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[null,"1.","Record Nr.",null,"UNINA9910162747103321"]
[null,null,"Autore",null,"Lee Mo Yee"]
[null,null,"Titolo",null,"Culturally competent research : using ethnography as a meta-framework"]
[null,null,"Pubbl/distr/stampa",null,"New York, : Oxford University Press, 2013"]
[null,null,"ISBN",null,"9780199315918 (ebook) :"]
[null,null,"Descrizione fisica",null,"1 online resource"]
[null,null,"Collana",null,"Pocket guides to social work research methods Culturally competent  research"]
[null,null,"Disciplina",null,"361.0072"]
[null,null,"Soggetti",null,"Social service - Research"]
[{"$nulls":4},"Ethnology - Research"]
[{"$nulls":4},"Social Welfare & Social Work"]
[{"$nulls":4},"Social Sciences"]
[{"$nulls":4},"Social Welfare & Social Work - General"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Introduction -- Understanding culture -- Acquiring cultural knowledge -- Designing and implementing culturally competent research -- Culturally competent analysis and interpretation -- Culturally competent reporting and dissemination -- Final thoughts -- References -- Index."]
[null,null,null,"Sommario/riassunto","This book provides a practical guide for social work researchers, doctoral students, and professionals who are interested in conducting culturally competent research with diverse populations and groups. 'Culturally Competent Research' adopts ethnography as a meta-framework for conducting culturally competent research. Since its inception as an academic discipline, anthropology has developed theories, concepts, methods, and a significant body of substantive studies for the purposes of guiding cultural research, describing cultural groups and processes, and providing data needed for cross-cultural research and theory-building."]
[null,"2.","Record Nr.",null,"UNINA9910627264903321"]
[null,null,"Titolo",null,"4th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing : BDCC 2021 / / edited by Anandakumar Haldorai, Arulmurugan Ramu, Sudha Mohanram, Rita Zgheib"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"3-031-07654-0"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (266 pages)"]
[null,null,"Collana",null,"EAI/Springer Innovations in Communication and Computing, , 2522-8609"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Telecommunication"]
[{"$nulls":4},"Signal processing"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Computational intelligence"]
[{"$nulls":4},"Communications Engineering, Networks"]
[{"$nulls":4},"Digital and Analog Signal Processing"]
[{"$nulls":4},"Computer Communication Networks"]
[{"$nulls":4},"Computational Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Part I. Bigdata Services -- Chapter 1. Modelling Cognitive Scores for Alzheimer's Disease Progression Prediction Using Longitudinal MRI D -- Chapter 2. Various Physiological Methods to Identify Sleep Onset -- Chapter 3. IoT Adoption: Challenges among Small and Medium Enterprises -- Chapter 4. Performance evaluation of Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Cloud Service Provider -- Part II. Bigdata and Security -- Chapter 5. Online Covid-19 Risk Analysis System for Early Detection of Possible Infection -- Chapter 6. Application of Multi focused and Multi Modal image fusion using Guided Filter on Bio-Medical Images -- Chapter 7. Experimental Comparative Analysis on Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) on Aspect Level Sentiment Analysis -- Part III. Bigdata Emerging Applications -- Chapter 8. Data hiding in binary images for secret and secure communication using decision tree -- Chapter 9. Private and Secure Blockchain-based mechanism for an Online Voting System -- Chapter 10. AI-Enabled Pregnancy Risk "]
[{"$nulls":4},"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 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 4th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2021). 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. Contains proceedings from EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2021); Features topics ranging from Data Science for Cognitive Analysis to Internet-Based Cognitive Platforms; Relevant for researchers, professionals, academics, and students in Cognitive Computing."]