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[null,"1.","Record Nr.",null,"UNINA9910910494003321"]
[null,null,"Autore",null,"Simic Milan"]
[null,null,"Titolo",null,"Smart Computing Paradigms: Artificial Intelligence and Network Applications : Proceedings of Sixth International Conference on Smart Computing and Informatics (SCI 2024), Volume 1 / / edited by Milan Simic, Vikrant Bhateja, M. Ramakrishna Murty, Sandeep Kumar Panda"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"9789819778805"]
[{"$nulls":4},"9819778808"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (546 pages)"]
[null,null,"Collana",null,"Lecture Notes in Networks and Systems, , 2367-3389 ; ; 1147"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Telecommunication"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Communications Engineering, Networks"]
[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,"Intro -- Committees -- Preface -- Contents -- Editors and Contributors -- Sub-threshold Model of NMOS for Low-Power Application -- 1 Introduction -- 2 Literature Review -- 3 Structural View of NMOS -- 4 Implementation Process for NMOS Modeling -- 5 Simulated Results and Discussions -- 6 Conclusion -- 7 Future Scope -- References -- From Farm to Fork: Applications of Artificial Intelligence in the Food Industry -- 1 Introduction -- 2 Technologies Integrated in the Food Industry -- 2.1 AI-Enabled Precision Fermentation -- 2.2 Seeds of Sustainability with Precision Agriculture Practices -- 2.3 Transforming the Bakery Industry Through AI -- 2.4 Decoding Durability: AI's Algorithmic Approach to Shelf Life -- 2.5 Elevating Alcoholic Beverages with Computer Vision -- 2.6 AI's Role in Enhancing Food Enzymes -- 2.7 The AI Revolution in Supply Chain Networks -- 2.8 Smart Insights, Smarter Decisions: AI and Demand Forecasting -- 2.9 Innovate, Validate, and Elevate: AI-Driven Quality Assurance Solutions -- 2.10 Eco-logistics: Smart Warehousing, Distribution, and Sustainable Packaging -- 3 Conclusion -- References -- Resilient Domain Authentication Framework for Enhancing Digital "]
[{"$nulls":4},"Identity Security -- 1 Introduction -- 1.1 Limitations of Traditional Authentication Methods -- 1.2 Significance of Domain Name-Based Authentication -- 2 Background -- 3 Proposed Authentication Framework -- 3.1 MetaMask Browser Extension and DNS -- 3.2 Architecture of the System and Its Components -- 4 Experimentation -- 4.1 Use Cases of TeSC -- 4.2 ERC-20 Transactions as an Example -- 4.3 TeSC in MetaMask Design Concept -- 5 Conclusion -- References -- Traffic Sign Detection with Pattern Recognition Techniques Using Image Processing -- 1 Introduction -- 2 Survey of Related Works -- 3 Architecture of Proposed System -- 4 Evaluation -- 5 Results and Discussion."]
[{"$nulls":4},"6 Conclusion and Future Scope -- Exploring Advanced Techniques in Natural Language Processing and Machine Learning for In-depth Analysis of Insurance Claims -- 1 Introduction -- 2 AI for Insurance -- 3 Literature Survey -- 4 Text Summarization -- 5 Keyword Extraction -- 6 Results and Observations -- 7 Conclusion -- References -- Network Intrusion Detection with SMOTE-ENN and Deep Learning Techniques -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 SMOTE-ENN -- 3.2 Autoencoders -- 3.3 Multi-layer Perceptron -- 4 Implementation -- 4.1 Datasets -- 4.2 Data Preprocessing -- 4.3 Feature Extraction and Classification -- 5 Performance Analysis and Results -- 5.1 Evaluation Metrics -- 5.2 Comparative Analysis -- 5.3 Results and Discussion -- 6 Conclusion -- References -- Leveraging Transfer Learning to Enhance Location Accuracy in Mapping Services: A Case Study of Google Maps -- 1 Introduction -- 2 Background -- 3 Related Work -- 4 Working of Google Maps -- 4.1 Dijkstra's Algorithm -- 4.2 A* Algorithm -- 4.3 Bellman-Ford Algorithm -- 5 Factors Influencing Google Maps Inaccuracies: -- 5.1 GPS Signal Problems -- 5.2 Wi-Fi and Cellular Data -- 5.3 Power Saving -- 5.4 Navigation Applications: -- 5.5 Supervised Learning: -- 5.6 Cache Information: -- 6 Transfer Learning -- 6.1 Machine Learning -- 6.2 Transfer Learning -- 7 Applying Transfer Learning for Location Accuracy -- 8 Methodology and Result Analysis -- 9 Future Directions -- References -- Assessment of Enhanced Email Spam Detection System Through Machine Learning Algorithms -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 The Machine Learning Classification Algorithms and Evaluation Indicators -- 4.1 Evaluation Indicators -- 5 Results and Discussion -- 6 Conclusion -- References -- Machine Learning Methods for Predicting Traffic Congestion Forecasting -- 1 Introduction."]
