10865nam 22004933 450 991084707700332120240405084504.0981-9701-80-5(MiAaPQ)EBC31246345(Au-PeEL)EBL31246345(CKB)31326334900041(MiAaPQ)EBC31266939(Au-PeEL)EBL31266939(EXLCZ)993132633490004120240405d2024 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierProceedings of International Joint Conference on Advances in Computational Intelligence Ijcaci 20231st ed.Singapore :Springer Singapore Pte. Limited,2024.©2024.1 online resource (797 pages)Algorithms for Intelligent Systems Series981-9701-79-1 Intro -- Preface -- Contents -- About the Editors -- 1 Conversational Swarm Intelligence (CSI) Enhances Groupwise Deliberation -- 1 Introduction -- 2 Conversational Swarm Intelligence (CSI) -- 3 Experimental Study -- 4 Results -- 5 Conclusions -- References -- 2 Enhancing Biometrics with Auto Encoder: Accurate Finger Detection from Fingerprint Images -- 1 Introduction -- 2 Related Study -- 3 Proposed Method -- 3.1 Work Flow -- 3.2 Proposed Model -- 4 Result and Discussion -- 4.1 Dataset -- 4.2 Model Training and Testing -- 4.3 Model Performance Analysis -- 5 Conclusion -- References -- 3 Minimization of Structural Systems Eccentricity by Means of the Imperialist Competitive Algorithm -- 1 Introduction -- 2 Minimization of Structural Eccentricity -- 2.1 Problem Formulation -- 2.2 Optimization Algorithm -- 3 Numerical Test Case -- 4 Structural Design Based on Design Codes -- 5 Design Based on the Minimization Problem of Torsional Response -- 5.1 Eccentricities of the Initial and Improved Structural System Using KANEPE -- 5.2 Stiffness Eccentricity Minimization Problem -- 5.3 Strength Eccentricity Minimization Problem -- 6 Conclusions -- References -- 4 Toward Early Detection of Neonatal Birth Asphyxia Utilizing Ensemble Machine Learning Approach -- 1 Introduction -- 2 Methodology -- 2.1 Dataset Description -- 2.2 Audio Sampling -- 2.3 Feature Extraction -- 2.4 Machine Learning Classifier -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- 5 Data Hiding System Based on Variations in Image Interpolation Algorithms -- 1 Introduction -- 2 Problem Statement -- 3 Literature Survey -- 4 Proposed Model -- 4.1 Overview -- 4.2 Embedding Technique -- 4.3 Extraction Methodology -- 4.4 Perceptual Distortion Function -- 4.5 Experimental Setup -- 4.6 Evaluation Metrics -- 4.7 Working -- 5 Results and Discussion -- 6 Conclusion -- 7 Future Scope.References -- 6 Fault Assessment and Early Performance Prediction of PV Module Using Machine Learning -- 1 Introduction -- 2 Anisotropic Diffusion Filter and Image Segmentation -- 3 Internet of Things (IoT)-Based Micro crack Detection -- 4 Electroluminescence Images and Machine Learning for Crack Identification -- 5 Crack Detection Using Complex Wavelet Transform and ANFIS Classification Method -- 5.1 Transfer Learning-Based Approach -- 6 Conclusion -- References -- 7 Speeding Classification by a Deep Learning Audio Analysis System Optimized by the Reptile Search Algorithm -- 1 Introduction -- 2 Related Works and Preliminaries -- 2.1 Deep Neural Networks -- 2.2 Metaheuristic Optimization -- 3 Methods -- 3.1 Reptile Search Algorithm -- 3.2 Modified RSA -- 4 Experimental Setup -- 4.1 Dataset Description -- 4.2 Metrics -- 4.3 Simulation Setup -- 5 Experiments Outcomes -- 6 Conclusion -- References -- 8 Exploring Sentiments in Text: A Survey of Implicit and Explicit Aspect-Based Sentiment Analysis -- 1 Introduction -- 2 Literature Review -- 3 Implicit and Explicit Sentiment Analysis -- 3.1 Terminology and Attributes -- 3.2 Data Requirements -- 3.3 Intricacy and Generalization -- 3.4 Methodologies and Techniques -- 3.5 Techniques Employed -- 3.6 Benefits -- 3.7 Techniques Utilized -- 3.8 Future Research Directions -- 3.9 Performance, Advantages, and Limitations of ABSA -- 4 Conclusion -- References -- 9 A Comprehensive Review on Prediction of Blood Glucose Level in Type 1 Diabetic Using Machine Learning Techniques -- 1 Introduction -- 2 Modeling Approach -- 3 Data Collection and Processing -- 3.1 Data Collection -- 3.2 Processing -- 4 Glucose Prediction Model -- 4.1 Data-Driven Model with CGM Data Only -- 4.2 Data-Driven Model with CGM Data and Additional Input Features -- 4.3 Hybrid Model with CGM and Additional Features -- 5 Discussion -- 6 Conclusion.References -- 10 Effect of Phosphorylation on the Circadian Clock of Drosophila by Analytical and Graph Theory Matrix Approach -- 1 Introduction -- 2 Mathematical Modelling -- 3 Analytical Expression Using Homotopy Perturbation Method -- 4 Graph Theory Matrix Approach -- 5 Effects of Kinetic Parameter from Graph Theory Matrix Approach -- 6 Matrix Representation of Structure Graph -- 7 Discussion -- 7.1 Effects of Kinetic Parameter from Analytical Expression by HPM -- References -- 11 Exploiting Deep Learning Techniques for Autistic Face Recognition -- 1 Introduction -- 2 Dataset Description -- 3 Introduction of VGG16 and EfficientNet and DenseNet Model -- 4 Comparison Analysis of Pre-trained Models -- 5 Conclusion and Future Work -- References -- 12 A