Institut für Informatik und Computational Science
Refine
Year of publication
Document Type
- Doctoral Thesis (206) (remove)
Keywords
- Maschinelles Lernen (7)
- Antwortmengenprogrammierung (6)
- Machine Learning (6)
- Modellierung (5)
- answer set programming (4)
- Answer Set Programming (3)
- Ontologie (3)
- Semantic Web (3)
- machine learning (3)
- Algorithmen (2)
- Algorithms (2)
- Bildungstechnologien (2)
- Bildverarbeitung (2)
- Codierungstheorie (2)
- Computergrafik (2)
- Computersicherheit (2)
- Coq (2)
- Deep Learning (2)
- EEG (2)
- Educational Technologies (2)
- FMC (2)
- Fehlererkennung (2)
- HCI (2)
- ICA (2)
- Informatik (2)
- Knowledge Representation and Reasoning (2)
- Komplexität (2)
- Künstliche Intelligenz (2)
- Mensch-Computer-Interaktion (2)
- Middleware (2)
- Modeling (2)
- Modell (2)
- Ontology (2)
- Optimierung (2)
- Process (2)
- Prozess (2)
- Prozessmodellierung (2)
- Software Engineering (2)
- Softwareentwicklung (2)
- Synthese (2)
- Systemstruktur (2)
- Texturen (2)
- Visualisierung (2)
- Vorhersage (2)
- computer graphics (2)
- human computer interaction (2)
- image processing (2)
- maschinelles Lernen (2)
- model (2)
- non-photorealistic rendering (2)
- systems biology (2)
- test (2)
- textures (2)
- virtual 3D city models (2)
- virtuelle 3D-Stadtmodelle (2)
- visualization (2)
- 'Peer To Peer' (1)
- 3D Computer Grafik (1)
- 3D Computer Graphics (1)
- 3D Drucken (1)
- 3D Semiotik (1)
- 3D Visualisierung (1)
- 3D computer graphics (1)
- 3D printing (1)
- 3D semiotics (1)
- 3D visualization (1)
- 3D-Stadtmodelle (1)
- 3d city models (1)
- 6LoWPAN (1)
- ASIC (1)
- ASIC (Applikationsspezifische Integrierte Schaltkreise) (1)
- ASP (Answer Set Programming) (1)
- Abbrecherquote (1)
- Abstraktion (1)
- Ackerschmalwand (1)
- Active Evaluation (1)
- Adaptivity (1)
- Adaptivität (1)
- Adversarial Learning (1)
- Aktive Evaluierung (1)
- Algorithmenablaufplanung (1)
- Algorithmenkonfiguration (1)
- Algorithmenselektion (1)
- Android Security (1)
- Angewandte Spieltheorie (1)
- Anisotroper Kuwahara Filter (1)
- Anleitung (1)
- Answer Set Solving modulo Theories (1)
- Antwortmengen Programmierung (1)
- Application Aggregation (1)
- Applications and Software Development (1)
- Applied Game Theory (1)
- Argumentation (1)
- Artificial Intelligence (1)
- Artificial Neuronal Network (1)
- Aspect-Oriented Programming (1)
- Aspektorientierte Programmierung (1)
- Asynchrone Schaltung (1)
- Attention (1)
- Aufmerksamkeit (1)
- Augenbewegungen (1)
- Ausreissererkennung (1)
- Autism (1)
- Autismus (1)
- Automatic UI Generation (1)
- BCH (1)
- BCH code (1)
- BCH-Code (1)
- BCI (1)
- BSS (1)
- Bachelorstudierende der Informatik (1)
- Baumweite (1)
- Behavior (1)
- Benutzeroberfläche (1)
- Benutzungsschnittstellen Ontologien (1)
- Berührungseingaben (1)
- Betrachtungsebenen (1)
- Beweis (1)
- Beweisassistent (1)
- Beweistheorie (1)
- Beweisumgebung (1)
- Bilddatenanalyse (1)
- Binäres Entscheidungsdiagramm (1)
- Bioelektrisches Signal (1)
- Bioinformatik (1)
- Boolean constraint solver (1)
- Boosting (1)
- Brain Computer Interface (1)
- Business Process (1)
- Business Process Models (1)
- CASP (Constraint Answer Set Programming) (1)
- CSC (1)
- Cactus (1)
- CertiCoq (1)
- Choreographien (1)
- CityGML (1)
- Classification (1)
- Cloud Computing (1)
- Cloud computing (1)
- Clusteranalyse (1)
- Code (1)
- Coding theory (1)
- Common Spatial Pattern (1)
- Complementary Circuits (1)
- Complexity (1)
- Compliance (1)
- Composed UIs (1)
- Composition (1)
- Computational Complexity (1)
- Computer Science (1)
- Conceptual (1)
- Constructive solid geometry (1)
- Covariate Shift (1)
- Curry (1)
- DDoS (1)
- DPLL (1)
- Data Privacy (1)
- Datenschutz (1)
- Declarative Problem Solving (1)
- Dempster-Shafer-Theorie (1)
- Dempster–Shafer theory (1)
- Description Logics (1)
- Deskriptive Logik (1)
- Diagonalisierung (1)
- Dialog-based User Interfaces (1)
- Dialogbasierte Benutzerschnittstellen (1)
- Didaktik (1)
- Didaktik der Informatik (1)
- Dienst-Ökosysteme (1)
- Dienstkomposition (1)
- Dienstplattform (1)
- Differenz von Gauss Filtern (1)
- Digital Design (1)
- Digital Media (1)
- Digitale Medien (1)
- Digitalisation (1)
- Digitalisierung (1)
- Distributed Computing (1)
- Domain-Specific Languages (1)
- Domänenspezifische Sprachen (1)
- Dreidimensionale Computergraphik (1)
- Dynamic Programming (1)
- Dynamische Programmierung (1)
- Dynamische Rekonfiguration (1)
- E-Government (1)
- E-Learning (1)
- Eingabegenauigkeit (1)
- Elektroencephalographie (1)
- Emotionen (1)
- Emotionsforschung (1)
- Enterprise Architecture (1)
- Enterprise Search (1)
- Entscheidungsbäume (1)
- Entwurf (1)
- Entwurfsmuster für SOA-Sicherheit (1)
- Entwurfsprinzipien (1)
- Entwurfsraumexploration (1)
- Erfüllbarkeit einer Formel der Aussagenlogik (1)
- Erfüllbarkeitsproblem (1)
- Erklärbarkeit (1)
- Error Estimation (1)
- Error-Detection Circuits (1)
- Evaluierung semantischer Suchmaschinen (1)
- Evidenztheorie (1)
- Explainability (1)
- Exploration (1)
- Exponential Time Hypothesis (1)
- Exponentialzeit Hypothese (1)
- FMC-QE (1)
- FPGA (1)
- Feature Combination (1)
- Feedback (1)
- Fehlende Daten (1)
- Fehlerkorrektur (1)
- Fehlerschätzung (1)
- Fehlvorstellung (1)
- Flussgesteuerter Bilateraler Filter (1)
- Focus+Context Visualization (1)
- Fokus-&-Kontext Visualisierung (1)
- Formalismus (1)
- Formalitätsgrad (1)
- Formeln der quantifizierten Aussagenlogik (1)
- Forschendes Lernen (1)
- GIS-Dienstkomposition (1)
- GPU (1)
- Gebäudemodelle (1)
- Gehirn-Computer-Schnittstelle (1)
- Geländemodelle (1)
- Generalisierung (1)
- Generative Programmierung (1)
- Generative Programming (1)
- Geodaten (1)
- Geometrieerzeugung (1)
- Geovisualisierung (1)
- Geräte-Treiber (1)
- Geschäftsprozess (1)
- Geschäftsprozessmodelle (1)
- Gesichtsausdruck (1)
- Globus (1)
- Grammatikalische Inferenz (1)
- Graph-basiertes Ranking (1)
- Grid (1)
- Grid Computing (1)
- Grounding Theory (1)
- Hardware Design (1)
- Hardware-Software-Co-Design (1)
- Hauptkomponentenanalyse (1)
- High-Level Synthesis (1)
- Hochschulsystem (1)
- Human-Technology Interaction (1)
- I/O-effiziente Algorithmen (1)
- IP core (1)
- IT security (1)
- IT-Security (1)
- IT-Sicherheit (1)
- Industrie 4.0 (1)
- Industry 4.0 (1)
- Informatik-Studiengänge (1)
- Informatikvoraussetzungen (1)
- Information Transfer Rate (1)
- Informationsextraktion (1)
- Inkonsistenz (1)
- Inquiry-based learning (1)
- Interactive Rendering (1)
- Interactive system (1)
- Interaktionsmodel (1)
- Interaktionsmodellierung (1)
- Interaktionstechniken (1)