[{"$nulls":4},"2 Literature Review -- 3 Proposed Method -- 3.1 Data Collection and Preprocessing -- 3.2 Feature Selection -- 3.3 Decision Tree -- 3.4 Random Forest -- 3.5 SVM -- 3.6 Neural Network -- 4 Experimental Setup -- 5 Results -- 6 Conclusion -- References -- Hybridization of Computational Intelligence Algorithm for Scheduling of Tasks and Balancing of Load in Cloud Network -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Proposed Hybrid Algorithm for Balancing Load Problem -- 5 Experimental Results -- 6 Conclusion -- References -- MDSV: Mobs Detection by Enhanced Fused Feature Base Deep Neural Network from Surveillance Camera -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Datasets -- 3.2 Illumination and Contrast Adjustment -- 3.3 Motion Estimation -- 3.4 Human Mobs Tracking -- 3.5 Feature Extraction -- 3.6 Feature Selection -- 3.7 Deep Belief Network (DBN) -- 4 Experimental Result and Performance Analysis -- 4.1 Comparative Analysis -- 5 Conclusion -- References -- IoT-Based Solution for Enhanced Tracking of Individuals Living with Dementia -- 1 Introduction -- 2 Methodology -- 2.1 Research Design -- 2.2 Planning Phase -- 2.3 Design Phase -- "]
[{"$nulls":4},"2.4 Development Phase -- 2.5 Feedback Phase -- 3 Results -- 4 Conclusion -- References -- A Novel Task Scheduling Algorithm in Heterogeneous Multi-cloud Environment -- 1 Introduction -- 1.1 Cloud and Cloud Environment -- 2 Related Work -- 3 Model and Problem Statement -- 3.1 Cloud Model -- 3.2 Application Model and Problem Statement -- 3.3 Scheduling Model Using Proposed Algorithm -- 4 Experimental Results -- 5 Conclusion -- References -- Evaluating the Integration and Usage of AI in Higher Education -- 1 Introduction -- 2 Artificial Intelligence (AI) -- 3 Role of AI in Higher Education -- 4 AI Challenges in Higher Education -- 5 Literature Review -- 6 Research Methodology."]
