Institut für Informatik und Computational Science
Refine
Year of publication
- 2023 (2)
- 2022 (18)
- 2021 (16)
- 2020 (22)
- 2019 (10)
- 2018 (21)
- 2017 (4)
- 2016 (9)
- 2015 (63)
- 2014 (29)
- 2013 (37)
- 2012 (23)
- 2011 (27)
- 2010 (32)
- 2009 (26)
- 2008 (1)
- 2007 (24)
- 2006 (38)
- 2005 (29)
- 2004 (27)
- 2003 (18)
- 2002 (15)
- 2001 (20)
- 2000 (31)
- 1999 (29)
- 1998 (30)
- 1997 (22)
- 1996 (25)
- 1995 (15)
- 1994 (17)
- 1993 (1)
Document Type
- Article (682) (remove)
Keywords
- Didaktik (13)
- Ausbildung (12)
- Hochschuldidaktik (12)
- Informatik (12)
- Answer set programming (10)
- answer set programming (8)
- Answer Set Programming (6)
- Computer Science Education (4)
- E-Learning (4)
- Competence Measurement (3)
- Machine learning (3)
- Secondary Education (3)
- Theory (3)
- education (3)
- formal languages (3)
- monitoring (3)
- Analytical models (2)
- Automata systems (2)
- Big Data (2)
- Competence Modelling (2)
- Computational thinking (2)
- Digitale Medien (2)
- E-learning (2)
- Equilibrium logic (2)
- Event mapping (2)
- Fault tolerance (2)
- IT-Infrastruktur (2)
- Informatics Education (2)
- Informatics Modelling (2)
- Informatics System Application (2)
- Informatics System Comprehension (2)
- Lindenmayer systems (2)
- Non-monotonic reasoning (2)
- Parameterized complexity (2)
- Process mining (2)
- ResNet (2)
- Strategie (2)
- bioinformatics (2)
- computational thinking (2)
- computer science education (2)
- cooperating systems (2)
- e-learning (2)
- higher education (2)
- knowledge representation and nonmonotonic reasoning (2)
- online learning (2)
- radhard design (2)
- relevance (2)
- security (2)
- soft errors (2)
- tools (2)
- (FPGA) (1)
- (SET) count rate (1)
- 2-tag system (1)
- 21st century skills, (1)
- 3D modeling (1)
- 3D visualization (1)
- ABRACADABRA (1)
- AODV (1)
- ARCS Modell (1)
- ASIC (1)
- Absorbed dose (1)
- Abstraction (1)
- Access control (1)
- Achievement (1)
- Active evaluation (1)
- Activity Theory (1)
- Activity-orientated Learning (1)
- Ad hoc routing (1)
- Adaptivity (1)
- Adaptivität (1)
- Advanced Video Codec (AVC) (1)
- Aggregates (1)
- Algorithm configuration (1)
- Algorithm portfolios (1)
- Algorithms (1)
- Android hybrid apps (1)
- Animal building (1)
- Anti-cancer drugs (1)
- Arduino (1)
- Argumentation structure (1)
- Assessment (1)
- Audience Response Systeme (1)
- Augmentation (1)
- Augmented and virtual reality (1)
- Austria (1)
- Autismus (1)
- Automated Theorem Proving (1)
- Automated parallelization (1)
- Automatic Item Generation (1)
- Automatically controlled windows (1)
- Automatisches Beweisen (1)
- Backdoors (1)
- Batch processing (1)
- Bean (1)
- Benchmark testing; (1)
- Berliner Modell (1)
- Blended Learning (1)
- Blind users (1)
- Bloom’s Taxonomy (1)
- Boolean logic models (1)
- Business process intelligence (1)
- CP-Logic (1)
- CS concepts (1)
- Campus (1)
- Capability approach (1)
- Challenges (1)
- Circuit faults (1)
- Clause Learning (1)
- Clock tree (1)
- Cloud (1)
- Cluster Computing (1)
- Cluster computing (1)
- Code generation (1)
- Cognitive Skills (1)
- Coherent phonons (1)
- Combinatorial multi-objective optimization (1)
- Competences (1)
- Competencies (1)
- Complex optimization (1)
- Complexity (1)
- Computational Thinking (1)
- Computational complexity (1)
- Computational grid (1)
- Computer Science (1)
- Computer Science in Context (1)
- Computer security (1)
- Computergestützes Training (1)
- Computing (1)
- Computing with DNA (1)
- Conformant Planning (1)
- Conrad Hal Waddington (1)
- Constraint satisfaction (1)
- Contest (1)
- Context awareness (1)
- Contextualisation (1)
- Contextualized learning (1)
- Continuous Testing (1)
- Continuous Versioning (1)
- Contradictions (1)
- Convolution (1)
- Course timetabling (1)
- Curriculum (1)
- Curriculum Development (1)
- Customer ownership (1)
- D-galactosamine (1)
- DMR (1)
- DNA hairpin formation (1)
- DPLL (1)
- DRMAA (1)
- DRMS (1)
- Data Analysis (1)
- Data Management (1)
- Data Privacy (1)
- Data federation (1)
- Database (1)
- Databases (1)
- Deal of the Day (1)
- Debugging (1)
- Decidability (1)
- Declare (1)
- Deep learning (1)
- Defining characteristics of physical computing (1)
- Denotational semantics (1)
- Design (1)
- Design for testability (DFT) (1)
- Digital Competence (1)
- Digital Education (1)
- Digital Game Based Learning (1)
- Digital Revolution (1)
- Digital image analysis (1)
- Digitalisierung (1)
- Digitalization (1)
- Dose rate (1)
- Double cell upsets (DCUs) (1)
- Dynamic assessment (1)
- Dynamical X-ray theory (1)
- E-Assessment (1)
- E-Klausuren (1)
- E-Portfolio (1)
- E-teaching (1)
- EDC (1)
- EEG (1)
- Early Literacy (1)
- Educational Standards (1)
- Educational game (1)
- Educational software (1)
- Educational timetabling (1)
- Elektronisches Prüfen (1)
- Embedded Systems (1)
- Encoding (1)
- Engines (1)
- Entity Linking (1)
- Epigenetic landscape (1)
- Epistemic Logic Programs (1)
- Euclid’s algorithm (1)
- Evaluation (1)
- Evolution (1)
- Experimentation (1)
- Explicit negation (1)
- Explore-first Programming (1)
- Extensibility (1)
- Extreme Model-Driven Development (1)
- FEDC (1)
- FPGA (1)
- Facebook (1)
- Fault Localization (1)
- Fault tolerant systems (1)
- Feature extraction (1)
- Fibonacci numbers (1)
- Field programmable gate arrays (1)
- Finite automata (1)
- Flip-flops (1)
- Forgetting (1)
- Forschungsdatenmanagement (1)
- Freshmen (1)
- Function (1)
- Fundamental Ideas (1)
- GERBIL (1)
- Gesture input (1)
- Graphensuche (1)
- Green computing (1)
- Grounded theory (1)
- H.264 (1)
- Hairpin completions (1)
- Hairpin reductions (1)
- Hardware accelerator (1)
- Heat diffusion (1)
- Hierarchically configurable mask register (1)
- Histograms (1)
- Hochschul-Cloud (1)
- Hochschullehre (1)
- Https traffic (1)
- Human Factors (1)
- Hurricane Sandy (1)
- ICT Competence (1)
- ICT competencies (1)
- ICT skills (1)
- IaaS (1)
- Identifiers (1)
- Image and video stylization (1)
- Image resolution (1)
- Imperative calculi (1)
- Improving classroom (1)
- Incoherent phonons (1)
- Incremental answer set programming (1)
- Inference (1)
- Informatics (1)
- Informatikstudium (1)
- Information federation (1)
- Information integration (1)
- Information retrieval (1)
- Information security (1)
- Innovation (1)
- Inquiry-based Learning (1)
- Insurance industry (1)
- Integrated circuit modeling (1)
- Interaktivität (1)
- Interface design (1)
- Internet of Things (1)
- Job monitoring (1)
- Job submission (1)
- Kernel (1)
- Kernelization (1)
- Key Competencies (1)
- Key input (1)
- Klausellernen (1)
- Knowledge representation (1)
- Kompetenzerwerb (1)
- L systems (1)
- LBA problem (1)
- LMS (1)
- Landmark visibility (1)
- Learners (1)
- Learning Fields (1)
- Learning ecology (1)
- Learning interfaces development (1)
- Learning with ICT (1)
- Lehrer*innenbildung (1)
- Lern-App (1)
- Lernaufgaben (1)
- Lernmotivation (1)
- Literature mining (1)
- Liver neoplasms (1)
- Load Balancing (1)
- Localization (1)
- Location awareness (1)
- Logarithm (1)
- Logic programming (1)
- Loss (1)
- Low Latency (1)
- Lower Secondary Level (1)
- Loyalty (1)
- MOOCs (1)
- MQTT (1)
- Machine Learning (1)
- Markov processes (1)
- Masking of X-values (1)
- Massive Open Online Courses (1)
- Measurement (1)
- Media in education (1)
- Meta-Programming (1)
- Metric learning (1)
- Minimal perturbation problems (1)
- Mobile App (1)
- Mobile application (1)
- Mobile devices (1)
- Mobile learning (1)
- Model checking (1)
- Modeling (1)
- Modelling (1)
- Multi-objective optimization (1)
- Multi-sided platforms (1)
- Multiple interpretation scheme (1)
- Music Technology (1)
- N-temperature model (1)
- NUI (1)
- Nash equilibrium (1)
- Natural Science Education (1)
- Natural language processing (1)
- Natural ventilation (1)
- Network (1)
- Network security (1)
- Neural networks (1)
- NoSQL (1)
- Non-Monotonic (1)
- Nonmonotonic reasoning (1)
- Norway (1)
- Novice programmers (1)
- OCCI (1)
- OSSE (1)
- OpenOLAT (1)
- Operation problem (1)
- Optimization (1)
- Parallel SAT solving (1)
- Parallel job execution time estimation (1)
- Particle detector (1)
- Partizipation (1)
- Pedagogical content knowledge (1)
- Pedagogical issues (1)
- Pedestrian navigation (1)
- Performance Evaluation (1)
- Personalization (1)
- Persönliche Lernumgebung (1)
- Pervasive computing (1)
- Pervasive game (1)
- Pervasive learning (1)
- Phantoms (1)
- Physical Science (1)
- Planar tactile display (1)
- Plant identification (1)
- Polarization (1)
- Preference Handling (1)
- Preprocessing (1)
- Problem Solving (1)
- Process model analysis (1)
- Product lifecycle management (1)
- Programming (1)
- Programming by optimization (1)
- Prototyping (1)
- RADFET (1)
- RADFETs (1)
- REST (1)
- RSA triangle (1)
- Radiation hardness (1)
- Random access memory (1)
- Ranking (1)
- Reasoning (1)
- Recommendations for CS-Curricula in Higher Education (1)
- Region of Interest (1)
- Relevanz (1)
- Reproducibility of results (1)
- Reversibility (1)
- SAT (1)
- SET pulsewidth distribution (1)
- SOA (1)
- SWOT (1)
- SaaSAbstract (1)
- Scalability (1)
- Scale-invariant feature transform (SIFT) (1)
- Scientific images (1)
- Screen reader (1)
- Seamless learning (1)
- Search problems (1)
- Security (1)
- Self-adaptive MPSoC (1)
- Semantic data (1)
- Semantic web (1)
- Semilinearity property (1)
- Sensors (1)
- Sequence embeddings (1)
- Service orientation (1)
- Sharing (1)
- Signal processing (1)
- Signaling transduction networks (1)
- Simulations (1)
- Single event effect (1)
- Single event upsets (1)
- Single-event transient (SET) (1)
- Small Private Online Courses (1)
- Social (1)
- Splicing (1)
- Splicing processor (1)
- Statistical relational learning (1)
- Stochastic relational process (1)
- Strong equivalence (1)
- Structural equation modeling (1)
- Studentenjobs (1)
- Studienabbrecher (1)
- Studiendauer (1)
- Systems biology (1)
- Systems of parallel communicating (1)
- TMR (1)
- TPACK (1)
- Tasks (1)
- Teacher perceptions (1)
- Teachers (1)
- Teaching information security (1)
- Technology proficiency (1)
- Terminology (1)
- Tests (1)
- Theorembeweisen (1)
- Theory formation (1)
- Thermoelasticity (1)
- Time series (1)
- Tomography (1)
- Tools (1)
- Tracking (1)
- Traffic data (1)
- Tree decomposition (1)
- Treewidth (1)
- Treewidth-aware reductions (1)
- Triple modular redundancy (TMR) (1)
- Tumor types (1)
- Turing machine (1)
- Type and effect systems (1)
- UAV imagery (1)
- UX (1)
- Ubiquitous learning (1)
- Ultrafast dynamics (1)
- Unary languages (1)
- Unifikation (1)
- Uniform Access Principle (1)
- Usability testing (1)
- User Experience (1)
- User submission pattern (1)
- User-centred design (1)
- VGG16 (1)
- Value network (1)
- Verification (1)
- Visual metaphor (1)
- Vocational Education (1)
- Weiterbildung (1)
- Wireless Sensor Networks (1)
- Word embeddings (1)
- X-masking (1)
- X-ray computed (1)
- X-values (1)
- Young People (1)
- abstraction (1)
- accepting grammars (1)
- action and change (1)
- activity (1)
- acute liver failure (1)
- acyclicity properties (1)
- adversarial classification (1)
- algorithm schedules (1)
- algorithms (1)
- analogical thinking (1)
- analysis (1)
- annealing (1)
- anti-cancer drugs (1)
- anxiety (1)
- approximate model counting (1)
- architecture (1)
- argument mining (1)
- arousal (1)
- artistic rendering (1)
- asynchrounous design (1)
- autism (1)
- automata (1)
- automated guided vehicle routing (1)
- automated planning (1)
- automatic feedback (1)
- behavioral abstraction (1)
- belief merging (1)
- belief revision (1)
- benchmark (1)
- bibliometric analysis (1)
- binary representation (1)
- binary search (1)
- block representation (1)
- bootstrapping (1)
- brain-computer interface (1)
- bulk built-in current sensor (1)
- bundled data (1)
- camera sensor (1)
- car assembly operations (1)
- cellular automata (1)
- circuit Faults (1)
- citation analysis (1)
- classroom language (1)
- click controller (1)