- Interaktives Rendering (1)
- Interaktives System (1)
- Internet Security (1)
- Internet applications (1)
- Internet of Things (1)
- Internet-Sicherheit (1)
- Internetanwendungen (1)
- Interoperability (1)
- Interoperabilität (1)
- Interpretability (1)
- Interpretierbarkeit (1)
- Intuition (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)
- Knowledge (1)
- Knowledge Management (1)
- Kommunikation (1)
- Kompilation (1)
- Komplexitätsbewältigung (1)
- Komplexitätstheorie (1)
- Komposition (1)
- Konzeptionell (1)
- Kybernetik (1)
- Künstliche Neuronale Netzwerke (1)
- LDPC code (1)
- LDPC-Code (1)
- Landmarken (1)
- Large Margin Classification (1)
- Laser Cutten (1)
- Learning (1)
- Lehrer (1)
- Leistungsfähigkeit (1)
- Leistungsvorhersage (1)
- Lernen (1)
- Linked Data Anwendungen (1)
- Linked Data Application Modelling (1)
- Linux (1)
- Linux device drivers (1)
- Logik (1)
- Logiksynthese (1)
- Lower Bounds (1)
- MEG (1)
- MQTT (1)
- Magnetoencephalographie (1)
- Malware (1)
- Mathematical Optimization (1)
- Mathematikdidaktik (1)
- Mathematikphilosophie (1)
- Mathematische Optimierung (1)
- Matrizen-Eigenwertaufgabe (1)
- Megamodel (1)
- Megamodell (1)
- Mehrklassen-Klassifikation (1)
- Mensch-Technik-Interaktion (1)
- Message Passing Interface (1)
- Metamodell (1)
- Methoden der semantischen Suche (1)
- Methodik (1)
- Methodology (1)
- Migration (1)
- Mischmodelle (1)
- Mischung <Signalverarbeitung> (1)
- Mobilgeräte (1)
- Model Based Engineering (1)
- Model Checking (1)
- Model Driven Architecture (1)
- Model Driven UI Development (1)
- Model Management (1)
- Model-Driven Engineering (1)
- Model-Driven Software Development (1)
- Modell Management (1)
- Modell-driven Security (1)
- Modell-getriebene Sicherheit (1)
- Modellbasiert (1)
- Modellgetriebene Architektur (1)
- Modellgetriebene Entwicklung (1)
- Modellgetriebene Softwareentwicklung (1)
- Modellgetriebene UI Entwicklung (1)
- Modelling (1)
- Molekulare Bioinformatik (1)
- Multi Task Learning (1)
- Multi-Class (1)
- Multi-Task-Lernen (1)
- Multimodal User Interfaces (1)
- Multimodale Benutzerschnittstellen (1)
- Multiprocessor (1)
- Multiprozessor (1)
- NETCONF (1)
- Network Management (1)
- Netzwerk Management (1)
- Netzwerke (1)
- Neuronales Netz (1)
- New On-Line Error-Detection Methode (1)
- Next Generation Network (1)
- Nicht-photorealistisches Rendering (1)
- Nichtfotorealistische Bildsynthese (1)
- Nutzungsinteresse (1)
- Objektive Schwierigkeit (1)
- Ontologien (1)
- Ontologies (1)
- Open Source (1)
- Optimierungsproblem (1)
- Optimization (1)
- Owner-Retained Access Control (ORAC) (1)
- Parallel Programming (1)
- Parallele Datenverarbeitung (1)
- Paralleles Rechnen (1)
- Parallelrechner (1)
- Parameterized Complexity (1)
- Parametrisierte Komplexität (1)
- Patterns (1)
- Peer-to-Peer-Netz ; GRID computing ; Zuverlässigkeit ; Web Services ; Betriebsmittelverwaltung ; Migration (1)
- Performance (1)
- Performance Prediction (1)
- Platzierung (1)
- Policy Enforcement (1)
- Policy Languages (1)
- Policy Sprachen (1)
- Power Monitoring (1)
- Pre-RS Traceability (1)
- Prediction Game (1)
- Predictive Models (1)
- Preference Handling (1)
- Privacy Protection (1)
- Probleme in der Studie (1)
- Process Management (1)
- Process modeling (1)
- Professoren (1)
- Programmierung (1)
- Proof Theory (1)
- Prozess Verbesserung (1)
- Prozesse (1)
- Prozessmanagement (1)
- Prozessmodell (1)
- Prozesssynchronisierung (1)
- Prädiktionsspiel (1)
- Präferenzen (1)
- Quantified Boolean Formula (QBF) (1)
- Quantitative Modeling (1)
- Quantitative Modellierung (1)
- Queuing Theory (1)
- Reconfigurable (1)
- Regression (1)
- Regularisierung (1)
- Regularization (1)
- Rekonfiguration (1)
- Rendering (1)
- Reparatur (1)
- Reuseable UIs (1)
- SMT (SAT Modulo Theories) (1)
- SOA Security Pattern (1)
- STG decomposition (1)
- STG-Dekomposition (1)
- Sample Selection Bias (1)
- Satisfiability (1)
- Scalability (1)
- Scene graph systems (1)
- Schulmaterial (1)
- Security Modelling (1)
- Segmentierung (1)
- Selektionsbias (1)
- Self-Checking Circuits (1)
- Semantic Search (1)
- Semantik Web (1)
- Semantische Suche (1)
- Sensornetzwerke (1)
- Service Creation (1)
- Service Delivery Platform (1)
- Service Ecosystems (1)
- Service Oriented Architectures (1)
- Service convergence (1)
- Service-Orientierte Architekturen (1)
- Service-oriented Architectures (1)
- Serviceorientierte Architektur (1)
- Sicherheitsmodellierung (1)
- Signal Processing (1)
- Signalquellentrennung (1)
- Signaltrennung (1)
- Simulation (1)
- Simultane Diagonalisierung (1)
- Single Event Transient (1)
- Single Trial Analysis (1)
- Skalierbarkeit (1)
- Skelettberechnung (1)
- Software (1)
- Software architecture (1)
- Software-basierte Cache-Kohärenz (1)
- Softwarearchitektur (1)
- Sonnenteilchen-Ereignis (1)
- Spam (1)
- Spam Filtering (1)
- Spam-Erkennung (1)
- Spam-Filter (1)
- Spam-Filtering (1)
- Spatio-Spectral Filter (1)
- Spawning (1)
- Speicher (1)
- Spielbasiertes Lernen (1)
- Sprachdesign (1)
- Static Analysis (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)
- System Biologie (1)
- System structure (1)
- Systembiologie (1)
- Systementwurf (1)
- Szenengraph (1)
- Tailored UI Variants (1)
- Taktik (1)
- Telekommunikation (1)
- Temporal Answer Set Solving (1)
- Temporal Logic (1)
- Temporallogik (1)
- Temporäre Anbindung (1)
- Terminologische Logik (1)
- Test (1)
- Theoretischen Vorlesungen (1)
- Time Augmented Petri Nets (1)
- Time Series Analysis (1)
- Traceability (1)
- Tracking (1)
- Transformation (1)
- Treewidth (1)
- UI Components (1)
- UI Metamodels (1)
- UI-Komponenten (1)
- Unabhängige Komponentenanalyse (1)
- Universität Bagdad (1)
- Universität Potsdam (1)
- Universitätseinstellungen (1)
- Untere Schranken (1)
- Unterrichtswerkzeuge (1)
- Unvollständigkeit (1)
- Usage Interest (1)
- User Interface Ontologies (1)
- User Interfaces (1)
- VM (1)
- Verhalten (1)
- Verifikation (1)
- Verletzung Auflösung (1)
- Verletzung Erklärung (1)
- Verteiltes Rechnen (1)
- Verteilungsunterschied (1)
- Violation Explanation (1)
- Violation Resolution (1)
- Virtual Reality (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)
- Wissen (1)
- Wissenschaftlichesworkflows (1)
- Wissensmanagement (1)
- Wissensrepräsentation und -verarbeitung (1)
- Wissensrepräsentation und Schlussfolgerung (1)
- Wohlstrukturiertheit (1)
- ZQSA (1)
- ZQSAT (1)
- Zeitbehaftete Petri Netze (1)
- Zero-Suppressed Binary Decision Diagram (ZDD) (1)
- Zuverlässigkeitsanalyse (1)
- abstraction (1)
- adaptiv (1)
- adaptive (1)
