Search Results - ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.4: Systems/H.2.4.4: Parallel databases

Source: DEXA 2011 - 22nd International Conference on Database and Expert Systems Applications ; https://inria.hal.science/hal-00640139 ; DEXA 2011 - 22nd International Conference on Database and Expert Systems Applications, Aug 2011, Toulouse, France. pp.1-11, ⟨10.1007/978-3-642-23088-2_1⟩

Subject Terms: ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.4: Systems/H.2.4.1: Distributed databases, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.5: Heterogeneous Databases, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.4: Systems/H.2.4.4: Parallel databases, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]

Subject Geographic: Toulouse, France

Relation: info:eu-repo/semantics/altIdentifier/arxiv/1111.2852; ARXIV: 1111.2852

Availability: https://inria.hal.science/hal-00640139
https://inria.hal.science/hal-00640139v1/document
https://inria.hal.science/hal-00640139v1/file/Dexa2011.pdf
https://doi.org/10.1007/978-3-642-23088-2_1

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8

New Trends in Databases and Information Systems ; New Trends in Databases and Information Systems: ADBIS 2019 Short Papers, Workshops BBIGAP, QAUCA, SemBDM, SIMPDA, M2P, MADEISD, and Doctoral Consortium

Authors: Welzer, Tatjana Eder, Johann Podgorelec, Vili et al.

Contributors: Welzer, Tatjana Eder, Johann Podgorelec, Vili et al.

Source: 23rd European Conference on Advances in Databases and Information Systems (ADBIS 2019)
https://hal.archives-ouvertes.fr/hal-02281167
23rd European Conference on Advances in Databases and Information Systems (ADBIS 2019), Sep 2019, Bled, Slovenia. 1064, Springer, 2019, Communications in Computer and Information Science

Subject Terms: ACM: H.: Information Systems, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]

Subject Geographic: Bled, Slovenia

Relation: hal-02281167; https://hal.archives-ouvertes.fr/hal-02281167

Availability: https://hal.archives-ouvertes.fr/hal-02281167

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9

On Intelligent Database Systems.

Authors: McLeod, Dennis Yanover, Paul

Source: Intelligent Systems in Accounting, Finance & Management; Dec1992, Vol. 1 Issue 4, p237-245, 9p

Subject Terms: DATABASES, DATABASE management, ARTIFICIAL intelligence, SYSTEM integration, CONCEPTUAL models, DISTRIBUTED databases

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10

The Evolution of the Massively Parallel Processing Database in Support of Visual Analytics.

Authors: Willson, Ian A.

Source: Information Resources Management Journal; Oct-Dec2011, Vol. 24 Issue 4, p1-26, 26p

Subject Terms: DATA warehousing, DATABASE industry, DATABASE management, INFORMATION storage & retrieval systems, VISUAL analytics

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11

Query Optimization in Distributed Networks of Autonomous Database Systems.

Authors: Pentaris, Fragkiskos Ioannidis, Yannis

Source: Javnost-The Public; 2006, Vol. 13 Issue 2, p537-583, 47p, 6 Diagrams, 6 Charts, 10 Graphs

Subject Terms: DATABASES, ELECTRONIC commerce, ALGORITHMS, DATABASE management, INFORMATION storage & retrieval systems

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12

Parallel Concurrency Control Activity for Transaction Management in Real-time Database Systems.

Authors: Bhalla, Subhash

Source: Journal of Supercomputing; Jun2004, Vol. 28 Issue 3, p345-369, 25p

Subject Terms: DATABASES, ELECTRONIC information resources, MANAGEMENT, REAL-time computing, TIME delay systems, COMPUTER systems, STOCHASTIC processes

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13

New Trends in Databases and Information Systems ; New Trends in Databases and Information Systems: ADBIS 2020 Short Papers

Authors: Darmont, Jérôme Novikov, Boris Wrembel, Robert et al.

Contributors: Darmont, Jérôme Novikov, Boris Wrembel, Robert et al.

Source: ISSN: 1865-0929 ; Communications in Computer and Information Science ; https://hal.science/hal-02928834 ; Communications in Computer and Information Science, 1259, Springer Nature, 2020, ⟨10.1007/978-3-030-54623-6⟩.

Subject Terms: Databases, Informaton Systems, ACM: H.: Information Systems, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]

Availability: https://hal.science/hal-02928834
https://doi.org/10.1007/978-3-030-54623-6

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14

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

Authors: Okunola, Abiodun

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15

DATAPLEX: An Access to Heterogenous Distributed Databases.

Authors: Chin-Wan Chung Sibley, Edgar H.

Source: Communications of the ACM; Jan1990, Vol. 33 Issue 1, p70-80, 11p, 6 Diagrams, 2 Charts

Subject Terms: DATABASE management, INFORMATION retrieval, RELATIONAL databases, SQL, MANAGEMENT information systems, PROGRAMMING languages

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16

The Forgotten Document-Oriented Database Management Systems: An Overview and Benchmark of Native XML DODBMSes in Comparison with JSON DODBMSes

Authors: Truică, Ciprian-Octavian Apostol, Elena Darmont, Jérôme et al.

Contributors: Truică, Ciprian-Octavian Apostol, Elena Darmont, Jérôme et al.

Source: ISSN: 2214-5796.

Subject Terms: XML Database Management Systems, JSON Database Management Systems, Document-Oriented Database Management Systems, Benchmark, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]

Availability: https://hal.science/hal-03112539
https://hal.science/hal-03112539v1/document
https://hal.science/hal-03112539v1/file/bdr2021tadp.pdf
https://doi.org/10.1016/j.bdr.2021.100205

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17

Evaluation of Database Management Systems and Techniques Applied in Distributed Systems.

Authors: Samonte, Mary Jane C. Samonte, Sasky A.

Source: IEOM African Conference Proceedings; 2022, p196-204, 9p

Subject Terms: DATABASES, DISTRIBUTED databases, RELATIONAL databases, INFORMATION retrieval, DATA warehousing, TRANSACTION systems (Computer systems)

18

PAXQuery: Efficient Parallel Processing of Complex XQuery

Authors: Camacho-Rodríguez, Jesús Colazzo, Dario Manolescu, Ioana et al.

Contributors: Camacho-Rodríguez, Jesús Colazzo, Dario Manolescu, Ioana et al.

Source: BDA'2014: 30e journées Bases de Données Avancées ; https://hal.science/hal-01086809 ; BDA'2014: 30e journées Bases de Données Avancées, Oct 2014, Grenoble-Autrans, France

Subject Terms: XML data management, XQuery parallelization, XQuery processing, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.4: Systems, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]

Subject Geographic: Grenoble-Autrans, France

Availability: https://hal.science/hal-01086809
https://hal.science/hal-01086809v1/document
https://hal.science/hal-01086809v1/file/paxquery-bda-2014.pdf

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19

24th European Conference on Advances in Databases and Information Systems (ADBIS 2020)

Authors: Darmont, Jérôme Novikov, Boris Wrembel, Robert et al.

Contributors: Darmont, Jérôme Novikov, Boris Wrembel, Robert et al.

Source: ISSN: 0302-9743 ; Lecture Notes in Computer Science ; https://hal.science/hal-02928830 ; Lecture Notes in Computer Science, 12245, Springer Nature, 2020, ⟨10.1007/978-3-030-54832-2⟩.

Subject Terms: Databases, Information Systems, ACM: H.: Information Systems, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]