodology applied, and we finally derive recommendations for future academic bridge policies.
Learning from failure
(2022)
Regression testing is a widespread practice in today's software industry to ensure software product quality. Developers derive a set of test cases, and execute them frequently to ensure that their change did not adversely affect existing functionality. As the software product and its test suite grow, the time to feedback during regression test sessions increases, and impedes programmer productivity: developers wait longer for tests to complete, and delays in fault detection render fault removal increasingly difficult.
Test case prioritization addresses the problem of long feedback loops by reordering test cases, such that test cases of high failure probability run first, and test case failures become actionable early in the testing process. We ask, given test execution schedules reconstructed from publicly available data, to which extent can their fault detection efficiency improved, and which technique yields the most efficient test schedules with respect to APFD?
To this end, we recover regression 6200 test sessions from the build log files of Travis CI, a popular continuous integration service, and gather 62000 accompanying changelists. We evaluate the efficiency of current test schedules, and examine the prioritization results of state-of-the-art lightweight, history-based heuristics. We propose and evaluate a novel set of prioritization algorithms, which connect software changes and test failures in a matrix-like data structure.
Our studies indicate that the optimization potential is substantial, because the existing test plans score only 30% APFD. The predictive power of past test failures proves to be outstanding: simple heuristics, such as repeating tests with failures in recent sessions, result in efficiency scores of 95% APFD. The best-performing matrix-based heuristic achieves a similar score of 92.5% APFD. In contrast to prior approaches, we argue that matrix-based techniques are useful beyond the scope of effective prioritization, and enable a number of use cases involving software maintenance.
We validate our findings from continuous integration processes by extending a continuous testing tool within development environments with means of test prioritization, and pose further research questions. We think that our findings are suited to propel adoption of (continuous) testing practices, and that programmers' toolboxes should contain test prioritization as an existential productivity tool.
N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully functional platforms are not yet available. Here, we present the open source StudyU platform, which includes the StudyU Designer and StudyU app. With the StudyU Designer, scientists are given a collaborative web application to digitally specify, publish, and conduct N-of-1 trials. The StudyU app is a smartphone app with innovative user-centric elements for participants to partake in trials published through the StudyU Designer to assess the effects of different interventions on their health. Thereby, the StudyU platform allows clinicians and researchers worldwide to easily design and conduct digital N-of-1 trials in a safe manner. We envision that StudyU can change the landscape of personalized treatments both for patients and healthy individuals, democratize and personalize evidence generation for self-optimization and medicine, and can be integrated in clinical practice.
Cyber-physical systems often encompass complex concurrent behavior with timing constraints and probabilistic failures on demand. The analysis whether such systems with probabilistic timed behavior adhere to a given specification is essential. When the states of the system can be represented by graphs, the rule-based formalism of Probabilistic Timed Graph Transformation Systems (PTGTSs) can be used to suitably capture structure dynamics as well as probabilistic and timed behavior of the system. The model checking support for PTGTSs w.r.t. properties specified using Probabilistic Timed Computation Tree Logic (PTCTL) has been already presented. Moreover, for timed graph-based runtime monitoring, Metric Temporal Graph Logic (MTGL) has been developed for stating metric temporal properties on identified subgraphs and their structural changes over time. In this paper, we (a) extend MTGL to the Probabilistic Metric Temporal Graph Logic (PMTGL) by allowing for the specification of probabilistic properties, (b) adapt our MTGL satisfaction checking approach to PTGTSs, and (c) combine the approaches for PTCTL model checking and MTGL satisfaction checking to obtain a Bounded Model Checking (BMC) approach for PMTGL. In our evaluation, we apply an implementation of our BMC approach in AutoGraph to a running example.
Duplicate detection describes the process of finding multiple representations of the same real-world entity in the absence of a unique identifier, and has many application areas, such as customer relationship management, genealogy and social sciences, or online shopping. Due to the increasing amount of data in recent years, the problem has become even more challenging on the one hand, but has led to a renaissance in duplicate detection research on the other hand.
This thesis examines the effects and opportunities of transitive relationships on the duplicate detection process. Transitivity implies that if record pairs ⟨ri,rj⟩ and ⟨rj,rk⟩ are classified as duplicates, then also record pair ⟨ri,rk⟩ has to be a duplicate. However, this reasoning might contradict with the pairwise classification, which is usually based on the similarity of objects. An essential property of similarity, in contrast to equivalence, is that similarity is not necessarily transitive.
First, we experimentally evaluate the effect of an increasing data volume on the threshold selection to classify whether a record pair is a duplicate or non-duplicate. Our experiments show that independently of the pair selection algorithm and the used similarity measure, selecting a suitable threshold becomes more difficult with an increasing number of records due to an increased probability of adding a false duplicate to an existing cluster. Thus, the best threshold changes with the dataset size, and a good threshold for a small (possibly sampled) dataset is not necessarily a good threshold for a larger (possibly complete) dataset. As data grows over time, earlier selected thresholds are no longer a suitable choice, and the problem becomes worse for datasets with larger clusters.
Second, we present with the Duplicate Count Strategy (DCS) and its enhancement DCS++ two alternatives to the standard Sorted Neighborhood Method (SNM) for the selection of candidate record pairs. DCS adapts SNMs window size based on the number of detected duplicates and DCS++ uses transitive dependencies to save complex comparisons for finding duplicates in larger clusters. We prove that with a proper (domain- and data-independent!) threshold, DCS++ is more efficient than SNM without loss of effectiveness.
Third, we tackle the problem of contradicting pairwise classifications. Usually, the transitive closure is used for pairwise classifications to obtain a transitively closed result set. However, the transitive closure disregards negative classifications. We present three new and several existing clustering algorithms and experimentally evaluate them on various datasets and under various algorithm configurations. The results show that the commonly used transitive closure is inferior to most other clustering algorithms, especially for the precision of results. In scenarios with larger clusters, our proposed EMCC algorithm is, together with Markov Clustering, the best performing clustering approach for duplicate detection, although its runtime is longer than Markov Clustering due to the subexponential time complexity. EMCC especially outperforms Markov Clustering regarding the precision of the results and additionally has the advantage that it can also be used in scenarios where edge weights are not available.
Polyglot programming allows developers to use multiple programming languages within the same software project. While it is common to use more than one language in certain programming domains, developers also apply polyglot programming for other purposes such as to re-use software written in other languages. Although established approaches to polyglot programming come with significant limitations, for example, in terms of performance and tool support, developers still use them to be able to combine languages.
Polyglot virtual machines (VMs) such as GraalVM provide a new level of polyglot programming, allowing languages to directly interact with each other. This reduces the amount of glue code needed to combine languages, results in better performance, and enables tools such as debuggers to work across languages. However, only a little research has focused on novel tools that are designed to support developers in building software with polyglot VMs. One reason is that tool-building is often an expensive activity, another one is that polyglot VMs are still a moving target as their use cases and requirements are not yet well understood.
In this thesis, we present an approach that builds on existing self-sustaining programming systems such as Squeak/Smalltalk to enable exploratory programming, a practice for exploring and gathering software requirements, and re-use their extensive tool-building capabilities in the context of polyglot VMs. Based on TruffleSqueak, our implementation for the GraalVM, we further present five case studies that demonstrate how our approach helps tool developers to design and build tools for polyglot programming. We further show that TruffleSqueak can also be used by application developers to build and evolve polyglot applications at run-time and by language and runtime developers to understand the dynamic behavior of GraalVM languages and internals. Since our platform allows all these developers to apply polyglot programming, it can further help to better understand the advantages, use cases, requirements, and challenges of polyglot VMs. Moreover, we demonstrate that our approach can also be applied to other polyglot VMs and that insights gained through it are transferable to other programming systems.
We conclude that our research on tools for polyglot programming is an important step toward making polyglot VMs more approachable for developers in practice. With good tool support, we believe polyglot VMs can make it much more common for developers to take advantage of multiple languages and their ecosystems when building software.
Identity management is at the forefront of applications’ security posture. It separates the unauthorised user from the legitimate individual. Identity management models have evolved from the isolated to the centralised paradigm and identity federations. Within this advancement, the identity provider emerged as a trusted third party that holds a powerful position. Allen postulated the novel self-sovereign identity paradigm to establish a new balance. Thus, extensive research is required to comprehend its virtues and limitations. Analysing the new paradigm, initially, we investigate the blockchain-based self-sovereign identity concept structurally. Moreover, we examine trust requirements in this context by reference to patterns. These shapes comprise major entities linked by a decentralised identity provider. By comparison to the traditional models, we conclude that trust in credential management and authentication is removed. Trust-enhancing attribute aggregation based on multiple attribute providers provokes a further trust shift. Subsequently, we formalise attribute assurance trust modelling by a metaframework. It encompasses the attestation and trust network as well as the trust decision process, including the trust function, as central components. A secure attribute assurance trust model depends on the security of the trust function. The trust function should consider high trust values and several attribute authorities. Furthermore, we evaluate classification, conceptual study, practical analysis and simulation as assessment strategies of trust models. For realising trust-enhancing attribute aggregation, we propose a probabilistic approach. The method exerts the principle characteristics of correctness and validity. These values are combined for one provider and subsequently for multiple issuers. We embed this trust function in a model within the self-sovereign identity ecosystem. To practically apply the trust function and solve several challenges for the service provider that arise from adopting self-sovereign identity solutions, we conceptualise and implement an identity broker. The mediator applies a component-based architecture to abstract from a single solution. Standard identity and access management protocols build the interface for applications. We can conclude that the broker’s usage at the side of the service provider does not undermine self-sovereign principles, but fosters the advancement of the ecosystem. The identity broker is applied to sample web applications with distinct attribute requirements to showcase usefulness for authentication and attribute-based access control within a case study.
Modeling and Formal Analysis of Meta-Ecosystems with Dynamic Structure using Graph Transformation
(2022)
The dynamics of ecosystems is of crucial importance. Various model-based approaches exist to understand and analyze their internal effects. In this paper, we model the space structure dynamics and ecological dynamics of meta-ecosystems using the formal technique of Graph Transformation (short GT). We build GT models to describe how a meta-ecosystem (modeled as a graph) can evolve over time (modeled by GT rules) and to analyze these GT models with respect to qualitative properties such as the existence of structural stabilities. As a case study, we build three GT models describing the space structure dynamics and ecological dynamics of three different savanna meta-ecosystems. The first GT model considers a savanna meta-ecosystem that is limited in space to two ecosystem patches, whereas the other two GT models consider two savanna meta-ecosystems that are unlimited in the number of ecosystem patches and only differ in one GT rule describing how the space structure of the meta-ecosystem grows. In the first two GT models, the space structure dynamics and ecological dynamics of the meta-ecosystem shows two main structural stabilities: the first one based on grassland-savanna-woodland transitions and the second one based on grassland-desert transitions. The transition between these two structural stabilities is driven by high-intensity fires affecting the tree components. In the third GT model, the GT rule for savanna regeneration induces desertification and therefore a collapse of the meta-ecosystem. We believe that GT models provide a complementary avenue to that of existing approaches to rigorously study ecological phenomena.