- algorithm configuration (1)
- algorithm scheduling (1)
- algorithm selection (1)
- anisotropic Kuwahara filter (1)
- approximate joint diagonalization (1)
- argumentation (1)
- arousal perception (1)
- artificial intelligence (1)
- assistive Technologien (1)
- assistive technologies (1)
- asynchronous circuit (1)
- bild (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 material (1)
- climate change (1)
- climate impact analysis (1)
- clustering (1)
- code (1)
- coherence-enhancing filtering (1)
- communication (1)
- compilation (1)
- complexity (1)
- computational biology (1)
- computational methods (1)
- computer science education (1)
- computer security (1)
- computergestützte Methoden (1)
- concurrent checking (1)
- constraints (1)
- decision trees (1)
- degree of formality (1)
- design (1)
- design principles (1)
- design space exploration (1)
- didactics (1)
- didaktische Rekonstruktion (1)
- difference of Gaussians (1)
- digital circuit (1)
- digital design (1)
- dropout (1)
- dynamic (1)
- dynamic classification (1)
- dynamic reconfiguration (1)
- dynamisch (1)
- dynamische Klassifikation (1)
- e-Learning (1)
- eGovernment (1)
- educational reconstruction (1)
- eingebettete Systeme (1)
- einseitige Kommunikation (1)
- email spam detection (1)
- embedded systems (1)
- emotion (1)
- emotion representation (1)
- emotion research (1)
- enterprise search (1)
- entity alignment (1)
- error correction (1)
- error detection (1)
- evidence theory (1)
- external memory algorithms (1)
- eye movements (1)
- face tracking (1)
- facial expression (1)
- flow-based bilateral filter (1)
- formalism (1)
- game based learning (1)
- generalization (1)
- geometry generation (1)
- geospatial data (1)
- geospatial services (1)
- geovisualization (1)
- grammar inference (1)
- graph clustering (1)
- graph-based ranking (1)
- hardware design (1)
- hardware-software-codesign (1)
- higher education (1)
- hybrid (1)
- hybrid semantic search (1)
- hybride semantische Suche (1)
- hybrides Problemlösen (1)
- image (1)
- image data analysis (1)
- incompleteness (1)
- inconsistency (1)
- independent component analysis (1)
- indirect economic impacts (1)
- indirekte ökonomische Effekte (1)
- informatics (1)
- information extraction (1)
- information retrieval (1)
- informatische Bildung im Sekundarbereich (1)
- input accuracy (1)
- interaction modeling (1)
- interaction techniques (1)
- intuition (1)
- kernel PCA (1)
- kernel methods (1)
- konvergente Dienste (1)
- landmarks (1)
- language design (1)
- linear code (1)
- linearer Code (1)
- logic (1)
- logic programming (1)
- logic synthesis (1)
- logical signaling networks (1)
- logische Ergänzung (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)
- medical (1)
- medizinisch (1)
- meta model (1)
- middleware (1)
- misconception (1)
- mixture models (1)
- mobile devices (1)
- model-based (1)
- model-driven architecture (1)
- modeling (1)
- molecular networks (1)
- molekulare Netzwerke (1)
- multi core data processing (1)
- multi-class classification (1)
- networks-on-chip (1)
- neue Online-Fehlererkennungsmethode (1)
- nichtlineare ICA (1)
- nichtlineare PCA (NLPCA) (1)
- nichtlineare Projektionen (1)
- nonlinear ICA (1)
- nonlinear PCA (NLPCA) (1)
- nonlinear projections (1)
- objective difficulty (1)
- on-chip (1)
- one-sided communication (1)
- oneM2M (1)
- online assistance (1)
- ontologies (1)
- open source (1)
- optimization (1)
- outlier detection (1)
- output space compaction (1)
- overcomplete ICA (1)
- parallel programming (1)
- parallel solving (1)
- parallele Programmierung (1)
- paralleles Lösen (1)
- pattern recognition (1)
- perception (1)
- perception differences (1)
- philosophy of mathematics (1)
- physical Computing (1)
- physical computing (1)
- placement (1)
- prediction (1)
- preferences (1)
- priorities (1)
- probabilistic deep learning (1)
- probabilistic deep metric learning (1)
- probabilistische tiefe neuronale Netze (1)
- probabilistisches tiefes metrisches Lernen (1)
- process (1)
- process improvement (1)
- process model (1)
- process modelling (1)
- process synchronization (1)
- professors (1)
- proof (1)
- proof assistant (1)
- proof environment (1)
- propagation probability (1)
- radiation hardness (1)
- radiation hardness design (1)
- reconfiguration (1)
- rekonfigurierbar (1)
- reliability assessment (1)
- repair (1)
- robust ICA (1)
- robuste ICA (1)
- scheduling (1)
- scientific workflows (1)
- secondary computer science education (1)
- segmentation (1)
- selbstanpassendes Multiprozessorsystem (1)
- selbstprüfende Schaltungen (1)
- self-adaptive multiprocessing system (1)
- semantic domain modeling (1)
- semantic ranking (1)
- semantic search (1)
- semantic search evaluation (1)
- semantic search methods (1)
- semantische Domänenmodellierung (1)
- semantische Suche (1)
- semantisches Netz (1)
- semantisches Ranking (1)
- service composition (1)
- sign language (1)
- single event upset (1)
- skeletonization (1)
- software (1)
- software development (1)
- software engineering (1)
- software-based cache coherence (1)
- solar particle event (1)
- speed independence (1)
- strahleninduzierte Einzelereignis-Effekte (1)
- structured output prediction (1)
- strukturierte Vorhersage (1)
- study problems (1)
- stylization (1)
- synthesis (1)
- tactic (1)
- teachers (1)
- temporary binding (1)
- terrain models (1)
- tools for teaching (1)
- topics (1)
- touch input (1)
- transformation (1)
- tutorial section (1)
- unidirektionale Fehler (1)
- user interfaces (1)
- verification (1)
- virtual machine (1)
- weather extremes (1)
- zero-aliasing (1)
- überbestimmte ICA (1)
Monitoring virtual team collaboration : methods, applications and experiences in engineering design
(2010)
Correctness proofs and probabilistic tests for constructive specifications and functional programs
(2001)
Real-Time-Non-Photorealistic rendering techniques for illustrating 3D scenes and their dynamics
(2005)
Experimentelles Software Engineering durch Modellierung wissensintensiver Entwicklungsprozesse
(2006)
Die Projektierung und Abwicklung sowie die statische und dynamische Analyse von Geschäftsprozessen im Bereich des Verwaltens und Regierens auf kommunaler, Länder- wie auch Bundesebene mit Hilfe von Informations- und Kommunikationstechniken beschäftigen Politiker und Strategen für Informationstechnologie ebenso wie die Öffentlichkeit seit Langem. Der hieraus entstandene Begriff E-Government wurde in der Folge aus den unterschiedlichsten technischen, politischen und semantischen Blickrichtungen beleuchtet.
