12701nam 22007935 450 991083100800332120240202094912.03-031-50993-510.1007/978-3-031-50993-3(MiAaPQ)EBC31129495(Au-PeEL)EBL31129495(DE-He213)978-3-031-50993-3(EXLCZ)993031511640004120240202d2024 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierComputational Sciences and Sustainable Technologies[electronic resource] First International Conference, ICCSST 2023, Bangalore, India, May 8–9, 2023, Revised Selected Papers /edited by Sagaya Aurelia, Chandra J., Ashok Immanuel, Joseph Mani, Vijaya Padmanabha1st ed. 2024.Cham :Springer Nature Switzerland :Imprint: Springer,2024.1 online resource (516 pages)Communications in Computer and Information Science,1865-0937 ;1973Print version: Aurelia, Sagaya Computational Sciences and Sustainable Technologies Cham : Springer International Publishing AG,c2024 9783031509926 Intro -- Preface -- Acknowledgements -- Organization -- Contents -- Performance Evaluation of Metaheuristics-Tuned Deep Neural Networks for HealthCare 4.0 -- 1 Introduction -- 2 Background and Related Works -- 3 Methods -- 3.1 Original Sine Cosine Algorithm (SCA) -- 3.2 SCA Bat Search Algorithm (SCA-BS) -- 4 Experiments and Comparative Analysis -- 4.1 Liver Disorder Dataset Details -- 4.2 Dermatology Dataset Details -- 4.3 Hepatitis Dataset Details -- 4.4 Experimental Setup -- 4.5 Evaluation Metrics -- 5 Results and Discussion -- 5.1 Liver Disorder Dataset Results -- 5.2 Dermatology Dataset Results -- 5.3 Hepatitis Dataset Results -- 6 Conclusion -- References -- Early Prediction of At-Risk Students in Higher Education Institutions Using Adaptive Dwarf Mongoose Optimization Enabled Deep Learning -- 1 Introduction -- 2 Motivation -- 2.1 Literature Survey -- 2.2 Major Challenges -- 3 Proposed ADMOADNFN for Prediction At-Risk Students -- 3.1 Data Acquisition -- 3.2 Data Transformation -- 3.3 Feature Selection -- 3.4 Data Augmentation (Oversampling) -- 3.5 Performance Prediction to Determine at Risk Students -- 4 Results and Discussion -- 4.1 Experimental Results -- 4.2 Dataset Description -- 4.3 Evaluation Metrics -- 4.4 Comparative Techniques -- 4.5 Comparative Discussion -- 5 Conclusion -- References -- Decomposition Aided Bidirectional Long-Short-Term Memory Optimized by Hybrid Metaheuristic Applied for Wind Power Forecasting -- 1 Introduction -- 2 Related Works -- 2.1 Variational Mode Decomposition VMD -- 2.2 Bidirectional Long Short-Term Memory (BiLSTM) -- 2.3 Metaheuristics Optimization -- 3 Methods -- 3.1 Original Reptile Search Algorithm (RSA) -- 3.2 Hybrid RSA (HRSA) -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Metrics -- 4.3 Setup -- 5 Results and Discussion -- 6 Conclusion -- References.Interpretable Drug Resistance Prediction for Patients on Anti-Retroviral Therapies (ART) -- 1 Introduction -- 2 Background and Motivation -- 3 Literature Review -- 3.1 Research Gaps -- 3.2 Paper Contributions -- 4 Data Analysis and Methods -- 4.1 Dataset Description -- 4.2 Data Preparation and Exploratory Data Analysis -- 4.3 Methodology -- 4.4 Model Evaluation -- 4.5 Feature Importance -- 5 Results and Discussion -- 5.1 ML Model Selection and Optimization -- 5.2 ML Model Selection Accountability -- 6 Conclusion and Future Works -- References -- Development of a Blockchain-Based Vehicle History System -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Design -- 4.1 Manufacturer-Dealer Workflow -- 4.2 Vehicle Sale/ Registration Workflow -- 4.3 Vehicle Transfer Workflow -- 4.4 Vehicle Resale Workflow -- 5 Testing and Evaluation -- 6 Results and Discussion -- 7 Conclusions -- References -- Social Distancing and Face Mask