Suchergebnisse - (dynamic OR dynamika) programming acm reference format~

Anchorage accurately assembles anchor-flanked synthetic long reads.

Autoren: Zang, Xiaofei Carl Li, Xiang Metcalfe, Kyle et al.

Quelle: Algorithms for Molecular Biology; 7/6/2025, Vol. 20 Issue 1, p1-16, 16p

Schlagwörter: DE Bruijn graph, DYNAMIC programming, ANCHORAGE

Proving expected sensitivity of probabilistic programs

Autoren: Barthe, Gilles Espitau, Thomas Grégoire, Benjamin et al.

Weitere Verfasser: Barthe, Gilles Espitau, Thomas Grégoire, Benjamin et al.

Quelle: Proceedings of the ACM on Programming Languages

Schlagwörter: FOS: Computer and information sciences, Computer Science - Logic in Computer Science, [INFO.INFO-PL]Computer Science [cs]/Programming Languages [cs.PL], Computer Science - Programming Languages, Additional Key Words and Phrases: Program sensitivity, Program analysis, 02 engineering and technology, 16. Peace & justice, CCS Concepts: • Theory of computation → Pre-and post-conditions, [INFO.INFO-PL] Computer Science [cs]/Programming Languages [cs.PL], Logic in Computer Science (cs.LO), Program verification, Kantorovich distance ACM Reference Format, 0202 electrical engineering, electronic engineering, information engineering, relational program logics, Programming Languages (cs.PL)

Dateibeschreibung: application/pdf

Zugangs-URL: http://dl.acm.org/ft_gateway.cfm?id=3158145&type=pdf
http://arxiv.org/abs/1708.02537
https://hal.science/hal-01959322v1/document
https://doi.org/10.1145/3158145
https://hal.science/hal-01959322v1
https://arxiv.org/pdf/1708.02537.pdf
https://ui.adsabs.harvard.edu/abs/2017arXiv170802537B/abstract
https://arxiv.org/abs/1708.02537
https://core.ac.uk/display/86419347
https://arxiv.org/abs/1708.02537
http://dblp.uni-trier.de/db/journals/pacmpl/pacmpl2.html#BartheEGHS18
https://dl.acm.org/doi/10.1145/3158145
https://hal.archives-ouvertes.fr/hal-01959322
https://dl.acm.org/doi/pdf/10.1145/3158145
https://dblp.uni-trier.de/db/journals/corr/corr1708.html#abs-1708-02537

Harnessing sequencing data for porcine reproductive and respiratory syndrome virus (PRRSV): tracking genetic evolution dynamics and emerging sequences in US swine industry.

Autoren: Chandra, Srijita Cezar, Guilherme Rupasinghe, Kinath et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-19. 19p.

Examining the Effects of Social Studies Instructional Material Format on Cognitive Load Among College Students.

Autoren: Javier, Mary C. Nistal, Conniebel C.

Quelle: Psychology & Education: A Multidisciplinary Journal; 2025, Vol. 46 Issue 6, p675-693, 19p

Natural language processing in veterinary pathology: A review.

Autoren: Stimmer, Lev Kuiper, Raoul V. Polledo, Laura et al.

Quelle: Veterinary Pathology. Nov2025, Vol. 62 Issue 6, p829-848. 20p.

Large-Scale Multiagent System Tracking Control Using Mean Field Games.

Autoren: Zhou, Zejian Xu, Hao

Quelle: IEEE Transactions on Neural Networks & Learning Systems; Oct2022, Vol. 33 Issue 10, p5602-5610, 9p

Schlagwörter: TRACKING control systems, MULTIAGENT systems, PROBABILITY density function, REINFORCEMENT learning, PDF (Computer file format), DYNAMIC programming

CrystalShift: A Versatile Command-Line Tool for Crystallographic Structural Data Analysis, Modification, and Format Conversion Prior to Solid-State DFT Calculations of Organic Crystals.

Autoren: Isupova, Ilona A. Rychkov, Denis A.

Quelle: Computation; Jun2025, Vol. 13 Issue 6, p138, 14p

Schlagwörter: PLASTIC crystals, C (Computer program language), CRYSTAL structure, MATERIALS science, CRYSTALLOGRAPHY, MOLECULAR crystals

Energy-Efficient Algorithms for . . .

Autoren: Susanne Albers HIROSHI FUJIWARA The Pennsylvania State University CiteSeerX Archives

Weitere Verfasser: Susanne Albers HIROSHI FUJIWARA The Pennsylvania State University CiteSeerX Archives

Quelle: http://www.cs.pitt.edu/~kirk/cs3150spring2010/a49-albers.pdf.

Schlagwörter: Categories and Subject Descriptors, F.2.2 [Analyis of Algorithms and Problem Complexity, Nonnumerical Algorithms and Problems—Sequencing and scheduling, G.2.1 [Discrete Mathematics, Combinatorics—Combinatorial algorithms General Terms, Algorithms, Theory Additional Key Words and Phrases, Variable-speed processor, flow time, online algorithms, competitive analysis, offline algorithms, dynamic programming ACM Reference Format

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.6036

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.6036
http://www.cs.pitt.edu/~kirk/cs3150spring2010/a49-albers.pdf

Author manuscript, published in 'DCE- 1st International Workshop on Dynamic compilation from SoC to Web Browser via HPC, in conjonction with HiPEAC 2012 (2012)' Does Dynamic and Speculative Parallelization Enable Advanced Parallelizing and Optimizing Code

Weitere Verfasser: The Pennsylvania State University CiteSeerX Archives

Quelle: http://hal.inria.fr/docs/00/66/43/39/PDF/paper.pdf.