Cyber-physical systems often encompass complex concurrent behavior with timing constraints and probabilistic failures on demand. The analysis whether such systems with probabilistic timed behavior adhere to a given specification is essential. When the states of the system can be represented by graphs, the rule-based formalism of Probabilistic Timed Graph Transformation Systems (PTGTSs) can be used to suitably capture structure dynamics as well as probabilistic and timed behavior of the system. The model checking support for PTGTSs w.r.t. properties specified using Probabilistic Timed Computation Tree Logic (PTCTL) has been already presented. Moreover, for timed graph-based runtime monitoring, Metric Temporal Graph Logic (MTGL) has been developed for stating metric temporal properties on identified subgraphs and their structural changes over time.
In this paper, we (a) extend MTGL to the Probabilistic Metric Temporal Graph Logic (PMTGL) by allowing for the specification of probabilistic properties, (b) adapt our MTGL satisfaction checking approach to PTGTSs, and (c) combine the approaches for PTCTL model checking and MTGL satisfaction checking to obtain a Bounded Model Checking (BMC) approach for PMTGL. In our evaluation, we apply an implementation of our BMC approach in AutoGraph to a running example.
The analysis of behavioral models such as Graph Transformation Systems (GTSs) is of central importance in model-driven engineering. However, GTSs often result in intractably large or even infinite state spaces and may be equipped with multiple or even infinitely many start graphs. To mitigate these problems, static analysis techniques based on finite symbolic representations of sets of states or paths thereof have been devised. We focus on the technique of k-induction for establishing invariants specified using graph conditions. To this end, k-induction generates symbolic paths backwards from a symbolic state representing a violation of a candidate invariant to gather information on how that violation could have been reached possibly obtaining contradictions to assumed invariants. However, GTSs where multiple agents regularly perform actions independently from each other cannot be analyzed using this technique as of now as the independence among backward steps may prevent the gathering of relevant knowledge altogether.
In this paper, we extend k-induction to GTSs with multiple agents thereby supporting a wide range of additional GTSs. As a running example, we consider an unbounded number of shuttles driving on a large-scale track topology, which adjust their velocity to speed limits to avoid derailing. As central contribution, we develop pruning techniques based on causality and independence among backward steps and verify that k-induction remains sound under this adaptation as well as terminates in cases where it did not terminate before.
It is estimated that data scientists spend up to 80% of the time exploring, cleaning, and transforming their data. A major reason for that expenditure is the lack of knowledge about the used data, which are often from different sources and have heterogeneous structures. As a means to describe various properties of data, metadata can help data scientists understand and prepare their data, saving time for innovative and valuable data analytics. However, metadata do not always exist: some data file formats are not capable of storing them; metadata were deleted for privacy concerns; legacy data may have been produced by systems that were not designed to store and handle meta- data. As data are being produced at an unprecedentedly fast pace and stored in diverse formats, manually creating metadata is not only impractical but also error-prone, demanding automatic approaches for metadata detection.
In this thesis, we are focused on detecting metadata in CSV files – a type of plain-text file that, similar to spreadsheets, may contain different types of content at arbitrary positions. We propose a taxonomy of metadata in CSV files and specifically address the discovery of three different metadata: line and cell type, aggregations, and primary keys and foreign keys.
Data are organized in an ad-hoc manner in CSV files, and do not follow a fixed structure, which is assumed by common data processing tools. Detecting the structure of such files is a prerequisite of extracting information from them, which can be addressed by detecting the semantic type, such as header, data, derived, or footnote, of each line or each cell. We propose the supervised- learning approach Strudel to detect the type of lines and cells. CSV files may also include aggregations. An aggregation represents the arithmetic relationship between a numeric cell and a set of other numeric cells. Our proposed AggreCol algorithm is capable of detecting aggregations of five arithmetic functions in CSV files. Note that stylistic features, such as font style and cell background color, do not exist in CSV files. Our proposed algorithms address the respective problems by using only content, contextual, and computational features.
Storing a relational table is also a common usage of CSV files. Primary keys and foreign keys are important metadata for relational databases, which are usually not present for database instances dumped as plain-text files. We propose the HoPF algorithm to holistically detect both constraints in relational databases. Our approach is capable of distinguishing true primary and foreign keys from a great amount of spurious unique column combinations and inclusion dependencies, which can be detected by state-of-the-art data profiling algorithms.
“Broadcast your gender.”
(2022)
Social media platforms provide a large array of behavioral data relevant to social scientific research. However, key information such as sociodemographic characteristics of agents are often missing. This paper aims to compare four methods of classifying social attributes from text. Specifically, we are interested in estimating the gender of German social media creators. By using the example of a random sample of 200 YouTube channels, we compare several classification methods, namely (1) a survey among university staff, (2) a name dictionary method with the World Gender Name Dictionary as a reference list, (3) an algorithmic approach using the website gender-api.com, and (4) a Multinomial Naïve Bayes (MNB) machine learning technique. These different methods identify gender attributes based on YouTube channel names and descriptions in German but are adaptable to other languages. Our contribution will evaluate the share of identifiable channels, accuracy and meaningfulness of classification, as well as limits and benefits of each approach. We aim to address methodological challenges connected to classifying gender attributes for YouTube channels as well as related to reinforcing stereotypes and ethical implications.
openHPI
(2022)
Anlässlich des 10-jährigen Jubiläums von openHPI informiert dieser technische Bericht über die HPI-MOOC-Plattform einschließlich ihrer Kernfunktionen, Technologie und Architektur.
In einer Einleitung wird die Plattformfamilie mit allen Partnerplattformen vorgestellt; diese belaufen sich inklusive openHPI aktuell auf neun Plattformen. In diesem Abschnitt wird außerdem gezeigt, wie openHPI als Berater und Forschungspartner in verschiedenen Projekten fungiert.
Im zweiten Kapitel werden die Funktionalitäten und gängigen Kursformate der Plattform präsentiert. Die Funktionalitäten sind in Lerner- und Admin-Funktionen unterteilt. Der Bereich Lernerfunktionen bietet detaillierte Informationen zu Leistungsnachweisen, Kursen und den Lernmaterialien, aus denen sich ein Kurs zusammensetzt: Videos, Texte und Quiz. Darüber hinaus können die Lernmaterialien durch externe Übungstools angereichert werden, die über den Standard Learning Tools Interoperability (LTI) mit der HPI MOOC-Plattform kommunizieren. Das Konzept der Peer-Assessments rundet die möglichen Lernmaterialien ab.
Der Abschnitt geht dann weiter auf das Diskussionsforum ein, das einen grundlegenden Unterschied von MOOCs im Vergleich zu traditionellen E-Learning-Angeboten darstellt. Zum Abschluss des Abschnitts folgen eine Beschreibung von Quiz-Recap, Lernzielen, mobilen Anwendungen, spielerischen Lernens und dem Helpdesk.
Der nächste Teil dieses Kapitels beschäftigt sich mit den Admin-Funktionen. Die Funktionalitätsbeschreibung beschränkt sich Neuigkeiten und Ankündigungen, Dashboards und Statistiken, Berichtsfunktionen, Forschungsoptionen mit A/B-Tests, den Kurs-Feed und das TransPipe-Tool zur Unterstützung beim Erstellen von automatischen oder manuellen Untertiteln. Die Plattform unterstützt außerdem eine Vielzahl zusätzlicher Funktionen, doch eine detaillierte Beschreibung dieser Funktionen würde den Rahmen des Berichts sprengen.
Das Kapitel geht dann auf gängige Kursformate und openHPI-Lehrveranstaltungen am HPI ein, bevor es mit einigen Best Practices für die Gestaltung und Durchführung von Kursen schließt.
Zum Abschluss des technischen Berichts gibt das letzte Kapitel eine Zusammenfassung und einen Ausblick auf die Zukunft der digitalen Bildung.
Ein besonderes Merkmal des openHPI-Projekts ist die bewusste Entscheidung, die komplette Anwendung von den physischen Netzwerkkomponenten bis zur Plattformentwicklung eigenständig zu betreiben. Bei der vorliegenden deutschen Variante handelt es sich um eine gekürzte Übersetzung des technischen Berichts 148, bei der kein Einblick in die Technologien und Architektur von openHPI gegeben wird. Interessierte Leser:innen können im technischen Bericht 148 (vollständige englische Version) detaillierte Informationen zum Rechenzentrum und den Geräten, der Cloud-Software und dem openHPI Cloud Service aber auch zu Infrastruktur-Anwendungskomponenten wie Entwicklungstools, Automatisierung, Deployment-Pipeline und Monitoring erhalten. Außerdem finden sich dort weitere Informationen über den Technologiestack und konkrete Implementierungsdetails der Plattform inklusive der serviceorientierten Ruby on Rails-Anwendung, die Kommunikation zwischen den Diensten, öffentliche APIs, sowie Designsystem und -komponenten. Der Abschnitt schließt mit einer Diskussion über die ursprüngliche Microservice-Architektur und die Migration zu einer monolithischen Anwendung.
openHPI
(2022)
On the occasion of the 10th openHPI anniversary, this technical report provides information about the HPI MOOC platform, including its core features, technology, and architecture.
In an introduction, the platform family with all partner platforms is presented; these now amount to nine platforms, including openHPI. This section introduces openHPI as an advisor and research partner in various projects.
In the second chapter, the functionalities and common course formats of the platform are presented. The functionalities are divided into learner and admin features. The learner features section provides detailed information about performance records, courses, and the learning materials of which a course is composed: videos, texts, and quizzes. In addition, the learning materials can be enriched by adding external exercise tools that communicate with the HPI MOOC platform via the Learning Tools Interoperability (LTI) standard. Furthermore, the concept of peer assessments completed the possible learning materials.
The section then proceeds with further information on the discussion forum, a fundamental concept of MOOCs compared to traditional e-learning offers. The section is concluded with a description of the quiz recap, learning objectives, mobile applications, gameful learning, and the help desk.
The next part of this chapter deals with the admin features. The described functionality is restricted to describing the news and announcements, dashboards and statistics, reporting capabilities, research options with A/B testing, the course feed, and the TransPipe tool to support the process of creating automated or manual subtitles. The platform supports a large variety of additional features, but a detailed description of these features goes beyond the scope of this report.
The chapter then elaborates on common course formats and openHPI teaching activities at the HPI. The chapter concludes with some best practices for course design and delivery.
The third chapter provides insights into the technology and architecture behind openHPI. A special characteristic of the openHPI project is the conscious decision to operate the complete application from bare metal to platform development. Hence, the chapter starts with a section about the openHPI Cloud, including detailed information about the data center and devices, the used cloud software OpenStack and Ceph, as well as the openHPI Cloud Service provided for the HPI.
Afterward, a section on the application technology stack and development tooling describes the application infrastructure components, the used automation, the deployment pipeline, and the tools used for monitoring and alerting. The chapter is concluded with detailed information about the technology stack and concrete platform implementation details. The section describes the service-oriented Ruby on Rails application, inter-service communication, and public APIs. It also provides more information on the design system and components used in the application. The section concludes with a discussion of the original microservice architecture, where we share our insights and reasoning for migrating back to a monolithic application.
The last chapter provides a summary and an outlook on the future of digital education.