[{"$nulls":4},"7 Conclusion -- References -- Evaluating the Connectional Benefits of Artificial Intelligence in the Digital Classroom -- 1 Introduction -- 2 AI in Education System -- 3 Literature Review -- 4 Learner Example -- 5 Model of Instruction -- 6 Domain Expertise -- 7 Module for Communication -- 8 Skill Module -- 9 Model of E-Learning -- 10 Here Are a Few Well-Known E-Learning Tools -- 11 AI-Powered Analysis of Student Learning -- 12 Preparing Data -- 13 AI Applications in Education -- 14 To Make the Grading System Better -- 15 Astute Content -- 16 Astute Instructions -- 17 Tailored Education -- 18 Advantages of AI in Classroom -- 19 Benefits of AI into the Classroom -- 20 Benefits of AI to the Teacher -- 21 Limitations of AI -- 21.1 Costly -- 21.2 Inadequate Interpersonal Relationship -- 21.3 Decrease in the Need for Tutors -- 21.4 Dependency -- 22 Conclusion -- 22.1 Information Loss -- References -- Influence of AI as an Aspect of Modern Education Era in Present World -- 1 Introduction -- 2 Artificial Intelligence (AI) -- 3 Artificial Intelligence (AI) in the Field of Education -- 4 Attitude Toward Artificial Intelligence (AI) -- 5 Attitude Toward Artificial Intelligence (AI) in Reference to Educational Field -- 6 AI Brings a Change in Educational Field -- 7 Conclusion -- References -- Hilbert-Huang Transform Framework-Based Email and SMS Spam Detection -- 1 Introduction -- 2 Literature Review -- 3 Proposed Model -- 4 Implementation of Hilbert-Huang Transform -- 5 Results and Analysis -- 5.1 Performance Evaluation -- 5.2 Results Using Hilbert-Huang Transform -- 6 Conclusion -- References -- The Advancement and Utilization of Artificial Intelligence and Machine Learning in the Financial Industry and Its Impact on Macro and Microeconomics -- 1 Introduction -- 2 Literature Survey -- 3 Artificial Intelligence -- 4 Machine Learning."]
[{"$nulls":4},"5 Advantages of Machine Learning for the Finance Industry -- 6 How Machine Learning Work in Finance -- 7 Enlargement and Relevance of AI and ML in Investment Sector -- 7.1 Artificial Intelligence's Advancement in the Financial Sector -- 7.2 Financial Sector Implications of Artificial Intelligence -- 8 Impacts of AI in Financial Market -- 9 Data Management -- 10 Algorithmic Trading -- 11 Fraud Detection and Prevention -- 12 Risk Management -- 13 Adoption of AI in Finance -- 14 Conclusion -- References -- Analysis on the Cutting-Edge Approach to Assess Artificial Intelligence's Educational Consequences in Contemporary Studies -- 1 Introduction -- 2 Literature Survey -- 3 Role of Artificial Intelligence in Education -- 3.1 Nature of Artificial Intelligence -- 4 Technical Aspects of AI in Education -- 5 Impact of AI on Education -- 6 Uses of Artificial Intelligence -- 7 Advantages of Artificial Intelligence -- 8 Disadvantages of Artificial Intelligence -- 9 Future Scope -- 10 Conclusion -- References -- Data Analytics in Sales and Marketing: A Comprehensive Methodology for Business Analysts -- 1 Introduction -- 2 Business Benefits of Big Data -- 3 Challenges of Big Data in Marketing -- 4 Big Data Analytics -- 5 Large-Scale Data -- 6 Volume "]
[{"$nulls":4},"-- 7 Authenticity -- 8 Speed -- 9 Diverse -- 10 Value -- 11 Projected Model -- 12 Sales and Marketing -- 12.1 Sales -- 12.2 Marketing -- 13 Model of Sales as Well as Marketing Integration -- 14 Steps to Implement Big Data Analytics -- 14.1 Strategy Formulation -- 14.2 Extraction of Data -- 14.3 Data Transformation and Storage -- 14.4 Information Analysis -- 14.5 Report/Graphic Design -- 15 Conclusion -- References -- Wireless Energy Transfer for UAV (Drone) Using Machine Learning -- 1 Introduction -- 2 Literature Survey -- 3 Existing System -- 4 Proposed System -- 4.1 Allocation of Resources Based on the HTS Model."]
[{"$nulls":4},"4.2 AP-RIS-UT Channel Model."]
[null,null,null,"Sommario/riassunto","This book presents best-selected papers presented at the 6th International Conference on Smart Computing and Informatics (SCI 2024), held at the Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology & Sciences (ANITS), Visakhapatnam, India, during 19–20 April 2024. It presents advanced and multidisciplinary research towards the design of smart computing and informatics. The theme is on a broader front and focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solutions to varied problems in society, environment and industries. The scope is also extended towards the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and healthcare. The work is published in three volumes."]