Data Science and Applications : Proceedings of ICDSA 2023, Volume 1

• Autore: Nanda Satyasai Jagannath
• Pubblicazione: Singapore : , : Springer, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (569 pages)
• Disciplina: 005.7
• Altri autori: YadavRajendra Prasad GandomiAmir H SaraswatMukesh
• Nota di contenuto: Intro -- Preface -- Contents -- Editors and Contributors -- Climate Change Parameter Dataset (CCPD): A Benchmark Dataset for Climate Change Parameters in Jammu and Kashmir -- 1 Introduction -- 2 Background and Related Work -- 3 Methodology -- 3.1 Overview -- 3.2 Forest Cover -- 3.3 Water Bodies -- 3.4 Agriculture and Vegetation -- 3.5 Population -- 3.6 Temperature -- 3.7 Construction -- 3.8 Air Index -- 4 Dataset Results -- 5 Conclusion -- References -- Brain Tumor Classification Using Deep Learning Techniques -- 1 Introduction -- 2 Review of Previous Work -- 3 Information About the Data and Environmental Setup -- 3.1 Data Preparation and Exploration -- 4 Convolutional Neural Networks and Techniques Implemented -- 4.1 AlexNetV2 -- 4.2 VGG-16 -- 4.3 ResNet-50 -- 4.4 Inception-ResNet -- 4.5 MobileNetv2 -- 5 Experimental Approaches -- 5.1 Novel CNN Architecture -- 5.2 Parallel Networks Model -- 5.3 Machine Learning Assisted -- 6 Optimisation Using Nature-Inspired Algorithms -- 6.1 Particle Swarm Optimization -- 6.2 Genetic Algorithm -- 7 Conclusion -- References -- Machine Learning-Based Hardware Trojans Detection in Integrated Circuits: A Systematic Review -- 1 Introduction -- 2 Machine Learning and Models -- 3 A Review of Machine Learning Methods for Hardware Trojan Detection -- 3.1 Reverse Engineering -- 3.2 Circuit Feature Analysis -- 3.3 Side-Channel Analysis -- 3.4 Golden Model Free Analysis -- 3.5 Classification Approaches -- 3.6 Final Result of Hardware Trojan Detection Approaches -- 4 Discussion and Future Work -- 5 Conclusion -- References -- Impact of Technostress on Employee Retention and Employee Turnover -- 1 Introduction -- 2 Literature Review -- 3 Theoretical Background and Hypothesis -- 4 Methodology -- 5 Data Analysis and Discussion -- 6 Limitations and Future Scope -- 7 Conclusion -- References. ; Single Image Dehazing Using DCP with Varying Scattering Constant -- 1 Introduction -- 2 Haze Formation Model -- 3 Solution Approach -- 3.1 Estimation of Atmospheric Light Using DCP -- 3.2 Estimating Omega -- 4 Results and Discussion -- 5 Conclusion -- References -- Detecting IoT Malware Using Federated Learning -- 1 Introduction -- 2 Related Works -- 2.1 Signature-Based Detection -- 2.2 Behavior-Based Detection -- 2.3 Machine Learning-Based Detection -- 2.4 Deep Learning-Based Detection -- 2.5 Motivation for Federated Learning -- 3 Federated Learning -- 3.1 Overview of Federated Learning -- 3.2 Mathematical Formulation -- 3.3 Challenges and Considerations in Federated Learning -- 4 Federated Learning Strategy for IoT Malware Recognition -- 4.1 Obstacles and Rationale -- 4.2 Model Design -- 4.3 Procedure of Federated Learning -- 5 Experimental Results and Evaluation -- 6 Conclusion -- References -- A Deep Learning Approach for BGP Security Improvement -- 1 Introduction -- 2 Related Work -- 3 Deep Learning Models -- 3.1 Convolutional Neural Network (CNN) -- 4 Dataset -- 5 Proposed Technique -- 6 Evaluation Metrics -- 7 Experimental Results -- 8 Conclusion -- References -- Wireless Sensor Network Protocols in Underwater Communication -- 1 Introduction -- 1.1 Underwater Wireless Sensor Network Architecture -- 2 Challenges Regarding UWSNs -- 2.1 Propagation Delay -- 2.2 Bandwidth -- 2.3 Energy Consumption -- 2.4 Communication Coverage -- 2.5 Attenuation -- 2.6 Cost -- 2.7 Sophisticated Techniques -- 3 Routing Protocols -- 3.1 Localization-Based Protocols -- 3.2 Localization-Free Protocols -- 3.3 Cooperation Routing -- 4 Conclusion -- References -- A Genetic Algorithm Approach for Portfolio Optimization -- 1 Introduction -- 1.1 Techniques for Portfolio Optimization -- 2 Genetic Algorithm -- 3 Scope of Genetic Algorithm -- 4 Fitness Function. ; 5 Genetic Algorithm-Based Portfolio Optimization -- 6 Result and Analysis -- 7 Advantages -- 8 Conclusion -- References -- Security Issues and Solutions in Post Quantum Authenticated Key Exchange for Mobile Devices -- 1 Introduction -- 2 Contribution -- 3 Description of Signal Leakage Attack -- 4 Preliminaries -- 5 Dabra et al. ``Lattice-Based Key Exchange for Mobile Devices ch10dabra2020lba'' -- 6 Statement of Problem -- 6.1 Registration Issues -- 6.2 Password Change Issues -- 6.3 Insider Attack -- 6.4 Signal Leakage Attack -- 7 Changes Required in Dabra et al.'s Registration Phase -- 8 Conclusion/Future Directions -- References -- Towards Decentralized Fog Computing: A Comprehensive Review of Models, Architectures, and Services -- 1 Introduction -- 1.1 Fog Computing, an Extension of Cloud Computing -- 1.2 Fog Over Cloud -- 1.3 Transition from Cloud to Fog -- 2 Motivation -- 3 