Institut für Informatik und Computational Science
Refine
Has Fulltext
- yes (125) (remove)
Year of publication
Document Type
- Doctoral Thesis (64)
- Article (40)
- Postprint (10)
- Conference Proceeding (5)
- Master's Thesis (3)
- Bachelor Thesis (1)
- Habilitation Thesis (1)
- Preprint (1)
Language
- English (125) (remove)
Keywords
- Maschinelles Lernen (7)
- Antwortmengenprogrammierung (5)
- Computer Science Education (5)
- Machine Learning (5)
- answer set programming (4)
- Answer Set Programming (3)
- Competence Measurement (3)
- DPLL (3)
- Secondary Education (3)
- machine learning (3)
- Algorithmen (2)
- Algorithms (2)
- Automatisches Beweisen (2)
- Big Data (2)
- Competence Modelling (2)
- Computational thinking (2)
- Computer Science (2)
- Computersicherheit (2)
- Constraint Solving (2)
- Data Privacy (2)
- Deduction (2)
- EEG (2)
- HCI (2)
- ICA (2)
- Informatics (2)
- Informatics Education (2)
- Informatics Modelling (2)
- Informatics System Application (2)
- Informatics System Comprehension (2)
- Informatik (2)
- Internet of Things (2)
- Key Competencies (2)
- Klausellernen (2)
- Knowledge Representation and Reasoning (2)
- Künstliche Intelligenz (2)
- Logic Programming (2)
- Logics (2)
- MQTT (2)
- Middleware (2)
- Modell (2)
- Ontologie (2)
- Optimization (2)
- Planing (2)
- Relevanz (2)
- SAT (2)
- Semantic Web (2)
- Theorembeweisen (2)
- Unifikation (2)
- Vorhersage (2)
- abstraction (2)
- complexity (2)
- computational thinking (2)
- computer science education (2)
- education (2)
- higher education (2)
- maschinelles Lernen (2)
- model (2)
- non-photorealistic rendering (2)
- relevance (2)
- scientific workflows (2)
- secondary computer science education (2)
- systems biology (2)
- theorem (2)
- 'Peer To Peer' (1)
- 13C metabolic flux analysis (1)
- 21st century skills, (1)
- 3D Computer Grafik (1)
- 3D Computer Graphics (1)
- 3D Drucken (1)
- 3D Linsen (1)
- 3D Semiotik (1)
- 3D Visualisierung (1)
- 3D lenses (1)
- 3D printing (1)
- 3D semiotics (1)
- 3D visualization (1)
- 3D-Stadtmodelle (1)
- 3d city models (1)
- 6LoWPAN (1)
- ABRACADABRA (1)
- ASIC (1)
- ASIC (Applikationsspezifische Integrierte Schaltkreise) (1)
- ASP (Answer Set Programming) (1)
- Abbrecherquote (1)
- Abstraktion (1)
- Accepting Grammars (1)
- Achievement (1)
- Ackerschmalwand (1)
- Active Evaluation (1)
- Activity Theory (1)
- Activity-orientated Learning (1)
- Adversarial Learning (1)
- Aktive Evaluierung (1)
- Akzeptierende Grammatiken (1)
- Algorithmenablaufplanung (1)
- Algorithmenkonfiguration (1)
- Algorithmenselektion (1)
- Alignment (1)
- Angewandte Spieltheorie (1)
- Anisotroper Kuwahara Filter (1)
- Anleitung (1)
- Antwortmengen Programmierung (1)
- Applied Game Theory (1)
- Arduino (1)
- Argumentation (1)
- Artificial Intelligence (1)
- Aspect-Oriented Programming (1)
- Aspektorientierte Programmierung (1)
- Assessment (1)
- Asynchrone Schaltung (1)
- Augenbewegungen (1)
- Ausreissererkennung (1)
- Austria (1)
- Authentifizierung (1)
- Automated Theorem Proving (1)
- BCI (1)
- BSS (1)
- Bachelorstudierende der Informatik (1)
- Baumweite (1)
- Behavior (1)
- Berührungseingaben (1)
- Beweis (1)
- Beweisassistent (1)
- Beweistheorie (1)
- Beweisumgebung (1)
- Bilddatenanalyse (1)
- Bildung (1)
- Bildverarbeitung (1)
- Binäres Entscheidungsdiagramm (1)
- Bio-jETI (1)
- Bioelektrisches Signal (1)
- Bioinformatik (1)
- Bloom’s Taxonomy (1)
- Boolean constraint solver (1)
- Boosting (1)
- Brain Computer Interface (1)
- Business Process Models (1)
- CASP (Constraint Answer Set Programming) (1)
- CS concepts (1)
- CSC (1)
- Cactus (1)
- Capability approach (1)
- Challenges (1)
- Choreographien (1)
- Classification (1)
- Clause Learning (1)
- Cloud Computing (1)
- Cloud computing (1)
- Clusteranalyse (1)
- Cognitive Skills (1)
- Common Spatial Pattern (1)
- Competences (1)
- Competencies (1)
- Compliance (1)
- Composition (1)
- Computational Complexity (1)
- Computational Thinking (1)
- Computer Science in Context (1)
- Computergrafik (1)
- Computing (1)
- Contest (1)
- Contextualisation (1)
- Contradictions (1)
- Controlled Derivations (1)
- Coq (1)
- Covariate Shift (1)
- Curriculum (1)
- Curriculum Development (1)
- Curry (1)
- DDoS (1)
- Data Analysis (1)
- Data Management (1)
- Databases (1)
- Datenschutz (1)
- Deep Learning (1)
- Defining characteristics of physical computing (1)
- Dempster-Shafer-Theorie (1)
- Dempster–Shafer theory (1)
- Description Logics (1)
- Deskriptive Logik (1)
- Diagonalisierung (1)
- Didaktik der Informatik (1)
- Dienstkomposition (1)
- Dienstplattform (1)
- Differenz von Gauss Filtern (1)
- Digital Competence (1)
- Digital Design (1)
- Digital Education (1)
- Digital Revolution (1)
- Distributed Computing (1)
- Dynamic Programming (1)
- Dynamic assessment (1)
- Dynamische Programmierung (1)
- Dynamische Rekonfiguration (1)
- E-Learning (1)
- Early Literacy (1)
- Echtzeitanwendung (1)
- Educational Standards (1)
- Educational software (1)
- Eingabegenauigkeit (1)
- Elektroencephalographie (1)
- Embedded Systems (1)
- Emotionen (1)
- Emotionsforschung (1)
- Entscheidungsbäume (1)
- Entwurfsmuster für SOA-Sicherheit (1)
- Entwurfsprinzipien (1)
- Equilibrium logic (1)
- Erfüllbarkeit einer Formel der Aussagenlogik (1)
- Erfüllbarkeitsproblem (1)
- Error Estimation (1)
- Euclid’s algorithm (1)
- European Bioinformatics Institute (1)
- Evidenztheorie (1)
- Exploration (1)
- Exponential Time Hypothesis (1)
- Exponentialzeit Hypothese (1)
- FMC-QE (1)
- Facebook (1)
- Feature Combination (1)
- Feedback (1)
- Fehlende Daten (1)
- Fehlerschätzung (1)
- Fibonacci numbers (1)
- Flussgesteuerter Bilateraler Filter (1)
- Focus+Context Visualization (1)
- Fokus-&-Kontext Visualisierung (1)
- Formalismus (1)
- Formalitätsgrad (1)
- Formeln der quantifizierten Aussagenlogik (1)
- Function (1)
- Fundamental Ideas (1)
- GIS-Dienstkomposition (1)
- GPU (1)
- Gebäudemodelle (1)
- Gehirn-Computer-Schnittstelle (1)
- Geländemodelle (1)
- Generalisierung (1)
- Geodaten (1)
- Geometrieerzeugung (1)
- Geovisualisierung (1)
- Geschäftsprozessmodelle (1)
- Gesichtsausdruck (1)
- Gesteuerte Ableitungen (1)
- Gleichheit (1)
- Globus (1)
- Grammar Systems (1)
- Grammatiksysteme (1)
- Graphensuche (1)
- Grid (1)
- Grid Computing (1)
- Hardware Design (1)
- Hauptkomponentenanalyse (1)
- High-Level Synthesis (1)
- Hochschulsystem (1)
- I/O-effiziente Algorithmen (1)
- ICT (1)
- ICT Competence (1)
- ICT competencies (1)
- ICT skills (1)
- IP core (1)
- IT security (1)
- IT-Security (1)
- IT-Sicherheit (1)
- Informatik-Studiengänge (1)
- Informatikdidaktik (1)
- Informatikvoraussetzungen (1)
- Information Transfer Rate (1)
- Inkonsistenz (1)
- Inquiry-based Learning (1)
- Integration (1)
- Interactive Rendering (1)
- Interaktionsmodel (1)
- Interaktionsmodellierung (1)
- Interaktives Rendering (1)
- Interface design (1)
- Internet Security (1)
- Internet applications (1)
- Internet-Sicherheit (1)
- Internetanwendungen (1)
- Interoperability (1)
- Interoperabilität (1)
- IoT (1)
- Java Security Framework (1)
- Kartografisches Design (1)
- Kern-PCA (1)
- Kernmethoden (1)
- Klassifikation (1)
- Klassifikation mit großem Margin (1)
- Klassifikator-Kalibrierung (1)
- Klimafolgenanalyse (1)
- Klimawandel (1)
- Kommunikation (1)
- Komplexität (1)
- Komplexitätsbewältigung (1)
- Komplexitätstheorie (1)
- Komposition (1)
- Konnektionskalkül (1)
- Kryptographie (1)
- Kybernetik (1)
- Landmarken (1)
- Large Margin Classification (1)
- Laser Cutten (1)
- Learners (1)
- Learning Fields (1)
- Learning ecology (1)
- Learning interfaces development (1)
- Learning with ICT (1)
- Leftmost Derivations (1)
- Lehrer (1)
- Leistungsfähigkeit (1)
- Leistungsvorhersage (1)
- Liguistisch (1)
- Linksableitungen (1)
- Logarithm (1)
- Logik (1)
- Logikkalkül (1)
- Logiksynthese (1)
- Lower Bounds (1)
- Lower Secondary Level (1)
- MEG (1)
- MFA (1)
- MOOCs (1)
- Magnetoencephalographie (1)
- Malware (1)
- Massive Open Online Courses (1)
- Mathematical Optimization (1)
- Mathematikdidaktik (1)
- Mathematikphilosophie (1)
- Mathematische Optimierung (1)
- Matrizen-Eigenwertaufgabe (1)
- Measurement (1)
- Megamodel (1)
- Megamodell (1)
- Mehrklassen-Klassifikation (1)
- Mensch-Computer-Interaktion (1)
- Message Passing Interface (1)
- Migration (1)
- Mischmodelle (1)
- Mischung <Signalverarbeitung> (1)
- Mobilgeräte (1)
- Model Management (1)
- Model-Driven Engineering (1)
- Modeling (1)
- Modell Management (1)
- Modell-driven Security (1)
- Modell-getriebene Sicherheit (1)
- Modellgetriebene Entwicklung (1)
- Modellierung (1)
- Molekulare Bioinformatik (1)
- Multi Task Learning (1)
- Multi-Class (1)
- Multi-Task-Lernen (1)
- Multiprocessor (1)
- Multiprozessor (1)
- Music Technology (1)
- NETCONF (1)
- NUI (1)
- Natural Science Education (1)
- Network Management (1)
- Netzwerk (1)
- Netzwerk Management (1)
- Netzwerke (1)
- Neuronales Netz (1)
- Next Generation Network (1)
- Nicht-photorealistisches Rendering (1)
- Nichtfotorealistische Bildsynthese (1)
- NoSQL (1)
- Norway (1)
- Novice programmers (1)
- Nutzungsinteresse (1)
- Objektive Schwierigkeit (1)
- Omega (1)
- Ontologien (1)
- Ontologies (1)
- Ontology (1)
- Optimierungsproblem (1)
- Owner-Retained Access Control (ORAC) (1)
- Parallel Programming (1)
- Paralleles Rechnen (1)
- Parallelrechner (1)
- Parameterized Complexity (1)
- Parametrisierte Komplexität (1)
- Parsing (1)
- Pedagogical content knowledge (1)
- Peer-to-Peer-Netz ; GRID computing ; Zuverlässigkeit ; Web Services ; Betriebsmittelverwaltung ; Migration (1)
- Performance (1)
- Performance Prediction (1)
- Physical Science (1)
- Platzierung (1)
- Policy Enforcement (1)
- Policy Languages (1)
- Policy Sprachen (1)
- Power Monitoring (1)
- Prediction Game (1)
- Predictive Models (1)
- Preprocessing (1)
- Problem Solving (1)
- Probleme in der Studie (1)
- Process (1)
- Process modeling (1)
- Professoren (1)
- Programmierung (1)
- Proof Theory (1)
- Prozess (1)
- Prozesse (1)
- Prozessmodellierung (1)
- Prozesssynchronisierung (1)
- Prädiktionsspiel (1)
- Präferenzen (1)
- Quantenkryptographie (1)
- Quantified Boolean Formula (QBF) (1)
- Quantitative Modeling (1)
- Quantitative Modellierung (1)
- Queuing Theory (1)
- Recommendations for CS-Curricula in Higher Education (1)
- Reconfigurable (1)
- Regression (1)
- Regularisierung (1)
- Regularization (1)
- Rekonfiguration (1)
- Reparatur (1)
- SMT (SAT Modulo Theories) (1)
- SOA Security Pattern (1)
- STG decomposition (1)
- STG-Dekomposition (1)
- Sample Selection Bias (1)
- Satisfiability (1)
- Scalability (1)
- Schlüsselkompetenzen (1)
- Schulmaterial (1)
- Security Modelling (1)
- Segmentierung (1)
- Selektion (1)
- Selektionsbias (1)
- Semantic Search (1)
- Semantik Web (1)
- Semantische Suche (1)
- Sensornetzwerke (1)
- Sensors (1)
- Service Creation (1)
- Service Delivery Platform (1)
- Service convergence (1)
- Service-Orientierte Architekturen (1)
- Service-oriented Architectures (1)
- Shader (1)
- Sicherheitsmodellierung (1)
- Signal Processing (1)
- Signalquellentrennung (1)
- Signaltrennung (1)