Die vorliegende Arbeit konzentriert sich dabei auf zwei Schwerpunktthemen:
> Das erste Schwerpunktthema behandelt den Entwurf eines hierarchischen Architekturmodells, für welches sieben hierarchische Schichten identifiziert werden können. Diese erscheinen notwendig, aber auch hinreichend, um den allgemeinen Fall zu beschreiben. Den Hintergrund hierfür liefert die langjährige Prozess- und Verwaltungserfahrung als Leiter der EDV-Abteilung der Stadtverwaltung Landshut, eine kreisfreie Stadt mit rund 69.000 Einwohnern im Nordosten von München. Sie steht als Repräsentant für viele Verwaltungsvorgänge in der Bundesrepublik Deutschland und ist dennoch als Analyseobjekt in der Gesamtkomplexität und Prozessquantität überschaubar. Somit können aus der Analyse sämtlicher Kernabläufe statische und dynamische Strukturen extrahiert und abstrakt modelliert werden. Die Schwerpunkte liegen in der Darstellung der vorhandenen Bedienabläufe in einer Kommune. Die Transformation der Bedienanforderung in einem hierarchischen System, die Darstellung der Kontroll- und der Operationszustände in allen Schichten wie auch die Strategie der Fehlererkennung und Fehlerbehebung schaffen eine transparente Basis für umfassende Restrukturierungen und Optimierungen. Für die Modellierung wurde FMC-eCS eingesetzt, eine am Hasso-Plattner-Institut für Softwaresystemtechnik GmbH (HPI) im Fachgebiet Kommunikationssysteme entwickelte Methodik zur Modellierung zustandsdiskreter Systeme unter Berücksichtigung möglicher Inkonsistenzen
>Das zweite Schwerpunktthema widmet sich der quantitativen Modellierung und Optimierung von E-Government-Bediensystemen, welche am Beispiel des Bürgerbüros der Stadt Landshut im Zeitraum 2008 bis 2015 durchgeführt wurden. Dies erfolgt auf Basis einer kontinuierlichen Betriebsdatenerfassung mit aufwendiger Vorverarbeitung zur Extrahierung mathematisch beschreibbarer Wahrscheinlichkeitsverteilungen. Der hieraus entwickelte Dienstplan wurde hinsichtlich der erzielbaren Optimierungen im dauerhaften Echteinsatz verifiziert.
The introduction of columnar in-memory databases, along with hardware evolution, has made the execution of transactional and analytical enterprise application workloads on a single system both feasible and viable. Yet, we argue that executing analytical aggregate queries directly on the transactional data can decrease the overall system performance. Despite the aggregation capabilities of columnar in-memory databases, the direct access to records of a materialized aggregate is always more efficient than aggregating on the fly. The traditional approach to materialized aggregates, however, introduces significant overhead in terms of materialized view selection, maintenance, and exploitation. When this overhead is handled by the application, it increases the application complexity, and can slow down the transactional throughput of inserts, updates, and deletes.
In this thesis, we motivate, propose, and evaluate the aggregate cache, a materialized aggregate engine in the main-delta architecture of a columnar in-memory database that provides efficient means to handle costly aggregate queries of enterprise applications. For our design, we leverage the specifics of the main-delta architecture that separates a table into a main and delta partition. The central concept is to only cache the partial aggregate query result as defined on the main partition of a table, because the main partition is relatively stable as records are only inserted into the delta partition. We contribute by proposing incremental aggregate maintenance and query compensation techniques for mixed workloads of enterprise applications. In addition, we introduce aggregate profit metrics that increase the likelihood of persisting the most profitable aggregates in the aggregate cache.
Query compensation and maintenance of materialized aggregates based on joins of multiple tables is expensive due to the partitioned tables in the main-delta architecture. Our analysis of enterprise applications has revealed several data schema and workload patterns. This includes the observation that transactional data is persisted in header and item tables, whereas in many cases, the insertion of related header and item records is executed in a single database transaction. We contribute by proposing an approach to transport these application object semantics to the database system and optimize the query processing using the aggregate cache by applying partition pruning and predicate pushdown techniques.
For the experimental evaluation, we propose the FICO benchmark that is based on data from a productive ERP system with extracted mixed workloads. Our evaluation reveals that the aggregate cache can accelerate the execution of aggregate queries up to a factor of 60 whereas the speedup highly depends on the number of aggregated records in the main and delta partitions. In mixed workloads, the proposed aggregate maintenance and query compensation techniques perform up to an order of magnitude better than traditional materialized aggregate maintenance approaches. The introduced aggregate profit metrics outperform existing costbased metrics by up to 20%. Lastly, the join pruning and predicate pushdown techniques can accelerate query execution in the aggregate cache in the presence of multiple partitioned tables by up to an order of magnitude.
Services that operate over the Internet are under constant threat of being exposed to fraudulent use. Maintaining good user experience for legitimate users often requires the classification of entities as malicious or legitimate in order to initiate countermeasures. As an example, inbound email spam filters decide for spam or non-spam. They can base their decision on both the content of each email as well as on features that summarize prior emails received from the sending server. In general, discriminative classification methods learn to distinguish positive from negative entities. Each decision for a label may be based on features of the entity and related entities. When labels of related entities have strong interdependencies---as can be assumed e.g. for emails being delivered by the same user---classification decisions should not be made independently and dependencies should be modeled in the decision function. This thesis addresses the formulation of discriminative classification problems that are tailored for the specific demands of the following three Internet security applications. Theoretical and algorithmic solutions are devised to protect an email service against flooding of user inboxes, to mitigate abusive usage of outbound email servers, and to protect web servers against distributed denial of service attacks.