Scrollytellings are an innovative form of web content. Combining the benefits of books, images, movies, and video games, they are a tool to tell compelling stories and provide excellent learning opportunities. Due to their multi-modality, creating high-quality scrollytellings is not an easy task. Different professions, such as content designers, graphics designers, and developers, need to collaborate to get the best out of the possibilities the scrollytelling format provides. Collaboration unlocks great potential. However, content designers cannot create scrollytellings directly and always need to consult with developers to implement their vision. This can result in misunderstandings. Often, the resulting scrollytelling will not match the designer’s vision sufficiently, causing unnecessary iterations. Our project partner Typeshift specializes in the creation of individualized scrollytellings for their clients. Examined existing solutions for authoring interactive content are not optimally suited for creating highly customized scrollytellings while still being able to manipulate all their elements programmatically. Based on their experience and expertise, we developed an editor to author scrollytellings in the lively.next live-programming environment. In this environment, a graphical user interface for content design is combined with powerful possibilities for programming behavior with the morphic system. The editor allows content designers to take on large parts of the creation process of scrollytellings on their own, such as creating the visible elements, animating content, and fine-tuning the scrollytelling. Hence, developers can focus on interactive elements such as simulations and games. Together with Typeshift, we evaluated the tool by recreating an existing scrollytelling and identified possible future enhancements. Our editor streamlines the creation process of scrollytellings. Content designers and developers can now both work on the same scrollytelling. Due to the editor inside of the lively.next environment, they can both work with a set of tools familiar to them and their traits. Thus, we mitigate unnecessary iterations and misunderstandings by enabling content designers to realize large parts of their vision of a scrollytelling on their own. Developers can add advanced and individual behavior. Thus, developers and content designers benefit from a clearer distribution of tasks while keeping the benefits of collaboration.
Text is a ubiquitous entity in our world and daily life. We encounter it nearly everywhere in shops, on the street, or in our flats. Nowadays, more and more text is contained in digital images. These images are either taken using cameras, e.g., smartphone cameras, or taken using scanning devices such as document scanners. The sheer amount of available data, e.g., millions of images taken by Google Streetview, prohibits manual analysis and metadata extraction. Although much progress was made in the area of optical character recognition (OCR) for printed text in documents, broad areas of OCR are still not fully explored and hold many research challenges. With the mainstream usage of machine learning and especially deep learning, one of the most pressing problems is the availability and acquisition of annotated ground truth for the training of machine learning models because obtaining annotated training data using manual annotation mechanisms is time-consuming and costly. In this thesis, we address of how we can reduce the costs of acquiring ground truth annotations for the application of state-of-the-art machine learning methods to optical character recognition pipelines. To this end, we investigate how we can reduce the annotation cost by using only a fraction of the typically required ground truth annotations, e.g., for scene text recognition systems. We also investigate how we can use synthetic data to reduce the need of manual annotation work, e.g., in the area of document analysis for archival material. In the area of scene text recognition, we have developed a novel end-to-end scene text recognition system that can be trained using inexact supervision and shows competitive/state-of-the-art performance on standard benchmark datasets for scene text recognition. Our method consists of two independent neural networks, combined using spatial transformer networks. Both networks learn together to perform text localization and text recognition at the same time while only using annotations for the recognition task. We apply our model to end-to-end scene text recognition (meaning localization and recognition of words) and pure scene text recognition without any changes in the network architecture.
In the second part of this thesis, we introduce novel approaches for using and generating synthetic data to analyze handwriting in archival data. First, we propose a novel preprocessing method to determine whether a given document page contains any handwriting. We propose a novel data synthesis strategy to train a classification model and show that our data synthesis strategy is viable by evaluating the trained model on real images from an archive. Second, we introduce the new analysis task of handwriting classification. Handwriting classification entails classifying a given handwritten word image into classes such as date, word, or number. Such an analysis step allows us to select the best fitting recognition model for subsequent text recognition; it also allows us to reason about the semantic content of a given document page without the need for fine-grained text recognition and further analysis steps, such as Named Entity Recognition. We show that our proposed approaches work well when trained on synthetic data. Further, we propose a flexible metric learning approach to allow zero-shot classification of classes unseen during the network’s training. Last, we propose a novel data synthesis algorithm to train off-the-shelf pixel-wise semantic segmentation networks for documents. Our data synthesis pipeline is based on the famous Style-GAN architecture and can synthesize realistic document images with their corresponding segmentation annotation without the need for any annotated data!
A decade ago, it became feasible to store multi-terabyte databases in main memory. These in-memory databases (IMDBs) profit from DRAM's low latency and high throughput as well as from the removal of costly abstractions used in disk-based systems, such as the buffer cache. However, as the DRAM technology approaches physical limits, scaling these databases becomes difficult. Non-volatile memory (NVM) addresses this challenge. This new type of memory is persistent, has more capacity than DRAM (4x), and does not suffer from its density-inhibiting limitations. Yet, as NVM has a higher latency (5-15x) and a lower throughput (0.35x), it cannot fully replace DRAM.
IMDBs thus need to navigate the trade-off between the two memory tiers. We present a solution to this optimization problem. Leveraging information about access frequencies and patterns, our solution utilizes NVM's additional capacity while minimizing the associated access costs. Unlike buffer cache-based implementations, our tiering abstraction does not add any costs when reading data from DRAM. As such, it can act as a drop-in replacement for existing IMDBs. Our contributions are as follows:
(1) As the foundation for our research, we present Hyrise, an open-source, columnar IMDB that we re-engineered and re-wrote from scratch. Hyrise enables realistic end-to-end benchmarks of SQL workloads and offers query performance which is competitive with other research and commercial systems. At the same time, Hyrise is easy to understand and modify as repeatedly demonstrated by its uses in research and teaching.
(2) We present a novel memory management framework for different memory and storage tiers. By encapsulating the allocation and access methods of these tiers, we enable existing data structures to be stored on different tiers with no modifications to their implementation. Besides DRAM and NVM, we also support and evaluate SSDs and have made provisions for upcoming technologies such as disaggregated memory.
(3) To identify the parts of the data that can be moved to (s)lower tiers with little performance impact, we present a tracking method that identifies access skew both in the row and column dimensions and that detects patterns within consecutive accesses. Unlike existing methods that have substantial associated costs, our access counters exhibit no identifiable overhead in standard benchmarks despite their increased accuracy.
(4) Finally, we introduce a tiering algorithm that optimizes the data placement for a given memory budget. In the TPC-H benchmark, this allows us to move 90% of the data to NVM while the throughput is reduced by only 10.8% and the query latency is increased by 11.6%. With this, we outperform approaches that ignore the workload's access skew and access patterns and increase the query latency by 20% or more.
Individually, our contributions provide novel approaches to current challenges in systems engineering and database research. Combining them allows IMDBs to scale past the limits of DRAM while continuing to profit from the benefits of in-memory computing.
The heterogeneity of today's state-of-the-art computer architectures is confronting application developers with an immense degree of complexity which results from two major challenges. First, developers need to acquire profound knowledge about the programming models or the interaction models associated with each type of heterogeneous system resource to make efficient use thereof. Second, developers must take into account that heterogeneous system resources always need to exchange data with each other in order to work on a problem together. However, this data exchange is always associated with a certain amount of overhead, which is why the amounts of data exchanged should be kept as low as possible.
This thesis proposes three programming abstractions to lessen the burdens imposed by these major challenges with the goal of making heterogeneous system resources accessible to a wider range of application developers. The lib842 compression library provides the first method for accessing the compression and decompression facilities of the NX-842 on-chip compression accelerator available in IBM Power CPUs from user space applications running on Linux. Addressing application development of scale-out GPU workloads, the CloudCL framework makes the resources of GPU clusters more accessible by hiding many aspects of distributed computing while enabling application developers to focus on the aspects of the data parallel programming model associated with GPUs. Furthermore, CloudCL is augmented with transparent data compression facilities based on the lib842 library in order to improve the efficiency of data transfers among cluster nodes. The improved data transfer efficiency provided by the integration of transparent data compression yields performance improvements ranging between 1.11x and 2.07x across four data-intensive scale-out GPU workloads. To investigate the impact of programming abstractions for data placement in NUMA systems, a comprehensive evaluation of the PGASUS framework for NUMA-aware C++ application development is conducted. On a wide range of test systems, the evaluation demonstrates that PGASUS does not only improve the developer experience across all workloads, but that it is also capable of outperforming NUMA-agnostic implementations with average performance improvements of 1.56x.
Based on these programming abstractions, this thesis demonstrates that by providing a sufficient degree of abstraction, the accessibility of heterogeneous system resources can be improved for application developers without occluding performance-critical properties of the underlying hardware.
First come, first served: Critical choices between alternative actions are often made based on events external to an organization, and reacting promptly to their occurrence can be a major advantage over the competition. In Business Process Management (BPM), such deferred choices can be expressed in process models, and they are an important aspect of process engines. Blockchain-based process execution approaches are no exception to this, but are severely limited by the inherent properties of the platform: The isolated environment prevents direct access to external entities and data, and the non-continual runtime based entirely on atomic transactions impedes the monitoring and detection of events. In this paper we provide an in-depth examination of the semantics of deferred choice, and transfer them to environments such as the blockchain. We introduce and compare several oracle architectures able to satisfy certain requirements, and show that they can be implemented using state-of-the-art blockchain technology.
Language developers who design domain-specific languages or new language features need a way to make fast changes to language definitions. Those fast changes require immediate feedback. Also, it should be possible to parse the developed languages quickly to handle extensive sets of code.
Parsing expression grammars provides an easy to understand method for language definitions. Packrat parsing is a method to parse grammars of this kind, but this method is unable to handle left-recursion properly. Existing solutions either partially rewrite left-recursive rules and partly forbid them, or use complex extensions to packrat parsing that are hard to understand and cost-intensive. We investigated methods to make parsing as fast as possible, using easy to follow algorithms while not losing the ability to make fast changes to grammars.
We focused our efforts on two approaches.
One is to start from an existing technique for limited left-recursion rewriting and enhance it to work for general left-recursive grammars. The second approach is to design a grammar compilation process to find left-recursion before parsing, and in this way, reduce computational costs wherever possible and generate ready to use parser classes.
Rewriting parsing expression grammars is a task that, if done in a general way, unveils a large number of cases such that any rewriting algorithm surpasses the complexity of other left-recursive parsing algorithms. Lookahead operators introduce this complexity. However, most languages have only little portions that are left-recursive and in virtually all cases, have no indirect or hidden left-recursion. This means that the distinction of left-recursive parts of grammars from components that are non-left-recursive holds great improvement potential for existing parsers.
In this report, we list all the required steps for grammar rewriting to handle left-recursion, including grammar analysis, grammar rewriting itself, and syntax tree restructuring. Also, we describe the implementation of a parsing expression grammar framework in Squeak/Smalltalk and the possible interactions with the already existing parser Ohm/S. We quantitatively benchmarked this framework directing our focus on parsing time and the ability to use it in a live programming context. Compared with Ohm, we achieved massive parsing time improvements while preserving the ability to use our parser it as a live programming tool.
