Výsledky vyhledávání - acm: c.: computer system organizations/c.4: performance of system/c.4.3: modeling techniques

1. American Heart Association. (2021). Heart disease and stroke statistics—2021 update. Circulation, 143(8), e254-e743. 2. Rahman, M., Al Amin, M., Hasan, R., Hossain, S. T., Rahman, M. H., & Rashed, R. A. M. (2025). A Predictive AI Framework for Cardiovascular Disease Screening in the US: Integrating EHR Data with Machine and Deep Learning Models. British Journal of Nursing Studies, 5(2), 40-48. 3. ZakirHossain, M., Khan, M. M., Thapa, S., Uddin, R., Meem, E. J., Niloy, S. K., ... & Bhavani, G. D. (2025, February). Advanced Deep Learning Techniques for Precision Diagnosis of Tea Leaf Diseases. In 2025 IEEE International Conference on Emerging Technologies and Applications (MPSec ICETA) (pp. 1-6). IEEE. 4. Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining (pp. 785-794). ACM. 5. Damen, J. A., Hooft, L., Schuit, E., Debray, T. P., Collins, G. S., Tzoulaki, I., Lassale, C. M., Siontis, G. C., Chiocchia, V., Roberts, C., Schlüssel, M. M., Gerry, S., Black, J. A., Heus, P., van der Schouw, Y. T., Peelen, L. M., & Moons, K. G. (2016). Prediction models for cardiovascular disease risk in the general population: systematic review. BMJ, 353, i2416. 6. Framingham Heart Study. (1948). Framingham Heart Study cohort research data. National Heart, Lung, and Blood Institute. 7. Johnson, A. E., Pollard, T. J., Shen, L., Lehman, L. H., Feng, M., Ghassemi, M., Moody, B., Szolovits, P., Celi, L. A., & Mark, R. G. (2016). MIMIC-III, a freely accessible critical care database. Scientific Data, 3, 160035. 8. Krittanawong, C., Zhang, H., Wang, Z., Aydar, M., & Kitai, T. (2017). Artificial intelligence in precision cardiovascular medicine. Journal of the American College of Cardiology, 69(21), 2657-2664. 9. Lundberg, S. M., & Lee, S. I. (2017). A unified approach to interpreting model predictions. In Advances in Neural Information Processing Systems 30 (NIPS 2017) (pp. 4765-4774). 10. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., & Duchesnay, É. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12, 2825–2830. 11. Shameer, K., Johnson, K. W., Glicksberg, B. S., Dudley, J. T., & Sengupta, P. P. (2018). Machine learning in cardiovascular medicine: are we there yet? Heart, 104(14), 1156-1164. 12. Steyerberg, E. W., Vergouwe, Y., & van Calster, B. (2019). Towards better clinical prediction models: seven steps for development and an ABCD for validation. European Heart Journal, 40(15), 1255–1264. 13. Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., Liu, B., Matthews, P., Ong, G., Pell, J., Silman, A., Young, A., Sprosen, T., Peakman, T., & Collins, R. (2015). UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLOS Medicine, 12(3), e1001779. 14. Weng, S. F., Reps, J., Kai, J., Garibaldi, J. M., & Qureshi, N. (2017). Can machine-learning improve cardiovascular risk prediction using routine clinical data? PLOS ONE, 12(4), e0174944. 15. World Health Organization. (2021). Cardiovascular diseases (CVDs). Retrieved from https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds) 16. Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., Kudlur, M., Levenberg, J., Monga, R., Moore, S., Murray, D. G., Steiner, B., Tucker, P., Vasudevan, V., Warden, P., ... Zheng, X. (2016). TensorFlow: A system for large-scale machine learning. In 12th USENIX symposium on operating systems design and implementation (OSDI 16) (pp. 265–283). 17. Chollet, F. (2015). Keras (Version 2.4.0) [Computer software]. https://github.com/fchollet/keras

Autoři: Okunola, Abiodun

Analysis of an M/G/1 queue with repeated inhomogeneous vacations -- Application to IEEE 802.16e power saving

Autoři: Alouf, Sara Altman, Eitan Azad, Amar Prakash a další

Přispěvatelé: Alouf, Sara Altman, Eitan Azad, Amar Prakash a další

Zdroj: https://inria.hal.science/inria-00266552 ; [Research Report] RR-6488, INRIA. 2008, pp.31.