In the application of filtering an inbound email stream for unsolicited emails, utilizing features that go beyond each individual email's content can be valuable. Information about each sending mail server can be aggregated over time and may help in identifying unwanted emails. However, while this information will be available to the deployed email filter, some parts of the training data that are compiled by third party providers may not contain this information. The missing features have to be estimated at training time in order to learn a classification model. In this thesis an algorithm is derived that learns a decision function that integrates over a distribution of values for each missing entry. The distribution of missing values is a free parameter that is optimized to learn an optimal decision function.
The outbound stream of emails of an email service provider can be separated by the customer IDs that ask for delivery. All emails that are sent by the same ID in the same period of time are related, both in content and in label. Hijacked customer accounts may send batches of unsolicited emails to other email providers, which in turn might blacklist the sender's email servers after detection of incoming spam emails. The risk of being blocked from further delivery depends on the rate of outgoing unwanted emails and the duration of high spam sending rates. An optimization problem is developed that minimizes the expected cost for the email provider by learning a decision function that assigns a limit on the sending rate to customers based on the each customer's email stream.
Identifying attacking IPs during HTTP-level DDoS attacks allows to block those IPs from further accessing the web servers. DDoS attacks are usually carried out by infected clients that are members of the same botnet and show similar traffic patterns. HTTP-level attacks aim at exhausting one or more resources of the web server infrastructure, such as CPU time. If the joint set of attackers cannot increase resource usage close to the maximum capacity, no effect will be experienced by legitimate users of hosted web sites. However, if the additional load raises the computational burden towards the critical range, user experience will degrade until service may be unavailable altogether. As the loss of missing one attacker depends on block decisions for other attackers---if most other attackers are detected, not blocking one client will likely not be harmful---a structured output model has to be learned. In this thesis an algorithm is developed that learns a structured prediction decoder that searches the space of label assignments, guided by a policy.
Each model is evaluated on real-world data and is compared to reference methods. The results show that modeling each classification problem according to the specific demands of the task improves performance over solutions that do not consider the constraints inherent to an application.
Personal fabrication tools, such as 3D printers, are on the way of enabling a future in which non-technical users will be able to create custom objects. However, while the hardware is there, the current interaction model behind existing design tools is not suitable for non-technical users. Today, 3D printers are operated by fabricating the object in one go, which tends to take overnight due to the slow 3D printing technology. Consequently, the current interaction model requires users to think carefully before printing as every mistake may imply another overnight print. Planning every step ahead, however, is not feasible for non-technical users as they lack the experience to reason about the consequences of their design decisions.
In this dissertation, we propose changing the interaction model around personal fabrication tools to better serve this user group. We draw inspiration from personal computing and argue that the evolution of personal fabrication may resemble the evolution of personal computing: Computing started with machines that executed a program in one go before returning the result to the user. By decreasing the interaction unit to single requests, turn-taking systems such as the command line evolved, which provided users with feedback after every input. Finally, with the introduction of direct-manipulation interfaces, users continuously interacted with a program receiving feedback about every action in real-time. In this dissertation, we explore whether these interaction concepts can be applied to personal fabrication as well.
We start with fabricating an object in one go and investigate how to tighten the feedback-cycle on an object-level: We contribute a method called low-fidelity fabrication, which saves up to 90% fabrication time by creating objects as fast low-fidelity previews, which are sufficient to evaluate key design aspects. Depending on what is currently being tested, we propose different conversions that enable users to focus on different parts: faBrickator allows for a modular design in the early stages of prototyping; when users move on WirePrint allows quickly testing an object's shape, while Platener allows testing an object's technical function. We present an interactive editor for each technique and explain the underlying conversion algorithms.
By interacting on smaller units, such as a single element of an object, we explore what it means to transition from systems that fabricate objects in one go to turn-taking systems. We start with a 2D system called constructable: Users draw with a laser pointer onto the workpiece inside a laser cutter. The drawing is captured with an overhead camera. As soon as the the user finishes drawing an element, such as a line, the constructable system beautifies the path and cuts it--resulting in physical output after every editing step. We extend constructable towards 3D editing by developing a novel laser-cutting technique for 3D objects called LaserOrigami that works by heating up the workpiece with the defocused laser until the material becomes compliant and bends down under gravity. While constructable and LaserOrigami allow for fast physical feedback, the interaction is still best described as turn-taking since it consists of two discrete steps: users first create an input and afterwards the system provides physical output.
By decreasing the interaction unit even further to a single feature, we can achieve real-time physical feedback: Input by the user and output by the fabrication device are so tightly coupled that no visible lag exists. This allows us to explore what it means to transition from turn-taking interfaces, which only allow exploring one option at a time, to direct manipulation interfaces with real-time physical feedback, which allow users to explore the entire space of options continuously with a single interaction. We present a system called FormFab, which allows for such direct control. FormFab is based on the same principle as LaserOrigami: It uses a workpiece that when warmed up becomes compliant and can be reshaped. However, FormFab achieves the reshaping not based on gravity, but through a pneumatic system that users can control interactively. As users interact, they see the shape change in real-time.
We conclude this dissertation by extrapolating the current evolution into a future in which large numbers of people use the new technology to create objects. We see two additional challenges on the horizon: sustainability and intellectual property. We investigate sustainability by demonstrating how to print less and instead patch physical objects. We explore questions around intellectual property with a system called Scotty that transfers objects without creating duplicates, thereby preserving the designer's copyright.
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.
Geospatial data has become a natural part of a growing number of information systems and services in the economy, society, and people's personal lives. In particular, virtual 3D city and landscape models constitute valuable information sources within a wide variety of applications such as urban planning, navigation, tourist information, and disaster management. Today, these models are often visualized in detail to provide realistic imagery. However, a photorealistic rendering does not automatically lead to high image quality, with respect to an effective information transfer, which requires important or prioritized information to be interactively highlighted in a context-dependent manner.
Approaches in non-photorealistic renderings particularly consider a user's task and camera perspective when attempting optimal expression, recognition, and communication of important or prioritized information. However, the design and implementation of non-photorealistic rendering techniques for 3D geospatial data pose a number of challenges, especially when inherently complex geometry, appearance, and thematic data must be processed interactively. Hence, a promising technical foundation is established by the programmable and parallel computing architecture of graphics processing units.
This thesis proposes non-photorealistic rendering techniques that enable both the computation and selection of the abstraction level of 3D geospatial model contents according to user interaction and dynamically changing thematic information. To achieve this goal, the techniques integrate with hardware-accelerated rendering pipelines using shader technologies of graphics processing units for real-time image synthesis. The techniques employ principles of artistic rendering, cartographic generalization, and 3D semiotics—unlike photorealistic rendering—to synthesize illustrative renditions of geospatial feature type entities such as water surfaces, buildings, and infrastructure networks. In addition, this thesis contributes a generic system that enables to integrate different graphic styles—photorealistic and non-photorealistic—and provide their seamless transition according to user tasks, camera view, and image resolution.
Evaluations of the proposed techniques have demonstrated their significance to the field of geospatial information visualization including topics such as spatial perception, cognition, and mapping. In addition, the applications in illustrative and focus+context visualization have reflected their potential impact on optimizing the information transfer regarding factors such as cognitive load, integration of non-realistic information, visualization of uncertainty, and visualization on small displays.
The main objective of this dissertation is to analyse prerequisites, expectations, apprehensions, and attitudes of students studying computer science, who are willing to gain a bachelor degree. The research will also investigate in the students’ learning style according to the Felder-Silverman model. These investigations fall in the attempt to make an impact on reducing the “dropout”/shrinkage rate among students, and to suggest a better learning environment.