The work is essential because, for one, we outlined the difficulties and complexity that come with grammar rewriting. Also, we removed the existing limitations that came with left-recursion by eliminating them before parsing.
Traditional organizations are strongly encouraged by emerging digital customer behavior and digital competition to transform their businesses for the digital age. Incumbents are particularly exposed to the field of tension between maintaining and renewing their business model. Banking is one of the industries most affected by digitalization, with a large stream of digital innovations around Fintech. Most research contributions focus on digital innovations, such as Fintech, but there are only a few studies on the related challenges and perspectives of incumbent organizations, such as traditional banks. Against this background, this dissertation examines the specific causes, effects and solutions for traditional banks in digital transformation − an underrepresented research area so far.
The first part of the thesis examines how digitalization has changed the latent customer expectations in banking and studies the underlying technological drivers of evolving business-to-consumer (B2C) business models. Online consumer reviews are systematized to identify latent concepts of customer behavior and future decision paths as strategic digitalization effects. Furthermore, the service attribute preferences, the impact of influencing factors and the underlying customer segments are uncovered for checking accounts in a discrete choice experiment. The dissertation contributes here to customer behavior research in digital transformation, moving beyond the technology acceptance model. In addition, the dissertation systematizes value proposition types in the evolving discourse around smart products and services as key drivers of business models and market power in the platform economy.
The second part of the thesis focuses on the effects of digital transformation on the strategy development of financial service providers, which are classified along with their firm performance levels. Standard types are derived based on fuzzy-set qualitative comparative analysis (fsQCA), with facade digitalization as one typical standard type for low performing incumbent banks that lack a holistic strategic response to digital transformation. Based on this, the contradictory impact of digitalization measures on key business figures is examined for German savings banks, confirming that the shift towards digital customer interaction was not accompanied by new revenue models diminishing bank profitability. The dissertation further contributes to the discourse on digitalized work designs and the consequences for job perceptions in banking customer advisory. The threefold impact of the IT support perceived in customer interaction on the job satisfaction of customer advisors is disentangled.
In the third part of the dissertation, solutions are developed design-oriented for core action areas of digitalized business models, i.e., data and platforms. A consolidated taxonomy for data-driven business models and a future reference model for digital banking have been developed. The impact of the platform economy is demonstrated here using the example of the market entry by Bigtech. The role-based e3-value modeling is extended by meta-roles and role segments and linked to value co-creation mapping in VDML. In this way, the dissertation extends enterprise modeling research on platform ecosystems and value co-creation using the example of banking.
Complex networks like the Internet or social networks are fundamental parts of our everyday lives. It is essential to understand their structural properties and how these networks are formed. A game-theoretic approach to network design problems has become of high interest in the last decades. The reason is that many real-world networks are the outcomes of decentralized strategic behavior of independent agents without central coordination. Fabrikant, Luthra, Maneva, Papadimitriou, and Schenker proposed a game-theoretic model aiming to explain the formation of the Internet-like networks. In this model, called the Network Creation Game, agents are associated with nodes of a network. Each agent seeks to maximize her centrality by establishing costly connections to other agents. The model is relatively simple but shows a high potential in modeling complex real-world networks. In this thesis, we contribute to the line of research on variants of the Network Creation Games. Inspired by real-world networks, we propose and analyze several novel network creation models. We aim to understand the impact of certain realistic modeling assumptions on the structure of the created networks and the involved agents’ behavior.
The first natural additional objective that we consider is the network’s robustness. We consider a game where the agents seek to maximize their centrality and, at the same time, the stability of the created network against random edge failure.
Our second point of interest is a model that incorporates an underlying geometry. We consider a network creation model where the agents correspond to points in some underlying space and where edge lengths are equal to the distances between the endpoints in that space. The geometric setting captures many physical real-world networks like transport networks and fiber-optic communication networks.
We focus on the formation of social networks and consider two models that incorporate particular realistic behavior observed in real-world networks. In the first model, we embed the anti-preferential attachment link formation. Namely, we assume that the cost of the connection is proportional to the popularity of the targeted agent. Our second model is based on the observation that the probability of two persons to connect is inversely proportional to the length of their shortest chain of mutual acquaintances.
For each of the four models above, we provide a complete game-theoretical analysis. In particular, we focus on distinctive structural properties of the equilibria, the hardness of computing a best response, the quality of equilibria in comparison to the centrally designed socially optimal networks. We also analyze the game dynamics, i.e., the process of sequential strategic improvements by the agents, and analyze the convergence to an equilibrium state and its properties.
Knowledge-intensive business processes are flexible and data-driven. Therefore, traditional process modeling languages do not meet their requirements: These languages focus on highly structured processes in which data plays a minor role. As a result, process-oriented information systems fail to assist knowledge workers on executing their processes. We propose a novel case management approach that combines flexible activity-centric processes with data models, and we provide a joint semantics using colored Petri nets. The approach is suited to model, verify, and enact knowledge-intensive processes and can aid the development of information systems that support knowledge work.
Knowledge-intensive processes are human-centered, multi-variant, and data-driven. Typical domains include healthcare, insurances, and law. The processes cannot be fully modeled, since the underlying knowledge is too vast and changes too quickly. Thus, models for knowledge-intensive processes are necessarily underspecified. In fact, a case emerges gradually as knowledge workers make informed decisions. Knowledge work imposes special requirements on modeling and managing respective processes. They include flexibility during design and execution, ad-hoc adaption to unforeseen situations, and the integration of behavior and data. However, the predominantly used process modeling languages (e.g., BPMN) are unsuited for this task.
Therefore, novel modeling languages have been proposed. Many of them focus on activities' data requirements and declarative constraints rather than imperative control flow. Fragment-Based Case Management, for example, combines activity-centric imperative process fragments with declarative data requirements. At runtime, fragments can be combined dynamically, and new ones can be added. Yet, no integrated semantics for flexible activity-centric process models and data models exists.
In this thesis, Wickr, a novel case modeling approach extending fragment-based Case Management, is presented. It supports batch processing of data, sharing data among cases, and a full-fledged data model with associations and multiplicity constraints. We develop a translational semantics for Wickr targeting (colored) Petri nets. The semantics assert that a case adheres to the constraints in both the process fragments and the data models. Among other things, multiplicity constraints must not be violated. Furthermore, the semantics are extended to multiple cases that operate on shared data. Wickr shows that the data structure may reflect process behavior and vice versa. Based on its semantics, prototypes for executing and verifying case models showcase the feasibility of Wickr. Its applicability to knowledge-intensive and to data-centric processes is evaluated using well-known requirements from related work.
These days design thinking is no longer a “new approach”. Among practitioners, as well as academics, interest in the topic has gathered pace over the last two decades. However, opinions are divided over the longevity of the phenomenon: whether design thinking is merely “old wine in new bottles,” a passing trend, or still evolving as it is being spread to an increasing number of organizations and industries. Despite its growing relevance and the diffusion of design thinking, knowledge on the actual status quo in organizations remains scarce. With a new study, the research team of Prof. Uebernickel and Stefanie Gerken investigates temporal developments and changes in design thinking practices in organizations over the past six years comparing the results of the 2015 “Parts without a whole” study with current practices and future developments. Companies of all sizes and from different parts of the world participated in the survey. The findings from qualitative interviews with experts, i.e., people who have years of knowledge with design thinking, were cross-checked with the results from an exploratory analysis of the survey data. This analysis uncovers significant variances and similarities in how design thinking is interpreted and applied in businesses.
Digitale Medien sind aus unserem Alltag kaum noch wegzudenken. Einer der zentralsten Bereiche für unsere Gesellschaft, die schulische Bildung, darf hier nicht hintanstehen. Wann immer der Einsatz digital unterstützter Tools pädagogisch sinnvoll ist, muss dieser in einem sicheren Rahmen ermöglicht werden können. Die HPI Schul-Cloud ist dieser Vision gefolgt, die vom Nationalen IT-Gipfel 2016 angestoßen wurde und dem Bericht vorangestellt ist – gefolgt. Sie hat sich in den vergangenen fünf Jahren vom Pilotprojekt zur unverzichtbaren IT-Infrastruktur für zahlreiche Schulen entwickelt. Während der Corona-Pandemie hat sie für viele Tausend Schulen wichtige Unterstützung bei der Umsetzung ihres Bildungsauftrags geboten. Das Ziel, eine zukunftssichere und datenschutzkonforme Infrastruktur zur digitalen Unterstützung des Unterrichts zur Verfügung zu stellen, hat sie damit mehr als erreicht. Aktuell greifen rund 1,4 Millionen Lehrkräfte und Schülerinnen und Schüler bundesweit und an den deutschen Auslandsschulen auf die HPI Schul-Cloud zu.
Dynamic resource management is an essential requirement for private and public cloud computing environments. With dynamic resource management, the physical resources assignment to the cloud virtual resources depends on the actual need of the applications or the running services, which enhances the cloud physical resources utilization and reduces the offered services cost. In addition, the virtual resources can be moved across different physical resources in the cloud environment without an obvious impact on the running applications or services production. This means that the availability of the running services and applications in the cloud is independent on the hardware resources including the servers, switches and storage failures. This increases the reliability of using cloud services compared to the classical data-centers environments.
In this thesis we briefly discuss the dynamic resource management topic and then deeply focus on live migration as the definition of the compute resource dynamic management. Live migration is a commonly used and an essential feature in cloud and virtual data-centers environments. Cloud computing load balance, power saving and fault tolerance features are all dependent on live migration to optimize the virtual and physical resources usage. As we will discuss in this thesis, live migration shows many benefits to cloud and virtual data-centers environments, however the cost of live migration can not be ignored. Live migration cost includes the migration time, downtime, network overhead, power consumption increases and CPU overhead.
IT admins run virtual machines live migrations without an idea about the migration cost. So, resources bottlenecks, higher migration cost and migration failures might happen. The first problem that we discuss in this thesis is how to model the cost of the virtual machines live migration. Secondly, we investigate how to make use of machine learning techniques to help the cloud admins getting an estimation of this cost before initiating the migration for one of multiple virtual machines. Also, we discuss the optimal timing for a specific virtual machine before live migration to another server. Finally, we propose practical solutions that can be used by the cloud admins to be integrated with the cloud administration portals to answer the raised research questions above.
Our research methodology to achieve the project objectives is to propose empirical models based on using VMware test-beds with different benchmarks tools. Then we make use of the machine learning techniques to propose a prediction approach for virtual machines live migration cost. Timing optimization for live migration is also proposed in this thesis based on using the cost prediction and data-centers network utilization prediction. Live migration with persistent memory clusters is also discussed at the end of the thesis. The cost prediction and timing optimization techniques proposed in this thesis could be practically integrated with VMware vSphere cluster portal such that the IT admins can now use the cost prediction feature and timing optimization option before proceeding with a virtual machine live migration.
Testing results show that our proposed approach for VMs live migration cost prediction shows acceptable results with less than 20% prediction error and can be easily implemented and integrated with VMware vSphere as an example of a commonly used resource management portal for virtual data-centers and private cloud environments. The results show that using our proposed VMs migration timing optimization technique also could save up to 51% of migration time of the VMs migration time for memory intensive workloads and up to 27% of the migration time for network intensive workloads. This timing optimization technique can be useful for network admins to save migration time with utilizing higher network rate and higher probability of success.