- Simultane Diagonalisierung (1)
- Single Event Transient (1)
- Single Trial Analysis (1)
- Skalierbarkeit (1)
- Skelettberechnung (1)
- Small Private Online Courses (1)
- Social (1)
- Software-basierte Cache-Kohärenz (1)
- Sonnenteilchen-Ereignis (1)
- Spam (1)
- Spam Filtering (1)
- Spam-Erkennung (1)
- Spam-Filter (1)
- Spam-Filtering (1)
- Spatio-Spectral Filter (1)
- Spawning (1)
- Sprachdesign (1)
- Statistical Tests (1)
- Statistische Tests (1)
- Stilisierung (1)
- Strahlungshartes Design (1)
- Strahlungshärte Entwurf (1)
- Stromverbrauchüberwachung (1)
- Structuring (1)
- Strukturierung (1)
- Studentenerwartungen (1)
- Studentenhaltungen (1)
- Support Vectors (1)
- Support-Vector Lernen (1)
- Synthese (1)
- System Biologie (1)
- Systembiologie (1)
- TPTP (1)
- Taktik (1)
- Tasks (1)
- Teacher perceptions (1)
- Teachers (1)
- Teaching information security (1)
- Technology proficiency (1)
- Telekommunikation (1)
- Temporal Logic (1)
- Temporallogik (1)
- Temporäre Anbindung (1)
- Terminologische Logik (1)
- Terminology (1)
- Tests (1)
- Texturen (1)
- Theoretischen Vorlesungen (1)
- Theory (1)
- Time Augmented Petri Nets (1)
- Time Series Analysis (1)
- Tool (1)
- Traceability (1)
- Tracking (1)
- Transformation (1)
- Treewidth (1)
- Unabhängige Komponentenanalyse (1)
- Universität Bagdad (1)
- Universität Potsdam (1)
- Universitätseinstellungen (1)
- Untere Schranken (1)
- Unterrichtswerkzeuge (1)
- Unvollständigkeit (1)
- Usage Interest (1)
- VM (1)
- Verhalten (1)
- Verifikation (1)
- Verletzung Auflösung (1)
- Verletzung Erklärung (1)
- Verteiltes Rechnen (1)
- Verteilungsunterschied (1)
- Violation Explanation (1)
- Violation Resolution (1)
- Virtuelles 3D Stadtmodell (1)
- Visualisierung (1)
- Vocational Education (1)
- Vorhersagemodelle (1)
- Wahrnehmung (1)
- Wahrnehmung von Arousal (1)
- Wahrnehmungsunterschiede (1)
- Warteschlangentheorie (1)
- Web Services (1)
- Web Sites (1)
- Web of Data (1)
- Webseite (1)
- Well-structuredness (1)
- Wetterextreme (1)
- Wirtschaftsinformatik (1)
- Wissenschaftlichesworkflows (1)
- Wissensrepräsentation und -verarbeitung (1)
- Wissensrepräsentation und Schlussfolgerung (1)
- Wohlstrukturiertheit (1)
- Workflow (1)
- Young People (1)
- ZQSA (1)
- ZQSAT (1)
- Zeitbehaftete Petri Netze (1)
- Zero-Suppressed Binary Decision Diagram (ZDD) (1)
- Zuverlässigkeitsanalyse (1)
- adaptiv (1)
- adaptive (1)
- algorithm configuration (1)
- algorithm scheduling (1)
- algorithm selection (1)
- analogical thinking (1)
- anisotropic Kuwahara filter (1)
- anti-cancer drugs (1)
- approximate joint diagonalization (1)
- argument mining (1)
- argumentation (1)
- argumentation structure (1)
- arithmethische Prozeduren (1)
- arithmetic procedures (1)
- arousal perception (1)
- artificial intelligence (1)
- assistive Technologien (1)
- assistive technologies (1)
- asynchronous circuit (1)
- authentication (1)
- automated theorem proving (1)
- automatic feedback (1)
- automatic theorem prover (1)
- automatisierter Theorembeweiser (1)
- bild (1)
- binary representation (1)
- binary search (1)
- biometrics (1)
- biometrische Identifikation (1)
- blind source separation (1)
- building models (1)
- business informatics (1)
- cartographic design (1)
- changing the study field (1)
- changing the university (1)
- choreographies (1)
- classifier calibration (1)
- classroom language (1)
- classroom material (1)
- clause learning (1)
- climate change (1)
- climate impact analysis (1)
- clustering (1)
- cognitive modifiability (1)
- coherence-enhancing filtering (1)
- communication (1)
- competence (1)
- competencies (1)
- competency (1)
- comprehension (1)
- computational biology (1)
- computational methods (1)
- computer graphics (1)
- computer science teachers (1)
- computer security (1)
- computergestützte Methoden (1)
- concurrent checking (1)
- connection calculus (1)
- constraints (1)
- cryptography (1)
- cs4fn (1)
- curriculum theory (1)
- decision trees (1)
- deep neural networks (1)
- degree of formality (1)
- design principles (1)
- didaktische Rekonstruktion (1)
- difference of Gaussians (1)
- digital circuit (1)
- digital design (1)
- digitally-enabled pedagogies (1)
- divide and conquer (1)
- dropout (1)
- drug-sensitivity prediction (1)
- dynamic (1)
- dynamic classification (1)
- dynamic reconfiguration (1)
- dynamisch (1)
- dynamische Klassifikation (1)
- e-Learning (1)
- e-mentoring (1)
- edge computing (1)
- education and public policy (1)
- educational programming (1)
- educational reconstruction (1)
- educational systems (1)
- edutainment (1)
- eingebettete Systeme (1)
- einseitige Kommunikation (1)
- email spam detection (1)
- embedded systems (1)
- emotion (1)
- emotion representation (1)
- emotion research (1)
- entity alignment (1)
- environments (1)
- epistemic logic programs (1)
- epistemic specifications (1)
- equality (1)
- evidence theory (1)
- explicit negation (1)
- exponentiation (1)
- external memory algorithms (1)
- eye movements (1)
- face tracking (1)
- facial expression (1)
- firmware update (1)
- flow-based bilateral filter (1)
- formalism (1)
- fun (1)
- generalization (1)
- geometry generation (1)
- geospatial data (1)
- geospatial services (1)
- geovisualization (1)
- graph clustering (1)
- graph-search (1)
- hardware design (1)
- high school (1)
- high-throughput analysis (1)
- higher (1)
- human computer interaction (1)
- hybrid (1)
- hybrides Problemlösen (1)
- image (1)
- image data analysis (1)
- image processing (1)
- incompleteness (1)
- inconsistency (1)
- independent component analysis (1)
- indirect economic impacts (1)
- indirekte ökonomische Effekte (1)
- informal and formal learning (1)
- informatics education (1)
- informatische Bildung im Sekundarbereich (1)
- innovation (1)
- input accuracy (1)
- interaction modeling (1)
- interactive course (1)
- interactive workshop (1)
- kernel PCA (1)
- kernel methods (1)
- key competences in physical computing (1)
- key competencies (1)
- kinaesthetic teaching (1)
- konvergente Dienste (1)
- landmarks (1)
- language design (1)
- leanCoP (1)
- learning (1)
- lesson planning (1)
- lesson preparation (1)
- linguistic (1)
- logic (1)
- logic programming (1)
- logic synthesis (1)
- logical calculus (1)
- logical signaling networks (1)
- logische Programmierung (1)
- logische Signalnetzwerke (1)
- macro-economic modelling (1)
- makroökonomische Modellierung (1)
- malware detection (1)
- map/reduce (1)
- maschninelles Lernen (1)
- mathematics education (1)
- mediated learning experience (1)
- medical (1)
- medizinisch (1)
- middleware (1)
- mixture models (1)
- mobile devices (1)
- mobile learning (1)
- mobile technologies and apps (1)
- molecular networks (1)
- molekulare Netzwerke (1)
- multi-class classification (1)
- multiuser (1)
- network (1)
- networks (1)
- networks-on-chip (1)
- nichtlineare ICA (1)
- nichtlineare PCA (NLPCA) (1)
- non-monotonic reasoning (1)
- nonlinear ICA (1)
- nonlinear PCA (NLPCA) (1)
- objective difficulty (1)
- omega (1)
- one-sided communication (1)
- oneM2M (1)
- online assistance (1)
- ontologies (1)
- operating system (1)
- organisational evolution (1)
- outlier detection (1)
- output space compaction (1)
- overcomplete ICA (1)
- paper prototyping (1)
- parallel programming (1)
- parallel solving (1)
- parallele Programmierung (1)
- paralleles Lösen (1)
- parameter (1)
- parsing (1)
- pattern recognition (1)
- pedagogy (1)
- perception (1)
- perception differences (1)
- personal (1)
- personal response systems (1)
- philosophical foundation of informatics pedagogy (1)
- philosophy of mathematics (1)
- physical Computing (1)
- physical computing (1)
- physical computing tools (1)
- placement (1)
- policy evaluation (1)
- pre-primary level (1)
- prediction (1)
- preferences (1)
- preprocessing (1)
- primary education (1)
- primary level (1)
- priorities (1)
- probabilistic deep learning (1)
- probabilistic deep metric learning (1)
- probabilistische tiefe neuronale Netze (1)
- probabilistisches tiefes metrisches Lernen (1)
- problem-solving (1)
- process (1)
- process synchronization (1)
- professional development (1)
- professors (1)
- programming (1)
- programming in context (1)
- proof (1)
- proof assistant (1)
- proof environment (1)
- propagation probability (1)
- proving (1)
- quantum cryptography (1)
- radiation hardness (1)
- radiation hardness design (1)
- real-time application (1)
- reconfiguration (1)
- rekonfigurierbar (1)
- reliability assessment (1)
- repair (1)
- robust ICA (1)
- robuste ICA (1)
- scheduling (1)
- secondary education (1)
- security (1)
- segmentation (1)
- selbstanpassendes Multiprozessorsystem (1)
- selection (1)
- self-adaptive multiprocessing system (1)
- self-efficacy (1)
- semantic domain modeling (1)
- semantische Domänenmodellierung (1)
- service composition (1)
- shader (1)
- sign language (1)
- single event upset (1)
- skeletonization (1)
- social media (1)
- software-based cache coherence (1)
- solar particle event (1)
- speed independence (1)
- strahleninduzierte Einzelereignis-Effekte (1)
- structured output prediction (1)
- strukturierte Vorhersage (1)
- student activation (1)
- student experience (1)
- student perceptions (1)
- students’ conceptions (1)
- students’ knowledge (1)
- study problems (1)
- stylization (1)
- support system (1)
- tactic (1)
- teacher competencies (1)
- teacher training (1)
- teachers (1)
- teaching informatics in general education (1)
- temporary binding (1)
- terrain models (1)
- test (1)
- textures (1)
- tools (1)
- tools for teaching (1)
- topics (1)
- touch input (1)
- tptp (1)
- tracing (1)
- transformation (1)
- tutorial section (1)
- unification (1)
- user interfaces (1)
- user-centred (1)
- verification (1)
- virtual 3D city model (1)
- virtual 3D city models (1)
- virtual machine (1)
- virtual mobility (1)
- virtual reality (1)
- virtuelle 3D-Stadtmodelle (1)
- visualization (1)
- weather extremes (1)
- workflow management (1)
- zero-aliasing (1)
- überbestimmte ICA (1)
- ‘unplugged’ computing (1)
We introduce a simple approach extending the input language of Answer Set Programming (ASP) systems by multi-valued propositions. Our approach is implemented as a (prototypical) preprocessor translating logic programs with multi-valued propositions into logic programs with Boolean propositions only. Our translation is modular and heavily benefits from the expressive input language of ASP. The resulting approach, along with its implementation, allows for solving interesting constraint satisfaction problems in ASP, showing a good performance.