- clocks (1)
- co-citation analysis (1)
- co-occurrence analysis (1)
- code generation (1)
- cognitive modifiability (1)
- coherence relation (1)
- collaborative learning (1)
- combinatorial optimization problems (1)
- combined task and motion planning (1)
- common spatial patterns (1)
- competence (1)
- competencies (1)
- competency (1)
- competition (1)
- complexity (1)
- compliance (1)
- comprehension (1)
- computer science teachers (1)
- computer vision (1)
- concession (1)
- concurrent checking (1)
- conductive argument (1)
- connective (1)
- consistency (1)
- consistency checking (1)
- consistency measures (1)
- context-free grammar (1)
- context-sensitive (1)
- contrast (1)
- controlled vocabularies (1)
- corpus analysis (1)
- correlated errors (1)
- course timetabling (1)
- craters (1)
- crop (1)
- cs4fn (1)
- curriculum theory (1)
- decidability questions (1)
- declarative problem solving (1)
- deep learning (1)
- deep neural networks (1)
- deep residual networks (1)
- degree of non-context-freeness (1)
- degree of non-regularity (1)
- degree of non-regulation (1)
- depression (1)
- design flow (1)
- determinism (1)
- detrending (1)
- developmental systems (1)
- diagnosis (1)
- didactics (1)
- didaktisches Konzept (1)
- digitale Bildung (1)
- digitale Medien (1)
- digitally-enabled pedagogies (1)
- divide and conquer (1)
- domain-specific APIs (1)
- drug discovery (1)
- drug-sensitivity prediction (1)
- dynamic service binding (1)
- e-mentoring (1)
- eLectures (1)
- economic ripples (1)
- edge computing (1)
- education and public policy (1)
- educational programming (1)
- educational systems (1)
- educational timetabling (1)
- edutainment (1)
- embedded systems (1)
- emission factor (1)
- endothelin (1)
- endothelin-converting enzyme (1)
- ensemble kalman filter (1)
- ensemble methods (1)
- environments (1)
- error propagation (1)
- evaluation (1)
- event-related desynchronization (1)
- evolution (1)
- exponentiation (1)
- external ambiguity (1)
- extreme weather (1)
- face tracking (1)
- facial expression (1)
- fading (1)
- fault tolerance (1)
- field-programmable gate array (1)
- finite model computation (1)
- finite state sequential transducers (1)
- firmware update (1)
- formal (1)
- formal argumentation systems (1)
- fun (1)
- functions (1)
- gap-filling (1)
- geovisualization (1)
- governance (1)
- gradient boosting (1)
- grammar (1)
- graph-search (1)
- greenhouse gas (1)
- hardware accelerator (1)
- hardware architecture (1)
- high school (1)
- higher (1)
- hybrid solving (1)
- ice harboring (1)
- image classification (1)
- image processing (1)
- image recognition (1)
- imaging (1)
- impacts (1)
- incremental SVM (1)
- informal and formal learning (1)
- informal logic (1)
- informatics (1)
- informatics education (1)
- information and communication technologies (1)
- information flow control (1)
- innovation (1)
- interactive course (1)
- interactive workshop (1)
- internal ambiguity (1)
- intrusion detection (1)
- irradiation (1)
- key competences in physical computing (1)
- key competencies (1)
- kidney cancer (1)
- kinaesthetic teaching (1)
- klinisch-praktischer Unterricht (1)
- knowledge representation and reasoning (1)
- latches (1)
- learning (1)
- leftmost derivations (1)
- lesson planning (1)
- lesson preparation (1)
- linear programming (1)
- logic programming (1)
- logic programming methodology and applications (1)
- logic-based modeling (1)
- loop formulas (1)
- loose programming (1)
- loss propagation (1)
- lunar exploration (1)
- machine learning (1)
- machine learning algorithms (1)
- manipulation planning (1)
- measure development (1)
- media (1)
- mediated learning experience (1)
- metabolic network (1)
- metabolism (1)
- metabolomics (1)
- metadata (1)
- metastasis (1)
- mobile learning (1)
- mobile technologies and apps (1)
- mobiles Lernen (1)
- natural disasters (1)
- natural language generation (1)
- neighborhood (1)
- networks (1)
- neural networks (1)
- neutral endopeptidase (1)
- nonphotorealistic rendering (NPR) (1)
- o-ambiguity (1)
- on-farm evaluation (1)
- open learning (1)
- operating system (1)
- organisational evolution (1)
- pMOS radiation dosimeter (1)
- paper prototyping (1)
- parallel processing (1)
- parallel rewriting (1)
- parameter (1)
- parity aggregate operator (1)
- parsing (1)
- pdf forms (1)
- pedagogy (1)
- perception (1)
- perception differences (1)
- personal (1)
- personal response systems (1)
- philosophical foundation of informatics pedagogy (1)
- physical computing (1)
- physical computing tools (1)
- planning (1)
- platform (1)
- plug-ins (1)
- policy evaluation (1)
- policy making (1)
- portfolio-based solving (1)
- pre-primary level (1)
- predictive models (1)
- premise acceptability (1)
- preprocessing (1)
- primary education (1)
- primary level (1)
- problem-solving (1)
- process model alignment (1)
- process modeling (1)
- professional development (1)
- program encodings (1)
- programmed grammars (1)
- programming (1)
- programming in context (1)
- projection (1)
- proof complexity (1)
- pruritus (1)
- pulse stretching inverters (1)
- quality of life (1)
- quantum (1)
- random forest (1)
- real arguments (1)
- real-time (1)
- real-time mapping (1)
- reference (1)
- referential effectiveness (1)
- regression (1)
- regular language (1)
- regulation (1)
- reliability (1)
- reliability analysis (1)
- resources (1)
- restricted parallelism (1)
- satisfiability (1)
- secondary computer science education (1)
- secondary education (1)
- selective fault tolerance (1)
- self-adaptive multiprocessing system (1)
- self-checking (1)
- self-efficacy (1)
- semantic web (1)
- sensitivity (1)
- simplicity (1)
- single event transients (1)
- single event upset (1)
- single event upsets (1)
- single-event transient (1)
- single-trial-analysis (1)
- site-specific weed management (1)
- sleep quality (1)
- smart farming (1)
- social media (1)
- solar particle event (1)
- space missions (1)
- stable model semantics (1)
- state complexity (1)
- static analysis (1)
- static prediction games (1)
- strong equivalence (1)
- student activation (1)
- student experience (1)
- student perceptions (1)
- students’ conceptions (1)
- students’ knowledge (1)
- sufficiency (1)
- suicidal ideations (1)
- supply chains (1)
- support system (1)
- support vector machines (1)
- tableau calculi (1)
- teacher competencies (1)
- teacher training (1)
- teaching (1)
- teaching informatics in general education (1)
- technical notes and rapid communications (1)
- technische Rahmenbedingungen (1)
- tele-teaching (1)
- test response compaction (1)
- theorem (1)
- theory (1)
- theory of computation (1)
- timing (1)
- tracing (1)
- transient Faults (1)
- transient analysis (1)
- triangulated irregular networks (1)
- triple modular redundancy (1)
- unfounded sets (1)
- unification (1)
- user experience (1)
- user-centred (1)
- verification (1)
- video annotation (1)
- virtual mobility (1)
- virtual reality (1)
- wheat crops (1)
- work productivity (1)
- xAPI (1)
- yellow rust (1)
- ‘unplugged’ computing (1)
Institute
- Institut für Informatik und Computational Science (682)
- Institut für Physik und Astronomie (2)
- eLiS - E-Learning in Studienbereichen (2)
- Department Erziehungswissenschaft (1)
- Department Linguistik (1)
- Extern (1)
- Fachgruppe Betriebswirtschaftslehre (1)
- Historisches Institut (1)
- Universitätsbibliothek (1)
- Zentrum für Qualitätsentwicklung in Lehre und Studium (ZfQ) (1)
Eine übliche Erzählung verknüpft lange Studienzeiten und hohe Abbrecherquoten im Informatikstudium zum einen mit der sehr gut bezahlten Nebentätigkeit von Studierenden in der Informatikbranche, die deutlich studienzeitverlängernd sei; zum anderen werde wegen des hohen Bedarfs an Informatikern ein formeller Studienabschluss von den Studierenden häufig als entbehrlich betrachtet und eine Karriere in der Informatikbranche ohne abgeschlossenes Studium begonnen. In dieser Studie, durchgeführt an der Universität Potsdam, untersuchen wir, wie viele Informatikstudierende neben dem Studium innerhalb und außerhalb der Informatikbranche arbeiten, welche Erwartungen sie neben der Bezahlung damit verbinden und wie sich die Tätigkeit auf ihr Studium und ihre spätere berufliche Perspektive auswirkt. Aus aktuellem Anlass interessieren uns auch die Auswirkungen der Covid-19-Pandemie auf die Arbeitstätigkeiten der Informatikstudierenden.
The educational sector currently faces a massive digital transformation with various digital offerings entering the market. To provide some orientation in this transforming space, a national digital education platform (NDEP) is under development in Germany as part of a nationwide flagship project. On the one hand, in efficiently connecting the relevant stakeholders to each other and to value-adding education-related offerings, various benefits emerge. On the other hand, monopolising the educational sector and influencing the respective market through a state-controlled platform bears potential regulatory risks from misuse of power by the platform to malpractice by the users. Against this background, we aim to identify and systematise these potential drawbacks prior to the platform’s actual development and implementation. We pursue a qualitative, interpretivist approach for policy analysis, based on ten elite interviews and two workshops. Our results are threefold: (1) We capture the consolidated NDEP architecture; (2) We categorise the range of relevant functions and value propositions of the NDEP; (3) We derive 23 regulatory areas of conflict across the three building blocks that result from the potential ecosystem and function scope configurations of the NDEP. As a contribution to research, we shed new interdisciplinary light on the governance and infrastructure of public-private platforms that enable innovation and collaboration while integrating respective market segments. As a contribution to practice, we provide clear guidance for policy-makers in strategizing the development and governance of and through national digital platforms in education.
Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models’ accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases.
Answer Set Programming (ASP) is a paradigm for modeling and solving problems for knowledge representation and reasoning. There are plenty of results dedicated to studying the hardness of (fragments of) ASP. So far, these studies resulted in characterizations in terms of computational complexity as well as in fine-grained insights presented in form of dichotomy-style results, lower bounds when translating to other formalisms like propositional satisfiability (SAT), and even detailed parameterized complexity landscapes. A generic parameter in parameterized complexity originating from graph theory is the socalled treewidth, which in a sense captures structural density of a program. Recently, there was an increase in the number of treewidth-based solvers related to SAT. While there are translations from (normal) ASP to SAT, no reduction that preserves treewidth or at least keeps track of the treewidth increase is known. In this paper we propose a novel reduction from normal ASP to SAT that is aware of the treewidth, and guarantees that a slight increase of treewidth is indeed sufficient. Further, we show a new result establishing that, when considering treewidth, already the fragment of normal ASP is slightly harder than SAT (under reasonable assumptions in computational complexity). This also confirms that our reduction probably cannot be significantly improved and that the slight increase of treewidth is unavoidable. Finally, we present an empirical study of our novel reduction from normal ASP to SAT, where we compare treewidth upper bounds that are obtained via known decomposition heuristics. Overall, our reduction works better with these heuristics than existing translations. (c) 2021 Elsevier B.V. All rights reserved.