The first investigation starts with a survey that has been made at the computer science department at the University of Baghdad to investigate the attitudes of computer science students in an environment dominated by women, showing the differences in attitudes between male and female students in different study years. Students are accepted to university studies via a centrally controlled admission procedure depending mainly on their final score at school. This leads to a high percentage of students studying subjects they do not want. Our analysis shows that 75% of the female students do not regret studying computer science although it was not their first choice. And according to statistics over previous years, women manage to succeed in their study and often graduate on top of their class. We finish with a comparison of attitudes between the freshman students of two different cultures and two different university enrolment procedures (University of Baghdad, in Iraq, and the University of Potsdam, in Germany) both with opposite gender majority.
The second step of investigation took place at the department of computer science at the University of Potsdam in Germany and analyzes the learning styles of students studying the three major fields of study offered by the department (computer science, business informatics, and computer science teaching). Investigating the differences in learning styles between the students of those study fields who usually take some joint courses is important to be aware of which changes are necessary to be adopted in the teaching methods to address those different students. It was a two stage study using two questionnaires; the main one is based on the Index of Learning Styles Questionnaire of B. A. Solomon and R. M. Felder, and the second questionnaire was an investigation on the students’ attitudes towards the findings of their personal first questionnaire. Our analysis shows differences in the preferences of learning style between male and female students of the different study fields, as well as differences between students with the different specialties (computer science, business informatics, and computer science teaching).
The third investigation looks closely into the difficulties, issues, apprehensions and expectations of freshman students studying computer science. The study took place at the computer science department at the University of Potsdam with a volunteer sample of students. The goal is to determine and discuss the difficulties and issues that they are facing in their study that may lead them to think in dropping-out, changing the study field, or changing the university. The research continued with the same sample of students (with business informatics students being the majority) through more than three semesters. Difficulties and issues during the study were documented, as well as students’ attitudes, apprehensions, and expectations. Some of the professors and lecturers opinions and solutions to some students’ problems were also documented. Many participants had apprehensions and difficulties, especially towards informatics subjects. Some business informatics participants began to think of changing the university, in particular when they reached their third semester, others thought about changing their field of study. Till the end of this research, most of the participants continued in their studies (the study they have started with or the new study they have changed to) without leaving the higher education system.
E-Learning-Anwendungen bieten Chancen für die gesetzlich vorgeschriebene Inklusion von Lernenden mit Beeinträchtigungen. Die gleichberechtigte Teilhabe von blinden Lernenden an Veranstaltungen in virtuellen Klassenzimmern ist jedoch durch den synchronen, multimedialen Charakter und den hohen Informationsumfang dieser Lösungen kaum möglich.
Die vorliegende Arbeit untersucht die Zugänglichkeit virtueller Klassenzimmer für blinde Nutzende, um eine möglichst gleichberechtigte Teilhabe an synchronen, kollaborativen Lernszenarien zu ermöglichen. Im Rahmen einer Produktanalyse werden dazu virtuelle Klassenzimmer auf ihre Zugänglichkeit und bestehende Barrieren untersucht und Richtlinien für die zugängliche Gestaltung von virtuellen Klassenzimmern definiert. Anschließend wird ein alternatives Benutzungskonzept zur Darstellung und Bedienung virtueller Klassenzimmer auf einem zweidimensionalen taktilen Braille-Display entwickelt, um eine möglichst gleichberechtigte Teilhabe blinder Lernender an synchronen Lehrveranstaltungen zu ermöglichen. Nach einer ersten Evaluation mit blinden Probanden erfolgt die prototypische Umsetzung des Benutzungskonzepts für ein Open-Source-Klassenzimmer. Die abschließende Evaluation der prototypischen Umsetzung zeigt die Verbesserung der Zugänglichkeit von virtuellen Klassenzimmern für blinde Lernende unter Verwendung eines taktilen Flächendisplays und bestätigt die Wirksamkeit der im Rahmen dieser Arbeit entwickelten Konzepte.
Software-as-a-Service (SaaS) offers several advantages to both service providers and users. Service providers can benefit from the reduction of Total Cost of Ownership (TCO), better scalability, and better resource utilization. On the other hand, users can use the service anywhere and anytime, and minimize upfront investment by following the pay-as-you-go model. Despite the benefits of SaaS, users still have concerns about the security and privacy of their data. Due to the nature of SaaS and the Cloud in general, the data and the computation are beyond the users' control, and hence data security becomes a vital factor in this new paradigm. Furthermore, in multi-tenant SaaS applications, the tenants become more concerned about the confidentiality of their data since several tenants are co-located onto a shared infrastructure.
To address those concerns, we start protecting the data from the provisioning process by controlling how tenants are being placed in the infrastructure. We present a resource allocation algorithm designed to minimize the risk of co-resident tenants called SecPlace. It enables the SaaS provider to control the resource (i.e., database instance) allocation process while taking into account the security of tenants as a requirement.
Due to the design principles of the multi-tenancy model, tenants follow some degree of sharing on both application and infrastructure levels. Thus, strong security-isolation should be present. Therefore, we develop SignedQuery, a technique that prevents one tenant from accessing others' data. We use the Signing Concept to create a signature that is used to sign the tenant's request, then the server can verifies the signature and recognizes the requesting tenant, and hence ensures that the data to be accessed is belonging to the legitimate tenant.
Finally, Data confidentiality remains a critical concern due to the fact that data in the Cloud is out of users' premises, and hence beyond their control. Cryptography is increasingly proposed as a potential approach to address such a challenge. Therefore, we present SecureDB, a system designed to run SQL-based applications over an encrypted database. SecureDB captures the schema design and analyzes it to understand the internal structure of the data (i.e., relationships between the tables and their attributes). Moreover, we determine the appropriate partialhomomorphic encryption scheme for each attribute where computation is possible even when the data is encrypted.
To evaluate our work, we conduct extensive experiments with di↵erent settings. The main use case in our work is a popular open source HRM application, called OrangeHRM. The results show that our multi-layered approach is practical, provides enhanced security and isolation among tenants, and have a moderate complexity in terms of processing encrypted data.
Cloud-RAID
(2014)
Boolean constraint solving technology has made tremendous progress over the last decade, leading to industrial-strength solvers, for example, in the areas of answer set programming (ASP), the constraint satisfaction problem (CSP), propositional satisfiability (SAT) and satisfiability of quantified Boolean formulas (QBF). However, in all these areas, there exist multiple solving strategies that work well on different applications; no strategy dominates all other strategies. Therefore, no individual solver shows robust state-of-the-art performance in all kinds of applications. Additionally, the question arises how to choose a well-performing solving strategy for a given application; this is a challenging question even for solver and domain experts. One way to address this issue is the use of portfolio solvers, that is, a set of different solvers or solver configurations. We present three new automatic portfolio methods: (i) automatic construction of parallel portfolio solvers (ACPP) via algorithm configuration,(ii) solving the $NP$-hard problem of finding effective algorithm schedules with Answer Set Programming (aspeed), and (iii) a flexible algorithm selection framework (claspfolio2) allowing for fair comparison of different selection approaches. All three methods show improved performance and robustness in comparison to individual solvers on heterogeneous instance sets from many different applications. Since parallel solvers are important to effectively solve hard problems on parallel computation systems (e.g., multi-core processors), we extend all three approaches to be effectively applicable in parallel settings. We conducted extensive experimental studies different instance sets from ASP, CSP, MAXSAT, Operation Research (OR), SAT and QBF that indicate an improvement in the state-of-the-art solving heterogeneous instance sets. Last but not least, from our experimental studies, we deduce practical advice regarding the question when to apply which of our methods.