The exponential expanding of the numbers of web sites and Internet users makes WWW the most important global information resource. From information publishing and electronic commerce to entertainment and social networking, the Web allows an inexpensive and efficient access to the services provided by individuals and institutions. The basic units for distributing these services are the web sites scattered throughout the world. However, the extreme fragility of web services and content, the high competence between similar services supplied by different sites, and the wide geographic distributions of the web users drive the urgent requirement from the web managers to track and understand the usage interest of their web customers. This thesis, "X-tracking the Usage Interest on Web Sites", aims to fulfill this requirement. "X" stands two meanings: one is that the usage interest differs from various web sites, and the other is that usage interest is depicted from multi aspects: internal and external, structural and conceptual, objective and subjective. "Tracking" shows that our concentration is on locating and measuring the differences and changes among usage patterns. This thesis presents the methodologies on discovering usage interest on three kinds of web sites: the public information portal site, e-learning site that provides kinds of streaming lectures and social site that supplies the public discussions on IT issues. On different sites, we concentrate on different issues related with mining usage interest. The educational information portal sites were the first implementation scenarios on discovering usage patterns and optimizing the organization of web services. In such cases, the usage patterns are modeled as frequent page sets, navigation paths, navigation structures or graphs. However, a necessary requirement is to rebuild the individual behaviors from usage history. We give a systematic study on how to rebuild individual behaviors. Besides, this thesis shows a new strategy on building content clusters based on pair browsing retrieved from usage logs. The difference between such clusters and the original web structure displays the distance between the destinations from usage side and the expectations from design side. Moreover, we study the problem on tracking the changes of usage patterns in their life cycles. The changes are described from internal side integrating conceptual and structure features, and from external side for the physical features; and described from local side measuring the difference between two time spans, and global side showing the change tendency along the life cycle. A platform, Web-Cares, is developed to discover the usage interest, to measure the difference between usage interest and site expectation and to track the changes of usage patterns. E-learning site provides the teaching materials such as slides, recorded lecture videos and exercise sheets. We focus on discovering the learning interest on streaming lectures, such as real medias, mp4 and flash clips. Compared to the information portal site, the usage on streaming lectures encapsulates the variables such as viewing time and actions during learning processes. The learning interest is discovered in the form of answering 6 questions, which covers finding the relations between pieces of lectures and the preference among different forms of lectures. We prefer on detecting the changes of learning interest on the same course from different semesters. The differences on the content and structure between two courses leverage the changes on the learning interest. We give an algorithm on measuring the difference on learning interest integrated with similarity comparison between courses. A search engine, TASK-Moniminer, is created to help the teacher query the learning interest on their streaming lectures on tele-TASK site. Social site acts as an online community attracting web users to discuss the common topics and share their interesting information. Compared to the public information portal site and e-learning web site, the rich interactions among users and web content bring the wider range of content quality, on the other hand, provide more possibilities to express and model usage interest. We propose a framework on finding and recommending high reputation articles in a social site. We observed that the reputation is classified into global and local categories; the quality of the articles having high reputation is related with the content features. Based on these observations, our framework is implemented firstly by finding the articles having global or local reputation, and secondly clustering articles based on their content relations, and then the articles are selected and recommended from each cluster based on their reputation ranks.
A survey has been carried out in the Computer Science (CS) department at the University of Baghdad to investigate the attitudes of CS students in a female dominant environment, showing the differences between male and female students in different academic years. We also compare the attitudes of the freshman students of two different cultures (University of Baghdad, Iraq, and the University of Potsdam).
A lot has been published about the competencies needed by
students in the 21st century (Ravenscroft et al., 2012). However, equally
important are the competencies needed by educators in the new era
of digital education. We review the key competencies for educators in
light of the new methods of teaching and learning proposed by Massive
Open Online Courses (MOOCs) and their on-campus counterparts,
Small Private Online Courses (SPOCs).
Scientific writing is an important skill for computer science and computer engineering professionals. In this paper we present a writing concept across the curriculum program directed towards scientific writing. The program is built around a hierarchy of learning outcomes. The hierarchy is constructed through analyzing the learning outcomes in relation to competencies that are needed to fulfill them.
Current curricular trends require teachers in Baden-
Wuerttemberg (Germany) to integrate Computer Science (CS) into
traditional subjects, such as Physical Science. However, concrete guidelines
are missing. To fill this gap, we outline an approach where a
microcontroller is used to perform and evaluate measurements in the
Physical Science classroom.
Using the open-source Arduino platform, we expect students to acquire
and develop both CS and Physical Science competencies by using a
self-programmed microcontroller. In addition to this combined development
of competencies in Physical Science and CS, the subject matter
will be embedded in suitable contexts and learning environments,
such as weather and climate.
Computational thinking is a fundamental skill set that is learned
by studying Informatics and ICT. We argue that its core ideas can
be introduced in an inspiring and integrated way to both teachers and
students using fun and contextually rich cs4fn ‘Computer Science for
Fun’ stories combined with ‘unplugged’ activities including games and
magic tricks. We also argue that understanding people is an important
part of computational thinking. Computational thinking can be fun for
everyone when taught in kinaesthetic ways away from technology.
Nowadays, model-driven engineering (MDE) promises to ease software development by decreasing the inherent complexity of classical software development. In order to deliver on this promise, MDE increases the level of abstraction and automation, through a consideration of domain-specific models (DSMs) and model operations (e.g. model transformations or code generations). DSMs conform to domain-specific modeling languages (DSMLs), which increase the level of abstraction, and model operations are first-class entities of software development because they increase the level of automation. Nevertheless, MDE has to deal with at least two new dimensions of complexity, which are basically caused by the increased linguistic and technological heterogeneity. The first dimension of complexity is setting up an MDE environment, an activity comprised of the implementation or selection of DSMLs and model operations. Setting up an MDE environment is both time-consuming and error-prone because of the implementation or adaptation of model operations. The second dimension of complexity is concerned with applying MDE for actual software development. Applying MDE is challenging because a collection of DSMs, which conform to potentially heterogeneous DSMLs, are required to completely specify a complex software system. A single DSML can only be used to describe a specific aspect of a software system at a certain level of abstraction and from a certain perspective. Additionally, DSMs are usually not independent but instead have inherent interdependencies, reflecting (partial) similar aspects of a software system at different levels of abstraction or from different perspectives. A subset of these dependencies are applications of various model operations, which are necessary to keep the degree of automation high. This becomes even worse when addressing the first dimension of complexity. Due to continuous changes, all kinds of dependencies, including the applications of model operations, must also be managed continuously. This comprises maintaining the existence of these dependencies and the appropriate (re-)application of model operations. The contribution of this thesis is an approach that combines traceability and model management to address the aforementioned challenges of configuring and applying MDE for software development. The approach is considered as a traceability approach because it supports capturing and automatically maintaining dependencies between DSMs. The approach is considered as a model management approach because it supports managing the automated (re-)application of heterogeneous model operations. In addition, the approach is considered as a comprehensive model management. Since the decomposition of model operations is encouraged to alleviate the first dimension of complexity, the subsequent composition of model operations is required to counteract their fragmentation. A significant portion of this thesis concerns itself with providing a method for the specification of decoupled yet still highly cohesive complex compositions of heterogeneous model operations. The approach supports two different kinds of compositions - data-flow compositions and context compositions. Data-flow composition is used to define a network of heterogeneous model operations coupled by sharing input and output DSMs alone. Context composition is related to a concept used in declarative model transformation approaches to compose individual model transformation rules (units) at any level of detail. In this thesis, context composition provides the ability to use a collection of dependencies as context for the composition of other dependencies, including model operations. In addition, the actual implementation of model operations, which are going to be composed, do not need to implement any composition concerns. The approach is realized by means of a formalism called an executable and dynamic hierarchical megamodel, based on the original idea of megamodels. This formalism supports specifying compositions of dependencies (traceability and model operations). On top of this formalism, traceability is realized by means of a localization concept, and model management by means of an execution concept.