The highly structured nature of the educational sector demands effective policy mechanisms close to the needs of the field. That is why evidence-based policy making, endorsed by the European Commission under Erasmus+ Key Action 3, aims to make an alignment between the domains of policy and practice. Against this background, this article addresses two issues: First, that there is a vertical gap in the translation of higher-level policies to local strategies and regulations. Second, that there is a horizontal gap between educational domains regarding the policy awareness of individual players. This was analyzed in quantitative and qualitative studies with domain experts from the fields of virtual mobility and teacher training. From our findings, we argue that the combination of both gaps puts the academic bridge from secondary to tertiary education at risk, including the associated knowledge proficiency levels. We discuss the role of digitalization in the academic bridge by asking the question: which value does the involved stakeholders expect from educational policies? As a theoretical basis, we rely on the model of value co-creation for and by stakeholders. We describe the used instruments along with the obtained results and proposed benefits. Moreover, we reflect on the methodology applied, and we finally derive recommendations for future academic bridge policies.
Continuous verification of network security compliance is an accepted need. Especially, the analysis of stateful packet filters plays a central role for network security in practice. But the few existing tools which support the analysis of stateful packet filters are based on general applicable formal methods like Satifiability Modulo Theories (SMT) or theorem prover and show runtimes in the order of minutes to hours making them unsuitable for continuous compliance verification. In this work, we address these challenges and present the concept of state shell interweaving to transform a stateful firewall rule set into a stateless rule set. This allows us to reuse any fast domain specific engine from the field of data plane verification tools leveraging smart, very fast, and domain specialized data structures and algorithms including Header Space Analysis (HSA). First, we introduce the formal language FPL that enables a high-level human-understandable specification of the desired state of network security. Second, we demonstrate the instantiation of a compliance process using a verification framework that analyzes the configuration of complex networks and devices - including stateful firewalls - for compliance with FPL policies. Our evaluation results show the scalability of the presented approach for the well known Internet2 and Stanford benchmarks as well as for large firewall rule sets where it outscales state-of-the-art tools by a factor of over 41.
Computational drug sensitivity models have the potential to improve therapeutic outcomes by identifying targeted drug components that are likely to achieve the highest efficacy for a cancer cell line at hand at a therapeutic dose. State of the art drug sensitivity models use regression techniques to predict the inhibitory concentration of a drug for a tumor cell line. This regression objective is not directly aligned with either of these principal goals of drug sensitivity models: We argue that drug sensitivity modeling should be seen as a ranking problem with an optimization criterion that quantifies a drug's inhibitory capacity for the cancer cell line at hand relative to its toxicity for healthy cells. We derive an extension to the well-established drug sensitivity regression model PaccMann that employs a ranking loss and focuses on the ratio of inhibitory concentration and therapeutic dosage range. We find that the ranking extension significantly enhances the model's capability to identify the most effective anticancer drugs for unseen tumor cell profiles based in on in-vitro data.
The use of neural networks is considered as the state of the art in the field of image classification. A large number of different networks are available for this purpose, which, appropriately trained, permit a high level of classification accuracy. Typically, these networks are applied to uncompressed image data, since a corresponding training was also carried out using image data of similar high quality. However, if image data contains image errors, the classification accuracy deteriorates drastically. This applies in particular to coding artifacts which occur due to image and video compression. Typical application scenarios for video compression are narrowband transmission channels for which video coding is required but a subsequent classification is to be carried out on the receiver side. In this paper we present a special H.264/Advanced Video Codec (AVC) based video codec that allows certain regions of a picture to be coded with near constant picture quality in order to allow a reliable classification using neural networks, whereas the remaining image will be coded using constant bit rate. We have combined this feature with the ability to run with lowest latency properties, which is usually also required in remote control applications scenarios. The codec has been implemented as a fully hardwired High Definition video capable hardware architecture which is suitable for Field Programmable Gate Arrays.
In this paper, we present a study comparing the depth to diameter (d/D) ratio of small simple craters (200-1000 m) of an area between -88.5 degrees to -90 degrees latitude at the lunar south pole containing Permanent Shadowed Regions (PSRs) versus craters without PSRs. As PSRs can reach temperatures of 110 K and are capable of harboring volatiles, especially water ice, we analyzed the relationship of depth versus diameter ratios and its possible implications for harboring water ice. Variations in the d/D ratios can also be caused by other processes such as degradation, isostatic adjustment, or differences in surface properties. The conducted d/D ratio analysis suggests that a differentiation between craters containing PSRs versus craters without PSRs occurs. Thus, a possible direct relation between d/D ratio, PSRs, and water ice harboring might exist. Our results suggest that differences in the target's surface properties may explain the obtained results. The resulting d/D ratios of craters with PSRs can help to select target areas for future In-Situ Resource Utilization (ISRU) missions.
Deep metric learning employs deep neural networks to embed instances into a metric space such that distances between instances of the same class are small and distances between instances from different classes are large. In most existing deep metric learning techniques, the embedding of an instance is given by a feature vector produced by a deep neural network and Euclidean distance or cosine similarity defines distances between these vectors. This paper studies deep distributional embeddings of sequences, where the embedding of a sequence is given by the distribution of learned deep features across the sequence. The motivation for this is to better capture statistical information about the distribution of patterns within the sequence in the embedding. When embeddings are distributions rather than vectors, measuring distances between embeddings involves comparing their respective distributions. The paper therefore proposes a distance metric based on Wasserstein distances between the distributions and a corresponding loss function for metric learning, which leads to a novel end-to-end trainable embedding model. We empirically observe that distributional embeddings outperform standard vector embeddings and that training with the proposed Wasserstein metric outperforms training with other distance functions.
Objectives To compare image quality of deep learning reconstruction (AiCE) for radiomics feature extraction with filtered back projection (FBP), hybrid iterative reconstruction (AIDR 3D), and model-based iterative reconstruction (FIRST). Methods Effects of image reconstruction on radiomics features were investigated using a phantom that realistically mimicked a 65-year-old patient's abdomen with hepatic metastases. The phantom was scanned at 18 doses from 0.2 to 4 mGy, with 20 repeated scans per dose. Images were reconstructed with FBP, AIDR 3D, FIRST, and AiCE. Ninety-three radiomics features were extracted from 24 regions of interest, which were evenly distributed across three tissue classes: normal liver, metastatic core, and metastatic rim. Features were analyzed in terms of their consistent characterization of tissues within the same image (intraclass correlation coefficient >= 0.75), discriminative power (Kruskal-Wallis test p value < 0.05), and repeatability (overall concordance correlation coefficient >= 0.75). Results The median fraction of consistent features across all doses was 6%, 8%, 6%, and 22% with FBP, AIDR 3D, FIRST, and AiCE, respectively. Adequate discriminative power was achieved by 48%, 82%, 84%, and 92% of features, and 52%, 20%, 17%, and 39% of features were repeatable, respectively. Only 5% of features combined consistency, discriminative power, and repeatability with FBP, AIDR 3D, and FIRST versus 13% with AiCE at doses above 1 mGy and 17% at doses >= 3 mGy. AiCE was the only reconstruction technique that enabled extraction of higher-order features. Conclusions AiCE more than doubled the yield of radiomics features at doses typically used clinically. Inconsistent tissue characterization within CT images contributes significantly to the poor stability of radiomics features.
Programs are often subjected to significant optimizing and parallelizing transformations based on extensive dependence analysis. Formal validation of such transformations needs modelling paradigms which can capture both control and data dependences in the program vividly. Being value-based with an inherent scope of capturing parallelism, the untimed coloured Petri net (CPN) models, reported in the literature, fit the bill well; accordingly, they are likely to be more convenient as the intermediate representations (IRs) of both the source and the transformed codes for translation validation than strictly sequential variable-based IRs like sequential control flow graphs (CFGs). In this work, an efficient path-based equivalence checking method for CPN models of programs on integers is presented. Extensive experimentation has been carried out on several sequential and parallel examples. Complexity and correctness issues have been treated rigorously for the method.
The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels.
We present a method employing Answer Set Programming in combination with Approximate Model Counting for fast and accurate calculation of error propagation probabilities in digital circuits. By an efficient problem encoding, we achieve an input data format similar to a Verilog netlist so that extensive preprocessing is avoided. By a tight interconnection of our application with the underlying solver, we avoid iterating over fault sites and reduce calls to the solver. Several circuits were analyzed with varying numbers of considered cycles and different degrees of approximation. Our experiments show, that the runtime can be reduced by approximation by a factor of 91, whereas the error compared to the exact result is below 1%.
Instruments for measuring the absorbed dose and dose rate under radiation exposure, known as radiation dosimeters, are indispensable in space missions. They are composed of radiation sensors that generate current or voltage response when exposed to ionizing radiation, and processing electronics for computing the absorbed dose and dose rate. Among a wide range of existing radiation sensors, the Radiation Sensitive Field Effect Transistors (RADFETs) have unique advantages for absorbed dose measurement, and a proven record of successful exploitation in space missions. It has been shown that the RADFETs may be also used for the dose rate monitoring. In that regard, we propose a unique design concept that supports the simultaneous operation of a single RADFET as absorbed dose and dose rate monitor. This enables to reduce the cost of implementation, since the need for other types of radiation sensors can be minimized or eliminated. For processing the RADFET's response we propose a readout system composed of analog signal conditioner (ASC) and a self-adaptive multiprocessing system-on-chip (MPSoC). The soft error rate of MPSoC is monitored in real time with embedded sensors, allowing the autonomous switching between three operating modes (high-performance, de-stress and fault-tolerant), according to the application requirements and radiation conditions.
The radiation-sensitive field-effect transistors (RADFETs) with an oxide thickness of 400 nm are irradiated with gate voltages of 2, 4 and 6 V, and without gate voltage.
A detailed analysis of the mechanisms responsible for the creation of traps during irradiation is performed.
The creation of the traps in the oxide, near and at the silicon/silicon-dioxide (Si/SiO2) interface during irradiation is modelled very well. This modelling can also be used for other MOS transistors containing SiO2.
The behaviour of radiation traps during postirradiation annealing is analysed, and the corresponding functions for their modelling are obtained. The switching traps (STs) do not have significant influence on threshold voltage shift, and two radiation-induced trap types fit the fixed traps (FTs) very well. The fading does not depend on the positive gate voltage applied during irradiation, but it is twice lower in case there is no gate voltage.
A new dosimetric parameter, called the Golden Ratio (GR), is proposed, which represents the ratio between the threshold voltage shift after irradiation and fading after spontaneous annealing. This parameter can be useful for comparing MOS dosimeters.
Answer set planning
(2022)
Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans, that is, solutions to planning problems, that transform a given state of the world to another state. The development of efficient and scalable answer set solvers has provided a significant boost to the development of ASP-based planning systems. This paper surveys the progress made during the last two and a half decades in the area of answer set planning, from its foundations to its use in challenging planning domains. The survey explores the advantages and disadvantages of answer set planning. It also discusses typical applications of answer set planning and presents a set of challenges for future research.
The bulk built-in current sensor (BBICS) is a cost-effective solution for detection of energetic particle strikes in integrated circuits.
With an appropriate number of BBICSs distributed across the chip, the soft error locations can be identified, and the dynamic fault-tolerant mechanisms can be activated locally to correct the soft errors in the affected logic.
In this work, we introduce a pulse stretching BBICS (PS-BBICS) constructed by connecting a standard BBICS and a custom-designed pulse stretching cell.
The aim of PS-BBICS is to enable the on-chip measurement of the single event transient (SET) pulse width, allowing to detect the linear energy transfer (LET) of incident particles, and thus assess more accurately the radiation conditions.
Based on Spectre simula-tions, we have shown that for the LET from 1 to 100 MeV cm2 mg -1, the SET pulse width detected by PS-BBICS varies by 620-800 ps. The threshold LET of PS-BBICS increases linearly with the number of monitored inverters, and it is around 1.7 MeV cm2 mg- 1 for ten monitored inverters.
On the other hand, the SET pulse width is in-dependent of the number of monitored inverters for LET > 4 MeV cm2 mg -1. It was shown that supply voltage, temperature and process variations have strong impact on the response of PS-BBICS.