Comprehensive Review of Migration of Big Data Applications to Public Clouds: Current Requirements, Types, Strategies, and Case Studies -- 1 Introduction -- 1.1 Motivation for Review -- 1.2 History of Data Migration -- 2 Related Works -- 3 Types of Strategies for Cloud Data Migration -- 4 Latest Advancements in Big Data Migration -- 5 Case Studies on Data Migration Services Offered by Popular Public Cloud Environments -- 6 Conclusion -- References -- 13 Potato Leaf Disease Detection and Classification Using VGG16 -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 3.1 Architecture -- 3.2 Transfer Learning -- 3.3 VGG 16 Architecture -- 4 Modules -- 4.1 Image Processing -- 4.2 Data Splitting -- 4.3 Feature Extraction -- 4.4 Data Classification -- 4.5 Testing -- 5 Results -- 6 Conclusion -- References -- 14 Assessing Student Engagement Levels Using Speech Emotion Recognition -- 1 Introduction -- 2 Literature Review -- 2.1 Importance of Understanding Student Emotions -- 2.2 Implementation Aspects of SER -- 2.3 Features Considered for SER -- 2.4 Databases Referred by Studies.2.5 The Conclusion from Literature Review -- 3 Methodology -- 3.1 Data Acquisition -- 3.2 Data Preprocessing and Exploratory Analysis -- 3.3 Feature Extraction -- 3.4 Building SER Models Using Machine Learning and Deep Learning -- 4 Results and Analysis -- 4.1 Machine Learning-Based Models -- 4.2 Deep Learning-Based Models -- 5 Conclusion and Future Scope -- References -- 15 K-Means Clustering and Support Vector Machine for Assamese Dialect Identification -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 3.1 Feature Extraction -- 3.2 K-Means Clustering -- 3.3 Feature Classification -- 4 Experimental Setup -- 4.1 Speech Database -- 5 Result and Discussion -- 6 Conclusion -- References -- 16 Emotion Recognition in Speech Using Convolutional Neural Networks (CNNs) -- 1 Introduction -- 2 Literature Survey -- 3 System Model -- 3.1 Dataset Being Used for the Work -- 3.2 Feature Extraction Methods -- 3.3 The CNN Model -- 4 Proposed Methodology -- 4.1 Data Augmentation -- 4.2 Data Pre-processing and Feature Extraction -- 4.3 Model Parameters -- 5 Experimental Results -- 6 Conclusion -- References -- 17 Single Value Neutrosophic Virtual Machine Resources Optimization -- 1 Introduction -- 2 Neutrosophic Virtual Machine Resource Optimization for Tasks Load Distribution -- 3 Experimental Discussions -- 4 Comparison Between Existing Approaches with Proposed Framework -- 5 Conclusion -- References -- 18 Route Selection in Multimodal Transport Networks Incorporating Disruption -- 1 Introduction -- 2 Literature Review -- 3 Problem Formulation -- 3.1 Pareto Optimality -- 3.2 Tiered Table -- 4 Multimodal Freight Route Selection via Tiered Table -- 4.1 Step 1: Formulating the Multi-objective Problem -- 4.2 Step 2: Obtaining Series of Possible Routes from Origin to Destination -- 4.3 Step 3: Processing MCS Results.4.4 Step 4: Populating the n n -tiered table -- 4.5 Lemma -- 4.6 Step 5: Interrogating the n-tiered Table -- 5 Numerical Case Study -- 6 Results -- 6.1 Case 1 -- 6.2 Case 2 -- 6.3 Case 3 -- 6.4 Case 4 -- 7 Discussion -- 8 Conclusion -- References -- 19 A Smart Surveillance System to Detect Modern Gun Using YOLOv5 Algorithm: A Deep Learning Approach -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset Explanation -- 3.2 Dataset Preprocessing -- 3.3 YOLOv5 Implementation for Gun Detection -- 4 Experiment Results -- 5 Conclusion -- References -- 20 A Comparative Analysis of Models for Dark Web Data Classification -- 1 Introduction -- 2 Related Work -- 2.1 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preparation -- 3.3 Model Training -- 4 Results -- 4.1 Accuracy -- 4.2 Performance Measures -- 5 Conclusion -- References -- 21 Optimizing Cloud Computing Load Balancing Through Extended Ant Colony Optimization -- 1 Introduction -- 2 Literature Survey -- 3 Virtual Machine Allocation -- 3.1 Basic Ant Colony Algorithm -- 3.2 Extended Ant Colony Algorithm (EACA) -- 4 Results -- 5 Conclusion -- References -- 22 Computationally Efficient and Statistical Attack Resistant Image Encryption System for Smart Healthcare -- 1 Introduction -- 2 Literature Survey -- 3 Preliminaries -- 4 Proposed Algorithm -- 4.1 Generation of Control Parameters -- 4.2 Generation of Key Image Blocks and Indexed Sequences -- 4.3 Intra-row Confusion and Row-Wide Diffusion -- 4.4 Intra-column Confusion and Column-Wide Diffusion -- 4.5 Intra-row Confusion and Row-Wide Diffusion -- 5 Experimental Results -- 5.1 Key Space Analysis -- 5.2 Key Sensitivity Analysis -- 5.3 Information Entropy Analysis (IE) -- 5.4 Statistical Analysis -- 5.5 Differential Attack Analysis -- 5.6 Execution Time (ET) -- 5.7 Perception Analysis -- 6 Decryption Process.7 Conclusion.Algorithms for Intelligent Systems Series006.3Uddin Mohammad Shorif1369079Bansal Jagdish Chand1338605MiAaPQMiAaPQMiAaPQBOOK9910847077003321Proceedings of International Joint Conference on Advances in Computational Intelligence4154607UNINA