Témata: M/G/1 queue with repeated inhomogeneous vacations, power save mode, system response time, constrained optimization, numerical analysis, ACM: C.: Computer Systems Organization/C.4: PERFORMANCE OF SYSTEMS/C.4.3: Modeling techniques, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.8: Queueing theory, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.11: Renewal theory, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.15: Stochastic processes, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.6: Optimization, ACM: C.: Computer Systems Organization/C.2: COMPUTER-COMMUNICATION NETWORKS/C.2.5: Local and Wide-Area Networks, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]

Relation: https://inria.hal.science/hal-00641076v1; https://inria.hal.science/hal-00641082v1

Dostupnost: https://inria.hal.science/inria-00266552
https://inria.hal.science/inria-00266552v3/document
https://inria.hal.science/inria-00266552v3/file/RR-6488.pdf

A Mean Field Approach for Optimization in Particles Systems and Applications

Autoři: Gast, Nicolas Gaujal, Bruno Middleware efficiently scalable (MESCAL) a další

Přispěvatelé: Gast, Nicolas Gaujal, Bruno Middleware efficiently scalable (MESCAL) a další

Zdroj: https://inria.hal.science/inria-00368011 ; [Research Report] RR-6877, INRIA. 2009, pp.23.

Témata: Markov Decision Processes, Mean Field, Optimization, Particles System, Grid Broker, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.4: Markov processes, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.15: Stochastic processes, ACM: C.: Computer Systems Organization/C.4: PERFORMANCE OF SYSTEMS/C.4.3: Modeling techniques, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], [INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF], [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/0903.2352; ARXIV: 0903.2352

Dostupnost: https://inria.hal.science/inria-00368011
https://inria.hal.science/inria-00368011v3/document
https://inria.hal.science/inria-00368011v3/file/RR-6877.pdf

HinCTI: A Cyber Threat Intelligence Modeling and Identification System Based on Heterogeneous Information Network.

Autoři: Gao, Yali Li, Xiaoyong Peng, Hao a další

Zdroj: IEEE Transactions on Knowledge & Data Engineering; Feb2022, Vol. 34 Issue 2, p708-722, 15p

Témata: CYBER intelligence (Computer security), CYBERTERRORISM, INFORMATION networks, SYSTEM identification, SECURITIES analysts, CYBER physical systems

Recommendation system based on semantic scholar mining and topic modeling on conference publications.

Autoři: Jelodar, Hamed Wang, Yongli Xiao, Gang a další

Zdroj: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Mar2021, Vol. 25 Issue 5, p3675-3696, 22p

Témata: RECOMMENDER systems, ONLINE social networks, COMPUTER science conferences, WEB portals, GIBBS sampling

Theory of continuous polling systems applied to the Design of Message Ferry Routes in sensor networks

Autoři: Voleti, Veeraruna Kavitha Altman, Eitan Models for the performance analysis and the control of networks (MAESTRO) a další

Přispěvatelé: Voleti, Veeraruna Kavitha Altman, Eitan Models for the performance analysis and the control of networks (MAESTRO) a další

Zdroj: https://inria.hal.science/inria-00573799 ; 2011.

Témata: Continuous Polling systems, Virtual Workload, Pseudo Conservation Laws, Ferry, Wireless LAN, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.8: Queueing theory, ACM: C.: Computer Systems Organization/C.2: COMPUTER-COMMUNICATION NETWORKS/C.2.5: Local and Wide-Area Networks, ACM: C.: Computer Systems Organization/C.4: PERFORMANCE OF SYSTEMS/C.4.3: Modeling techniques, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]

Dostupnost: https://inria.hal.science/inria-00573799
https://inria.hal.science/inria-00573799v2/document
https://inria.hal.science/inria-00573799v2/file/HALFinANORRev2.pdf

The PowerPC Performance Modeling Methodology.