We present SURFER, a novel reduced model for estimating the impact of CO2 emissions and solar radiation modification options on sea level rise and ocean acidification over timescales of several thousands of years.
SURFER has been designed for the analysis of CO2 emission and solar radiation modification policies, for supporting the computation of optimal (CO2 emission and solar radiation modification) policies and for the study of commitment and responsibility under uncertainty.
The model is based on a combination of conservation laws for the masses of atmospheric and oceanic carbon and for the oceanic temperature anomalies, and of adhoc parameterisations for the different sea level rise contributors: ice sheets, glaciers and ocean thermal expansion. It consists of 9 loosely coupled ordinary differential equations, is understandable, fast and easy to modify and calibrate.
It reproduces the results of more sophisticated, high-dimensional earth system models on timescales up to millennia.
We study the concept of reversibility in connection with parallel communicating systems of finite automata (PCFA in short). We define the notion of reversibility in the case of PCFA (also covering the non-deterministic case) and discuss the relationship of the reversibility of the systems and the reversibility of its components. We show that a system can be reversible with non-reversible components, and the other way around, the reversibility of the components does not necessarily imply the reversibility of the system as a whole. We also investigate the computational power of deterministic centralized reversible PCFA. We show that these very simple types of PCFA (returning or non-returning) can recognize regular languages which cannot be accepted by reversible (deterministic) finite automata, and that they can even accept languages that are not context-free. We also separate the deterministic and non-deterministic variants in the case of systems with non-returning communication. We show that there are languages accepted by non-deterministic centralized PCFA, which cannot be recognized by any deterministic variant of the same type.
We introduce a new measure of descriptional complexity on finite automata, called the number of active states. Roughly speaking, the number of active states of an automaton A on input w counts the number of different states visited during the most economic computation of the automaton A for the word w. This concept generalizes to finite automata and regular languages in a straightforward way. We show that the number of active states of both finite automata and regular languages is computable, even with respect to nondeterministic finite automata. We further compare the number of active states to related measures for regular languages. In particular, we show incomparability to the radius of regular languages and that the difference between the number of active states and the total number of states needed in finite automata for a regular language can be of exponential order.
Image feature detection is a key task in computer vision. Scale Invariant Feature Transform (SIFT) is a prevalent and well known algorithm for robust feature detection. However, it is computationally demanding and software implementations are not applicable for real-time performance. In this paper, a versatile and pipelined hardware implementation is proposed, that is capable of computing keypoints and rotation invariant descriptors on-chip. All computations are performed in single precision floating-point format which makes it possible to implement the original algorithm with little alteration. Various rotation resolutions and filter kernel sizes are supported for images of any resolution up to ultra-high definition. For full high definition images, 84 fps can be processed. Ultra high definition images can be processed at 21 fps.
Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types
(2021)
Background:
There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually.
Methods:
In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data.
Results:
We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: .
Conclusions:
Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the interactive knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs.
Student teachers often struggle to keep track of everything that is happening in the classroom, and particularly to notice and respond when students cause disruptions. The complexity of the classroom environment is a potential contributing factor that has not been empirically tested. In this experimental study, we utilized a virtual reality (VR) classroom to examine whether classroom complexity affects the likelihood of student teachers noticing disruptions and how they react after noticing. Classroom complexity was operationalized as the number of disruptions and the existence of overlapping disruptions (multidimensionality) as well as the existence of parallel teaching tasks (simultaneity). Results showed that student teachers (n = 50) were less likely to notice the scripted disruptions, and also less likely to respond to the disruptions in a comprehensive and effortful manner when facing greater complexity. These results may have implications for both teacher training and the design of VR for training or research purpose. This study contributes to the field from two aspects: 1) it revealed how features of the classroom environment can affect student teachers' noticing of and reaction to disruptions; and 2) it extends the functionality of the VR environment-from a teacher training tool to a testbed of fundamental classroom processes that are difficult to manipulate in real-life.
Background:
Pruritus often accompanies chronic skin diseases, exerting considerable burden on many areas of patient functioning; this burden and the features of pruritus remain insufficiently characterized.
Objective:
To investigate characteristics, including localization patterns, and burden of pruritus in patients with chronic dermatoses.
Methods:
We recruited 800 patients with active chronic skin diseases. We assessed pruritus intensity, localization, and further characteristics. We used validated questionnaires to assess quality of life, work productivity and activity impairment, anxiety, depression, and sleep quality.
Results:
Nine out of every 10 patients had experienced pruritus throughout their disease and 73% in the last 7 days. Pruritus often affected the entire body and was not restricted to skin lesions. Patients with moderate to severe pruritus reported significantly more impairment to their sleep quality and work productivity, and they were more depressed and anxious than control individuals and patients with mild or no pruritus. Suicidal ideations were highly prevalent in patients with chronic pruritus (18.5%) and atopic dermatitis (11.8%).
Conclusions:
Pruritus prevalence and intensity are very high across all dermatoses studied; intensity is linked to impairment in many areas of daily functioning. Effective treatment strategies are urgently required to treat pruritus and the underlying skin disease. ( J Am Acad Dermatol 2021;84:691-700.)
Tropical cyclones range among the costliest disasters on Earth. Their economic repercussions along the supply and trade network also affect remote economies that are not directly affected. We here simulate possible global repercussions on consumption for the example case of Hurricane Sandy in the US (2012) using the shock-propagation model Acclimate. The modeled shock yields a global three-phase ripple: an initial production demand reduction and associated consumption price decrease, followed by a supply shortage with increasing prices, and finally a recovery phase. Regions with strong trade relations to the US experience strong magnitudes of the ripple. A dominating demand reduction or supply shortage leads to overall consumption gains or losses of a region, respectively. While finding these repercussions in historic data is challenging due to strong volatility of economic interactions, numerical models like ours can help to identify them by approaching the problem from an exploratory angle, isolating the effect of interest. For this, our model simulates the economic interactions of over 7000 regional economic sectors, interlinked through about 1.8 million trade relations. Under global warming, the wave-like structures of the economic response to major hurricanes like the one simulated here are likely to intensify and potentially overlap with other weather extremes.
Due to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.
Stripe rust (Pst) is a major disease of wheat crops leading untreated to severe yield losses. The use of fungicides is often essential to control Pst when sudden outbreaks are imminent. Sensors capable of detecting Pst in wheat crops could optimize the use of fungicides and improve disease monitoring in high-throughput field phenotyping. Now, deep learning provides new tools for image recognition and may pave the way for new camera based sensors that can identify symptoms in early stages of a disease outbreak within the field. The aim of this study was to teach an image classifier to detect Pst symptoms in winter wheat canopies based on a deep residual neural network (ResNet). For this purpose, a large annotation database was created from images taken by a standard RGB camera that was mounted on a platform at a height of 2 m. Images were acquired while the platform was moved over a randomized field experiment with Pst-inoculated and Pst-free plots of winter wheat. The image classifier was trained with 224 x 224 px patches tiled from the original, unprocessed camera images. The image classifier was tested on different stages of the disease outbreak. At patch level the image classifier reached a total accuracy of 90%. To test the image classifier on image level, the image classifier was evaluated with a sliding window using a large striding length of 224 px allowing for fast test performance. At image level, the image classifier reached a total accuracy of 77%. Even in a stage with very low disease spreading (0.5%) at the very beginning of the Pst outbreak, a detection accuracy of 57% was obtained. Still in the initial phase of the Pst outbreak with 2 to 4% of Pst disease spreading, detection accuracy with 76% could be attained. With further optimizations, the image classifier could be implemented in embedded systems and deployed on drones, vehicles or scanning systems for fast mapping of Pst outbreaks.
Machine learning for improvement of thermal conditions inside a hybrid ventilated animal building
(2021)
In buildings with hybrid ventilation, natural ventilation opening positions (windows), mechanical ventilation rates, heating, and cooling are manipulated to maintain desired thermal conditions. The indoor temperature is regulated solely by ventilation (natural and mechanical) when the external conditions are favorable to save external heating and cooling energy. The ventilation parameters are determined by a rule-based control scheme, which is not optimal. This study proposes a methodology to enable real-time optimum control of ventilation parameters. We developed offline prediction models to estimate future thermal conditions from the data collected from building in operation. The developed offline model is then used to find the optimal controllable ventilation parameters in real-time to minimize the setpoint deviation in the building. With the proposed methodology, the experimental building's setpoint deviation improved for 87% of time, on average, by 0.53 degrees C compared to the current deviations.
Optimized deep learning model as a basis for fast UAV mapping of weed species in winter wheat crops
(2021)
Weed maps should be available quickly, reliably, and with high detail to be useful for site-specific management in crop protection and to promote more sustainable agriculture by reducing pesticide use. Here, the optimization of a deep residual convolutional neural network (ResNet-18) for the classification of weed and crop plants in UAV imagery is proposed. The target was to reach sufficient performance on an embedded system by maintaining the same features of the ResNet-18 model as a basis for fast UAV mapping. This would enable online recognition and subsequent mapping of weeds during UAV flying operation. Optimization was achieved mainly by avoiding redundant computations that arise when a classification model is applied on overlapping tiles in a larger input image. The model was trained and tested with imagery obtained from a UAV flight campaign at low altitude over a winter wheat field, and classification was performed on species level with the weed species Matricaria chamomilla L., Papaver rhoeas L., Veronica hederifolia L., and Viola arvensis ssp. arvensis observed in that field. The ResNet-18 model with the optimized image-level prediction pipeline reached a performance of 2.2 frames per second with an NVIDIA Jetson AGX Xavier on the full resolution UAV image, which would amount to about 1.78 ha h(-1) area output for continuous field mapping. The overall accuracy for determining crop, soil, and weed species was 94%. There were some limitations in the detection of species unknown to the model. When shifting from 16-bit to 32-bit model precision, no improvement in classification accuracy was observed, but a strong decline in speed performance, especially when a higher number of filters was used in the ResNet-18 model. Future work should be directed towards the integration of the mapping process on UAV platforms, guiding UAVs autonomously for mapping purpose, and ensuring the transferability of the models to other crop fields.
In control theory, to solve a finite-horizon sequential decision problem (SDP) commonly means to find a list of decision rules that result in an optimal expected total reward (or cost) when taking a given number of decision steps. SDPs are routinely solved using Bellman's backward induction. Textbook authors (e.g. Bertsekas or Puterman) typically give more or less formal proofs to show that the backward induction algorithm is correct as solution method for deterministic and stochastic SDPs. Botta, Jansson and Ionescu propose a generic framework for finite horizon, monadic SDPs together with a monadic version of backward induction for solving such SDPs. In monadic SDPs, the monad captures a generic notion of uncertainty, while a generic measure function aggregates rewards. In the present paper, we define a notion of correctness for monadic SDPs and identify three conditions that allow us to prove a correctness result for monadic backward induction that is comparable to textbook correctness proofs for ordinary backward induction. The conditions that we impose are fairly general and can be cast in category-theoretical terms using the notion of Eilenberg-Moore algebra. They hold in familiar settings like those of deterministic or stochastic SDPs, but we also give examples in which they fail. Our results show that backward induction can safely be employed for a broader class of SDPs than usually treated in textbooks. However, they also rule out certain instances that were considered admissible in the context of Botta et al. 's generic framework. Our development is formalised in Idris as an extension of the Botta et al. framework and the sources are available as supplementary material.
This study investigates the use of pulse stretching (skew-sized) inverters for monitoring the variation of count rate and linear energy transfer (LET) of energetic particles. The basic particle detector is a cascade of two pulse stretching inverters, and the required sensing area is obtained by connecting up to 12 two-inverter cells in parallel and employing the required number of parallel arrays. The incident particles are detected as single-event transients (SETs), whereby the SET count rate denotes the particle count rate, while the SET pulsewidth distribution depicts the LET variations. The advantage of the proposed solution is the possibility to sense the LET variations using fully digital processing logic. SPICE simulations conducted on IHP's 130-nm CMOS technology have shown that the SET pulsewidth varies by approximately 550 ps over the LET range from 1 to 100 MeV center dot cm(2) center dot mg(-1). The proposed detector is intended for triggering the fault-tolerant mechanisms within a self-adaptive multiprocessing system employed in space. It can be implemented as a standalone detector or integrated in the same chip with the target system.
