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1. |
Record Nr. |
UNINA9911114301803321 |
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Autore |
Kumar Sandeep |
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Titolo |
Proceedings of International Conference on Information Technology and Artificial Intelligence : ITAI 2025, Volume 1 / / edited by Sandeep Kumar, Robin T. Bye, Mukesh Prasad |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026 |
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ISBN |
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981-9686-87-3 |
9789819686872 |
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Edizione |
[1st ed. 2026.] |
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Descrizione fisica |
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1 online resource (745 pages) |
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Collana |
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Lecture Notes in Networks and Systems, , 2367-3389 ; ; 1505 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Artificial intelligence |
Image processing - Digital techniques |
Computer vision |
Data protection |
Computational Intelligence |
Artificial Intelligence |
Computer Imaging, Vision, Pattern Recognition and Graphics |
Data and Information Security |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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1. Quantum-Enhanced Edge Computing for Optimized Resource Allocation in Heterogeneous IoT Networks A Deep Reinforcement Learning Approach -- 2. Comprehensive Framework for Brain Tumor Diagnosis using Integrated Multi-modal Imaging Techniques -- 3. Machine Learning in Domestic Violence Current Trends and Future Prospective -- 4. A Forgery Detection Framework for Facial Images Using Deep Learning -- 5. Empathy and Parasport Engagement Among Young Vietnamese Audiences A Perspective Using Extended TPB -- 6. Enhanced Academic Assessments Using BERT and Top Sampling for Student Performance Optimization -- 7. Harnessing Large Language Models and EHRs for Enhanced Predictive Analytics in Personalized Healthcare -- 8. Optimizing Ride-Hailing Demand Forecasting with |
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Explainable AI and Ensemble Learning Techniques. |
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Sommario/riassunto |
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This book presents a collection of high-quality, peer-reviewed research papers from First International Conference on Information Technology and Artificial Intelligence (ITAI 2025), organized by Soft Computing Research Society held in Gurgaon, India, from January 24–25, 2025. It covers topics such as artificial intelligence, data science and applications, cybersecurity, internet of things, cloud computing, information retrieval, and knowledge management. |
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2. |
Record Nr. |
UNINA9911136154003321 |
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Autore |
Best Joel |
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Titolo |
Damned lies and statistics : untangling numbers from the media, politicians, and activists / / Joel Best |
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Pubbl/distr/stampa |
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University of California Press, 2012 |
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ISBN |
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9786613906915 |
9781283594462 |
1283594463 |
9780520953512 |
0520953517 |
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Edizione |
[Updated ed.] |
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Descrizione fisica |
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1 online resource (218 p.) |
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Classificazione |
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Disciplina |
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Soggetti |
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Social indicators |
Social problems - Statistical methods |
Sociology - Statistical methods |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Frontmatter -- CONTENTS -- ACKNOWLEDGMENTS -- PREFACE TO THE UPDATED EDITION -- INTRODUCTION. The Worst Social Statistic Ever -- 1. THE IMPORTANCE OF SOCIAL STATISTICS -- 2. SOFT FACTS: Sources of Bad Statistics -- 3. MUTANT STATISTICS: Methods for Mangling Numbers -- 4. APPLES AND ORANGES: Inappropriate Comparisons -- 5. STAT WARS: Conflicts over Social Statistics -- 6. THINKING ABOUT |
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SOCIAL STATISTICS: The Critical Approach -- Afterword. BAD STATISTICS: WHAT'S THE PROBLEM? -- NOTES -- INDEX |
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Sommario/riassunto |
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Here, by popular demand, is the updated edition to Joel Best's classic guide to understanding how numbers can confuse us. In his new afterword, Best uses examples from recent policy debates to reflect on the challenges to improving statistical literacy. Since its publication ten years ago, Damned Lies and Statistics has emerged as the go-to handbook for spotting bad statistics and learning to think critically about these influential numbers. |
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