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.
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.
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.
This thesis presents novel ideas and research findings for the Web of Data – a global data space spanning many so-called Linked Open Data sources. Linked Open Data adheres to a set of simple principles to allow easy access and reuse for data published on the Web. Linked Open Data is by now an established concept and many (mostly academic) publishers adopted the principles building a powerful web of structured knowledge available to everybody. However, so far, Linked Open Data does not yet play a significant role among common web technologies that currently facilitate a high-standard Web experience. In this work, we thoroughly discuss the state-of-the-art for Linked Open Data and highlight several shortcomings – some of them we tackle in the main part of this work. First, we propose a novel type of data source meta-information, namely the topics of a dataset. This information could be published with dataset descriptions and support a variety of use cases, such as data source exploration and selection. For the topic retrieval, we present an approach coined Annotated Pattern Percolation (APP), which we evaluate with respect to topics extracted from Wikipedia portals. Second, we contribute to entity linking research by presenting an optimization model for joint entity linking, showing its hardness, and proposing three heuristics implemented in the LINked Data Alignment (LINDA) system. Our first solution can exploit multi-core machines, whereas the second and third approach are designed to run in a distributed shared-nothing environment. We discuss and evaluate the properties of our approaches leading to recommendations which algorithm to use in a specific scenario. The distributed algorithms are among the first of their kind, i.e., approaches for joint entity linking in a distributed fashion. Also, we illustrate that we can tackle the entity linking problem on the very large scale with data comprising more than 100 millions of entity representations from very many sources. Finally, we approach a sub-problem of entity linking, namely the alignment of concepts. We again target a method that looks at the data in its entirety and does not neglect existing relations. Also, this concept alignment method shall execute very fast to serve as a preprocessing for further computations. Our approach, called Holistic Concept Matching (HCM), achieves the required speed through grouping the input by comparing so-called knowledge representations. Within the groups, we perform complex similarity computations, relation conclusions, and detect semantic contradictions. The quality of our result is again evaluated on a large and heterogeneous dataset from the real Web. In summary, this work contributes a set of techniques for enhancing the current state of the Web of Data. All approaches have been tested on large and heterogeneous real-world input.
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.
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.
3D from 2D touch
(2013)
While interaction with computers used to be dominated by mice and keyboards, new types of sensors now allow users to interact through touch, speech, or using their whole body in 3D space. These new interaction modalities are often referred to as "natural user interfaces" or "NUIs." While 2D NUIs have experienced major success on billions of mobile touch devices sold, 3D NUI systems have so far been unable to deliver a mobile form factor, mainly due to their use of cameras. The fact that cameras require a certain distance from the capture volume has prevented 3D NUI systems from reaching the flat form factor mobile users expect. In this dissertation, we address this issue by sensing 3D input using flat 2D sensors. The systems we present observe the input from 3D objects as 2D imprints upon physical contact. By sampling these imprints at very high resolutions, we obtain the objects' textures. In some cases, a texture uniquely identifies a biometric feature, such as the user's fingerprint. In other cases, an imprint stems from the user's clothing, such as when walking on multitouch floors. By analyzing from which part of the 3D object the 2D imprint results, we reconstruct the object's pose in 3D space. While our main contribution is a general approach to sensing 3D input on 2D sensors upon physical contact, we also demonstrate three applications of our approach. (1) We present high-accuracy touch devices that allow users to reliably touch targets that are a third of the size of those on current touch devices. We show that different users and 3D finger poses systematically affect touch sensing, which current devices perceive as random input noise. We introduce a model for touch that compensates for this systematic effect by deriving the 3D finger pose and the user's identity from each touch imprint. We then investigate this systematic effect in detail and explore how users conceptually touch targets. Our findings indicate that users aim by aligning visual features of their fingers with the target. We present a visual model for touch input that eliminates virtually all systematic effects on touch accuracy. (2) From each touch, we identify users biometrically by analyzing their fingerprints. Our prototype Fiberio integrates fingerprint scanning and a display into the same flat surface, solving a long-standing problem in human-computer interaction: secure authentication on touchscreens. Sensing 3D input and authenticating users upon touch allows Fiberio to implement a variety of applications that traditionally require the bulky setups of current 3D NUI systems. (3) To demonstrate the versatility of 3D reconstruction on larger touch surfaces, we present a high-resolution pressure-sensitive floor that resolves the texture of objects upon touch. Using the same principles as before, our system GravitySpace analyzes all imprints and identifies users based on their shoe soles, detects furniture, and enables accurate touch input using feet. By classifying all imprints, GravitySpace detects the users' body parts that are in contact with the floor and then reconstructs their 3D body poses using inverse kinematics. GravitySpace thus enables a range of applications for future 3D NUI systems based on a flat sensor, such as smart rooms in future homes. We conclude this dissertation by projecting into the future of mobile devices. Focusing on the mobility aspect of our work, we explore how NUI devices may one day augment users directly in the form of implanted devices.
Interactive rendering techniques for focus+context visualization of 3D geovirtual environments
(2013)
This thesis introduces a collection of new real-time rendering techniques and applications for focus+context visualization of interactive 3D geovirtual environments such as virtual 3D city and landscape models. These environments are generally characterized by a large number of objects and are of high complexity with respect to geometry and textures. For these reasons, their interactive 3D rendering represents a major challenge. Their 3D depiction implies a number of weaknesses such as occlusions, cluttered image contents, and partial screen-space usage. To overcome these limitations and, thus, to facilitate the effective communication of geo-information, principles of focus+context visualization can be used for the design of real-time 3D rendering techniques for 3D geovirtual environments (see Figure). In general, detailed views of a 3D geovirtual environment are combined seamlessly with abstracted views of the context within a single image. To perform the real-time image synthesis required for interactive visualization, dedicated parallel processors (GPUs) for rasterization of computer graphics primitives are used. For this purpose, the design and implementation of appropriate data structures and rendering pipelines are necessary. The contribution of this work comprises the following five real-time rendering methods: • The rendering technique for 3D generalization lenses enables the combination of different 3D city geometries (e.g., generalized versions of a 3D city model) in a single image in real time. The method is based on a generalized and fragment-precise clipping approach, which uses a compressible, raster-based data structure. It enables the combination of detailed views in the focus area with the representation of abstracted variants in the context area. • The rendering technique for the interactive visualization of dynamic raster data in 3D geovirtual environments facilitates the rendering of 2D surface lenses. It enables a flexible combination of different raster layers (e.g., aerial images or videos) using projective texturing for decoupling image and geometry data. Thus, various overlapping and nested 2D surface lenses of different contents can be visualized interactively. • The interactive rendering technique for image-based deformation of 3D geovirtual environments enables the real-time image synthesis of non-planar projections, such as cylindrical and spherical projections, as well as multi-focal 3D fisheye-lenses and the combination of planar and non-planar projections. • The rendering technique for view-dependent multi-perspective views of 3D geovirtual environments, based on the application of global deformations to the 3D scene geometry, can be used for synthesizing interactive panorama maps to combine detailed views close to the camera (focus) with abstract views in the background (context). This approach reduces occlusions, increases the usage the available screen space, and reduces the overload of image contents. • The object-based and image-based rendering techniques for highlighting objects and focus areas inside and outside the view frustum facilitate preattentive perception. The concepts and implementations of interactive image synthesis for focus+context visualization and their selected applications enable a more effective communication of spatial information, and provide building blocks for design and development of new applications and systems in the field of 3D geovirtual environments.