Use of a standard non-rad-hard digital cell library in the rad-hard design can be a cost-effective solution for space applications. In this paper we demonstrate how a standard non-rad-hard flip-flop, as one of the most vulnerable digital cells, can be converted into a rad-hard flip-flop without modifying its internal structure. We present five variants of a Triple Modular Redundancy (TMR) flip-flop: baseline TMR flip-flop, latch-based TMR flip-flop, True-Single Phase Clock (TSPC) TMR flip-flop, scannable TMR flip-flop and self-correcting TMR flipflop. For all variants, the multi-bit upsets have been addressed by applying special placement constraints, while the Single Event Transient (SET) mitigation was achieved through the usage of customized SET filters and selection of optimal inverter sizes for the clock and reset trees. The proposed flip-flop variants feature differing performance, thus enabling to choose the optimal solution for every sensitive node in the circuit, according to the predefined design constraints. Several flip-flop designs have been validated on IHP's 130nm BiCMOS process, by irradiation of custom-designed shift registers. It has been shown that the proposed TMR flip-flops are robust to soft errors with a threshold Linear Energy Transfer (LET) from (32.4 MeV.cm(2)/mg) to (62.5 MeV.cm(2)/mg), depending on the variant.
In recent years, many efforts have been made to apply image processing techniques for plant leaf identification. However, categorizing leaf images at the cultivar/variety level, because of the very low inter-class variability, is still a challenging task. In this research, we propose an automatic discriminative method based on convolutional neural networks (CNNs) for classifying 12 different cultivars of common beans that belong to three various species. We show that employing advanced loss functions, such as Additive Angular Margin Loss and Large Margin Cosine Loss, instead of the standard softmax loss function for the classification can yield better discrimination between classes and thereby mitigate the problem of low inter-class variability. The method was evaluated by classifying species (level I), cultivars from the same species (level II), and cultivars from different species (level III), based on images from the leaf foreside and backside. The results indicate that the performance of the classification algorithm on the leaf backside image dataset is superior. The maximum mean classification accuracies of 95.86, 91.37 and 86.87% were obtained at the levels I, II and III, respectively. The proposed method outperforms the previous relevant works and provides a reliable approach for plant cultivars identification.
Epistemic logic programs constitute an extension of the stable model semantics to deal with new constructs called subjective literals. Informally speaking, a subjective literal allows checking whether some objective literal is true in all or some stable models. As it can be imagined, the associated semantics has proved to be non-trivial, since the truth of subjective literals may interfere with the set of stable models it is supposed to query. As a consequence, no clear agreement has been reached and different semantic proposals have been made in the literature. Unfortunately, comparison among these proposals has been limited to a study of their effect on individual examples, rather than identifying general properties to be checked. In this paper, we propose an extension of the well-known splitting property for logic programs to the epistemic case. We formally define when an arbitrary semantics satisfies the epistemic splitting property and examine some of the consequences that can be derived from that, including its relation to conformant planning and to epistemic constraints. Interestingly, we prove (through counterexamples) that most of the existing approaches fail to fulfill the epistemic splitting property, except the original semantics proposed by Gelfond 1991 and a recent proposal by the authors, called Founded Autoepistemic Equilibrium Logic.
Answer Set Programming (ASP) is a successful rule-based formalism for modeling and solving knowledge-intense combinatorial (optimization) problems. Despite its success in both academic and industry, open challenges like automatic source code optimization, and software engineering remains. This is because a problem encoded into an ASP might not have the desired solving performance compared to an equivalent representation. Motivated by these two challenges, this paper has three main contributions. First, we propose a developing process towards a methodology to implement ASP programs, being faithful to existing methods. Second, we present ASP encodings that serve as the basis from the developing process. Third, we demonstrate the use of ASP to reverse the standard solving process. That is, knowing answer sets in advance, and desired strong equivalent properties, “we” exhaustively reconstruct ASP programs if they exist. This paper was originally motivated by the search of propositional formulas (if they exist) that represent the semantics of a new aggregate operator. Particularly, a parity aggregate. This aggregate comes as an improvement from the already existing parity (xor) constraints from xorro, where lacks expressiveness, even though these constraints fit perfectly for reasoning modes like sampling or model counting. To this end, this extended version covers the fundaments from parity constraints as well as the xorro system. Hence, we delve a little more in the examples and the proposed methodology over parity constraints. Finally, we discuss our results by showing the only representation available, that satisfies different properties from the classical logic xor operator, which is also consistent with the semantics of parity constraints from xorro.
Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility. Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.
The notion of coherence relations is quite widely accepted in general, but concrete proposals differ considerably on the questions of how they should be motivated, which relations are to be assumed, and how they should be defined. This paper takes a "bottom-up" perspective by assessing the contribution made by linguistic signals (connectives), using insights from the relevant literature as well as verification by practical text annotation. We work primarily with the German language here and focus on the realm of contrast. Thus, we suggest a new inventory of contrastive connective functions and discuss their relationship to contrastive coherence relations that have been proposed in earlier work.
Many Android applications embed webpages via WebView components and execute JavaScript code within Android. Hybrid applications leverage dedicated APIs to load a resource and render it in a WebView. Furthermore, Android objects can be shared with the JavaScript world. However, bridging the interfaces of the Android and JavaScript world might also incur severe security threats: Potentially untrusted webpages and their JavaScript might interfere with the Android environment and its access to native features.
No general analysis is currently available to assess the implications of such hybrid apps bridging the two worlds. To understand the semantics and effects of hybrid apps, we perform a large-scale study on the usage of the hybridization APIs in the wild. We analyze and categorize the parameters to hybridization APIs for 7,500 randomly selected and the 196 most popular applications from the Google Playstore as well as 1000 malware samples. Our results advance the general understanding of hybrid applications, as well as implications for potential program analyses, and the current security situation: We discovered thousands of flows of sensitive data from Android to JavaScript, the vast majority of which could flow to potentially untrustworthy code. Our analysis identified numerous web pages embedding vulnerabilities, which we exemplarily exploited. Additionally, we discovered a multitude of applications in which potentially untrusted JavaScript code may interfere with (trusted) Android objects, both in benign and malign applications.
M-rate 0L systems are interactionless Lindenmayer systems together with a function assigning to every string a set of multisets of productions that may be applied simultaneously to the string. Some questions that have been left open in the forerunner papers are examined, and the computational power of deterministic M-rate 0L systems is investigated, where also tabled and extended variants are taken into consideration.
We study the derivational complexity of context-free and context-sensitive grammars by counting the maximal number of non-regular and non-context-free rules used in a derivation, respectively. The degree of non-regularity/non-context-freeness of a language is the minimum degree of non-regularity/non-context-freeness of context-free/context-sensitive grammars generating it. A language has finite degree of non-regularity iff it is regular. We give a condition for deciding whether the degree of non-regularity of a given unambiguous context-free grammar is finite. The problem becomes undecidable for arbitrary linear context-free grammars. The degree of non-regularity of unambiguous context-free grammars generating non-regular languages as well as that of grammars generating deterministic context-free languages that are not regular is of order Omega(n). Context-free non-regular languages of sublinear degree of non-regularity are presented. A language has finite degree of non-context-freeness if it is context-free. Context-sensitive grammars with a quadratic degree of non-context-freeness are more powerful than those of a linear degree.
Many knowledge representation tasks involve trees or similar structures as abstract datatypes. However, devising compact and efficient declarative representations of such structural properties is non-obvious and can be challenging indeed. In this article, we take a number of acyclicity properties into consideration and investigate various logic-based approaches to encode them. We use answer set programming as the primary representation language but also consider mappings to related formalisms, such as propositional logic, difference logic and linear programming. We study the compactness of encodings and the resulting computational performance on benchmarks involving acyclic or tree structures.
Answer Set Programming (ASP) is a prominent knowledge representation language with roots in logic programming and non-monotonic reasoning. Biennial ASP competitions are organized in order to furnish challenging benchmark collections and assess the advancement of the state of the art in ASP solving. In this paper, we report on the design and results of the Seventh ASP Competition, jointly organized by the University of Calabria (Italy), the University of Genova (Italy), and the University of Potsdam (Germany), in affiliation with the 14th International Conference on Logic Programming and Non-Monotonic Reasoning (LPNMR 2017).
MUP
(2020)
Message Queuing Telemetry Transport (MQTT) is one of the dominating protocols for edge- and cloud-based Internet of Things (IoT) solutions. When a security vulnerability of an IoT device is known, it has to be fixed as soon as possible. This requires a firmware update procedure. In this paper, we propose a secure update protocol for MQTT-connected devices which ensures the freshness of the firmware, authenticates the new firmware and considers constrained devices. We show that the update protocol is easy to integrate in an MQTT-based IoT network using a semantic approach. The feasibility of our approach is demonstrated by a detailed performance analysis of our prototype implementation on a IoT device with 32 kB RAM. Thereby, we identify design issues in MQTT 5 which can help to improve the support of constrained devices.
This paper is part of the investigation of some operations on words and languages with motivations coming from DNA biochemistry, namely three variants of hairpin completion and three variants of hairpin reduction. Since not all the hairpin completions or reductions of semilinear languages remain semilinear, we study sufficient conditions for semilinear languages to preserve their semilinearity property after applying the non-iterated hairpin completion or hairpin reduction. A similar approach is then applied to the iterated variants of these operations. Along these lines, we define the hairpin reduction root of a language and show that the hairpin reduction root of a semilinear language is not necessarily semilinear except the universal language. A few open problems are finally discussed.
Arousal is one of the dimensions of core affect and frequently used to describe experienced or observed emotional states. While arousal ratings of facial expressions are collected in many studies it is not well understood how arousal is displayed in or interpreted from facial expressions. In the context of socioemotional disorders such as Autism Spectrum Disorder, this poses the question of a differential use of facial information for arousal perception. In this study, we demonstrate how automated face-tracking tools can be used to extract predictors of arousal judgments. We find moderate to strong correlations among all measures of static information on one hand and all measures of dynamic information on the other. Based on these results, we tested two measures, average distance to the neutral face and average facial movement speed, within and between neurotypical individuals (N = 401) and individuals with autism (N = 19). Distance to the neutral face was predictive of arousal in both groups. Lower mean arousal ratings were found for the autistic group, but no difference in correlation of the measures and arousal ratings could be found between groups. Results were replicated in an high autistic traits group. The findings suggest a qualitatively similar perception of arousal for individuals with and without autism. No correlations between valence ratings and any of the measures could be found, emphasizing the specificity of our tested measures. Distance and speed predictors share variability and thus speed should not be discarded as a predictor of arousal ratings.
User Experience (UX) describes the holistic experience of a user before, during, and after interaction with a platform, product, or service. UX adds value and attraction to their sole functionality and is therefore highly relevant for firms. The increased interest in UX has produced a vast amount of scholarly research since 1983. The research field is, therefore, complex and scattered. Conducting a bibliometric analysis, we aim at structuring the field quantitatively and rather abstractly. We employed citation analyses, co-citation analyses, and content analyses to evaluate productivity and impact of extant research. We suggest that future research should focus more on business and management related topics.
Die Setzung strategischer Ziele sowie die Zuordnung und Umsetzung dazugehörender Maßnahmen sind ein wesentliches Element, um die Innovationsfähigkeit von Organisationen zu erhalten. In den vergangenen Jahren ist auch an Hochschulen die Strategiebildung deutlich vorangetrieben worden. Dies betrifft verschiedene Handlungsfelder, und es werden verschiedene Ansätze verfolgt. Der vorliegende Beitrag greift am Beispiel der Universität Potsdam drei in den vergangenen Jahren adressierte Strategiebereiche heraus: IT, E-Learning und Forschungsdaten. Die damit verbundenen Prozesse waren in unterschiedlichem Maß von Partizipation geprägt. Die gesammelten Erfahrungen werden reflektiert, und es werden Empfehlungen für Strategieentwicklungsprozesse abgeleitet.
Supervised machine learning to assess methane emissions of a dairy building with natural ventilation
(2020)
A reliable quantification of greenhouse gas emissions is a basis for the development of adequate mitigation measures. Protocols for emission measurements and data analysis approaches to extrapolate to accurate annual emission values are a substantial prerequisite in this context. We systematically analyzed the benefit of supervised machine learning methods to project methane emissions from a naturally ventilated cattle building with a concrete solid floor and manure scraper located in Northern Germany. We took into account approximately 40 weeks of hourly emission measurements and compared model predictions using eight regression approaches, 27 different sampling scenarios and four measures of model accuracy. Data normalization was applied based on median and quartile range. A correlation analysis was performed to evaluate the influence of individual features. This indicated only a very weak linear relation between the methane emission and features that are typically used to predict methane emission values of naturally ventilated barns. It further highlighted the added value of including day-time and squared ambient temperature as features. The error of the predicted emission values was in general below 10%. The results from Gaussian processes, ordinary multilinear regression and neural networks were least robust. More robust results were obtained with multilinear regression with regularization, support vector machines and particularly the ensemble methods gradient boosting and random forest. The latter had the added value to be rather insensitive against the normalization procedure. In the case of multilinear regression, also the removal of not significantly linearly related variables (i.e., keeping only the day-time component) led to robust modeling results. We concluded that measurement protocols with 7 days and six measurement periods can be considered sufficient to model methane emissions from the dairy barn with solid floor with manure scraper, particularly when periods are distributed over the year with a preference for transition periods. Features should be normalized according to median and quartile range and must be carefully selected depending on the modeling approach.