Detection Using YOLO Object Detection Algorithm -- 1 Introduction -- 2 Related Works -- 3 Relevant Methodologies -- 3.1 Convolutional Neural Network (CNN) -- 3.2 Object Detection -- 3.3 YOLO Object Detection Model -- 3.4 Faster R-CNN -- 3.5 Single-Shot Detector (SSD) -- 3.6 AlexNet -- 3.7 Inception V3 -- 3.8 MobileNet -- 3.9 Visual Geometry Group (VGG) -- 4 Implementation -- 4.1 Face Mask Detectıon -- 4.2 Socıal Dıstance Detectıon -- 5 Results -- 6 Conclusion and Future Scope -- References -- Review on Colon Cancer Prevention Techniques and Polyp Classification -- 1 Introduction -- 1.1 Objectives -- 2 Design -- 3 Setting and Participants -- 4 Methods -- 5 Results -- 6 Conclusion and Implications -- References -- Security Testing of Android Applications Using Drozer -- 1 Introduction -- 2 Methodology -- 2.1 Online Questionnaire -- 2.2 Emulation of Penetration Testing -- 3 Implementation -- 3.1 Retrieving Package Information.3.2 Identifying the Attack Surface -- 3.3 Identifying and Launching Activities -- 3.4 Exploiting Content Providers -- 3.5 Interacting with Services -- 3.6 Listing Broadcast Receivers -- 4 Results and Discussion -- 4.1 Questionnaire Results and Discussion -- 4.2 Vulnerability Testing Results -- 5 Conclusions -- References -- Contemporary Global Trends in Small Project Management Practices and Their Impact on Oman -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 Results and Discussion -- 4.1 Participants -- 5 Conclusion -- References -- Early Prediction of Sepsis Using Machine Learning Algorithms: A Review -- 1 Introduction -- 1.1 Description of Sepsis -- 1.2 Challenges -- 2 Methodology -- 2.1 Pathogenesis -- 2.2 Host Response -- 2.3 Analysis and Selection of Patients -- 2.4 Collection of Data -- 2.5 Data Imputation -- 3 Model Design and Technique -- 3.1 Gradient Boosting -- 3.2 Random Forest Model -- 3.3 Support Vector Machine -- 3.4 XG Boost Algorithm -- 4 Conclusion -- References -- Solve My Problem-Grievance Redressal System -- 1 Introduction -- 2 Literature Review -- 3 Problem Statement -- 4 Existing Systems -- 5 Proposed System -- 6 Implementation -- 7 Conclusion -- References -- Finite Automata Application in Monitoring the Digital Scoreboard of a Cricket Game -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Tracking of On-Strike Batsman -- 3.2 Ball Tracking in an Over -- 4 Results/Discussion -- 5 Conclusion -- References -- Diabetes Prediction Using Machine Learning: A Detailed Insight -- 1 Introduction -- 2 Identification of Symptoms for Diabetes Prediction -- 3 Feature Analysis -- 4 Comparative Analysis of Different ML Algorithms in Diabetes Onset Prediction -- 5 Conclusion -- References -- Empirical Analysis of Resource Scheduling Algorithms in Cloud Simulated Environment -- 1 Introduction -- 2 Literature Review.3 EA of the Results and Their Implications -- 3.1 EA Concerning A.S.T -- 3.2 EA Concerning A.C.T -- 3.3 EA Concerning A.T.A.T -- 3.4 EA Concerning A.C -- 4 Improving Resource Scheduling Using Intelligence Mechanism -- 5 Conclusion -- References -- A Recommendation Model System Using Health Aware- Krill Herd Optimization that Develops Food Habits and Retains Physical Fitness -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Architecture of RecSys -- 3.2 Krill Herd Algorithm for Optimization -- 3.3 Genetic Operators -- 3.4 Recommendation System (Recsys) Using KHO Algorithm -- 3.5 Evaluation of Fitness Value -- 4 Results and Analysis -- 4.1 Quantitative Analysis -- 4.2 Qualitative Analysis -- 5 Conclusion -- References -- Video Summarization on E-Sport -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 