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[null,"1.","Record Nr.",null,"UNINA9910728931003321"]
[null,null,"Titolo",null,"5th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing : BDCC 2022 / / edited by Anandakumar Haldorai, Arulmurugan Ramu, Sudha Mohanram"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"3-031-28324-4"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (221 pages)"]
[null,null,"Collana",null,"EAI/Springer Innovations in Communication and Computing, , 2522-8609"]
[null,null,"Disciplina",null,"170"]
[null,null,"Soggetti",null,"Telecommunication"]
[{"$nulls":4},"Signal processing"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Communications Engineering, Networks"]
[{"$nulls":4},"Digital and Analog Signal Processing"]
[{"$nulls":4},"Computer Communication Networks"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Part I. Bigdata Services -- Chapter 1. Modelling Cognitive Scores for Alzheimer's Disease Progression Prediction Using Longitudinal MRI D -- Chapter 2. Various Physiological Methods to Identify Sleep Onset -- Chapter 3. IoT Adoption: Challenges among Small and Medium Enterprises -- Chapter 4. Performance evaluation of Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Cloud Service Provider -- Part II. Bigdata and Security -- Chapter 5. Online Covid-19 Risk Analysis System for Early Detection of Possible Infection -- Chapter 6. Application of Multi focused and Multi Modal image fusion using Guided Filter on Bio-Medical Images -- Chapter 7. Experimental Comparative Analysis on Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) on Aspect Level Sentiment Analysis -- Part III. Bigdata Emerging Applications -- Chapter 8. Data hiding in binary images for secret and secure communication using decision tree -- Chapter 9. Private and Secure Blockchain-based mechanism for an Online Voting System -- Chapter 10. AI-Enabled Pregnancy Risk Monitoring and Prediction: A Review -- Chapter 11. Finger Knuckle Print Recognition using Complex Conjugate Feature Vector -- Part IV. Bigdata and Technology -- Chapter 12. What Your Tweets Say about "]
[{"$nulls":4},"You – A case study of Extraversion and word usage -- Chapter 13. An Automated Cervical Cancer Detection mechanism using Pap smear images -- Chapter 14. A Systematic Literature Review on Data Freshness for reinforcing mutual authentication in Wireless Body Area Networks -- Chapter 15. Detection of Non-Technical Losses in Power Utilities Using Machine Learning -- Part V. Bigdata in Medical Applications -- Chapter 16. A Novel Real Time 3D Object Detection Network in Autonomous Driving using reformed rs-resnet network -- Chapter 17. Solar radiation prediction using the random forest regression algorithm -- Chapter 18. Vehicular Support System for User and Vehicle Accident Prevention."]
[null,null,null,"Sommario/riassunto","This book features the proceedings of the 5th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2022). The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on technologies from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform."]
[null,"2.","Record Nr.",null,"UNINA9910303441703321"]
[null,null,"Autore",null,"Cadamuro Luca"]
[null,null,"Titolo",null,"Search for Higgs Boson Pair Production in the bb̅ τ+ τ- Decay Channel : with the CMS detector at the LHC / / by Luca Cadamuro"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018"]
[null,null,"ISBN",null,"3-030-04055-0"]
[null,null,"Edizione",null,"[1st ed. 2018.]"]
[null,null,"Descrizione fisica",null,"1 online resource (283 pages)"]
[null,null,"Collana",null,"Springer Theses, Recognizing Outstanding Ph.D. Research, , 2190-5053"]
[null,null,"Disciplina",null,"539.721"]
[null,null,"Soggetti",null,"Particles (Nuclear physics)"]
[{"$nulls":4},"Quantum field theory"]
[{"$nulls":4},"String models"]
[{"$nulls":4},"Elementary Particles, Quantum Field Theory"]
[{"$nulls":4},"Quantum Field Theories, String Theory"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Preamble -- Introduction to Higgs Boson Pair Production -- Experimental Apparatus -- The L1 τ Trigger -- Event Selection and Categorization -- Modelling of Physics Processes -- Results on HH → bbτ +τ − -- Future prospects for HH searches -- Conclusions -- Appendix."]
[null,null,null,"Sommario/riassunto","This thesis presents innovative contributions to the CMS experiment in the new trigger system for the restart of the LHC collisions in Run II, as well as original analysis methods and important results that led to official publications of the Collaboration. The author's novel reconstruction algorithms, deployed on the Field-Programmable Gate Arrays of the new CMS trigger architecture, have brought a gain of over a factor 2 in efficiency for the identification of tau leptons, with a very significant impact on important H boson measurements, such as its decays to tau lepton pairs and the search for H boson pair production. He also describes a novel analysis of HH → bb tautau, a high priority physics topic in a difficult channel. The original strategy, optimisation of event categories, and the control of the background have made the result one of the most sensitive concerning the self-coupling of the Higgs boson among all possible channels at the LHC."]