E-Assessment etablieren
(2020)
Elektronische Lernstandserhebungen, sogenannte E-Assessments, bieten für Lehrende und Studierende viele Vorteile z. B. hinsichtlich schneller Rückmeldungen oder kompetenzorientierter Fragenformate, und ermöglichen es, unabhängig von Ort und Zeit Prüfungen zu absolvieren. In diesem Beitrag werden die Einführung von summativen Lernstandserhebungen, sogenannter E-Klausuren, am Beispiel der Universität Potsdam, der Aufbau einer länderübergreifenden Initiative für E-Assessment sowie technische Möglichkeiten für dezentrale elektronische Klausuren vorgestellt. Dabei werden der aktuelle Stand, die Ziele und die gewählte stufenweise Umsetzungsstrategie der Universität Potsdam skizziert. Darauf aufbauend folgt eine Beschreibung des Vorgehens, der Kooperationsmöglichkeiten für den Wissens- und Erfahrungsaustausch sowie Herausforderungen der E-Assessment- Initiative. Abschließend werden verschiedene E-Klausurformen und technische Möglichkeiten zur Umsetzung komplexer Prüfungsumgebungen klassifiziert sowie mit ihren charakteristischen Vor- und Nachteilen diskutiert und eine integrierte Lösung vorgeschlagen.
Das größte der fächerübergreifenden Projekte im Potsdamer Projekt Qualitätspakt Lehre hatte die flächendeckende Etablierung von digitalen Medien als einen integralen Bestandteil von Lehre und Studium zum Gegenstand. Im Teilprojekt E-Learning in Studienbereichen (eLiS) wurden dafür Maßnahmen in den Feldern Organisations-, technische und Inhaltsentwicklung zusammengeführt. Der vorliegende Beitrag präsentiert auf Basis von Ausgangslage und Zielsetzungen die Ergebnisse rund um die Digitalisierung von Lehre und Studium an der Universität Potsdam. Exemplarisch werden fünf Dienste näher vorgestellt, die inzwischen größtenteils in den Regelbetrieb der Hochschule übergegangen sind: die Videoplattform Media.UP, die mobile App Reflect.UP, die persönliche Lernumgebung Campus. UP, das Self-Service-Portal Cook.UP und das Anzeigesystem Freiraum.UP. Dabei wird jeweils ein technischer Blick „unter die Haube“ verbunden mit einer Erläuterung der Nutzungsmöglichkeiten, denen eine aktuelle Einschätzung von Lehrenden und Studierenden der Hochschule gegenübergestellt wird. Der Beitrag schließt mit einer Einbettung der vorgestellten Entwicklungen in einen größeren Kontext und einem Ausblick auf die weiterhin anstehenden Aufgaben.
Full error detection and correction method applied on pipelined structure using two approaches
(2020)
In this paper, two approaches are evaluated using the Full Error Detection and Correction (FEDC) method for a pipelined structure. The approaches are referred to as Full Duplication with Comparison (FDC) and Concurrent Checking with Parity Prediction (CCPP). Aforementioned approaches are focused on the borderline cases of FEDC method which implement Error Detection Circuit (EDC) in two manners for the purpose of protection of combinational logic to address the soft errors of unspecified duration. The FDC approach implements a full duplication of the combinational circuit, as the most complex and expensive implementation of the FEDC method, and the CCPP approach implements only the parity prediction bit, being the simplest and cheapest technique, for soft error detection. Both approaches are capable of detecting soft errors in the combinational logic, with single faults being injected into the design. On the one hand, the FDC approach managed to detect and correct all injected faults while the CCPP approach could not detect multiple faults created at the output of combinational circuit. On the other hand, the FDC approach leads to higher power consumption and area increase compared to the CCPP approach.
A triple modular redundancy (TMR) based design technique for double cell upsets (DCUs) mitigation is investigated in this paper. This technique adds three extra self-voter circuits into a traditional TMR structure to enable the enhanced error correction capability. Fault-injection simulations show that the soft error rate (SER) of the proposed technique is lower than 3% of that of TMR. The implementation of this proposed technique is compatible with the automatic digital design flow, and its applicability and performance are evaluated on an FIFO circuit.
We elaborate upon the theoretical foundations of a metric temporal extension of Answer Set Programming. In analogy to previous extensions of ASP with constructs from Linear Temporal and Dynamic Logic, we accomplish this in the setting of the logic of Here-and-There and its non-monotonic extension, called Equilibrium Logic. More precisely, we develop our logic on the same semantic underpinnings as its predecessors and thus use a simple time domain of bounded time steps. This allows us to compare all variants in a uniform framework and ultimately combine them in a common implementation.
Eclingo
(2020)
We describe eclingo, a solver for epistemic logic programs under Gelfond 1991 semantics built upon the Answer Set Programming system clingo. The input language of eclingo uses the syntax extension capabilities of clingo to define subjective literals that, as usual in epistemic logic programs, allow for checking the truth of a regular literal in all or in some of the answer sets of a program. The eclingo solving process follows a guess and check strategy. It first generates potential truth values for subjective literals and, in a second step, it checks the obtained result with respect to the cautious and brave consequences of the program. This process is implemented using the multi-shot functionalities of clingo. We have also implemented some optimisations, aiming at reducing the search space and, therefore, increasing eclingo 's efficiency in some scenarios. Finally, we compare the efficiency of eclingo with two state-of-the-art solvers for epistemic logic programs on a pair of benchmark scenarios and show that eclingo generally outperforms their obtained results.
This paper continues the line of research aimed at investigating the relationship between logic programs and first-order theories. We extend the definition of program completion to programs with input and output in a subset of the input language of the ASP grounder gringo, study the relationship between stable models and completion in this context, and describe preliminary experiments with the use of two software tools, anthem and vampire, for verifying the correctness of programs with input and output. Proofs of theorems are based on a lemma that relates the semantics of programs studied in this paper to stable models of first-order formulas.
In this paper, an asynchronous design for soft error detection and correction in combinational and sequential circuits is presented. The proposed architecture is called Asynchronous Full Error Detection and Correction (AFEDC). A custom design flow with integrated commercial EDA tools generates the AFEDC using the asynchronous bundled-data design style. The AFEDC relies on an Error Detection Circuit (EDC) for protecting the combinational logic and fault-tolerant latches for protecting the sequential logic. The EDC can be implemented using different detection methods. For this work, two boundary variants are considered, the Full Duplication with Comparison (FDC) and the Partial Duplication with Parity Prediction (PDPP). The AFEDC architecture can handle single events and timing faults of arbitrarily long duration as well as the synchronous FEDC, but additionally can address known metastability issues of the FEDC and other similar synchronous architectures and provide a more practical solution for handling the error recovery process. Two case studies are developed, a carry look-ahead adder and a pipelined non-restoring array divider. Results show that the AFEDC provides equivalent fault coverage when compared to the FEDC while reducing area, ranging from 9.6% to 17.6%, and increasing energy efficiency, which can be up to 6.5%.
Detection of malware-infected computers and detection of malicious web domains based on their encrypted HTTPS traffic are challenging problems, because only addresses, timestamps, and data volumes are observable. The detection problems are coupled, because infected clients tend to interact with malicious domains. Traffic data can be collected at a large scale, and antivirus tools can be used to identify infected clients in retrospect. Domains, by contrast, have to be labeled individually after forensic analysis. We explore transfer learning based on sluice networks; this allows the detection models to bootstrap each other. In a large-scale experimental study, we find that the model outperforms known reference models and detects previously unknown malware, previously unknown malware families, and previously unknown malicious domains.
The Surface Water and Ocean Topography (SWOT) mission is a next generation satellite mission expected to provide a 2 km-resolution observation of the sea surface height (SSH) on a two-dimensional swath. Processing SWOT data will be challenging because of the large amount of data, the mismatch between a high spatial resolution and a low temporal resolution, and the observation errors. The present paper focuses on the reduction of the spatially structured errors of SWOT SSH data. It investigates a new error reduction method and assesses its performance in an observing system simulation experiment. The proposed error-reduction method first projects the SWOT SSH onto a subspace spanned by the SWOT spatially structured errors. This projection is removed from the SWOT SSH to obtain a detrended SSH. The detrended SSH is then processed within an ensemble data assimilation analysis to retrieve a full SSH field. In the latter step, the detrending is applied to both the SWOT data and an ensemble of model-simulated SSH fields. Numerical experiments are performed with synthetic SWOT observations and an ensemble from a North Atlantic, 1/60 degrees simulation of the ocean circulation (NATL60). The data assimilation analysis is carried out with an ensemble Kalman filter. The results are assessed with root mean square errors, power spectrum density, and spatial coherence. They show that a significant part of the large scale SWOT errors is reduced. The filter analysis also reduces the small scale errors and allows for an accurate recovery of the energy of the signal down to 25 km scales. In addition, using the SWOT nadir data to adjust the SSH detrending further reduces the errors.
Multi-sided platforms (MSP) strongly affect markets and play a crucial part within the digital and networked economy. Although empirical evidence indicates their occurrence in many industries, research has not investigated the game-changing impact of MSP on traditional markets to a sufficient extent. More specifically, we have little knowledge of how MSP affect value creation and customer interaction in entire markets, exploiting the potential of digital technologies to offer new value propositions. Our paper addresses this research gap and provides an initial systematic approach to analyze the impact of MSP on the insurance industry. For this purpose, we analyze the state of the art in research and practice in order to develop a reference model of the value network for the insurance industry. On this basis, we conduct a case-study analysis to discover and analyze roles which are occupied or even newly created by MSP. As a final step, we categorize MSP with regard to their relation to traditional insurance companies, resulting in a classification scheme with four MSP standard types: Competition, Coordination, Cooperation, Collaboration.
In recent years, named entity linking (NEL) tools were primarily developed in terms of a general approach, whereas today numerous tools are focusing on specific domains such as e.g. the mapping of persons and organizations only, or the annotation of locations or events in microposts. However, the available benchmark datasets necessary for the evaluation of NEL tools do not reflect this focalizing trend. We have analyzed the evaluation process applied in the NEL benchmarking framework GERBIL [in: Proceedings of the 24th International Conference on World Wide Web (WWW’15), International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 2015, pp. 1133–1143, Semantic Web 9(5) (2018), 605–625] and all its benchmark datasets. Based on these insights we have extended the GERBIL framework to enable a more fine grained evaluation and in depth analysis of the available benchmark datasets with respect to different emphases. This paper presents the implementation of an adaptive filter for arbitrary entities and customized benchmark creation as well as the automated determination of typical NEL benchmark dataset properties, such as the extent of content-related ambiguity and diversity. These properties are integrated on different levels, which also enables to tailor customized new datasets out of the existing ones by remixing documents based on desired emphases. Besides a new system library to enrich provided NIF [in: International Semantic Web Conference (ISWC’13), Lecture Notes in Computer Science, Vol. 8219, Springer, Berlin, Heidelberg, 2013, pp. 98–113] datasets with statistical information, best practices for dataset remixing are presented, and an in depth analysis of the performance of entity linking systems on special focus datasets is presented.
PLATON
(2019)
Lesson planning is both an important and demanding task—especially as part of teacher training. This paper presents the requirements for a lesson planning system and evaluates existing systems regarding these requirements. One major drawback of existing software tools is that most are limited to a text- or form-based representation of the lesson designs. In this article, a new approach with a graphical, time-based representation with (automatic) analyses methods is proposed and the system architecture and domain model are described in detail. The approach is implemented in an interactive, web-based prototype called PLATON, which additionally supports the management of lessons in units as well as the modelling of teacher and student-generated resources. The prototype was evaluated in a study with 61 prospective teachers (bachelor’s and master’s preservice teachers as well as teacher trainees in post-university teacher training) in Berlin, Germany, with a focus on usability. The results show that this approach proofed usable for lesson planning and offers positive effects for the perception of time and self-reflection.