Think logarithmically!
(2015)
We discuss here a number of algorithmic topics which we
use in our teaching and in learning of mathematics and informatics to
illustrate and document the power of logarithm in designing very efficient
algorithms and computations – logarithmic thinking is one of the
most important key competencies for solving real world practical problems.
We demonstrate also how to introduce logarithm independently
of mathematical formalism using a conceptual model for reducing a
problem size by at least half. It is quite surprising that the idea, which
leads to logarithm, is present in Euclid’s algorithm described almost
2000 years before John Napier invented logarithm.
The Technology Proficiency Self-Assessment (TPSA) questionnaire
has been used for 15 years in the USA and other nations as a
self-efficacy measure for proficiencies fundamental to effective technology
integration in the classroom learning environment. Internal consistency
reliabilities for each of the five-item scales have typically ranged
from .73 to .88 for preservice or inservice technology-using teachers.
Due to changing technologies used in education, researchers sought to
renovate partially obsolete items and extend self-efficacy assessment to
new areas, such as social media and mobile learning. Analysis of 2014
data gathered on a new, 34 item version of the TPSA indicates that the
four established areas of email, World Wide Web (WWW), integrated
applications, and teaching with technology continue to form consistent
scales with reliabilities ranging from .81 to .93, while the 14 new items
gathered to represent emerging technologies and media separate into
two scales, each with internal consistency reliabilities greater than .9.
The renovated TPSA is deemed to be worthy of continued use in the
teaching with technology context.
The Student Learning Ecology
(2015)
Educational research on social media has showed that
students use it for socialisation, personal communication, and informal
learning. Recent studies have argued that students to some degree use
social media to carry out formal schoolwork. This article gives an
explorative account on how a small sample of Norwegian high school
students use social media to self-organise formal schoolwork. This
user pattern can be called a “student learning ecology”, which is a
user perspective on how participating students gain access to learning
resources.
This article shows a discussion about the key competencies
in informatics and ICT viewed from a philosophical foundation presented
by Martha Nussbaum, which is known as ‘ten central capabilities’.
Firstly, the outline of ‘The Capability Approach’, which has been presented
by Amartya Sen and Nussbaum as a theoretical framework of
assessing the state of social welfare, will be explained. Secondly, the
body of Nussbaum’s ten central capabilities and the reason for being
applied as the basis of discussion will be shown. Thirdly, the relationship
between the concept of ‘capability’ and ‘competency’ is to be
discussed. After that, the author’s assumption of the key competencies
in informatics and ICT led from the examination of Nussbaum’s ten
capabilities will be presented.
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.
With increasing number of applications in Internet and mobile environments, distributed software systems are demanded to be more powerful and flexible, especially in terms of dynamism and security. This dissertation describes my work concerning three aspects: dynamic reconfiguration of component software, security control on middleware applications, and web services dynamic composition. Firstly, I proposed a technology named Routing Based Workflow (RBW) to model the execution and management of collaborative components and realize temporary binding for component instances. The temporary binding means component instances are temporarily loaded into a created execution environment to execute their functions, and then are released to their repository after executions. The temporary binding allows to create an idle execution environment for all collaborative components, on which the change operations can be immediately carried out. The changes on execution environment will result in a new collaboration of all involved components, and also greatly simplifies the classical issues arising from dynamic changes, such as consistency preserving etc. To demonstrate the feasibility of RBW, I created a dynamic secure middleware system - the Smart Data Server Version 3.0 (SDS3). In SDS3, an open source implementation of CORBA is adopted and modified as the communication infrastructure, and three secure components managed by RBW, are created to enhance the security on the access of deployed applications. SDS3 offers multi-level security control on its applications from strategy control to application-specific detail control. For the management by RBW, the strategy control of SDS3 applications could be dynamically changed by reorganizing the collaboration of the three secure components. In addition, I created the Dynamic Services Composer (DSC) based on Apache open source projects, Apache Axis and WSIF. In DSC, RBW is employed to model the interaction and collaboration of web services and to enable the dynamic changes on the flow structure of web services. Finally, overall performance tests were made to evaluate the efficiency of the developed RBW and SDS3. The results demonstrated that temporary binding of component instances makes slight impacts on the execution efficiency of components, and the blackout time arising from dynamic changes can be extremely reduced in any applications.
This document presents a formula selection system for classical first order theorem proving based on the relevance of formulae for the proof of a conjecture. It is based on unifiability of predicates and is also able to use a linguistic approach for the selection. The scope of the technique is the reduction of the set of formulae and the increase of the amount of provable conjectures in a given time. Since the technique generates a subset of the formula set, it can be used as a preprocessor for automated theorem proving. The document contains the conception, implementation and evaluation of both selection concepts. While the one concept generates a search graph over the negation normal forms or Skolem normal forms of the given formulae, the linguistic concept analyses the formulae and determines frequencies of lexemes and uses a tf-idf weighting algorithm to determine the relevance of the formulae. Though the concept is built for first order logic, it is not limited to it. The concept can be used for higher order and modal logik, too, with minimal adoptions. The system was also evaluated at the world championship of automated theorem provers (CADE ATP Systems Competition, CASC-24) in combination with the leanCoP theorem prover and the evaluation of the results of the CASC and the benchmarks with the problems of the CASC of the year 2012 (CASC-J6) show that the concept of the system has positive impact to the performance of automated theorem provers. Also, the benchmarks with two different theorem provers which use different calculi have shown that the selection is independent from the calculus. Moreover, the concept of TEMPLAR has shown to be competitive to some extent with the concept of SinE and even helped one of the theorem provers to solve problems that were not (or slower) solved with SinE selection in the CASC. Finally, the evaluation implies that the combination of the unification based and linguistic selection yields more improved results though no optimisation was done for the problems.
The poster and abstract describe the importance of teaching
information security in school. After a short description of information
security and important aspects, I will show, how information security
fits into different guidelines or models for computer science educations
and that it is therefore on of the key competencies. Afterwards I will
present you a rough insight of teaching information security in Austria.
Teaching Data Management
(2015)
Data management is a central topic in computer science as
well as in computer science education. Within the last years, this topic is
changing tremendously, as its impact on daily life becomes increasingly
visible. Nowadays, everyone not only needs to manage data of various
kinds, but also continuously generates large amounts of data. In
addition, Big Data and data analysis are intensively discussed in public
dialogue because of their influences on society. For the understanding of
such discussions and for being able to participate in them, fundamental
knowledge on data management is necessary. Especially, being aware
of the threats accompanying the ability to analyze large amounts of
data in nearly real-time becomes increasingly important. This raises the
question, which key competencies are necessary for daily dealings with
data and data management.
In this paper, we will first point out the importance of data management
and of Big Data in daily life. On this basis, we will analyze which are
the key competencies everyone needs concerning data management to
be able to handle data in a proper way in daily life. Afterwards, we will
discuss the impact of these changes in data management on computer
science education and in particular database education.
Regardless of what is intended by government curriculum
specifications and advised by educational experts, the competencies
taught and learned in and out of classrooms can vary considerably.
In this paper, we discuss in particular how we can investigate the
perceptions that individual teachers have of competencies in ICT,
and how these and other factors may influence students’ learning. We
report case study research which identifies contradictions within the
teaching of ICT competencies as an activity system, highlighting issues
concerning the object of the curriculum, the roles of the participants and
the school cultures. In a particular case, contradictions in the learning
objectives between higher order skills and the use of application tools
have been resolved by a change in the teacher’s perceptions which
have not led to changes in other aspects of the activity system. We look
forward to further investigation of the effects of these contradictions in
other case studies and on forthcoming curriculum change.
The growing impact of globalisation and the development of
a ‘knowledge society’ have led many to argue that 21st century skills are
essential for life in twenty-first century society and that ICT is central
to their development. This paper describes how 21st century skills, in
particular digital literacy, critical thinking, creativity, communication
and collaboration skills, have been conceptualised and embedded in the
resources developed for teachers in iTEC, a four-year, European project.
The effectiveness of this approach is considered in light of the data
collected through the evaluation of the pilots, which considers both the
potential benefits of using technology to support the development of
21st century skills, but also the challenges of doing so. Finally, the paper
discusses the learning support systems required in order to transform
pedagogies and embed 21st century skills. It is argued that support is
required in standards and assessment; curriculum and instruction; professional
development; and learning environments.
Social networks are currently at the forefront of tools that
lend to Personal Learning Environments (PLEs). This study aimed to
observe how students perceived PLEs, what they believed were the
integral components of social presence when using Facebook as part
of a PLE, and to describe student’s preferences for types of interactions
when using Facebook as part of their PLE. This study used mixed
methods to analyze the perceptions of graduate and undergraduate
students on the use of social networks, more specifically Facebook as a
learning tool. Fifty surveys were returned representing a 65 % response
rate. Survey questions included both closed and open-ended questions.
Findings suggested that even though students rated themselves relatively
well in having requisite technology skills, and 94 % of students used
Facebook primarily for social use, they were hesitant to migrate these
skills to academic use because of concerns of privacy, believing that
other platforms could fulfil the same purpose, and by not seeing the
validity to use Facebook in establishing social presence. What lies
at odds with these beliefs is that when asked to identify strategies in
Facebook that enabled social presence to occur in academic work, the
majority of students identified strategies in five categories that lead to
social presence establishment on Facebook during their coursework.
Structuring process models
(2012)
One can fairly adopt the ideas of Donald E. Knuth to conclude that process modeling is both a science and an art. Process modeling does have an aesthetic sense. Similar to composing an opera or writing a novel, process modeling is carried out by humans who undergo creative practices when engineering a process model. Therefore, the very same process can be modeled in a myriad number of ways. Once modeled, processes can be analyzed by employing scientific methods. Usually, process models are formalized as directed graphs, with nodes representing tasks and decisions, and directed arcs describing temporal constraints between the nodes. Common process definition languages, such as Business Process Model and Notation (BPMN) and Event-driven Process Chain (EPC) allow process analysts to define models with arbitrary complex topologies. The absence of structural constraints supports creativity and productivity, as there is no need to force ideas into a limited amount of available structural patterns. Nevertheless, it is often preferable that models follow certain structural rules. A well-known structural property of process models is (well-)structuredness. A process model is (well-)structured if and only if every node with multiple outgoing arcs (a split) has a corresponding node with multiple incoming arcs (a join), and vice versa, such that the set of nodes between the split and the join induces a single-entry-single-exit (SESE) region; otherwise the process model is unstructured. The motivations for well-structured process models are manifold: (i) Well-structured process models are easier to layout for visual representation as their formalizations are planar graphs. (ii) Well-structured process models are easier to comprehend by humans. (iii) Well-structured process models tend to have fewer errors than unstructured ones and it is less probable to introduce new errors when modifying a well-structured process model. (iv) Well-structured process models are better suited for analysis with many existing formal techniques applicable only for well-structured process models. (v) Well-structured process models are better suited for efficient execution and optimization, e.g., when discovering independent regions of a process model that can be executed concurrently. Consequently, there are process modeling languages that encourage well-structured modeling, e.g., Business Process Execution Language (BPEL) and ADEPT. However, the well-structured process modeling implies some limitations: (i) There exist processes that cannot be formalized as well-structured process models. (ii) There exist processes that when formalized as well-structured process models require a considerable duplication of modeling constructs. Rather than expecting well-structured modeling from start, we advocate for the absence of structural constraints when modeling. Afterwards, automated methods can suggest, upon request and whenever possible, alternative formalizations that are "better" structured, preferably well-structured. In this thesis, we study the problem of automatically transforming process models into equivalent well-structured models. The developed transformations are performed under a strong notion of behavioral equivalence which preserves concurrency. The findings are implemented in a tool, which is publicly available.