Autoři: Poursepanj, Ali

Zdroj: Communications of the ACM; Jun94, Vol. 37 Issue 6, p47-55, 9p

Témata: POWERPC microprocessors, ARCHITECTURE, MEMORY, COMPUTER storage devices, ELECTRONIC systems, MICROPROCESSORS

professional activities.

Zdroj: Communications of the ACM; Sep81, Vol. 24 Issue 9, p610-614, 5p

Témata: ASSOCIATIONS, institutions, etc., COMPUTERS, CONFERENCES & conventions, OFFICE practice automation, COMPUTER graphics, COMPUTER input-output equipment

Geografický termín: UNITED States

A Survey of Machine Learning for Computer Architecture and Systems.

Autoři: NAN WU YUAN XIE

Zdroj: ACM Computing Surveys; Apr2023, Vol. 55 Issue 3, p1-39, 39p

Témata: COMPUTER architecture, COMPUTER systems, MACHINE learning, SYSTEMS design, COMPILERS (Computer programs), SERVER farms (Computer network management), ARCHITECTURAL design

Process Modeling in Web Applications.

Autoři: Brambilla, Marco Ceri, Stefano Fraternali, Piero a další

Zdroj: ACM Transactions on Software Engineering & Methodology; Oct2006, Vol. 15 Issue 4, p360-409, 50p

Témata: WORLD Wide Web, ORGANIZATION, COMPUTER software, SOFTWARE engineering, MULTIMEDIA systems

ACM REFERENCE GUIDES.

Zdroj: Communications of the ACM; Jan1971, Vol. 14 Issue 1, p62-63, 2p

Témata: SPECIAL interest groups (Associations), DATA transmission systems, ELECTRONIC data processing, MEDICAL research, COMPUTER science, PROFESSIONAL associations

Korporace: ASSOCIATION for Computing Machinery

Enhancing Monitoring Performance: A Microservices Approach to Monitoring with Spyware Techniques and Prediction Models.

Autoři: Rossetto, Anubis Graciela de Moraes Noetzold, Darlan Silva, Luis Augusto a další

Zdroj: Sensors (14248220); Jul2024, Vol. 24 Issue 13, p4212, 25p

Témata: COMPUTER architecture, SPYWARE (Computer software), PREDICTION models, DATA security failures, COMPUTER monitors, AUTOMATIC speech recognition

International Symposium on Computer Performance Modeling, Measurement and Evaluation : March 29-31 1976, Cambridge. Massachusetts / ed. by P. P. S. Chen and Mark Franklin ; sponsored by ACM-SIGMETRICS, IPIP-Working Group 7.3.
Proceedings of the International Symposium on Computer Performance Modeling, Measurement and Evaluation

Autoři: International Symposium on Computer Performance Modeling, Measurement and Evaluation (1976 ; Cambridge, Massachusetts). Chen, Peter P. S. (1947- ). Franklin, Mark A. (1940- ). a další

Přispěvatelé: International Symposium on Computer Performance Modeling, Measurement and Evaluation (1976 ; Cambridge, Massachusetts). Chen, Peter P. S. (1947- ). Franklin, Mark A. (1940- ). a další

Zdroj: Bibliogr. przy ref.

Témata: Komputery -- ocena -- konferencje

Přístupová URL adresa: http://katalog.nukat.edu.pl/lib/item?id=chamo:4001581&theme=nukat

1977 Candidates for ACM Council.

Zdroj: Communications of the ACM; Apr1977, Vol. 20 Issue 4, p290-293, 4p

Témata: COMPUTER industry, MEMBERSHIP, EDUCATIONAL attainment, AWARDS, SOCIETIES

People: COTTERMAN, William W., WHITE, Michael P., ATCHISON, William F.

ACM REFERENCE GUIDES.