At the end of this thesis, we discuss the persistent memory technology as a new trend in servers memory technology. Persistent memory modes of operation and configurations are discussed in detail to explain how live migration works between servers with different memory configuration set up. Then, we build a VMware cluster with persistent memory inside server and also with DRAM only servers to show the live migration cost difference between the VMs with DRAM only versus the VMs with persistent memory inside.
The analysis of behavioral models is of high importance for cyber-physical systems, as the systems often encompass complex behavior based on e.g. concurrent components with mutual exclusion or probabilistic failures on demand. The rule-based formalism of probabilistic timed graph transformation systems is a suitable choice when the models representing states of the system can be understood as graphs and timed and probabilistic behavior is important. However, model checking PTGTSs is limited to systems with rather small state spaces.
We present an approach for the analysis of large scale systems modeled as probabilistic timed graph transformation systems by systematically decomposing their state spaces into manageable fragments. To obtain qualitative and quantitative analysis results for a large scale system, we verify that results obtained for its fragments serve as overapproximations for the corresponding results of the large scale system. Hence, our approach allows for the detection of violations of qualitative and quantitative safety properties for the large scale system under analysis. We consider a running example in which we model shuttles driving on tracks of a large scale topology and for which we verify that shuttles never collide and are unlikely to execute emergency brakes. In our evaluation, we apply an implementation of our approach to the running example.
Generative adversarial networks (GANs) have been broadly applied to a wide range of application domains since their proposal. In this thesis, we propose several methods that aim to tackle different existing problems in GANs. Particularly, even though GANs are generally able to generate high-quality samples, the diversity of the generated set is often sub-optimal. Moreover, the common increase of the number of models in the original GANs framework, as well as their architectural sizes, introduces additional costs. Additionally, even though challenging, the proper evaluation of a generated set is an important direction to ultimately improve the generation process in GANs. We start by introducing two diversification methods that extend the original GANs framework to multiple adversaries to stimulate sample diversity in a generated set. Then, we introduce a new post-training compression method based on Monte Carlo methods and importance sampling to quantize and prune the weights and activations of pre-trained neural networks without any additional training. The previous method may be used to reduce the memory and computational costs introduced by increasing the number of models in the original GANs framework. Moreover, we use a similar procedure to quantize and prune gradients during training, which also reduces the communication costs between different workers in a distributed training setting. We introduce several topology-based evaluation methods to assess data generation in different settings, namely image generation and language generation. Our methods retrieve both single-valued and double-valued metrics, which, given a real set, may be used to broadly assess a generated set or separately evaluate sample quality and sample diversity, respectively. Moreover, two of our metrics use locality-sensitive hashing to accurately assess the generated sets of highly compressed GANs. The analysis of the compression effects in GANs paves the way for their efficient employment in real-world applications. Given their general applicability, the methods proposed in this thesis may be extended beyond the context of GANs. Hence, they may be generally applied to enhance existing neural networks and, in particular, generative frameworks.
3D point clouds are a universal and discrete digital representation of three-dimensional objects and environments. For geospatial applications, 3D point clouds have become a fundamental type of raw data acquired and generated using various methods and techniques. In particular, 3D point clouds serve as raw data for creating digital twins of the built environment.
This thesis concentrates on the research and development of concepts, methods, and techniques for preprocessing, semantically enriching, analyzing, and visualizing 3D point clouds for applications around transport infrastructure. It introduces a collection of preprocessing techniques that aim to harmonize raw 3D point cloud data, such as point density reduction and scan profile detection. Metrics such as, e.g., local density, verticality, and planarity are calculated for later use. One of the key contributions tackles the problem of analyzing and deriving semantic information in 3D point clouds. Three different approaches are investigated: a geometric analysis, a machine learning approach operating on synthetically generated 2D images, and a machine learning approach operating on 3D point clouds without intermediate representation.
In the first application case, 2D image classification is applied and evaluated for mobile mapping data focusing on road networks to derive road marking vector data. The second application case investigates how 3D point clouds can be merged with ground-penetrating radar data for a combined visualization and to automatically identify atypical areas in the data. For example, the approach detects pavement regions with developing potholes. The third application case explores the combination of a 3D environment based on 3D point clouds with panoramic imagery to improve visual representation and the detection of 3D objects such as traffic signs.
The presented methods were implemented and tested based on software frameworks for 3D point clouds and 3D visualization. In particular, modules for metric computation, classification procedures, and visualization techniques were integrated into a modular pipeline-based C++ research framework for geospatial data processing, extended by Python machine learning scripts. All visualization and analysis techniques scale to large real-world datasets such as road networks of entire cities or railroad networks.
The thesis shows that some use cases allow taking advantage of established image vision methods to analyze images rendered from mobile mapping data efficiently. The two presented semantic classification methods working directly on 3D point clouds are use case independent and show similar overall accuracy when compared to each other. While the geometry-based method requires less computation time, the machine learning-based method supports arbitrary semantic classes but requires training the network with ground truth data. Both methods can be used in combination to gradually build this ground truth with manual corrections via a respective annotation tool.
This thesis contributes results for IT system engineering of applications, systems, and services that require spatial digital twins of transport infrastructure such as road networks and railroad networks based on 3D point clouds as raw data. It demonstrates the feasibility of fully automated data flows that map captured 3D point clouds to semantically classified models. This provides a key component for seamlessly integrated spatial digital twins in IT solutions that require up-to-date, object-based, and semantically enriched information about the built environment.
Die stetige Weiterentwicklung von VR-Systemen bietet neue Möglichkeiten der Interaktion mit virtuellen Objekten im dreidimensionalen Raum, stellt Entwickelnde von VRAnwendungen aber auch vor neue Herausforderungen. Selektions- und Manipulationstechniken müssen unter Berücksichtigung des Anwendungsszenarios, der Zielgruppe und der zur Verfügung stehenden Ein- und Ausgabegeräte ausgewählt werden. Diese Arbeit leistet einen Beitrag dazu, die Auswahl von passenden Interaktionstechniken zu unterstützen. Hierfür wurde eine repräsentative Menge von Selektions- und Manipulationstechniken untersucht und, unter Berücksichtigung existierender Klassifikationssysteme, eine Taxonomie entwickelt, die die Analyse der Techniken hinsichtlich interaktionsrelevanter Eigenschaften ermöglicht. Auf Basis dieser Taxonomie wurden Techniken ausgewählt, die in einer explorativen Studie verglichen wurden, um Rückschlüsse auf die Dimensionen der Taxonomie zu ziehen und neue Indizien für Vor- und Nachteile der Techniken in spezifischen Anwendungsszenarien zu generieren. Die Ergebnisse der Arbeit münden in eine Webanwendung, die Entwickelnde von VR-Anwendungen gezielt dabei unterstützt, passende Selektions- und Manipulationstechniken für ein Anwendungsszenario auszuwählen, indem Techniken auf Basis der Taxonomie gefiltert und unter Verwendung der Resultate aus der Studie sortiert werden können.
The formal modeling and analysis is of crucial importance for software development processes following the model based approach. We present the formalism of Interval Probabilistic Timed Graph Transformation Systems (IPTGTSs) as a high-level modeling language. This language supports structure dynamics (based on graph transformation), timed behavior (based on clocks, guards, resets, and invariants as in Timed Automata (TA)), and interval probabilistic behavior (based on Discrete Interval Probability Distributions). That is, for the probabilistic behavior, the modeler using IPTGTSs does not need to provide precise probabilities, which are often impossible to obtain, but rather provides a probability range instead from which a precise probability is chosen nondeterministically. In fact, this feature on capturing probabilistic behavior distinguishes IPTGTSs from Probabilistic Timed Graph Transformation Systems (PTGTSs) presented earlier.
Following earlier work on Interval Probabilistic Timed Automata (IPTA) and PTGTSs, we also provide an analysis tool chain for IPTGTSs based on inter-formalism transformations. In particular, we provide in our tool AutoGraph a translation of IPTGTSs to IPTA and rely on a mapping of IPTA to Probabilistic Timed Automata (PTA) to allow for the usage of the Prism model checker. The tool Prism can then be used to analyze the resulting PTA w.r.t. probabilistic real-time queries asking for worst-case and best-case probabilities to reach a certain set of target states in a given amount of time.
Learning analytics at scale
(2021)
Digital technologies are paving the way for innovative educational approaches. The learning format of Massive Open Online Courses (MOOCs) provides a highly accessible path to lifelong learning while being more affordable and flexible than face-to-face courses. Thereby, thousands of learners can enroll in courses mostly without admission restrictions, but this also raises challenges. Individual supervision by teachers is barely feasible, and learning persistence and success depend on students' self-regulatory skills. Here, technology provides the means for support. The use of data for decision-making is already transforming many fields, whereas in education, it is still a young research discipline. Learning Analytics (LA) is defined as the measurement, collection, analysis, and reporting of data about learners and their learning contexts with the purpose of understanding and improving learning and learning environments. The vast amount of data that MOOCs produce on the learning behavior and success of thousands of students provides the opportunity to study human learning and develop approaches addressing the demands of learners and teachers.
The overall purpose of this dissertation is to investigate the implementation of LA at the scale of MOOCs and to explore how data-driven technology can support learning and teaching in this context. To this end, several research prototypes have been iteratively developed for the HPI MOOC Platform. Hence, they were tested and evaluated in an authentic real-world learning environment. Most of the results can be applied on a conceptual level to other MOOC platforms as well. The research contribution of this thesis thus provides practical insights beyond what is theoretically possible. In total, four system components were developed and extended:
(1) The Learning Analytics Architecture: A technical infrastructure to collect, process, and analyze event-driven learning data based on schema-agnostic pipelining in a service-oriented MOOC platform. (2) The Learning Analytics Dashboard for Learners: A tool for data-driven support of self-regulated learning, in particular to enable learners to evaluate and plan their learning activities, progress, and success by themselves. (3) Personalized Learning Objectives: A set of features to better connect learners' success to their personal intentions based on selected learning objectives to offer guidance and align the provided data-driven insights about their learning progress. (4) The Learning Analytics Dashboard for Teachers: A tool supporting teachers with data-driven insights to enable the monitoring of their courses with thousands of learners, identify potential issues, and take informed action.
For all aspects examined in this dissertation, related research is presented, development processes and implementation concepts are explained, and evaluations are conducted in case studies. Among other findings, the usage of the learner dashboard in combination with personalized learning objectives demonstrated improved certification rates of 11.62% to 12.63%. Furthermore, it was observed that the teacher dashboard is a key tool and an integral part for teaching in MOOCs. In addition to the results and contributions, general limitations of the work are discussed—which altogether provide a solid foundation for practical implications and future research.