Schlagwörter: Categories and Subject Descriptors, D.3.4 [Programming Languages, Processors General Terms, Performance Additional Key Words and Phrases, Speculative parallelization, dynamic system, polytope model, dynamic code transformations ACM Reference Format

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.220.4279; http://hal.inria.fr/docs/00/66/43/39/PDF/paper.pdf

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.220.4279
http://hal.inria.fr/docs/00/66/43/39/PDF/paper.pdf

Dynamic Model Evolution

Autoren: ATZMON HEN-TOV David H. Lorenz Lena Nikolaev et al.

Weitere Verfasser: ATZMON HEN-TOV David H. Lorenz Lena Nikolaev et al.

Quelle: http://www.hillside.net/plop/2010/papers/ACMVersions/papers/hen-tov.pdf.

Schlagwörter: Categories and Subject Descriptors, D.1.5 [Programming Techniques, Object-oriented Programming, D.2.2 [Design Tools and Techniques, Object-oriented design methods, D.2.11 [Software Architectures, Patterns—Adaptive Object Model General Terms, Design Additional Key Words and Phrases, Factory Objects, Adaptive Object Model (AOM, Creational Patterns, Lazy Loading, ModelTalk ACM Reference Format

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.434.9345

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.434.9345
http://www.hillside.net/plop/2010/papers/ACMVersions/papers/hen-tov.pdf

Smart Osteology: An AI-Powered Two-Stage System for Multi-Species Long Bone Detection and Classification Using YOLOv5 and CNN Architectures for Veterinary Anatomy Education and Forensic Applications.

Autoren: Orhan, İmdat¹ (AUTHOR)

Quelle: Veterinary Sciences. Aug2025, Vol. 12 Issue 8, p765. 19p.

Mobile Forensics – The File Format Handbook : Common File Formats and File Systems Used in Mobile Devices

Autoren: Christian Hummert Dirk Pawlaszczyk

Resource Type: eBook.

Schlagworte: Computer programs, Digital forensic science, Smartphones

Categories: COMPUTERS / Database Administration & Management, COMPUTERS / Security / General, COMPUTERS / Programming / Mobile Devices

AI-Driven Ambient Intelligence Systems for Mental Health Monitoring and Proactive Intervention.

Autoren: Roy, Piyal Ghosh, Shivnath Sarkar, Saptarshi Kumar et al.

Quelle: Cuestiones de Fisioterapia; 2025, Vol. 54 Issue 3, p2743-2752, 10p

Schlagwörter: MENTAL health services, AMBIENT intelligence, MACHINE dynamics, ARTIFICIAL intelligence, CRISIS management

AA Hybrid Dynamic Programming Approach to the Biobjective Binary Knapsack Problem

Weitere Verfasser: The Pennsylvania State University CiteSeerX Archives

Quelle: http://www-desir.lip6.fr/%7Espanjaard/articles/jea2013.pdf.

Schlagwörter: Categories and Subject Descriptors, F.2.2 [Nonnumerical Algorithms and Problems, Computations on discrete structures, G.2.1 [Combinatorics, Combinatorial algorithms, I.2.8 [Information Systems Applications, Dynamic programming General Terms, Algorithms, Performance Additional Key Words and Phrases, multiobjective optimization, biobjective binary knapsack problem ACM Reference Format

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.679.9571

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.679.9571
http://www-desir.lip6.fr/%7Espanjaard/articles/jea2013.pdf

On the potential of agentic workflows for animal training plan generation.

Autoren: Schultz, Jörg¹ (AUTHOR) Joerg.Schultz@Tier-Wohl-Team.de

Quelle: Frontiers in Veterinary Science. 2025, p1-16. 16p.

Predicting Weight Loss Success After Gastric Sleeve Surgery: A Machine Learning-Based Approach.

Autoren: Casas Domínguez, Mónica Herrena Montano, Isabel López Gómez, Juan José et al.

Quelle: Nutrients. Apr2025, Vol. 17 Issue 8, p1391. 13p.

HMM-guided removal of dye blinking effects from single-molecule FRET burst data.

Autoren: Kache, Tom Hendrix, Jelle

Quelle: BMC Methods; 8/7/2025, Vol. 2 Issue 1, p1-14, 14p

A Data-Driven Framework for Flood Mitigation: Transformer-Based Damage Prediction and Reinforcement Learning for Reservoir Operations.

Autoren: Tofighi, Soheyla Gurbuz, Faruk Mantilla, Ricardo et al.

Quelle: Water (20734441); Oct2025, Vol. 17 Issue 20, p3024, 37p

Schlagwörter: TRANSFORMER models, REINFORCEMENT learning, WATER storage, RISK assessment, HYDRAULIC models, EMPIRICAL research, FLOOD damage prevention

Geografische Kategorien: UNITED States

Hierarchical Dual-Model Detection Framework for Spotted Seals Using Deep Learning on UAVs.

Autoren: Liu, Jun Jin, Fengxiang Ji, Min et al.

Quelle: Animals (2076-2615); Nov2025, Vol. 15 Issue 21, p3100, 23p

Schlagwörter: DEEP learning, DRONE aircraft, IMAGE processing, MARINE mammals, ENVIRONMENTAL protection, ENDANGERED species, OBJECT recognition (Computer vision)

Super-resolution microscopy and deep learning methods: what can they bring to neuroscience: from neuron to 3D spine segmentation.

Autoren: Nazac, Paul Xu, Shengyan Breton, Victor et al.

Quelle: Frontiers in Neuroinformatics; 2025, p1-11, 11p

Schlagwörter: NEURON analysis, DEEP learning, FLUORESCENT probes, HIGH resolution imaging, DENDRITIC spines, NEURODEGENERATION, NEUROSCIENCES, SEGMENTATION (Biology)