Zdroj: Communications of the ACM; Mar1970, Vol. 13 Issue 3, p199-200, 2p

Témata: ASSOCIATIONS, institutions, etc., COMPUTER industry, SPECIAL interest groups (Associations), COMMITTEES, ARTIFICIAL intelligence, DATA transmission systems

Korporace: ASSOCIATION for Computing Machinery

Floor the Ceil & Ceil the Floor: Revisiting AIMD Evaluation

Autoři: Rao, Ashwin Legout, Arnaud Cessac, Bruno a další

Přispěvatelé: Rao, Ashwin Legout, Arnaud Cessac, Bruno a další

Zdroj: https://inria.hal.science/hal-00733890 ; [Research Report] 2012.

Témata: AIMD, Sensitivity, Fairness, Efficiency, Integer Arithmetic, ACM: C.: Computer Systems Organization/C.4: PERFORMANCE OF SYSTEMS/C.4.3: Modeling techniques, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation

Dostupnost: https://inria.hal.science/hal-00733890
https://inria.hal.science/hal-00733890v1/document
https://inria.hal.science/hal-00733890v1/file/revisit-aimd-floor-ceil.pdf

Impact of mobility on call block, call drops and optimal cell size in small cell networks

Autoři: Ramanath, Sreenath Voleti, Veeraruna Kavitha Altman, Eitan a další

Přispěvatelé: Ramanath, Sreenath Voleti, Veeraruna Kavitha Altman, Eitan a další

Zdroj: https://inria.hal.science/inria-00573966 ; 2011.

Témata: ACM: C.: Computer Systems Organization/C.4: PERFORMANCE OF SYSTEMS/C.4.3: Modeling techniques, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]

Dostupnost: https://inria.hal.science/inria-00573966
https://inria.hal.science/inria-00573966v1/document
https://inria.hal.science/inria-00573966v1/file/2DSmallCellMobility.pdf

Reliability and Performance of Mirrored Disk Organizations.

Autoři: Alexander Thomasian Jun Xu

Zdroj: Computer Journal; 2008, Vol. 51 Issue 6, p615-615, 1p

Témata: ASYMPTOTIC expansions, DATA transmission systems, DIGITAL communications research, DATA protection research, COMPUTER storage devices, ELECTRONIC file management

MARTE: A Profile for RT/E Systems Modeling, Analysis (and Simulation?)

Autoři: Mallet, Frédéric de Simone, Robert Models and methods of analysis and optimization for systems with real-time and embedding constraints (AOSTE) a další

Přispěvatelé: Mallet, Frédéric de Simone, Robert Models and methods of analysis and optimization for systems with real-time and embedding constraints (AOSTE) a další

Zdroj: First International Conference on Simulation Tools and Techniques for Communications, Networks and Systems SIMUTools'08 ; https://inria.hal.science/inria-00371397 ; First International Conference on Simulation Tools and Techniques for Communications, Networks and Systems SIMUTools'08, ICST, Mar 2008, Marseille, France. pp.1-8

Témata: UML, MARTE, Simulation, ACM: C.: Computer Systems Organization/C.3: SPECIAL-PURPOSE AND APPLICATION-BASED SYSTEMS/C.3.2: Real-time and embedded systems, ACM: C.: Computer Systems Organization/C.4: PERFORMANCE OF SYSTEMS/C.4.3: Modeling techniques, [INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing

Geografické téma: Marseille, France

Dostupnost: https://inria.hal.science/inria-00371397
https://inria.hal.science/inria-00371397v1/document
https://inria.hal.science/inria-00371397v1/file/simutools08.pdf

An evaluation of novice end-user computing performance: Data modeling, query writing, and comprehension.

Autoři: Chan, H. C. Teo, H. H. Zeng, X. H.

Zdroj: Journal of the American Society for Information Science & Technology; Jun2005, Vol. 56 Issue 8, p843-853, 11p

Témata: ELECTRONIC data processing, DATABASES, COMPUTER science, INFORMATION science, DATABASE management, ELECTRONIC information resources