In the early days of computer graphics, research was mainly driven by the goal to create realistic synthetic imagery. By contrast, non-photorealistic computer graphics, established as its own branch of computer graphics in the early 1990s, is mainly motivated by concepts and principles found in traditional art forms, such as painting, illustration, and graphic design, and it investigates concepts and techniques that abstract from reality using expressive, stylized, or illustrative rendering techniques. This thesis focuses on the artistic stylization of two-dimensional content and presents several novel automatic techniques for the creation of simplified stylistic illustrations from color images, video, and 3D renderings. Primary innovation of these novel techniques is that they utilize the smooth structure tensor as a simple and efficient way to obtain information about the local structure of an image. More specifically, this thesis contributes to knowledge in this field in the following ways. First, a comprehensive review of the structure tensor is provided. In particular, different methods for integrating the minor eigenvector field of the smoothed structure tensor are developed, and the superiority of the smoothed structure tensor over the popular edge tangent flow is demonstrated. Second, separable implementations of the popular bilateral and difference of Gaussians filters that adapt to the local structure are presented. These filters avoid artifacts while being computationally highly efficient. Taken together, both provide an effective way to create a cartoon-style effect. Third, a generalization of the Kuwahara filter is presented that avoids artifacts by adapting the shape, scale, and orientation of the filter to the local structure. This causes directional image features to be better preserved and emphasized, resulting in overall sharper edges and a more feature-abiding painterly effect. In addition to the single-scale variant, a multi-scale variant is presented, which is capable of performing a highly aggressive abstraction. Fourth, a technique that builds upon the idea of combining flow-guided smoothing with shock filtering is presented, allowing for an aggressive exaggeration and an emphasis of directional image features. All presented techniques are suitable for temporally coherent per-frame filtering of video or dynamic 3D renderings, without requiring expensive extra processing, such as optical flow. Moreover, they can be efficiently implemented to process content in real-time on a GPU.
This work introduces novel internal and external memory algorithms for computing voxel skeletons of massive voxel objects with complex network-like architecture and for converting these voxel skeletons to piecewise linear geometry, that is triangle meshes and piecewise straight lines. The presented techniques help to tackle the challenge of visualizing and analyzing 3d images of increasing size and complexity, which are becoming more and more important in, for example, biological and medical research. Section 2.3.1 contributes to the theoretical foundations of thinning algorithms with a discussion of homotopic thinning in the grid cell model. The grid cell model explicitly represents a cell complex built of faces, edges, and vertices shared between voxels. A characterization of pairs of cells to be deleted is much simpler than characterizations of simple voxels were before. The grid cell model resolves topologically unclear voxel configurations at junctions and locked voxel configurations causing, for example, interior voxels in sets of non-simple voxels. A general conclusion is that the grid cell model is superior to indecomposable voxels for algorithms that need detailed control of topology. Section 2.3.2 introduces a noise-insensitive measure based on the geodesic distance along the boundary to compute two-dimensional skeletons. The measure is able to retain thin object structures if they are geometrically important while ignoring noise on the object's boundary. This combination of properties is not known of other measures. The measure is also used to guide erosion in a thinning process from the boundary towards lines centered within plate-like structures. Geodesic distance based quantities seem to be well suited to robustly identify one- and two-dimensional skeletons. Chapter 6 applies the method to visualization of bone micro-architecture. Chapter 3 describes a novel geometry generation scheme for representing voxel skeletons, which retracts voxel skeletons to piecewise linear geometry per dual cube. The generated triangle meshes and graphs provide a link to geometry processing and efficient rendering of voxel skeletons. The scheme creates non-closed surfaces with boundaries, which contain fewer triangles than a representation of voxel skeletons using closed surfaces like small cubes or iso-surfaces. A conclusion is that thinking specifically about voxel skeleton configurations instead of generic voxel configurations helps to deal with the topological implications. The geometry generation is one foundation of the applications presented in Chapter 6. Chapter 5 presents a novel external memory algorithm for distance ordered homotopic thinning. The presented method extends known algorithms for computing chamfer distance transformations and thinning to execute I/O-efficiently when input is larger than the available main memory. The applied block-wise decomposition schemes are quite simple. Yet it was necessary to carefully analyze effects of block boundaries to devise globally correct external memory variants of known algorithms. In general, doing so is superior to naive block-wise processing ignoring boundary effects. Chapter 6 applies the algorithms in a novel method based on confocal microscopy for quantitative study of micro-vascular networks in the field of microcirculation.
Although it has become common practice to build applications based on the reuse of existing components or services, technical complexity and semantic challenges constitute barriers to ensuring a successful and wide reuse of components and services. In the geospatial application domain, the barriers are self-evident due to heterogeneous geographic data, a lack of interoperability and complex analysis processes.
Constructing workflows manually and discovering proper services and data that match user intents and preferences is difficult and time-consuming especially for users who are not trained in software development. Furthermore, considering the multi-objective nature of environmental modeling for the assessment of climate change impacts and the various types of geospatial data (e.g., formats, scales, and georeferencing systems) increases the complexity challenges.
Automatic service composition approaches that provide semantics-based assistance in the process of workflow design have proven to be a solution to overcome these challenges and have become a frequent demand especially by end users who are not IT experts. In this light, the major contributions of this thesis are:
(i) Simplification of service reuse and workflow design of applications for climate impact analysis by following the eXtreme Model-Driven Development (XMDD) paradigm.
(ii) Design of a semantic domain model for climate impact analysis applications that comprises specifically designed services, ontologies that provide domain-specific vocabulary for referring to types and services, and the input/output annotation of the services using the terms defined in the ontologies.
(iii) Application of a constraint-driven method for the automatic composition of workflows for analyzing the impacts of sea-level rise. The application scenario demonstrates the impact of domain modeling decisions on the results and the performance of the synthesis algorithm.
Cloud computing is a model for enabling on-demand access to a shared pool of computing resources. With virtually limitless on-demand resources, a cloud environment enables the hosted Internet application to quickly cope when there is an increase in the workload. However, the overhead of provisioning resources exposes the Internet application to periods of under-provisioning and performance degradation. Moreover, the performance interference, due to the consolidation in the cloud environment, complicates the performance management of the Internet applications. In this dissertation, we propose two approaches to mitigate the impact of the resources provisioning overhead. The first approach employs control theory to scale resources vertically and cope fast with workload. This approach assumes that the provider has knowledge and control over the platform running in the virtual machines (VMs), which limits it to Platform as a Service (PaaS) and Software as a Service (SaaS) providers. The second approach is a customer-side one that deals with the horizontal scalability in an Infrastructure as a Service (IaaS) model. It addresses the trade-off problem between cost and performance with a multi-goal optimization solution. This approach finds the scale thresholds that achieve the highest performance with the lowest increase in the cost. Moreover, the second approach employs a proposed time series forecasting algorithm to scale the application proactively and avoid under-utilization periods. Furthermore, to mitigate the interference impact on the Internet application performance, we developed a system which finds and eliminates the VMs suffering from performance interference. The developed system is a light-weight solution which does not imply provider involvement. To evaluate our approaches and the designed algorithms at large-scale level, we developed a simulator called (ScaleSim). In the simulator, we implemented scalability components acting as the scalability components of Amazon EC2. The current scalability implementation in Amazon EC2 is used as a reference point for evaluating the improvement in the scalable application performance. ScaleSim is fed with realistic models of the RUBiS benchmark extracted from the real environment. The workload is generated from the access logs of the 1998 world cup website. The results show that optimizing the scalability thresholds and adopting proactive scalability can mitigate 88% of the resources provisioning overhead impact with only a 9% increase in the cost.
In this work we consider statistical learning problems. A learning machine aims to extract information from a set of training examples such that it is able to predict the associated label on unseen examples. We consider the case where the resulting classification or regression rule is a combination of simple rules - also called base hypotheses. The so-called boosting algorithms iteratively find a weighted linear combination of base hypotheses that predict well on unseen data. We address the following issues: o The statistical learning theory framework for analyzing boosting methods. We study learning theoretic guarantees on the prediction performance on unseen examples. Recently, large margin classification techniques emerged as a practical result of the theory of generalization, in particular Boosting and Support Vector Machines. A large margin implies a good generalization performance. Hence, we analyze how large the margins in boosting are and find an improved algorithm that is able to generate the maximum margin solution. o How can boosting methods be related to mathematical optimization techniques? To analyze the properties of the resulting classification or regression rule, it is of high importance to understand whether and under which conditions boosting converges. We show that boosting can be used to solve large scale constrained optimization problems, whose solutions are well characterizable. To show this, we relate boosting methods to methods known from mathematical optimization, and derive convergence guarantees for a quite general family of boosting algorithms. o How to make Boosting noise robust? One of the problems of current boosting techniques is that they are sensitive to noise in the training sample. In order to make boosting robust, we transfer the soft margin idea from support vector learning to boosting. We develop theoretically motivated regularized algorithms that exhibit a high noise robustness. o How to adapt boosting to regression problems? Boosting methods are originally designed for classification problems. To extend the boosting idea to regression problems, we use the previous convergence results and relations to semi-infinite programming to design boosting-like algorithms for regression problems. We show that these leveraging algorithms have desirable theoretical and practical properties. o Can boosting techniques be useful in practice? The presented theoretical results are guided by simulation results either to illustrate properties of the proposed algorithms or to show that they work well in practice. We report on successful applications in a non-intrusive power monitoring system, chaotic time series analysis and a drug discovery process. --- Anmerkung: Der Autor ist Träger des von der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam vergebenen Michelson-Preises für die beste Promotion des Jahres 2001/2002.
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.
The constantly growing capacity of reconfigurable devices allows simultaneous execution of complex applications on those devices. The mere diversity of applications deems it impossible to design an interconnection network matching the requirements of every possible application perfectly, leading to suboptimal performance in many cases. However, the architecture of the interconnection network is not the only aspect affecting performance of communication. The resource manager places applications on the device and therefore influences latency between communicating partners and overall network load. Communication protocols affect performance by introducing data and processing overhead putting higher load on the network and increasing resource demand. Approaching communication holistically not only considers the architecture of the interconnect, but communication-aware resource management, communication protocols and resource usage just as well. Incorporation of different parts of a reconfigurable system during design- and runtime and optimizing them with respect to communication demand results in more resource efficient communication. Extensive evaluation shows enhanced performance and flexibility, if communication on reconfigurable devices is regarded in a holistic fashion.
Deciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks.