In recent years, computer vision algorithms based on machine learning have seen rapid development. In the past, research mostly focused on solving computer vision problems such as image classification or object detection on images displaying natural scenes. Nowadays other fields such as the field of cultural heritage, where an abundance of data is available, also get into the focus of research. In the line of current research endeavours, we collaborated with the Getty Research Institute which provided us with a challenging dataset, containing images of paintings and drawings. In this technical report, we present the results of the seminar "Deep Learning for Computer Vision". In this seminar, students of the Hasso Plattner Institute evaluated state-of-the-art approaches for image classification, object detection and image recognition on the dataset of the Getty Research Institute. The main challenge when applying modern computer vision methods to the available data is the availability of annotated training data, as the dataset provided by the Getty Research Institute does not contain a sufficient amount of annotated samples for the training of deep neural networks. However, throughout the report we show that it is possible to achieve satisfying to very good results, when using further publicly available datasets, such as the WikiArt dataset, for the training of machine learning models.
Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility. Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.
The noble way to substantiate decisions that affect many people is to ask these people for their opinions. For governments that run whole countries, this means asking all citizens for their views to consider their situations and needs.
Organizations such as Africa's Voices Foundation, who want to facilitate communication between decision-makers and citizens of a country, have difficulty mediating between these groups. To enable understanding, statements need to be summarized and visualized. Accomplishing these goals in a way that does justice to the citizens' voices and situations proves challenging. Standard charts do not help this cause as they fail to create empathy for the people behind their graphical abstractions. Furthermore, these charts do not create trust in the data they are representing as there is no way to see or navigate back to the underlying code and the original data. To fulfill these functions, visualizations would highly benefit from interactions to explore the displayed data, which standard charts often only limitedly provide.
To help improve the understanding of people's voices, we developed and categorized 80 ideas for new visualizations, new interactions, and better connections between different charts, which we present in this report. From those ideas, we implemented 10 prototypes and two systems that integrate different visualizations. We show that this integration allows consistent appearance and behavior of visualizations. The visualizations all share the same main concept: representing each individual with a single dot. To realize this idea, we discuss technologies that efficiently allow the rendering of a large number of these dots. With these visualizations, direct interactions with representations of individuals are achievable by clicking on them or by dragging a selection around them. This direct interaction is only possible with a bidirectional connection from the visualization to the data it displays. We discuss different strategies for bidirectional mappings and the trade-offs involved. Having unified behavior across visualizations enhances exploration. For our prototypes, that includes grouping, filtering, highlighting, and coloring of dots. Our prototyping work was enabled by the development environment Lively4. We explain which parts of Lively4 facilitated our prototyping process. Finally, we evaluate our approach to domain problems and our developed visualization concepts.
Our work provides inspiration and a starting point for visualization development in this domain. Our visualizations can improve communication between citizens and their government and motivate empathetic decisions. Our approach, combining low-level entities to create visualizations, provides value to an explorative and empathetic workflow. We show that the design space for visualizing this kind of data has a lot of potential and that it is possible to combine qualitative and quantitative approaches to data analysis.
Crochet is a popular handcraft all over the world. While other techniques such as knitting or weaving have received technical support over the years through machines, crochet is still a purely manual craft. Not just the act of crochet itself is manual but also the process of creating instructions for new crochet patterns, which is barely supported by domain specific digital solutions. This leads to unstructured and often also ambiguous and erroneous pattern instructions. In this report, we propose a concept to digitally represent crochet patterns. This format incorporates crochet techniques which allows domain specific support for crochet pattern designers during the pattern creation and instruction writing process. As contributions, we present a thorough domain analysis, the concept of a graph structure used as domain specific language to specify crochet patterns and a prototype of a projectional editor using the graph as representation format of patterns and a diagramming system to visualize them in 2D and 3D. By analyzing the domain, we learned about crochet techniques and pain points of designers in their pattern creation workflow. These insights are the basis on which we defined the pattern representation. In order to evaluate our concept, we built a prototype by which the feasibility of the concept is shown and we tested the software with professional crochet designers who approved of the concept.
In the last decades, there was a notable progress in solving the well-known Boolean satisfiability (Sat) problem, which can be witnessed by powerful Sat solvers. One of the reasons why these solvers are so fast are structural properties of instances that are utilized by the solver’s interna. This thesis deals with the well-studied structural property treewidth, which measures the closeness of an instance to being a tree. In fact, there are many problems parameterized by treewidth that are solvable in polynomial time in the instance size when parameterized by treewidth.
In this work, we study advanced treewidth-based methods and tools for problems in knowledge representation and reasoning (KR). Thereby, we provide means to establish precise runtime results (upper bounds) for canonical problems relevant to KR. Then, we present a new type of problem reduction, which we call decomposition-guided (DG) that
allows us to precisely monitor the treewidth when reducing from one problem to another problem. This new reduction type will be the basis for a long-open lower bound result for quantified Boolean formulas and allows us to design a new methodology for establishing runtime lower bounds for problems parameterized by treewidth.
Finally, despite these lower bounds, we provide an efficient implementation of algorithms that adhere to treewidth. Our approach finds suitable abstractions of instances, which are subsequently refined in a recursive fashion, and it uses Sat solvers for solving subproblems. It turns out that our resulting solver is quite competitive for two canonical counting problems related to Sat.
EMOOCs 2021
(2021)
From June 22 to June 24, 2021, Hasso Plattner Institute, Potsdam, hosted the seventh European MOOC Stakeholder Summit (EMOOCs 2021) together with the eighth ACM Learning@Scale Conference.
Due to the COVID-19 situation, the conference was held fully online.
The boost in digital education worldwide as a result of the pandemic was also one of the main topics of this year’s EMOOCs. All institutions of learning have been forced to transform and redesign their educational methods, moving from traditional models to hybrid or completely online models at scale. The learnings, derived from practical experience and research, have been explored in EMOOCs 2021 in six tracks and additional workshops, covering various aspects of this field. In this publication, we present papers from the conference’s Experience Track, the Policy Track, the Business Track, the International Track, and the Workshops.
Compound values are not universally supported in virtual machine (VM)-based programming systems and languages. However, providing data structures with value characteristics can be beneficial. On one hand, programming systems and languages can adequately represent physical quantities with compound values and avoid inconsistencies, for example, in representation of large numbers. On the other hand, just-in-time (JIT) compilers, which are often found in VMs, can rely on the fact that compound values are immutable, which is an important property in optimizing programs. Considering this, compound values have an optimization potential that can be put to use by implementing them in VMs in a way that is efficient in memory usage and execution time. Yet, optimized compound values in VMs face certain challenges: to maintain consistency, it should not be observable by the program whether compound values are represented in an optimized way by a VM; an optimization should take into account, that the usage of compound values can exhibit certain patterns at run-time; and that necessary value-incompatible properties due to implementation restrictions should be reduced.
We propose a technique to detect and compress common patterns of compound value usage at run-time to improve memory usage and execution speed. Our approach identifies patterns of frequent compound value references and introduces abbreviated forms for them. Thus, it is possible to store multiple inter-referenced compound values in an inlined memory representation, reducing the overhead of metadata and object references. We extend our approach by a notion of limited mutability, using cells that act as barriers for our approach and provide a location for shared, mutable access with the possibility of type specialization. We devise an extension to our approach that allows us to express automatic unboxing of boxed primitive data types in terms of our initial technique. We show that our approach is versatile enough to express another optimization technique that relies on values, such as Booleans, that are unique throughout a programming system. Furthermore, we demonstrate how to re-use learned usage patterns and optimizations across program runs, thus reducing the performance impact of pattern recognition.
We show in a best-case prototype that the implementation of our approach is feasible and can also be applied to general purpose programming systems, namely implementations of the Racket language and Squeak/Smalltalk. In several micro-benchmarks, we found that our approach can effectively reduce memory consumption and improve execution speed.
A common feature in Answer Set Programming is the use of a second negation, stronger than default negation and sometimes called explicit, strong or classical negation. This explicit negation is normally used in front of atoms, rather than allowing its use as a regular operator. In this paper we consider the arbitrary combination of explicit negation with nested expressions, as those defined by Lifschitz, Tang and Turner. We extend the concept of reduct for this new syntax and then prove that it can be captured by an extension of Equilibrium Logic with this second negation. We study some properties of this variant and compare to the already known combination of Equilibrium Logic with Nelson's strong negation.
Comment sections of online news platforms are an essential space to express opinions and discuss political topics. However, the misuse by spammers, haters, and trolls raises doubts about whether the benefits justify the costs of the time-consuming content moderation. As a consequence, many platforms limited or even shut down comment sections completely. In this thesis, we present deep learning approaches for comment classification, recommendation, and prediction to foster respectful and engaging online discussions. The main focus is on two kinds of comments: toxic comments, which make readers leave a discussion, and engaging comments, which make readers join a discussion. First, we discourage and remove toxic comments, e.g., insults or threats. To this end, we present a semi-automatic comment moderation process, which is based on fine-grained text classification models and supports moderators. Our experiments demonstrate that data augmentation, transfer learning, and ensemble learning allow training robust classifiers even on small datasets. To establish trust in the machine-learned models, we reveal which input features are decisive for their output with attribution-based explanation methods. Second, we encourage and highlight engaging comments, e.g., serious questions or factual statements. We automatically identify the most engaging comments, so that readers need not scroll through thousands of comments to find them. The model training process builds on upvotes and replies as a measure of reader engagement. We also identify comments that address the article authors or are otherwise relevant to them to support interactions between journalists and their readership. Taking into account the readers' interests, we further provide personalized recommendations of discussions that align with their favored topics or involve frequent co-commenters. Our models outperform multiple baselines and recent related work in experiments on comment datasets from different platforms.
While the role of and consequences of being a bystander to face-to-face bullying has received some attention in the literature, to date, little is known about the effects of being a bystander to cyberbullying. It is also unknown how empathy might impact the negative consequences associated with being a bystander of cyberbullying. The present study focused on examining the longitudinal association between bystander of cyberbullying depression, and anxiety, and the moderating role of empathy in the relationship between bystander of cyberbullying and subsequent depression and anxiety. There were 1,090 adolescents (M-age = 12.19; 50% female) from the United States included at Time 1, and they completed questionnaires on empathy, cyberbullying roles (bystander, perpetrator, victim), depression, and anxiety. One year later, at Time 2, 1,067 adolescents (M-age = 13.76; 51% female) completed questionnaires on depression and anxiety. Results revealed a positive association between bystander of cyberbullying and depression and anxiety. Further, empathy moderated the positive relationship between bystander of cyberbullying and depression, but not for anxiety. Implications for intervention and prevention programs are discussed.
User Experience (UX) describes the holistic experience of a user before, during, and after interaction with a platform, product, or service. UX adds value and attraction to their sole functionality and is therefore highly relevant for firms. The increased interest in UX has produced a vast amount of scholarly research since 1983. The research field is, therefore, complex and scattered. Conducting a bibliometric analysis, we aim at structuring the field quantitatively and rather abstractly. We employed citation analyses, co-citation analyses, and content analyses to evaluate productivity and impact of extant research. We suggest that future research should focus more on business and management related topics.