Answer Set Programming (ASP) has become a popular and widespread paradigm for practical Knowledge Representation thanks to its expressiveness and the available enhancements of its input language. One of such enhancements is the use of aggregates, for which different semantic proposals have been made. In this paper, we show that any ASP aggregate interpreted under Gelfond and Zhang's (GZ) semantics can be replaced (under strong equivalence) by a propositional formula. Restricted to the original GZ syntax, the resulting formula is reducible to a disjunction of conjunctions of literals but the formulation is still applicable even when the syntax is extended to allow for arbitrary formulas (including nested aggregates) in the condition. Once GZ-aggregates are represented as formulas, we establish a formal comparison (in terms of the logic of Here-and-There) to Ferraris' (F) aggregates, which are defined by a different formula translation involving nested implications. In particular, we prove that if we replace an F-aggregate by a GZ-aggregate in a rule head, we do not lose answer sets (although more can be gained). This extends the previously known result that the opposite happens in rule bodies, i.e., replacing a GZ-aggregate by an F-aggregate in the body may yield more answer sets. Finally, we characterize a class of aggregates for which GZ- and F-semantics coincide.
In this work we tackle the problem of checking strong equivalence of logic programs that may contain local auxiliary atoms, to be removed from their stable models and to be forbidden in any external context. We call this property projective strong equivalence (PSE). It has been recently proved that not any logic program containing auxiliary atoms can be reformulated, under PSE, as another logic program or formula without them – this is known as strongly persistent forgetting. In this paper, we introduce a conservative extension of Equilibrium Logic and its monotonic basis, the logic of Here-and-There, in which we deal with a new connective ‘|’ we call fork. We provide a semantic characterisation of PSE for forks and use it to show that, in this extension, it is always possible to forget auxiliary atoms under strong persistence. We further define when the obtained fork is representable as a regular formula.
plasp 3
(2019)
We describe the new version of the Planning Domain Definition Language (PDDL)-to-Answer Set Programming (ASP) translator plasp. First, it widens the range of accepted PDDL features. Second, it contains novel planning encodings, some inspired by Satisfiability Testing (SAT) planning and others exploiting ASP features such as well-foundedness. All of them are designed for handling multivalued fluents in order to capture both PDDL as well as SAS planning formats. Third, enabled by multishot ASP solving, it offers advanced planning algorithms also borrowed from SAT planning. As a result, plasp provides us with an ASP-based framework for studying a variety of planning techniques in a uniform setting. Finally, we demonstrate in an empirical analysis that these techniques have a significant impact on the performance of ASP planning.
Metabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an answer set programming (ASP)-based approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system dingo for solving the resulting logic program with linear constraints over reals. We empirically evaluate our approach by means of the metabolic network of Escherichia coli. Our analysis shows that our novel approach yields greatly superior results than obtainable from purely qualitative or quantitative approaches.
Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during the execution of a process. These event data can be used to analyze the process using process mining techniques to discover the real process, measure conformance to a given process model, or to enhance existing models with performance information. Mapping the produced events to activities of a given process model is essential for conformance checking, annotation and understanding of process mining results. In order to accomplish this mapping with low manual effort, we developed a semi-automatic approach that maps events to activities using insights from behavioral analysis and label analysis. The approach extracts Declare constraints from both the log and the model to build matching constraints to efficiently reduce the number of possible mappings. These mappings are further reduced using techniques from natural language processing, which allow for a matching based on labels and external knowledge sources. The evaluation with synthetic and real-life data demonstrates the effectiveness of the approach and its robustness toward non-conforming execution logs.
In computer science, computer systems are both, objects of investigation and tools that enable creative learning and design. Tools for learning have a long tradition in computer science education. Already in the late 1960s, Papert developed a concept which had an immense impact on the development of informal education in the following years: his theory of constructionism understands learning as a creative process of knowledge construction that is most effective when learners create something purposeful that they can try out, show around, discuss, analyse and receive praise for. By now, there are numerous learning and programming environments that are based on the constructionist ideas. Modern tools offer opportunities for students to learn in motivating ways and gain impressive results in programming games, animations, implementing 3D models or developing interactive objects. This article gives an overview of computer science education research related to tools and media to be used in educational settings. We analyse different types of tools with a special focus on the categorization and development of tools for student adequate physical computing activities in the classroom. Research around the development and evaluation of tools and learning resources in the domain of physical computing is illustrated with the example of "My Interactive Garden", a constructionist learning and programming environment. It is explained how the results from empirical studies are integrated in the continuous development of the learning material.
Novel two-dimensional tactile displays enable blind users to not only get access to the textual but also to the graphical content of a graphical user interface. Due to the higher amount of information that can be presented in parallel, orientation and exploration can be more complex. In this paper we present the HyperBraille system, which consists of a pin-matrix device as well as a graphical screen reader providing the user with appropriate presentation and interaction possibilities. To allow for a detailed analysis of bimanual interaction strategies on a pin-matrix device, we conducted two user studies with a total of 12 blind people. The task was to fill in .pdf forms on the pin-matrix device by using different input methods, namely gestures, built-in hardware buttons as well as a conventional PC keyboard. The forms were presented in a semigraphic view type that not only contains Braille but also tactile widgets in a spatial arrangement. While completion time and error rate partly depended on the chosen input method, the usage of special reading strategies seemed to be independent of it. A direct comparison of the system and a conventional assistive technology (screen reader with single-line Braille device) showed that interaction on the pin-matrix device can be very efficient if the user is trained. The two-dimensional output can improve access to .pdf forms with insufficient accessibility as the mapping of input controls and the corresponding labels can be supported by a spatial presentation.
Parsing of argumentative structures has become a very active line of research in recent years. Like discourse parsing or any other natural language task that requires prediction of linguistic structures, most approaches choose to learn a local model and then perform global decoding over the local probability distributions, often imposing constraints that are specific to the task at hand. Specifically for argumentation parsing, two decoding approaches have been recently proposed: Minimum Spanning Trees (MST) and Integer Linear Programming (ILP), following similar trends in discourse parsing. In contrast to discourse parsing though, where trees are not always used as underlying annotation schemes, argumentation structures so far have always been represented with trees. Using the ‘argumentative microtext corpus’ [in: Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon 2015 / Vol. 2, College Publications, London, 2016, pp. 801–815] as underlying data and replicating three different decoding mechanisms, in this paper we propose a novel ILP decoder and an extension to our earlier MST work, and then thoroughly compare the approaches. The result is that our new decoder outperforms related work in important respects, and that in general, ILP and MST yield very similar performance.
We introduce a type and effect system, for an imperative object calculus, which infers sharing possibly introduced by the evaluation of an expression, represented as an equivalence relation among its free variables. This direct representation of sharing effects at the syntactic level allows us to express in a natural way, and to generalize, widely-used notions in literature, notably uniqueness and borrowing. Moreover, the calculus is pure in the sense that reduction is defined on language terms only, since they directly encode store. The advantage of this non-standard execution model with respect to a behaviorally equivalent standard model using a global auxiliary structure is that reachability relations among references are partly encoded by scoping. (C) 2018 Elsevier B.V. All rights reserved.
In this paper, we consider the computational power of a new variant of networks of splicing processors in which each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined (negative, neutral, positive), the polarization of data is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that networks of polarized splicing processors (NPSP) of size 2 are computationally complete, which immediately settles the question of designing computationally complete NPSPs of minimal size. With two more nodes we can simulate every nondeterministic Turing machine without increasing the time complexity. Particularly, we prove that NPSP of size 4 can accept all languages in NP in polynomial time. Furthermore, another computational model that is universal, namely the 2-tag system, can be simulated by NPSP of size 3 preserving the time complexity. All these results can be obtained with NPSPs with valuations in the set as well. We finally show that Turing machines can simulate a variant of NPSPs and discuss the time complexity of this simulation.
Digitale Medien enthalten bislang vor allem Inhalte in verschiedenen Darstellungsformen. Dies allein erzeugt jedoch nur einen geringen Mehrwert zu klassischen Lernressourcen, da die Kriterien der Interaktivität und Adaptivität nicht mit einbezogen werden. Dies scheitert jedoch oft an dem damit verbundenen Erstellungsaufwand. Der folgende Beitrag zeigt, wie durch die automatische Erzeugung von Aufgaben ein hochwertiger Wissenserwerb mit digitalen Medien ermöglicht wird. Ferner werden Vor- und Nachteile der automatischen Erstellung von Aufgaben erörtert.
Die Veröffentlichung eines global frei verfügbaren Onlinekurses abseits der großen MOOC Plattformen bringt spezielle Herausforderungen mit sich. Neben technischen Herausforderungen sind eine effiziente Wissensvermittlung und die Erhaltung der Lernmotivation zentral. Der folgende Beitrag stellt Techniken zur Steigerung der Lerneffizienz und -motivation anhand des ARCS Modells vor. Er zeigt auf, wie die verschiedenen Techniken in der Entwicklung des Onlinekurses „Designing Sustainable Food Systems“ umgesetzt wurden und inwieweit sie erfolgreich waren.
Das Training sozioemotionaler Kompetenzen ist gerade für Menschen mit Autismus nützlich. Ein solches Training kann mithilfe einer spielbasierten Anwendung effektiv gestaltet werden. Zwei Minispiele, Mimikry und Emo-Mahjong, wurden realisiert und hinsichtlich User Experience evaluiert. Die jeweiligen Konzepte und die Evaluationsergebnisse sollen hier vorgestellt werden.
Einsatz einer mobilen Lern-App - Ein Werkzeug zur Verbesserung von klinisch-praktischem Unterricht
(2018)
Der Unterricht am Krankenbett ist im Medizinstudium eine wertvolle Möglichkeit klinisch-praktische Fertigkeiten zu erlernen. Eine optimale Vorbereitung der Studierenden ist dabei Voraussetzung. Eine mobile Lern-App wurde entwickelt, die den Studierenden, neben Lernzielen, Kursinhalte und Anleitungen zu Untersuchungstechniken bietet, um die Vorbereitung auf einen klinisch-praktischen Kurs zu fördern und Kurzinformationen auch während des Kurses zur Verfügung zu stellen. 175 Studierende hatten die Möglichkeit die App parallel zu einem klinischen Untersuchungs-Kurs im Semester zu nutzen. Im Anschluss beantworteten die Studierenden einen Fragebogen zur Nützlichkeit und Vielseitigkeit der App und zur Zufriedenheit mit der App unter Verwendung eine 5-Punkt-Likert-Skala und zwei offenen Fragen. In diesem Beitrag wird das Kurskonzept zusammen mit der Lern-App, die Ergebnisse aus dem Fragebogen und unsere Schlussfolgerungen daraus vorgestellt. Studierende bewerteten die App grundsätzlich als hilfreich. Sie sollte dabei gründlich eingeführt werden. Patienten sollten über die Nutzung von Smartphones im Studentenunterricht zu Lernzwecken informiert werden.
Der vorliegende Beitrag berichtet auf der Grundlage von Erfahrungen mit dem Audience Response System (ARS) „Auditorium Mobile Classroom Service“ von Erfolgsfaktoren für den Einsatz in der universitären Lehre. Dabei werden sowohl die technischen Rahmenbedingungen und Herausforderungen der Anwendungen berücksichtigt, als auch die unterschiedlichen didaktischen Konzepte und Ziele der beteiligten Akteure (Studierende, Lehrende und Institution). Ziel ist es, Einflussfaktoren für den erfolgreichen Einsatz sowohl für die Praxis als auch die wissenschaftliche Untersuchung und Weiterentwicklung der Systeme zu benennen und ein heuristisches Framework für Chancen und Herausforderungen beim Einsatz von ARS anzubieten.
Der Beitrag skizziert ein Modell, das die Entwicklung digitaler Kompetenzen im Lehramtsstudium fördern soll. Zwar wird das Kompetenzmodell aus der Deutschdidaktik heraus entwickelt, nimmt aber auch fachübergreifende Anforderungen in den Bereichen Informationskompetenz, medientechnischer Kompetenzen, Fähigkeiten der Medienanalyse und -reflexion sowie Sprachhandlungskompetenz in den Blick. Damit wird das Ziel verfolgt, die besonderen Anforderungen angehender Lehrkräfte als Mediator*innen digitaler Kompetenzen darzustellen. Das beschriebene Modell dieser Vermittlungskompetenz dient der Verankerung digitaler Lehr-Lernkonzepte als wesentlicher Bestandteil der modernen Lehrer*innenbildung.