An increasing number of applications requires user interfaces that facilitate the handling of large geodata sets. Using virtual 3D city models, complex geospatial information can be communicated visually in an intuitive way. Therefore, real-time visualization of virtual 3D city models represents a key functionality for interactive exploration, presentation, analysis, and manipulation of geospatial data. This thesis concentrates on the development and implementation of concepts and techniques for real-time city model visualization. It discusses rendering algorithms as well as complementary modeling concepts and interaction techniques. Particularly, the work introduces a new real-time rendering technique to handle city models of high complexity concerning texture size and number of textures. Such models are difficult to handle by current technology, primarily due to two problems: - Limited texture memory: The amount of simultaneously usable texture data is limited by the memory of the graphics hardware. - Limited number of textures: Using several thousand different textures simultaneously causes significant performance problems due to texture switch operations during rendering. The multiresolution texture atlases approach, introduced in this thesis, overcomes both problems. During rendering, it permanently maintains a small set of textures that are sufficient for the current view and the screen resolution available. The efficiency of multiresolution texture atlases is evaluated in performance tests. To summarize, the results demonstrate that the following goals have been achieved: - Real-time rendering becomes possible for 3D scenes whose amount of texture data exceeds the main memory capacity. - Overhead due to texture switches is kept permanently low, so that the number of different textures has no significant effect on the rendering frame rate. Furthermore, this thesis introduces two new approaches for real-time city model visualization that use textures as core visualization elements: - An approach for visualization of thematic information. - An approach for illustrative visualization of 3D city models. Both techniques demonstrate that multiresolution texture atlases provide a basic functionality for the development of new applications and systems in the domain of city model visualization.
Three quantum cryptographic protocols of multiuser quantum networks with embedded authentication, allowing quantum key distribution or quantum direct communication, are discussed in this work. The security of the protocols against different types of attacks is analysed with a focus on various impersonation attacks and the man-in-the-middle attack. On the basis of the security analyses several improvements are suggested and implemented in order to adjust the investigated vulnerabilities. Furthermore, the impact of the eavesdropping test procedure on impersonation attacks is outlined. The framework of a general eavesdropping test is proposed to provide additional protection against security risks in impersonation attacks.
The modeling and evaluation calculus FMC-QE, the Fundamental Modeling Concepts for Quanti-tative Evaluation [1], extends the Fundamental Modeling Concepts (FMC) for performance modeling and prediction. In this new methodology, the hierarchical service requests are in the main focus, because they are the origin of every service provisioning process. Similar to physics, these service requests are a tuple of value and unit, which enables hierarchical service request transformations at the hierarchical borders and therefore the hierarchical modeling. Through reducing the model complexity of the models by decomposing the system in different hierarchical views, the distinction between operational and control states and the calculation of the performance values on the assumption of the steady state, FMC-QE has a scalable applica-bility on complex systems. According to FMC, the system is modeled in a 3-dimensional hierarchical representation space, where system performance parameters are described in three arbitrarily fine-grained hierarchi-cal bipartite diagrams. The hierarchical service request structures are modeled in Entity Relationship Diagrams. The static server structures, divided into logical and real servers, are de-scribed as Block Diagrams. The dynamic behavior and the control structures are specified as Petri Nets, more precisely Colored Time Augmented Petri Nets. From the structures and pa-rameters of the performance model, a hierarchical set of equations is derived. The calculation of the performance values is done on the assumption of stationary processes and is based on fundamental laws of the performance analysis: Little's Law and the Forced Traffic Flow Law. Little's Law is used within the different hierarchical levels (horizontal) and the Forced Traffic Flow Law is the key to the dependencies among the hierarchical levels (vertical). This calculation is suitable for complex models and allows a fast (re-)calculation of different performance scenarios in order to support development and configuration decisions. Within the Research Group Zorn at the Hasso Plattner Institute, the work is embedded in a broader research in the development of FMC-QE. While this work is concentrated on the theoretical background, description and definition of the methodology as well as the extension and validation of the applicability, other topics are in the development of an FMC-QE modeling and evaluation tool and the usage of FMC-QE in the design of an adaptive transport layer in order to fulfill Quality of Service and Service Level Agreements in volatile service based environments. This thesis contains a state-of-the-art, the description of FMC-QE as well as extensions of FMC-QE in representative general models and case studies. In the state-of-the-art part of the thesis in chapter 2, an overview on existing Queueing Theory and Time Augmented Petri Net models and other quantitative modeling and evaluation languages and methodologies is given. Also other hierarchical quantitative modeling frameworks will be considered. The description of FMC-QE in chapter 3 consists of a summary of the foundations of FMC-QE, basic definitions, the graphical notations, the FMC-QE Calculus and the modeling of open queueing networks as an introductory example. The extensions of FMC-QE in chapter 4 consist of the integration of the summation method in order to support the handling of closed networks and the modeling of multiclass and semaphore scenarios. Furthermore, FMC-QE is compared to other performance modeling and evaluation approaches. In the case study part in chapter 5, proof-of-concept examples, like the modeling of a service based search portal, a service based SAP NetWeaver application and the Axis2 Web service framework will be provided. Finally, conclusions are given by a summary of contributions and an outlook on future work in chapter 6. [1] Werner Zorn. FMC-QE - A New Approach in Quantitative Modeling. In Hamid R. Arabnia, editor, Procee-dings of the International Conference on Modeling, Simulation and Visualization Methods (MSV 2007) within WorldComp ’07, pages 280 – 287, Las Vegas, NV, USA, June 2007. CSREA Press. ISBN 1-60132-029-9.
ProtoSense
(2015)
Answer Set Programming (ASP) is an emerging paradigm for declarative programming, in which a computational problem is specified by a logic program such that particular models, called answer sets, match solutions. ASP faces a growing range of applications, demanding for high-performance tools able to solve complex problems. ASP integrates ideas from a variety of neighboring fields. In particular, automated techniques to search for answer sets are inspired by Boolean Satisfiability (SAT) solving approaches. While the latter have firm proof-theoretic foundations, ASP lacks formal frameworks for characterizing and comparing solving methods. Furthermore, sophisticated search patterns of modern SAT solvers, successfully applied in areas like, e.g., model checking and verification, are not yet established in ASP solving. We address these deficiencies by, for one, providing proof-theoretic frameworks that allow for characterizing, comparing, and analyzing approaches to answer set computation. For another, we devise modern ASP solving algorithms that integrate and extend state-of-the-art techniques for Boolean constraint solving. We thus contribute to the understanding of existing ASP solving approaches and their interconnections as well as to their enhancement by incorporating sophisticated search patterns. The central idea of our approach is to identify atomic as well as composite constituents of a propositional logic program with Boolean variables. This enables us to describe fundamental inference steps, and to selectively combine them in proof-theoretic characterizations of various ASP solving methods. In particular, we show that different concepts of case analyses applied by existing ASP solvers implicate mutual exponential separations regarding their best-case complexities. We also develop a generic proof-theoretic framework amenable to language extensions, and we point out that exponential separations can likewise be obtained due to case analyses on them. We further exploit fundamental inference steps to derive Boolean constraints characterizing answer sets. They enable the conception of ASP solving algorithms including search patterns of modern SAT solvers, while also allowing for direct technology transfers between the areas of ASP and SAT solving. Beyond the search for one answer set of a logic program, we address the enumeration of answer sets and their projections to a subvocabulary, respectively. The algorithms we develop enable repetition-free enumeration in polynomial space without being intrusive, i.e., they do not necessitate any modifications of computations before an answer set is found. Our approach to ASP solving is implemented in clasp, a state-of-the-art Boolean constraint solver that has successfully participated in recent solver competitions. Although we do here not address the implementation techniques of clasp or all of its features, we present the principles of its success in the context of ASP solving.
The study reported in this paper involved the employment
of specific in-class exercises using a Personal Response System (PRS).
These exercises were designed with two goals: to enhance students’
capabilities of tracing a given code and of explaining a given code in
natural language with some abstraction. The paper presents evidence
from the actual use of the PRS along with students’ subjective impressions
regarding both the use of the PRS and the special exercises. The
conclusions from the findings are followed with a short discussion on
benefits of PRS-based mental processing exercises for learning programming
and beyond.
The workshops on (constraint) logic programming (WLP) are the annual meeting of the Society of Logic Programming (GLP e.V.) and bring together researchers interested in logic programming, constraint programming, and related areas like databases, artificial intelligence and operations research. The 23rd WLP was held in Potsdam at September 15 – 16, 2009. The topics of the presentations of WLP2009 were grouped into the major areas: Databases, Answer Set Programming, Theory and Practice of Logic Programming as well as Constraints and Constraint Handling Rules.
A central insight from psychological studies on human eye movements is that eye movement patterns are highly individually characteristic. They can, therefore, be used as a biometric feature, that is, subjects can be identified based on their eye movements. This thesis introduces new machine learning methods to identify subjects based on their eye movements while viewing arbitrary content. The thesis focuses on probabilistic modeling of the problem, which has yielded the best results in the most recent literature. The thesis studies the problem in three phases by proposing a purely probabilistic, probabilistic deep learning, and probabilistic deep metric learning approach. In the first phase, the thesis studies models that rely on psychological concepts about eye movements. Recent literature illustrates that individual-specific distributions of gaze patterns can be used to accurately identify individuals. In these studies, models were based on a simple parametric family of distributions. Such simple parametric models can be robustly estimated from sparse data, but have limited flexibility to capture the differences between individuals. Therefore, this thesis proposes a semiparametric model of gaze patterns that is flexible yet robust for individual identification. These patterns can be understood as domain knowledge derived from psychological literature. Fixations and saccades are examples of simple gaze patterns. The proposed semiparametric densities are drawn under a Gaussian process prior centered at a simple parametric distribution. Thus, the model will stay close to the parametric class of densities if little data is available, but it can also deviate from this class if enough data is available, increasing the flexibility of the model. The proposed method is evaluated on a large-scale dataset, showing significant improvements over the state-of-the-art. Later, the thesis replaces the model based on gaze patterns derived from psychological concepts with a deep neural network that can learn more informative and complex patterns from raw eye movement data. As previous work has shown that the distribution of these patterns across a sequence is informative, a novel statistical aggregation layer called the quantile layer is introduced. It explicitly fits the distribution of deep patterns learned directly from the raw eye movement data. The proposed deep learning approach is end-to-end learnable, such that the deep model learns to extract informative, short local patterns while the quantile layer learns to approximate the distributions of these patterns. Quantile layers are a generic approach that can converge to standard pooling layers or have a more detailed description of the features being pooled, depending on the problem. The proposed model is evaluated in a large-scale study using the eye movements of subjects viewing arbitrary visual input. The model improves upon the standard pooling layers and other statistical aggregation layers proposed in the literature. It also improves upon the state-of-the-art eye movement biometrics by a wide margin. Finally, for the model to identify any subject — not just the set of subjects it is trained on — a metric learning approach is developed. Metric learning learns a distance function over instances. The metric learning model maps the instances into a metric space, where sequences of the same individual are close, and sequences of different individuals are further apart. This thesis introduces a deep metric learning approach with distributional embeddings. The approach represents sequences as a set of continuous distributions in a metric space; to achieve this, a new loss function based on Wasserstein distances is introduced. The proposed method is evaluated on multiple domains besides eye movement biometrics. This approach outperforms the state of the art in deep metric learning in several domains while also outperforming the state of the art in eye movement biometrics.