Literature Survey -- 4 Architectural Model -- 4.1 Architectural Styles -- 4.2 Views -- 4.3 Dimensions -- 4.4 Related Work -- 5 Discussion -- 6 Research Contributions -- 7 Conclusion -- References -- Analysis of Various Mac Protocols in 802.11 AX -- 1 Introduction -- 1.1 OFDMA Multi-user Transmissions in 802.11ax -- 2 Literature Review -- 2.1 Comparison Table -- 3 Conclusion -- References -- Monkeypox Disease Classification Using HOG-SVM Model -- 1 Introduction -- 1.1 Transmission -- 1.2 Symptoms of Monkeypox Disease -- 1.3 Traditional Detection -- 1.4 Traditional Treatments of Monkeypox -- 1.5 AI-Based Detection -- 2 Literature Survey -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Feature Extraction -- 3.3 Classification -- 3.4 Support Vector Machine (SVM) -- 4 Implementation -- 5 Evaluation Matrices -- 6 Result -- 7 Conclusion -- References -- A Deep Learning Model for Automatic Recognition of Facial Expressions Using Haar Cascade Images -- 1 Introduction. ; 2 Literature Review -- 3 The Presented Approach -- 3.1 Dataset -- 3.2 Pre-processing -- 3.3 Presented Deep Learning Model -- 3.4 Testing -- 4 Result -- 5 Conclusion and Future Work -- References -- Sensing Performance Analysis Using Choatic Signal-Based SCMA Codebook for Secure Cognitive Communication System in 5G -- 1 Introduction -- 1.1 Related Work -- 2 SCMA with Chaotic Sequence-Based System Analysis -- 2.1 Dynamic Characteristic of Chaotic Sequence -- 2.2 SCMA Modeling -- 3 System Model -- 3.1 SCMA Encoding -- 3.2 SCMA Decoding -- 4 Proposed Detection Method -- 4.1 Binary Hypothesis Testing -- 4.2 Wald Hypothesis Test -- 4.3 Weight Assignment Method -- 4.4 Experimental Setup -- 5 Detection Performance Analysis -- 6 Conclusion -- References -- Identification of Severity Level for Diabetic Retinopathy Detection Using Neural Networks -- 1 Introduction -- 2 Review of Literature -- 3 Motivation of Proposed Research Work -- 4 Existing Datasets -- 4.1 Dataset from Zenodo -- 4.2 EyePACS Dataset from Kaggle -- 4.3 APTOS Dataset from Kaggle -- 5 Proposed Methodology -- 5.1 Flow of the Proposed Work -- 5.2 Preprocessing on the Dataset -- 5.3 Architecture Used for the Proposed Work -- 5.4 Implementation Platform and Performance Matrix -- 6 Results -- 7 Conclusion -- 8 Future Work -- References -- Metaheuristic Optimized BiLSTM Univariate Time Series Forecasting of Gold Prices -- 1 Introduction -- 2 Related Works -- 2.1 BiLSTM Overview -- 2.2 Variation Mode Decomposition -- 2.3 Metaheuristics Optimization -- 3 Methods -- 3.1 Overview of Basic Moth Flame Optimizer Algorithm -- 3.2 Modified MFO -- 4 Experiments and Discussion -- 4.1 Dataset -- 4.2 Experimental Setup -- 4.3 Results and Discussion -- 5 Conclusion -- References -- Improvised Neural Machine Translation Model for Hinglish to English -- 1 Introduction -- 2 Literature Review. ; 2.1 Sequence-to-Sequence (STS) -- 2.2 Attention (ATT) Model -- 3 Methodology -- 3.1 Dataset -- 3.2 Processing Data -- 3.3 Proposed System -- 4 Results -- 5 Discussion -- 5.1 No Smoothing -- 5.2 Laplace Smoothing -- 5.3 Additive Smoothing -- 5.4 Exponential Smoothing -- 5.5 Chen and Cherry Smoothing -- 6 Conclusion -- References -- Recording of Class Attendance Using DL-Based Face Recognition Method -- 1 Introduction -- 2 Related Work -- 3 Proposed System -- 3.1 Dataset Creation -- 3.2 Preprocessing -- 3.3 Face Detection and Recognition -- 3.4 Attendance Marking and Report Generation -- 3.5 Implementation -- 4 Result Analysis -- 5 Conclusions -- References -- Machine Learning Enabled Hairstyle Recommender System Using Multilayer Perceptron -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Data Preprocessing -- 3.3 Facial Landmark Detection -- 3.4 Face Shape Classification -- 3.5 Model Comparison -- 3.6 Recommendation -- 4 Results and Discussion -- 5 Conclusion -- References -- Automated Health Insurance Management Framework with Intelligent Fraud Detection, Premium Prediction, and Risk Prediction -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Dataset Specifics -- 3.2 Exploratory Data Analysis -- 3.3 Feature Engineering and Selection -- 3.4 Machine Learning Models -- 4 Experimental Results and Discussion -- 5 Conclusion and Future Work -- References -- Responsible Artificial Intelligence for Music Recommendation -- 1 Introduction -- 2 Background and Motivation -- 3 Literature Review -- 3.1 Identifying Research Gaps in the Literature -- 3.2 Contributions of This Paper -- 4 Methodology -- 4.1 Data Acquiring and EDA -- 4.2 Model Development and Evaluation -- 4.3 Feature Importance and Model Retrain -- 4.4 Explainable AI -- 5 Results -- 6 Conclusion -- 7 Future Work -- References. ; A Robot Mapping Technique for Indoor Environments.
• Titolo autorizzato: Data Science and Applications
• ISBN: 981-9978-62-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910838288103321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Networks and Systems Series