In a recent line of research, two familiar concepts from logic programming semantics (unfounded sets and splitting) were extrapolated to the case of epistemic logic programs. The property of epistemic splitting provides a natural and modular way to understand programs without epistemic cycles but, surprisingly, was only fulfilled by Gelfond's original semantics (G91), among the many proposals in the literature. On the other hand, G91 may suffer from a kind of self-supported, unfounded derivations when epistemic cycles come into play. Recently, the absence of these derivations was also formalised as a property of epistemic semantics called foundedness. Moreover, a first semantics proved to satisfy foundedness was also proposed, the so-called Founded Autoepistemic Equilibrium Logic (FAEEL). In this paper, we prove that FAEEL also satisfies the epistemic splitting property something that, together with foundedness, was not fulfilled by any other approach up to date. To prove this result, we provide an alternative characterisation of FAEEL as a combination of G91 with a simpler logic we called Founded Epistemic Equilibrium Logic (FEEL), which is somehow an extrapolation of the stable model semantics to the modal logic S5.
Parsing of argumentative structures has become a very active line of research in recent years. Like discourse parsing or any other natural language task that requires prediction of linguistic structures, most approaches choose to learn a local model and then perform global decoding over the local probability distributions, often imposing constraints that are specific to the task at hand. Specifically for argumentation parsing, two decoding approaches have been recently proposed: Minimum Spanning Trees (MST) and Integer Linear Programming (ILP), following similar trends in discourse parsing. In contrast to discourse parsing though, where trees are not always used as underlying annotation schemes, argumentation structures so far have always been represented with trees. Using the 'argumentative microtext corpus' [in: Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon 2015 / Vol. 2, College Publications, London, 2016, pp. 801-815] as underlying data and replicating three different decoding mechanisms, in this paper we propose a novel ILP decoder and an extension to our earlier MST work, and then thoroughly compare the approaches. The result is that our new decoder outperforms related work in important respects, and that in general, ILP and MST yield very similar performance.
The development of new and better optimization and approximation methods for Job Shop Scheduling Problems (JSP) uses simulations to compare their performance. The test data required for this has an uncertain influence on the simulation results, because the feasable search space can be changed drastically by small variations of the initial problem model. Methods could benefit from this to varying degrees. This speaks in favor of defining standardized and reusable test data for JSP problem classes, which in turn requires a systematic describability of the test data in order to be able to compile problem adequate data sets. This article looks at the test data used for comparing methods by literature review. It also shows how and why the differences in test data have to be taken into account. From this, corresponding challenges are derived which the management of test data must face in the context of JSP research.
Keywords
Social Media, Quo Vadis?
(2020)
Over the past two decades, social media have become a crucial and omnipresent cultural and economic phenomenon, which has seen platforms come and go and advance technologically. In this study, we explore the further development of social media regarding interactive technologies, platform development, relationships to news media, the activities of institutional and organizational users, and effects of social media on the individual and the society over the next five to ten years by conducting an international, two-stage Delphi study. Our results show that enhanced interaction on platforms, including virtual and augmented reality, somatosensory sense, and touch- and movement-based navigation are expected. AIs will interact with other social media users. Inactive user profiles will outnumber active ones. Platform providers will diversify into the WWW, e-commerce, edu-tech, fintechs, the automobile industry, and HR. They will change to a freemium business model and put more effort into combating cybercrime. Social media will become the predominant news distributor, but fake news will still be problematic. Firms will spend greater amounts of their budgets on social media advertising, and schools, politicians, and the medical sector will increase their social media engagement. Social media use will increasingly lead to individuals’ psychic issues. Society will benefit from economic growth and new jobs, increased political interest, democratic progress, and education due to social media. However, censorship and the energy consumption of platform operators might rise.
In this study we examine the tonal organization of a series of recordings of liturgical chants, sung in 1966 by the Georgian master singer Artem Erkomaishvili. This dataset is the oldest corpus of Georgian chants from which the time synchronous F0-trajectories for all three voices have been reliably determined (Müller et al. 2017). It is therefore of outstanding importance for the understanding of the tuning principles of traditional Georgian vocal music.
The aim of the present study is to use various computational methods to analyze what these recordings can contribute to the ongoing scientific dispute about traditional Georgian tuning systems. Starting point for the present analysis is the re-release of the original audio data together with estimated fundamental frequency (F0) trajectories for each of the three voices, beat annotations, and digital scores (Rosenzweig et al. 2020). We present synoptic models for the pitch and the harmonic interval distributions, which are the first of such models for which the complete Erkomaishvili dataset was used. We show that these distributions can be very compactly be expressed as Gaussian mixture models, anchored on discrete sets of pitch or interval values for the pitch and interval distributions, respectively. As part of our study we demonstrate that these pitch values, which we refer to as scale pitches, and which are determined as the mean values of the Gaussian mixture elements, define the scale degrees of the melodic sound scales which build the skeleton of Artem Erkomaishvili’s intonation. The observation of consistent pitch bending of notes in melodic phrases, which appear in identical form in a group of chants, as well as the observation of harmonically driven intonation adjustments, which are clearly documented for all pure harmonic intervals, demonstrate that Artem Erkomaishvili intentionally deviates from the scale pitch skeleton quite freely. As a central result of our study, we proof that this melodic freedom is always constrained by the attracting influence of the scale pitches. Deviations of the F0-values of individual note events from the scale pitches at one instance of time are compensated for in the subsequent melodic steps. This suggests a deviation-compensation mechanism at the core of Artem Erkomaishvili’s melody generation, which clearly honors the scales but still allows for a large degree of melodic flexibility. This model, which summarizes all partial aspects of our analysis, is consistent with the melodic scale models derived from the observed pitch distributions, as well as with the melodic and harmonic interval distributions. In addition to the tangible results of our work, we believe that our work has general implications for the determination of tuning models from audio data, in particular for non-tempered music.
Dimensional psychiatry
(2014)
A dimensional approach in psychiatry aims to identify core mechanisms of mental disorders across nosological boundaries.
We compared anticipation of reward between major psychiatric disorders, and investigated whether reward anticipation is impaired in several mental disorders and whether there is a common psychopathological correlate (negative mood) of such an impairment.
We used functional magnetic resonance imaging (fMRI) and a monetary incentive delay (MID) task to study the functional correlates of reward anticipation across major psychiatric disorders in 184 subjects, with the diagnoses of alcohol dependence (n = 26), schizophrenia (n = 44), major depressive disorder (MDD, n = 24), bipolar disorder (acute manic episode, n = 13), attention deficit/hyperactivity disorder (ADHD, n = 23), and healthy controls (n = 54). Subjects' individual Beck Depression Inventory-and State-Trait Anxiety Inventory-scores were correlated with clusters showing significant activation during reward anticipation.
During reward anticipation, we observed significant group differences in ventral striatal (VS) activation: patients with schizophrenia, alcohol dependence, and major depression showed significantly less ventral striatal activation compared to healthy controls. Depressive symptoms correlated with dysfunction in reward anticipation regardless of diagnostic entity. There was no significant correlation between anxiety symptoms and VS functional activation.
Our findings demonstrate a neurobiological dysfunction related to reward prediction that transcended disorder categories and was related to measures of depressed mood. The findings underline the potential of a dimensional approach in psychiatry and strengthen the hypothesis that neurobiological research in psychiatric disorders can be targeted at core mechanisms that are likely to be implicated in a range of clinical entities.
Technical report
(2019)
Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application.
Commonly used technologies, such as J2EE and .NET, form de facto standards for the realization of complex distributed systems. Evolution of component systems has lead to web services and service-based architectures. This has been manifested in a multitude of industry standards and initiatives such as XML, WSDL UDDI, SOAP, etc. All these achievements lead to a new and promising paradigm in IT systems engineering which proposes to design complex software solutions as collaboration of contractually defined software services.
Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns.
The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.
We propose a network structure-based model for heterosis, and investigate it relying on metabolite profiles from Arabidopsis. A simple feed-forward two-layer network model (the Steinbuch matrix) is used in our conceptual approach. It allows for directly relating structural network properties with biological function. Interpreting heterosis as increased adaptability, our model predicts that the biological networks involved show increasing connectivity of regulatory interactions. A detailed analysis of metabolite profile data reveals that the increasing-connectivity prediction is true for graphical Gaussian models in our data from early development. This mirrors properties of observed heterotic Arabidopsis phenotypes. Furthermore, the model predicts a limit for increasing hybrid vigor with increasing heterozygosity—a known phenomenon in the literature.
QuantPrime
(2008)
Background
Medium- to large-scale expression profiling using quantitative polymerase chain reaction (qPCR) assays are becoming increasingly important in genomics research. A major bottleneck in experiment preparation is the design of specific primer pairs, where researchers have to make several informed choices, often outside their area of expertise. Using currently available primer design tools, several interactive decisions have to be made, resulting in lengthy design processes with varying qualities of the assays.
Results
Here we present QuantPrime, an intuitive and user-friendly, fully automated tool for primer pair design in small- to large-scale qPCR analyses. QuantPrime can be used online through the internet http://www.quantprime.de/ or on a local computer after download; it offers design and specificity checking with highly customizable parameters and is ready to use with many publicly available transcriptomes of important higher eukaryotic model organisms and plant crops (currently 295 species in total), while benefiting from exon-intron border and alternative splice variant information in available genome annotations. Experimental results with the model plant Arabidopsis thaliana, the crop Hordeum vulgare and the model green alga Chlamydomonas reinhardtii show success rates of designed primer pairs exceeding 96%.
Conclusion
QuantPrime constitutes a flexible, fully automated web application for reliable primer design for use in larger qPCR experiments, as proven by experimental data. The flexible framework is also open for simple use in other quantification applications, such as hydrolyzation probe design for qPCR and oligonucleotide probe design for quantitative in situ hybridization. Future suggestions made by users can be easily implemented, thus allowing QuantPrime to be developed into a broad-range platform for the design of RNA expression assays.
F2C2
(2012)
Background: Flux coupling analysis (FCA) has become a useful tool in the constraint-based analysis of genome-scale metabolic networks. FCA allows detecting dependencies between reaction fluxes of metabolic networks at steady-state. On the one hand, this can help in the curation of reconstructed metabolic networks by verifying whether the coupling between reactions is in agreement with the experimental findings. On the other hand, FCA can aid in defining intervention strategies to knock out target reactions.
Results: We present a new method F2C2 for FCA, which is orders of magnitude faster than previous approaches. As a consequence, FCA of genome-scale metabolic networks can now be performed in a routine manner.
Conclusions: We propose F2C2 as a fast tool for the computation of flux coupling in genome-scale metabolic networks. F2C2 is freely available for non-commercial use at https://sourceforge.net/projects/f2c2/files/.
We present an approach that provides automatic or semi-automatic support for evolution and change management in heterogeneous legacy landscapes where (1) legacy heterogeneous, possibly distributed platforms are integrated in a service oriented fashion, (2) the coordination of functionality is provided at the service level, through orchestration, (3) compliance and correctness are provided through policies and business rules, (4) evolution and correctness-by-design are supported by the eXtreme Model Driven Development paradigm (XMDD) offered by the jABC (Margaria and Steffen in Annu. Rev. Commun. 57, 2004)—the model-driven service oriented development platform we use here for integration, design, evolution, and governance. The artifacts are here semantically enriched, so that automatic synthesis plugins can field the vision of Enterprise Physics: knowledge driven business process development for the end user.