This thesis proposes a privacy protection framework for the controlled distribution and use of personal private data. The framework is based on the idea that privacy policies can be set directly by the data owner and can be automatically enforced against the data user. Data privacy continues to be a very important topic, as our dependency on electronic communication maintains its current growth, and private data is shared between multiple devices, users and locations. The growing amount and the ubiquitous availability of personal private data increases the likelihood of data misuse. Early privacy protection techniques, such as anonymous email and payment systems have focused on data avoidance and anonymous use of services. They did not take into account that data sharing cannot be avoided when people participate in electronic communication scenarios that involve social interactions. This leads to a situation where data is shared widely and uncontrollably and in most cases the data owner has no control over further distribution and use of personal private data. Previous efforts to integrate privacy awareness into data processing workflows have focused on the extension of existing access control frameworks with privacy aware functions or have analysed specific individual problems such as the expressiveness of policy languages. So far, very few implementations of integrated privacy protection mechanisms exist and can be studied to prove their effectiveness for privacy protection. Second level issues that stem from practical application of the implemented mechanisms, such as usability, life-time data management and changes in trustworthiness have received very little attention so far, mainly because they require actual implementations to be studied. Most existing privacy protection schemes silently assume that it is the privilege of the data user to define the contract under which personal private data is released. Such an approach simplifies policy management and policy enforcement for the data user, but leaves the data owner with a binary decision to submit or withhold his or her personal data based on the provided policy. We wanted to empower the data owner to express his or her privacy preferences through privacy policies that follow the so-called Owner-Retained Access Control (ORAC) model. ORAC has been proposed by McCollum, et al. as an alternate access control mechanism that leaves the authority over access decisions by the originator of the data. The data owner is given control over the release policy for his or her personal data, and he or she can set permissions or restrictions according to individually perceived trust values. Such a policy needs to be expressed in a coherent way and must allow the deterministic policy evaluation by different entities. The privacy policy also needs to be communicated from the data owner to the data user, so that it can be enforced. Data and policy are stored together as a Protected Data Object that follows the Sticky Policy paradigm as defined by Mont, et al. and others. We developed a unique policy combination approach that takes usability aspects for the creation and maintenance of policies into consideration. Our privacy policy consists of three parts: A Default Policy provides basic privacy protection if no specific rules have been entered by the data owner. An Owner Policy part allows the customisation of the default policy by the data owner. And a so-called Safety Policy guarantees that the data owner cannot specify disadvantageous policies, which, for example, exclude him or her from further access to the private data. The combined evaluation of these three policy-parts yields the necessary access decision. The automatic enforcement of privacy policies in our protection framework is supported by a reference monitor implementation. We started our work with the development of a client-side protection mechanism that allows the enforcement of data-use restrictions after private data has been released to the data user. The client-side enforcement component for data-use policies is based on a modified Java Security Framework. Privacy policies are translated into corresponding Java permissions that can be automatically enforced by the Java Security Manager. When we later extended our work to implement server-side protection mechanisms, we found several drawbacks for the privacy enforcement through the Java Security Framework. We solved this problem by extending our reference monitor design to use Aspect-Oriented Programming (AOP) and the Java Reflection API to intercept data accesses in existing applications and provide a way to enforce data owner-defined privacy policies for business applications.
Answer Set Programming (ASP) emerged in the late 1990s as a new logic programming paradigm, having its roots in nonmonotonic reasoning, deductive databases, and logic programming with negation as failure. The basic idea of ASP is to represent a computational problem as a logic program whose answer sets correspond to solutions, and then to use an answer set solver for finding answer sets of the program. ASP is particularly suited for solving NP-complete search problems. Among these, we find applications to product configuration, diagnosis, and graph-theoretical problems, e.g. finding Hamiltonian cycles. On different lines of ASP research, many extensions of the basic formalism have been proposed. The most intensively studied one is the modelling of preferences in ASP. They constitute a natural and effective way of selecting preferred solutions among a plethora of solutions for a problem. For example, preferences have been successfully used for timetabling, auctioning, and product configuration. In this thesis, we concentrate on preferences within answer set programming. Among several formalisms and semantics for preference handling in ASP, we concentrate on ordered logic programs with the underlying D-, W-, and B-semantics. In this setting, preferences are defined among rules of a logic program. They select preferred answer sets among (standard) answer sets of the underlying logic program. Up to now, those preferred answer sets have been computed either via a compilation method or by meta-interpretation. Hence, the question comes up, whether and how preferences can be integrated into an existing ASP solver. To solve this question, we develop an operational graph-based framework for the computation of answer sets of logic programs. Then, we integrate preferences into this operational approach. We empirically observe that our integrative approach performs in most cases better than the compilation method or meta-interpretation. Another research issue in ASP are optimization methods that remove redundancies, as also found in database query optimizers. For these purposes, the rather recently suggested notion of strong equivalence for ASP can be used. If a program is strongly equivalent to a subprogram of itself, then one can always use the subprogram instead of the original program, a technique which serves as an effective optimization method. Up to now, strong equivalence has not been considered for logic programs with preferences. In this thesis, we tackle this issue and generalize the notion of strong equivalence to ordered logic programs. We give necessary and sufficient conditions for the strong equivalence of two ordered logic programs. Furthermore, we provide program transformations for ordered logic programs and show in how far preferences can be simplified. Finally, we present two new applications for preferences within answer set programming. First, we define new procedures for group decision making, which we apply to the problem of scheduling a group meeting. As a second new application, we reconstruct a linguistic problem appearing in German dialects within ASP. Regarding linguistic studies, there is an ongoing debate about how unique the rule systems of language are in human cognition. The reconstruction of grammatical regularities with tools from computer science has consequences for this debate: if grammars can be modelled this way, then they share core properties with other non-linguistic rule systems.
Preface
(2010)
The workshops on (constraint) logic programming (WLP) are the annual meeting of the Society of Logic Programming (GLP e.V.) and bring together researchers interested in logic programming, constraint programming, and related areas like databases, artificial intelligence and operations research. In this decade, previous workshops took place in Dresden (2008), Würzburg (2007), Vienna (2006), Ulm (2005), Potsdam (2004), Dresden (2002), Kiel (2001), and Würzburg (2000). Contributions to workshops deal with all theoretical, experimental, and application aspects of constraint programming (CP) and logic programming (LP), including foundations of constraint/ logic programming. Some of the special topics are constraint solving and optimization, extensions of functional logic programming, deductive databases, data mining, nonmonotonic reasoning, , interaction of CP/LP with other formalisms like agents, XML, JAVA, program analysis, program transformation, program verification, meta programming, parallelism and concurrency, answer set programming, implementation and software techniques (e.g., types, modularity, design patterns), applications (e.g., in production, environment, education, internet), constraint/logic programming for semantic web systems and applications, reasoning on the semantic web, data modelling for the web, semistructured data, and web query languages.
Learning a model for the relationship between the attributes and the annotated labels of data examples serves two purposes. Firstly, it enables the prediction of the label for examples without annotation. Secondly, the parameters of the model can provide useful insights into the structure of the data. If the data has an inherent partitioned structure, it is natural to mirror this structure in the model. Such mixture models predict by combining the individual predictions generated by the mixture components which correspond to the partitions in the data. Often the partitioned structure is latent, and has to be inferred when learning the mixture model. Directly evaluating the accuracy of the inferred partition structure is, in many cases, impossible because the ground truth cannot be obtained for comparison. However it can be assessed indirectly by measuring the prediction accuracy of the mixture model that arises from it. This thesis addresses the interplay between the improvement of predictive accuracy by uncovering latent cluster structure in data, and further addresses the validation of the estimated structure by measuring the accuracy of the resulting predictive model. In the application of filtering unsolicited emails, the emails in the training set are latently clustered into advertisement campaigns. Uncovering this latent structure allows filtering of future emails with very low false positive rates. In order to model the cluster structure, a Bayesian clustering model for dependent binary features is developed in this thesis. Knowing the clustering of emails into campaigns can also aid in uncovering which emails have been sent on behalf of the same network of captured hosts, so-called botnets. This association of emails to networks is another layer of latent clustering. Uncovering this latent structure allows service providers to further increase the accuracy of email filtering and to effectively defend against distributed denial-of-service attacks. To this end, a discriminative clustering model is derived in this thesis that is based on the graph of observed emails. The partitionings inferred using this model are evaluated through their capacity to predict the campaigns of new emails. Furthermore, when classifying the content of emails, statistical information about the sending server can be valuable. Learning a model that is able to make use of it requires training data that includes server statistics. In order to also use training data where the server statistics are missing, a model that is a mixture over potentially all substitutions thereof is developed. Another application is to predict the navigation behavior of the users of a website. Here, there is no a priori partitioning of the users into clusters, but to understand different usage scenarios and design different layouts for them, imposing a partitioning is necessary. The presented approach simultaneously optimizes the discriminative as well as the predictive power of the clusters. Each model is evaluated on real-world data and compared to baseline methods. The results show that explicitly modeling the assumptions about the latent cluster structure leads to improved predictions compared to the baselines. It is beneficial to incorporate a small number of hyperparameters that can be tuned to yield the best predictions in cases where the prediction accuracy can not be optimized directly.
In many applications one is faced with the problem of inferring some functional relation between input and output variables from given data. Consider, for instance, the task of email spam filtering where one seeks to find a model which automatically assigns new, previously unseen emails to class spam or non-spam. Building such a predictive model based on observed training inputs (e.g., emails) with corresponding outputs (e.g., spam labels) is a major goal of machine learning. Many learning methods assume that these training data are governed by the same distribution as the test data which the predictive model will be exposed to at application time. That assumption is violated when the test data are generated in response to the presence of a predictive model. This becomes apparent, for instance, in the above example of email spam filtering. Here, email service providers employ spam filters and spam senders engineer campaign templates such as to achieve a high rate of successful deliveries despite any filters. Most of the existing work casts such situations as learning robust models which are unsusceptible against small changes of the data generation process. The models are constructed under the worst-case assumption that these changes are performed such to produce the highest possible adverse effect on the performance of the predictive model. However, this approach is not capable to realistically model the true dependency between the model-building process and the process of generating future data. We therefore establish the concept of prediction games: We model the interaction between a learner, who builds the predictive model, and a data generator, who controls the process of data generation, as an one-shot game. The game-theoretic framework enables us to explicitly model the players' interests, their possible actions, their level of knowledge about each other, and the order at which they decide for an action. We model the players' interests as minimizing their own cost function which both depend on both players' actions. The learner's action is to choose the model parameters and the data generator's action is to perturbate the training data which reflects the modification of the data generation process with respect to the past data. We extensively study three instances of prediction games which differ regarding the order in which the players decide for their action. We first assume that both player choose their actions simultaneously, that is, without the knowledge of their opponent's decision. We identify conditions under which this Nash prediction game has a meaningful solution, that is, a unique Nash equilibrium, and derive algorithms that find the equilibrial prediction model. As a second case, we consider a data generator who is potentially fully informed about the move of the learner. This setting establishes a Stackelberg competition. We derive a relaxed optimization criterion to determine the solution of this game and show that this Stackelberg prediction game generalizes existing prediction models. Finally, we study the setting where the learner observes the data generator's action, that is, the (unlabeled) test data, before building the predictive model. As the test data and the training data may be governed by differing probability distributions, this scenario reduces to learning under covariate shift. We derive a new integrated as well as a two-stage method to account for this data set shift. In case studies on email spam filtering we empirically explore properties of all derived models as well as several existing baseline methods. We show that spam filters resulting from the Nash prediction game as well as the Stackelberg prediction game in the majority of cases outperform other existing baseline methods.
Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models’ accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases.
PLATON
(2019)
Lesson planning is both an important and demanding task—especially as part of teacher training. This paper presents the requirements for a lesson planning system and evaluates existing systems regarding these requirements. One major drawback of existing software tools is that most are limited to a text- or form-based representation of the lesson designs. In this article, a new approach with a graphical, time-based representation with (automatic) analyses methods is proposed and the system architecture and domain model are described in detail. The approach is implemented in an interactive, web-based prototype called PLATON, which additionally supports the management of lessons in units as well as the modelling of teacher and student-generated resources. The prototype was evaluated in a study with 61 prospective teachers (bachelor’s and master’s preservice teachers as well as teacher trainees in post-university teacher training) in Berlin, Germany, with a focus on usability. The results show that this approach proofed usable for lesson planning and offers positive effects for the perception of time and self-reflection.
The objective and motivation behind this research is to provide applications with easy-to-use interfaces to communities of deaf and functionally illiterate users, which enables them to work without any human assistance. Although recent years have witnessed technological advancements, the availability of technology does not ensure accessibility to information and communication technologies (ICT). Extensive use of text from menus to document contents means that deaf or functionally illiterate can not access services implemented on most computer software. Consequently, most existing computer applications pose an accessibility barrier to those who are unable to read fluently. Online technologies intended for such groups should be developed in continuous partnership with primary users and include a thorough investigation into their limitations, requirements and usability barriers. In this research, I investigated existing tools in voice, web and other multimedia technologies to identify learning gaps and explored ways to enhance the information literacy for deaf and functionally illiterate users. I worked on the development of user-centered interfaces to increase the capabilities of deaf and low literacy users by enhancing lexical resources and by evaluating several multimedia interfaces for them. The interface of the platform-independent Italian Sign Language (LIS) Dictionary has been developed to enhance the lexical resources for deaf users. The Sign Language Dictionary accepts Italian lemmas as input and provides their representation in the Italian Sign Language as output. The Sign Language dictionary has 3082 signs as set of Avatar animations in which each sign is linked to a corresponding Italian lemma. I integrated the LIS lexical resources with MultiWordNet (MWN) database to form the first LIS MultiWordNet(LMWN). LMWN contains information about lexical relations between words, semantic relations between lexical concepts (synsets), correspondences between Italian and sign language lexical concepts and semantic fields (domains). The approach enhances the deaf users’ understanding of written Italian language and shows that a relatively small set of lexicon can cover a significant portion of MWN. Integration of LIS signs with MWN made it useful tool for computational linguistics and natural language processing. The rule-based translation process from written Italian text to LIS has been transformed into service-oriented system. The translation process is composed of various modules including parser, semantic interpreter, generator, and spatial allocation planner. This translation procedure has been implemented in the Java Application Building Center (jABC), which is a framework for extreme model driven design (XMDD). The XMDD approach focuses on bringing software development closer to conceptual design, so that the functionality of a software solution could be understood by someone who is unfamiliar with programming concepts. The transformation addresses the heterogeneity challenge and enhances the re-usability of the system. For enhancing the e-participation of functionally illiterate users, two detailed studies were conducted in the Republic of Rwanda. In the first study, the traditional (textual) interface was compared with the virtual character-based interactive interface. The study helped to identify usability barriers and users evaluated these interfaces according to three fundamental areas of usability, i.e. effectiveness, efficiency and satisfaction. In another study, we developed four different interfaces to analyze the usability and effects of online assistance (consistent help) for functionally illiterate users and compared different help modes including textual, vocal and virtual character on the performance of semi-literate users. In our newly designed interfaces the instructions were automatically translated in Swahili language. All the interfaces were evaluated on the basis of task accomplishment, time consumption, System Usability Scale (SUS) rating and number of times the help was acquired. The results show that the performance of semi-literate users improved significantly when using the online assistance. The dissertation thus introduces a new development approach in which virtual characters are used as additional support for barely literate or naturally challenged users. Such components enhanced the application utility by offering a variety of services like translating contents in local language, providing additional vocal information, and performing automatic translation from text to sign language. Obviously, there is no such thing as one design solution that fits for all in the underlying domain. Context sensitivity, literacy and mental abilities are key factors on which I concentrated and the results emphasize that computer interfaces must be based on a thoughtful definition of target groups, purposes and objectives.
Computer Security deals with the detection and mitigation of threats to computer networks, data, and computing hardware. This
thesis addresses the following two computer security problems: email spam campaign and malware detection.
Email spam campaigns can easily be generated using popular dissemination tools by specifying simple grammars that serve as message templates. A grammar is disseminated to nodes of a bot net, the nodes create messages by instantiating the grammar at random. Email spam campaigns can encompass huge data volumes and therefore pose a threat to the stability of the infrastructure of email service providers that have to store them. Malware -software that serves a malicious purpose- is affecting web servers, client computers via active content, and client computers through executable files. Without the help of malware detection systems it would be easy for malware creators to collect sensitive information or to infiltrate computers.
The detection of threats -such as email-spam messages, phishing messages, or malware- is an adversarial and therefore intrinsically
difficult problem. Threats vary greatly and evolve over time. The detection of threats based on manually-designed rules is therefore
difficult and requires a constant engineering effort. Machine-learning is a research area that revolves around the analysis of data and the discovery of patterns that describe aspects of the data. Discriminative learning methods extract prediction models from data that are optimized to predict a target attribute as accurately as possible. Machine-learning methods hold the promise of automatically identifying patterns that robustly and accurately detect threats. This thesis focuses on the design and analysis of discriminative learning methods for the two computer-security problems under investigation: email-campaign and malware detection.
The first part of this thesis addresses email-campaign detection. We focus on regular expressions as a syntactic framework, because regular expressions are intuitively comprehensible by security engineers and administrators, and they can be applied as a detection mechanism in an extremely efficient manner. In this setting, a prediction model is provided with exemplary messages from an email-spam campaign. The prediction model has to generate a regular expression that reveals the syntactic pattern that underlies the entire campaign, and that a security engineers finds comprehensible and feels confident enough to use the expression to blacklist further messages at the email server. We model this problem as two-stage learning problem with structured input and output spaces which can be solved using standard cutting plane methods. Therefore we develop an appropriate loss function, and derive a decoder for the resulting optimization problem.
The second part of this thesis deals with the problem of predicting whether a given JavaScript or PHP file is malicious or benign. Recent malware analysis techniques use static or dynamic features, or both. In fully dynamic analysis, the software or script is executed and observed for malicious behavior in a sandbox environment. By contrast, static analysis is based on features that can be extracted directly from the program file. In order to bypass static detection mechanisms, code obfuscation techniques are used to spread a malicious program file in many different syntactic variants. Deobfuscating the code before applying a static classifier can be subjected to mostly static code analysis and can overcome the problem of obfuscated malicious code, but on the other hand increases the computational costs of malware detection by an order of magnitude. In this thesis we present a cascaded architecture in which a classifier first performs a static analysis of the original code and -based on the outcome of this first classification step- the code may be deobfuscated and classified again. We explore several types of features including token $n$-grams, orthogonal sparse bigrams, subroutine-hashings, and syntax-tree features and study the robustness of detection methods and feature types against the evolution of malware over time. The developed tool scans very large file collections quickly and accurately.
Each model is evaluated on real-world data and compared to reference methods. Our approach of inferring regular expressions to filter emails belonging to an email spam campaigns leads to models with a high true-positive rate at a very low false-positive rate that is an order of magnitude lower than that of a commercial content-based filter. Our presented system -REx-SVMshort- is being used by a commercial email service provider and complements content-based and IP-address based filtering.
Our cascaded malware detection system is evaluated on a high-quality data set of almost 400,000 conspicuous PHP files and a collection of more than 1,00,000 JavaScript files. From our case study we can conclude that our system can quickly and accurately process large data collections at a low false-positive rate.
The objective of this thesis is to provide new space compaction techniques for testing or concurrent checking of digital circuits. In particular, the work focuses on the design of space compactors that achieve high compaction ratio and minimal loss of testability of the circuits. In the first part, the compactors are designed for combinational circuits based on the knowledge of the circuit structure. Several algorithms for analyzing circuit structures are introduced and discussed for the first time. The complexity of each design procedure is linear with respect to the number of gates of the circuit. Thus, the procedures are applicable to large circuits. In the second part, the first structural approach for output compaction for sequential circuits is introduced. Essentially, it enhances the first part. For the approach introduced in the third part it is assumed that the structure of the circuit and the underlying fault model are unknown. The space compaction approach requires only the knowledge of the fault-free test responses for a precomputed test set. The proposed compactor design guarantees zero-aliasing with respect to the precomputed test set.
Contemporary multi-core processors are parallel systems that also provide shared memory for programs running on them. Both the increasing number of cores in so-called many-core systems and the still growing computational power of the cores demand for memory systems that are able to deliver high bandwidths. Caches are essential components to satisfy this requirement. Nevertheless, hardware-based cache coherence in many-core chips faces practical limits to provide both coherence and high memory bandwidths. In addition, a shift away from global coherence can be observed. As a result, alternative architectures and suitable programming models need to be investigated.
This thesis focuses on fast communication for non-cache-coherent many-core architectures. Experiments are conducted on the Single-Chip Cloud Computer (SCC), a non-cache-coherent many-core processor with 48 mesh-connected cores. Although originally designed for message passing, the results of this thesis show that shared memory can be efficiently used for one-sided communication on this kind of architecture. One-sided communication enables data exchanges between processes where the receiver is not required to know the details of the performed communication. In the notion of the Message Passing Interface (MPI) standard, this type of communication allows to access memory of remote processes. In order to support this communication scheme on non-cache-coherent architectures, both an efficient process synchronization and a communication scheme with software-managed cache coherence are designed and investigated.
The process synchronization realizes the concept of the general active target synchronization scheme from the MPI standard. An existing classification of implementation approaches is extended and used to identify an appropriate class for the non-cache-coherent shared memory platform. Based on this classification, existing implementations are surveyed in order to find beneficial concepts, which are then used to design a lightweight synchronization protocol for the SCC that uses shared memory and uncached memory accesses. The proposed scheme is not prone to process skew and also enables direct communication as soon as both communication partners are ready. Experimental results show very good scaling properties and up to five times lower synchronization latency compared to a tuned message-based MPI implementation for the SCC.
For the communication, SCOSCo, a shared memory approach with software-managed cache coherence, is presented. According requirements for the coherence that fulfill MPI's separate memory model are formulated, and a lightweight implementation exploiting SCC hard- and software features is developed. Despite a discovered malfunction in the SCC's memory subsystem, the experimental evaluation of the design reveals up to five times better bandwidths and nearly four times lower latencies in micro-benchmarks compared to the SCC-tuned but message-based MPI library. For application benchmarks, like a parallel 3D fast Fourier transform, the runtime share of communication can be reduced by a factor of up to five. In addition, this thesis postulates beneficial hardware concepts that would support software-managed coherence for one-sided communication on future non-cache-coherent architectures where coherence might be only available in local subdomains but not on a global processor level.