The field of machine learning studies algorithms that infer predictive models from data. Predictive models are applicable for many practical tasks such as spam filtering, face and handwritten digit recognition, and personalized product recommendation. In general, they are used to predict a target label for a given data instance. In order to make an informed decision about the deployment of a predictive model, it is crucial to know the model’s approximate performance. To evaluate performance, a set of labeled test instances is required that is drawn from the distribution the model will be exposed to at application time. In many practical scenarios, unlabeled test instances are readily available, but the process of labeling them can be a time- and cost-intensive task and may involve a human expert. This thesis addresses the problem of evaluating a given predictive model accurately with minimal labeling effort. We study an active model evaluation process that selects certain instances of the data according to an instrumental sampling distribution and queries their labels. We derive sampling distributions that minimize estimation error with respect to different performance measures such as error rate, mean squared error, and F-measures. An analysis of the distribution that governs the estimator leads to confidence intervals, which indicate how precise the error estimation is. Labeling costs may vary across different instances depending on certain characteristics of the data. For instance, documents differ in their length, comprehensibility, and technical requirements; these attributes affect the time a human labeler needs to judge relevance or to assign topics. To address this, the sampling distribution is extended to incorporate instance-specific costs. We empirically study conditions under which the active evaluation processes are more accurate than a standard estimate that draws equally many instances from the test distribution. We also address the problem of comparing the risks of two predictive models. The standard approach would be to draw instances according to the test distribution, label the selected instances, and apply statistical tests to identify significant differences. Drawing instances according to an instrumental distribution affects the power of a statistical test. We derive a sampling procedure that maximizes test power when used to select instances, and thereby minimizes the likelihood of choosing the inferior model. Furthermore, we investigate the task of comparing several alternative models; the objective of an evaluation could be to rank the models according to the risk that they incur or to identify the model with lowest risk. An experimental study shows that the active procedure leads to higher test power than the standard test in many application domains. Finally, we study the problem of evaluating the performance of ranking functions, which are used for example for web search. In practice, ranking performance is estimated by applying a given ranking model to a representative set of test queries and manually assessing the relevance of all retrieved items for each query. We apply the concepts of active evaluation and active comparison to ranking functions and derive optimal sampling distributions for the commonly used performance measures Discounted Cumulative Gain and Expected Reciprocal Rank. Experiments on web search engine data illustrate significant reductions in labeling costs.
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.
Virtual 3D city and landscape models are the main subject investigated in this thesis. They digitally represent urban space and have many applications in different domains, e.g., simulation, cadastral management, and city planning. Visualization is an elementary component of these applications. Photo-realistic visualization with an increasingly high degree of detail leads to fundamental problems for comprehensible visualization. A large number of highly detailed and textured objects within a virtual 3D city model may create visual noise and overload the users with information. Objects are subject to perspective foreshortening and may be occluded or not displayed in a meaningful way, as they are too small. In this thesis we present abstraction techniques that automatically process virtual 3D city and landscape models to derive abstracted representations. These have a reduced degree of detail, while essential characteristics are preserved. After introducing definitions for model, scale, and multi-scale representations, we discuss the fundamentals of map generalization as well as techniques for 3D generalization. The first presented technique is a cell-based generalization of virtual 3D city models. It creates abstract representations that have a highly reduced level of detail while maintaining essential structures, e.g., the infrastructure network, landmark buildings, and free spaces. The technique automatically partitions the input virtual 3D city model into cells based on the infrastructure network. The single building models contained in each cell are aggregated to abstracted cell blocks. Using weighted infrastructure elements, cell blocks can be computed on different hierarchical levels, storing the hierarchy relation between the cell blocks. Furthermore, we identify initial landmark buildings within a cell by comparing the properties of individual buildings with the aggregated properties of the cell. For each block, the identified landmark building models are subtracted using Boolean operations and integrated in a photo-realistic way. Finally, for the interactive 3D visualization we discuss the creation of the virtual 3D geometry and their appearance styling through colors, labeling, and transparency. We demonstrate the technique with example data sets. Additionally, we discuss applications of generalization lenses and transitions between abstract representations. The second technique is a real-time-rendering technique for geometric enhancement of landmark objects within a virtual 3D city model. Depending on the virtual camera distance, landmark objects are scaled to ensure their visibility within a specific distance interval while deforming their environment. First, in a preprocessing step a landmark hierarchy is computed, this is then used to derive distance intervals for the interactive rendering. At runtime, using the virtual camera distance, a scaling factor is computed and applied to each landmark. The scaling factor is interpolated smoothly at the interval boundaries using cubic Bézier splines. Non-landmark geometry that is near landmark objects is deformed with respect to a limited number of landmarks. We demonstrate the technique by applying it to a highly detailed virtual 3D city model and a generalized 3D city model. In addition we discuss an adaptation of the technique for non-linear projections and mobile devices. The third technique is a real-time rendering technique to create abstract 3D isocontour visualization of virtual 3D terrain models. The virtual 3D terrain model is visualized as a layered or stepped relief. The technique works without preprocessing and, as it is implemented using programmable graphics hardware, can be integrated with minimal changes into common terrain rendering techniques. Consequently, the computation is done in the rendering pipeline for each vertex, primitive, i.e., triangle, and fragment. For each vertex, the height is quantized to the nearest isovalue. For each triangle, the vertex configuration with respect to their isovalues is determined first. Using the configuration, the triangle is then subdivided. The subdivision forms a partial step geometry aligned with the triangle. For each fragment, the surface appearance is determined, e.g., depending on the surface texture, shading, and height-color-mapping. Flexible usage of the technique is demonstrated with applications from focus+context visualization, out-of-core terrain rendering, and information visualization. This thesis presents components for the creation of abstract representations of virtual 3D city and landscape models. Re-using visual language from cartography, the techniques enable users to build on their experience with maps when interpreting these representations. Simultaneously, characteristics of 3D geovirtual environments are taken into account by addressing and discussing, e.g., continuous scale, interaction, and perspective.
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.
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.
Business process models are used within a range of organizational initiatives, where every stakeholder has a unique perspective on a process and demands the respective model. As a consequence, multiple process models capturing the very same business process coexist. Keeping such models in sync is a challenge within an ever changing business environment: once a process is changed, all its models have to be updated. Due to a large number of models and their complex relations, model maintenance becomes error-prone and expensive. Against this background, business process model abstraction emerged as an operation reducing the number of stored process models and facilitating model management. Business process model abstraction is an operation preserving essential process properties and leaving out insignificant details in order to retain information relevant for a particular purpose. Process model abstraction has been addressed by several researchers. The focus of their studies has been on particular use cases and model transformations supporting these use cases. This thesis systematically approaches the problem of business process model abstraction shaping the outcome into a framework. We investigate the current industry demand in abstraction summarizing it in a catalog of business process model abstraction use cases. The thesis focuses on one prominent use case where the user demands a model with coarse-grained activities and overall process ordering constraints. We develop model transformations that support this use case starting with the transformations based on process model structure analysis. Further, abstraction methods considering the semantics of process model elements are investigated. First, we suggest how semantically related activities can be discovered in process models-a barely researched challenge. The thesis validates the designed abstraction methods against sets of industrial process models and discusses the method implementation aspects. Second, we develop a novel model transformation, which combined with the related activity discovery allows flexible non-hierarchical abstraction. In this way this thesis advocates novel model transformations that facilitate business process model management and provides the foundations for innovative tool support.