We demonstrate this vision along a concrete case study that became over the past three years a benchmark for Semantic Web Service discovery and mediation. We enhance the Mediation Scenario of the Semantic Web Service Challenge along the 2 central evolution paradigms that occur in practice: (a) Platform migration: platform substitution of a legacy system by an ERP system and (b) Backend extension: extension of the legacy Customer Relationship Management (CRM) and Order Management System (OMS) backends via an additional ERP layer.
The Runge-Kutta type regularization method was recently proposed as a potent tool for the iterative solution of nonlinear ill-posed problems. In this paper we analyze the applicability of this regularization method for solving inverse problems arising in atmospheric remote sensing, particularly for the retrieval of spheroidal particle distribution. Our numerical simulations reveal that the Runge-Kutta type regularization method is able to retrieve two-dimensional particle distributions using optical backscatter and extinction coefficient profiles, as well as depolarization information.
Emotions are a central element of human experience. They occur with high frequency in everyday life and play an important role in decision making. However, currently there is no consensus among researchers on what constitutes an emotion and on how emotions should be investigated. This dissertation identifies three problems of current emotion research: the problem of ground truth, the problem of incomplete constructs and the problem of optimal representation. I argue for a focus on the detailed measurement of emotion manifestations with computer-aided methods to solve these problems. This approach is demonstrated in three research projects, which describe the development of methods specific to these problems as well as their application to concrete research questions.
The problem of ground truth describes the practice to presuppose a certain structure of emotions as the a priori ground truth. This determines the range of emotion descriptions and sets a standard for the correct assignment of these descriptions. The first project illustrates how this problem can be circumvented with a multidimensional emotion perception paradigm which stands in contrast to the emotion recognition paradigm typically employed in emotion research. This paradigm allows to calculate an objective difficulty measure and to collect subjective difficulty ratings for the perception of emotional stimuli. Moreover, it enables the use of an arbitrary number of emotion stimuli categories as compared to the commonly used six basic emotion categories. Accordingly, we collected data from 441 participants using dynamic facial expression stimuli from 40 emotion categories. Our findings suggest an increase in emotion perception difficulty with increasing actor age and provide evidence to suggest that young adults, the elderly and men underestimate their emotion perception difficulty. While these effects were predicted from the literature, we also found unexpected and novel results. In particular, the increased difficulty on the objective difficulty measure for female actors and observers stood in contrast to reported findings. Exploratory analyses revealed low relevance of person-specific variables for the prediction of emotion perception difficulty, but highlighted the importance of a general pleasure dimension for the ease of emotion perception.
The second project targets the problem of incomplete constructs which relates to vaguely defined psychological constructs on emotion with insufficient ties to tangible manifestations. The project exemplifies how a modern data collection method such as face tracking data can be used to sharpen these constructs on the example of arousal, a long-standing but fuzzy construct in emotion research. It describes how measures of distance, speed and magnitude of acceleration can be computed from face tracking data and investigates their intercorrelations. We find moderate to strong correlations among all measures of static information on one hand and all measures of dynamic information on the other. The project then investigates how self-rated arousal is tied to these measures in 401 neurotypical individuals and 19 individuals with autism. Distance to the neutral face was predictive of arousal ratings in both groups. Lower mean arousal ratings were found for the autistic group, but no difference in correlation of the measures and arousal ratings could be found between groups. Results were replicated in a high autistic traits group consisting of 41 participants. The findings suggest a qualitatively similar perception of arousal for individuals with and without autism. No correlations between valence ratings and any of the measures could be found which emphasizes the specificity of our tested measures for the construct of arousal.
The problem of optimal representation refers to the search for the best representation of emotions and the assumption that there is a one-fits-all solution. In the third project we introduce partial least squares analysis as a general method to find an optimal representation to relate two high-dimensional data sets to each other. The project demonstrates its applicability to emotion research on the question of emotion perception differences between men and women. The method was used with emotion rating data from 441 participants and face tracking data computed on 306 videos. We found quantitative as well as qualitative differences in the perception of emotional facial expressions between these groups. We showed that women’s emotional perception systematically captured more of the variance in facial expressions. Additionally, we could show that significant differences exist in the way that women and men perceive some facial expressions which could be visualized as concrete facial expression sequences. These expressions suggest differing perceptions of masked and ambiguous facial expressions between the sexes. In order to facilitate use of the developed method by the research community, a package for the statistical environment R was written. Furthermore, to call attention to the method and its usefulness for emotion research, a website was designed that allows users to explore a model of emotion ratings and facial expression data in an interactive fashion.
Dutch allows for variation as to whether the first position in the sentence is occupied by the subject or by some other constituent, such as the direct object. In particular situations, however, this commonly observed variation in word order is ‘frozen’ and only the subject appears in first position. We hypothesize that this partial freezing of word order in Dutch can be explained from the dependence of the speaker’s choice of word order on the hearer’s interpretation of this word order. A formal model of this interaction between the speaker’s perspective and the hearer’s perspective is presented in terms of bidirectional Optimality Theory. Empirical predictions of this model regarding the interaction between word order and definiteness are confirmed by a quantitative corpus study.
In a recent paper, the Lefschetz number for endomorphisms (modulo trace class operators) of sequences of trace class curvature was introduced. We show that this is a well defined, canonical extension of the classical Lefschetz number and establish the homotopy invariance of this number. Moreover, we apply the results to show that the Lefschetz fixed point formula holds for geometric quasiendomorphisms of elliptic quasicomplexes.
GeneFisher-P
(2008)
Background: PCR primer design is an everyday, but not trivial task requiring state-of-the-art software. We describe the popular tool GeneFisher and explain its recent restructuring using workflow techniques. We apply a service-oriented approach to model and implement GeneFisher-P, a process-based version of the GeneFisher web application, as a part of the Bio-jETI platform for service modeling and execution. We show how to introduce a flexible process layer to meet the growing demand for improved user-friendliness and flexibility.
Results: Within Bio-jETI, we model the process using the jABC framework, a mature model-driven, service-oriented process definition platform. We encapsulate remote legacy tools and integrate web services using jETI, an extension of the jABC for seamless integration of remote resources as basic services, ready to be used in the process. Some of the basic services used by GeneFisher are in fact already provided as individual web services at BiBiServ and can be directly accessed. Others are legacy programs, and are made available to Bio-jETI via the jETI technology.
The full power of service-based process orientation is required when more bioinformatics tools, available as web services or via jETI, lead to easy extensions or variations of the basic process. This concerns for instance variations of data retrieval or alignment tools as provided by the European Bioinformatics Institute (EBI).
Conclusions: The resulting service-and process-oriented GeneFisher-P demonstrates how basic services from heterogeneous sources can be easily orchestrated in the Bio-jETI platform and lead to a flexible family of specialized processes tailored to specific tasks.
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.
Results: Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.
Conclusions: The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.
We describe an approach to modeling biological networks by action languages via answer set programming. To this end, we propose an action language for modeling biological networks, building on previous work by Baral et al. We introduce its syntax and semantics along with a translation into answer set programming, an efficient Boolean Constraint Programming Paradigm. Finally, we describe one of its applications, namely, the sulfur starvation response-pathway of the model plant Arabidopsis thaliana and sketch the functionality of our system and its usage.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2017. Selected projects have presented their results on April 25th and November 15th 2017 at the Future SOC Lab Day events.
Bio-jETI
(2008)
Background: With Bio-jETI, we introduce a service platform for interdisciplinary work on biological application domains and illustrate its use in a concrete application concerning statistical data processing in R and xcms for an LC/MS analysis of FAAH gene knockout.
Methods: Bio-jETI uses the jABC environment for service-oriented modeling and design as a graphical process modeling tool and the jETI service integration technology for remote tool execution.
Conclusions: As a service definition and provisioning platform, Bio-jETI has the potential to become a core technology in interdisciplinary service orchestration and technology transfer. Domain experts, like biologists not trained in computer science, directly define complex service orchestrations as process models and use efficient and complex bioinformatics tools in a simple and intuitive way.
SandBlocks
(2020)
Visuelle Programmiersprachen werden heutzutage zugunsten textueller Programmiersprachen nahezu nicht verwendet, obwohl visuelle Programmiersprachen einige Vorteile bieten. Diese reichen von der Vermeidung von Syntaxfehlern, über die Nutzung konkreter domänenspezifischer Notation bis hin zu besserer Lesbarkeit und Wartbarkeit des Programms. Trotzdem greifen professionelle Softwareentwickler nahezu ausschließlich auf textuelle Programmiersprachen zurück.
Damit Entwickler diese Vorteile visueller Programmiersprachen nutzen können, aber trotzdem nicht auf die ihnen bekannten textuellen Programmiersprachen verzichten müssen, gibt es die Idee, textuelle und visuelle Programmelemente gemeinsam in einer Programmiersprache nutzbar zu machen. Damit ist dem Entwickler überlassen wann und wie er visuelle Elemente in seinem Programmcode verwendet.
Diese Arbeit stellt das SandBlocks-Framework vor, das diese gemeinsame Nutzung visueller und textueller Programmelemente ermöglicht. Neben einer Auswertung visueller Programmiersprachen, zeigt es die technische Integration visueller Programmelemente in das Squeak/Smalltalk-System auf, gibt Einblicke in die Umsetzung und Verwendung in Live-Programmiersystemen und diskutiert ihre Verwendung in unterschiedlichen Domänen.
This work presents a new design for programming environments that promote the exploration of domain-specific software artifacts and the construction of graphical tools for such program comprehension tasks. In complex software projects, tool building is essential because domain- or task-specific tools can support decision making by representing concerns concisely with low cognitive effort. In contrast, generic tools can only support anticipated scenarios, which usually align with programming language concepts or well-known project domains.
However, the creation and modification of interactive tools is expensive because the glue that connects data to graphics is hard to find, change, and test. Even if valuable data is available in a common format and even if promising visualizations could be populated, programmers have to invest many resources to make changes in the programming environment. Consequently, only ideas of predictably high value will be implemented. In the non-graphical, command-line world, the situation looks different and inspiring: programmers can easily build their own tools as shell scripts by configuring and combining filter programs to process data.
We propose a new perspective on graphical tools and provide a concept to build and modify such tools with a focus on high quality, low effort, and continuous adaptability. That is, (1) we propose an object-oriented, data-driven, declarative scripting language that reduces the amount of and governs the effects of glue code for view-model specifications, and (2) we propose a scalable UI-design language that promotes short feedback loops in an interactive, graphical environment such as Morphic known from Self or Squeak/Smalltalk systems.
We implemented our concept as a tool building environment, which we call VIVIDE, on top of Squeak/Smalltalk and Morphic. We replaced existing code browsing and debugging tools to iterate within our solution more quickly. In several case studies with undergraduate and graduate students, we observed that VIVIDE can be applied to many domains such as live language development, source-code versioning, modular code browsing, and multi-language debugging. Then, we designed a controlled experiment to measure the effect on the time to build tools. Several pilot runs showed that training is crucial and, presumably, takes days or weeks, which implies a need for further research.
As a result, programmers as users can directly work with tangible representations of their software artifacts in the VIVIDE environment. Tool builders can write domain-specific scripts to populate views to approach comprehension tasks from different angles. Our novel perspective on graphical tools can inspire the creation of new trade-offs in modularity for both data providers and view designers.