Ob Online-Kurse, videobasierte Lehrangebote, mobile Applikationen, eigenentwickelte oder kommerzielle Web 2.0-Anwendungen, die Fülle digitaler Unterstützungsangebote ist kaum zu überblicken. Dabei bieten mobile Endgeräte, Web-Anwendungen und Apps Chancen Lehre, Studium und Forschung maßgeblich neu zu gestalten. Im Beitrag wird ein Beschreibungsrahmen für die mediendidaktische Ausgestaltung von Lehr-, Lern- und Forschungsarrangements vorgestellt, der die technischen Gesichtspunkte hervorhebt. Anschließend werden unterschiedliche Nutzungsszenarien unter Einbeziehung digitaler Medien skizziert. Diese werden als Ausgangspunkt genommen um das Konzept einer Systemarchitektur vorzustellen, die es zum einen ermöglicht beliebige Applikationen automatisiert bereit zu stellen und zum anderen die anfallenden Nutzendendaten plattformübergreifend zu aggregieren und für eine Ausgestaltung virtueller Lehr- und Lernräumen zu nutzen.
Berufsbegleitende Studiengänge stehen vor besonderen Schwierigkeiten, für die der Einsatz von Blended Learning-Szenarien sinnvoll sein kann. Welche speziellen Herausforderungen sich dabei ergeben und welche Lösungsansätze dagegen steuern, betrachtet der folgende Artikel anhand eines Praxisberichts aus dem Studiengang M. P. A. Wissenschaftsmanagement an der Universität Speyer.
The soft error rate (SER) due to heavy-ion irradiation of a clock tree is investigated in this paper. A method for clock tree SER prediction is developed, which employs a dedicated soft error analysis tool to characterize the single-event transient (SET) sensitivities of clock inverters and other commercial tools to calculate the SER through fault-injection simulations. A test circuit including a flip-flop chain and clock tree in a 65 nm CMOS technology is developed through the automatic ASIC design flow. This circuit is analyzed with the developed method to calculate its clock tree SER. In addition, this circuit is implemented in a 65 nm test chip and irradiated by heavy ions to measure its SER resulting from the SETs in the clock tree. The experimental and calculation results of this case study present good correlation, which verifies the effectiveness of the developed method.
Answer Set Programming faces an increasing popularity for problem solving in various domains. While its modeling language allows us to express many complex problems in an easy way, its solving technology enables their effective resolution. In what follows, we detail some of the key factors of its success. Answer Set Programming [ASP; Brewka et al. Commun ACM 54(12):92–103, (2011)] is seeing a rapid proliferation in academia and industry due to its easy and flexible way to model and solve knowledge-intense combinatorial (optimization) problems. To this end, ASP offers a high-level modeling language paired with high-performance solving technology. As a result, ASP systems provide out-off-the-box, general-purpose search engines that allow for enumerating (optimal) solutions. They are represented as answer sets, each being a set of atoms representing a solution. The declarative approach of ASP allows a user to concentrate on a problem’s specification rather than the computational means to solve it. This makes ASP a prime candidate for rapid prototyping and an attractive tool for teaching key AI techniques since complex problems can be expressed in a succinct and elaboration tolerant way. This is eased by the tuning of ASP’s modeling language to knowledge representation and reasoning (KRR). The resulting impact is nicely reflected by a growing range of successful applications of ASP [Erdem et al. AI Mag 37(3):53–68, 2016; Falkner et al. Industrial applications of answer set programming. K++nstliche Intelligenz (2018)]
Automated storage and retrieval systems are principal components of modern production and warehouse facilities. In particular, automated guided vehicles nowadays substitute human-operated pallet trucks in transporting production materials between storage locations and assembly stations. While low-level control systems take care of navigating such driverless vehicles along programmed routes and avoid collisions even under unforeseen circumstances, in the common case of multiple vehicles sharing the same operation area, the problem remains how to set up routes such that a collection of transport tasks is accomplished most effectively. We address this prevalent problem in the context of car assembly at Mercedes-Benz Ludwigsfelde GmbH, a large-scale producer of commercial vehicles, where routes for automated guided vehicles used in the production process have traditionally been hand-coded by human engineers. Such adhoc methods may suffice as long as a running production process remains in place, while any change in the factory layout or production targets necessitates tedious manual reconfiguration, not to mention the missing portability between different production plants. Unlike this, we propose a declarative approach based on Answer Set Programming to optimize the routes taken by automated guided vehicles for accomplishing transport tasks. The advantages include a transparent and executable problem formalization, provable optimality of routes relative to objective criteria, as well as elaboration tolerance towards particular factory layouts and production targets. Moreover, we demonstrate that our approach is efficient enough to deal with the transport tasks evolving in realistic production processes at the car factory of Mercedes-Benz Ludwigsfelde GmbH.
teaspoon
(2018)
Answer Set Programming (ASP) is an approach to declarative problem solving, combining a rich yet simple modeling language with high performance solving capacities. We here develop an ASP-based approach to curriculum-based course timetabling (CB-CTT), one of the most widely studied course timetabling problems. The resulting teaspoon system reads a CB-CTT instance of a standard input format and converts it into a set of ASP facts. In turn, these facts are combined with a first-order encoding for CB-CTT solving, which can subsequently be solved by any off-the-shelf ASP systems. We establish the competitiveness of our approach by empirically contrasting it to the best known bounds obtained so far via dedicated implementations. Furthermore, we extend the teaspoon system to multi-objective course timetabling and consider minimal perturbation problems.
The Potsdam answer set solving collection, or Potassco for short, bundles various tools implementing and/or applying answer set programming. The article at hand succeeds an earlier description of the Potassco project published in Gebser et al. (AI Commun 24(2):107-124, 2011). Hence, we concentrate in what follows on the major features of the most recent, fifth generation of the ASP system clingo and highlight some recent resulting application systems.
The aim of our project design space exploration with answer set programming is to develop a general framework based on Answer Set Programming (ASP) that finds valid solutions to the system design problem and simultaneously performs Design Space Exploration (DSE) to find the most favorable alternatives. We leverage recent developments in ASP solving that allow for tight integration of background theories to create a holistic framework for effective DSE.
Recent philosophical analyses of the epistemic dimension of images in the sciences show a certain trend in acknowledging potential roles of these images beyond their merely decorative or pedagogical functions. We argue, however, that this new debate has yet paid little attention to a special type of pictures, we call ‘visual metaphor’, and its versatile heuristic potential in organizing data, supporting communication, and guiding research, modeling, and theory formation. Based on a case study of Conrad Hal Waddington’s epigenetic landscape images in biology, we develop a descriptive framework applicable to heuristic roles of various visual metaphors in the sciences.
Answer Set Programming (ASP) is a well-known paradigm of declarative programming with roots in logic programming and non-monotonic reasoning. Similar to other closely related problemsolving technologies, such as SAT/SMT, QBF, Planning and Scheduling, advancements in ASP solving are assessed in competition events. In this paper, we report about the design and results of the Sixth ASP Competition, which was jointly organized by the University of Calabria (Italy), Aalto University (Finland), and the University of Genoa (Italy), in affiliation with the 13th International Conference on Logic Programming and Non-Monotonic Reasoning. This edition maintained some of the design decisions introduced in 2014, e.g., the conception of sub-tracks, the scoring scheme,and the adherence to a fixed modeling language in order to push the adoption of the ASP-Core-2 standard. On the other hand, it featured also some novelties, like a benchmark selection stage classifying instances according to their empirical hardness, and a “Marathon” track where the topperforming systems are given more time for solving hard benchmarks.
THIS INSTALLMENT OF Research for Practice provides curated reading guides to technology for underserved communities and to new developments in personal fabrication. First, Tawanna Dillahunt describes design considerations and technology for underserved and impoverished communities. Designing for the more than 1.6 billion impoverished individuals worldwide requires special consideration of community needs, constraints, and context. Her selections span protocols for poor-quality communication networks, community-driven content generation, and resource and public service discovery. Second, Stefanie Mueller and Patrick Baudisch provide an overview of recent advances in personal fabrication (for example, 3D printers).
Since 2004, increases in computational power described by Moore's law have substantially been realized in the form of additional cores rather than through faster clock speeds. To make effective use of modern hardware when solving hard computational problems, it is therefore necessary to employ parallel solution strategies. In this work, we demonstrate how effective parallel solvers for propositional satisfiability (SAT), one of the most widely studied NP-complete problems, can be produced automatically from any existing sequential, highly parametric SAT solver. Our Automatic Construction of Parallel Portfolios (ACPP) approach uses an automatic algorithm configuration procedure to identify a set of configurations that perform well when executed in parallel. Applied to two prominent SAT solvers, Lingeling and clasp, our ACPP procedure identified 8-core solvers that significantly outperformed their sequential counterparts on a diverse set of instances from the application and hard combinatorial category of the 2012 SAT Challenge. We further extended our ACPP approach to produce parallel portfolio solvers consisting of several different solvers by combining their configuration spaces. Applied to the component solvers of the 2012 SAT Challenge gold medal winning SAT Solver pfolioUZK, our ACPP procedures produced a significantly better-performing parallel SAT solver.
Dieser Beitrag diskutiert die Konzeption eines Software-Projektpraktikums im Bereich E-Learning, welches Lehramts- und Fachstudierenden der Informatik ermöglicht, voneinander zu profitieren und praxisrelevante Ergebnisse generiert. Vorbereitungen, Organisation und Durchführung werden vorgestellt und diskutiert. Den Abschluss bildet ein Ausblick auf die Fortführung des Konzepts und den Ausbau des Forschungsgebietes.
Das „Startprojekt“
(2016)
Absolventinnen und Absolventen unserer Informatik-Bachelorstudiengänge benötigen für kompetentes berufliches Handeln sowohl fachliche als auch überfachliche Kompetenzen. Vielfach verlangen wir von Erstsemestern in Grundlagen-Lehrveranstaltungen fast ausschließlich den Aufbau von Fachkompetenz und vernachlässigen dabei häufig Selbstkompetenz, Methodenkompetenz und Sozialkompetenz. Gerade die drei letztgenannten sind für ein erfolgreiches Studium unabdingbar und sollten von Anfang an entwickelt werden. Wir stellen unser „Startprojekt“ als einen Beitrag vor, im ersten Semester die eigenverantwortliche, überfachliche Kompetenzentwicklung in einem fachlichen Kontext zu fördern.
Aus einer Vergleichsstudie mit starken und schwachen Problemlösern konnten Erkenntnisse über die effizienten Herangehensweisen von Hochleistern an Informatikprobleme gewonnen werden. Diese Erkenntnisse wurden in einem Lehrvideo zum informatischen Problemlösen didaktisch aufgearbeitet, sodass Lernenden der Einsatz von Baumstrukturen und Rekursion im konkreten Kontext gezeigt werden kann. Nun wurde die tatsächliche Lernwirksamkeit des Videos sowie die Definition der Zielgruppe in einer Vergleichsstudie mit 66 Studienanfängern überprüft.
Der Unterricht großer Studierendengruppen im wissenschaftlichen Schreiben birgt vielfältige organisatorische Herausforderungen und eine zeitintensive Betreuung durch die Dozenten. Diese Arbeit stellt ein Lehrkonzept mit Peer-Reviews vor, in dem das Feedback der Peers durch eine automatisierte Analyse ergänzt wird. Die Software Confopy liefert metrik- und strukturbasierte Hinweise für die Verbesserung des wissenschaftlichen Schreibstils. Der Nutzen von Confopy wird an 47 studentischen Arbeiten in Draft- und Final-Version illustriert.
Informatik-Studierende haben in der Mehrzahl Schwierigkeiten, einen Einstieg in die Theoretische
Informatik zu finden und die Leistungsanforderungen in den
Endklausuren der zugehörigen Lehrveranstaltungen zu erfüllen. Wir argumentieren, dass dieser Symptomatik mangelnde Kompetenzen im Umgang mit abstrakten und stark formalisierten Themeninhalten zugrunde liegen und schlagen vor, einen Beweisassistenten als interaktives Lernwerkzeug in der Eingangslehre der Theoretischen Informatik zu nutzen, um entsprechende Kompetenzen zu stärken.
Dieser Beitrag diskutiert den Einsatz von interaktiven und automatischen Theorembeweisern in der universitären Lehre. Moderne Theorembeweiser scheinen geeignet zur Implementierung des dialogischen Lernens und als E-Assessment-Werkzeug in der Logikausbilding. Exemplarisch skizzieren wir ein innovaties Lehrprojekt zum Thema „Komputationale Metaphysik“, in dem die zuvor genannten Werkzeuge eingesetzt werden.
Die Unterrichtsmethode Stationsarbeit kann verwendet werden, um Individualisierung und Differenzierung im Lernprozess zu ermöglichen. Dieser Beitrag schlägt Aufgabenformate vor, die in einer Stationsarbeit über das Klassendiagramm aus der Unified Modeling Language verwendet werden können. Die Aufgabenformate wurden bereits mit Studierenden erprobt.