3.1 Flow Diagram -- 3.2 Algorithmic Steps -- 4 Implementation -- 5 Results -- 6 Conclusion -- References -- SQL Injection Attack Detection and Prevention Based on Manipulating the SQL Query Input Attributes -- 1 Introduction -- 2 SQL-Injection Attacks -- 3 Work Model of SQL Injection -- 4 Related Work -- 5 Proposed Work -- 5.1 Proposed Algorithm for Replacing Special String Constraints Instead of Input Parameter -- 5.2 Levenshtein Method -- 6 Implementation -- 7 Conclusion and Future Work -- References -- Comparative Analysis of State-of-the-Art Face Recognition Models: FaceNet, ArcFace, and OpenFace Using Image Classification Metrics -- 1 Introduction -- 2 Problem Statement -- 3 Literature Review -- 3.1 Convolutional Neural Networks -- 3.2 FaceNet -- 3.3 ArcFace -- 3.4 OpenFace -- 3.5 RetinaFace -- 4 Design Methodology -- 4.1 Face Extraction by RetinaFace -- 4.2 Vectorization by FaceNet, ArcFace and OpenFace -- 4.3 Results -- 4.4 Loss Functions -- 5 Conclusion -- References.Hash Edward Curve Signcryption for Secure Big Data Transmission -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Theil-Sen Robust Linear Regression -- 3.2 Pseudoephemeral Kupyna HashEdward-Signcryption-Based Secure Data Transmission -- 4 Assessment Settings -- 5 Performance Comparison -- 6 Conclusion -- References -- An Energy Efficient, Spontaneous, Multi-path Data Routing Algorithm with Private Key Creation for Heterogeneous Network -- 1 Introduction -- 1.1 Difficulties in Formation of a Heterogeneous Network -- 2 Literature Survey -- 2.1 Contribution of Proposed Research Mechanism -- 3 Intelligent Swarm Adapted Colony Based Optimization Methodology -- 4 Spontaneous Energy Proficient Multi-path Data Routing (SEPMDR) -- 4.1 Formation of Basic Network Metrics -- 4.2 Algorithm 1 for SEPMDR -- 4.3 Algorithm 2 for Private Key Creation -- 4.4 Operational Phases of SEPMDR -- 5 Performance Evaluation and Its Results -- 5.1 Power Conservation of Nodes -- 5.2 Comparison of Packet Delivery Ratio (PDR) of the Proposed System -- 5.3 Evaluation of Routing Overhead of the Different Methodologies -- 5.4 Comparison of Network Throughput -- 6 Conclusion and Future Scope -- References -- A Hybrid Model for Epileptic Seizure Prediction Using EEG Data -- 1 Introduction -- 1.1 Organization -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Preprocessing of EEG signals -- 3.2 Feature Extraction -- 3.3 Classification -- 4 Performance Analysis -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Performance Analysis -- 5 Conclusion -- References -- Adapting to Noise in Forensic Speaker Verification Using GMM-UBM I-Vector Method in High-Noise Backgrounds -- 1 Introduction -- 2 Data Acquisition -- 3 Feature Extraction -- 4 Mel-Frequency Cepstral Coefficients (MFCC) -- 5 Speaker Verification System Using GMM-UBM I Vector Frame Work.6 Modified Feature Extraction for Noise Adapting.This book constitutes the revised selected papers of the First International Conference, ICCSST 2023, held in Bangalore, India, during May 8–9, 2023. The 39 full papers included in this volume were carefully reviewed and selected from 200 submissions. They focus on artificial intelligence, blockchain technology, cloud computing, cyber security, data science, e-commerce, computer architecture, image and video processing, pandemic preparedness and digital technology, pattern recognition and classification.Communications in Computer and Information Science,1865-0937 ;1973Artificial intelligenceDatabase managementMachine learningApplication softwareComputer engineeringComputer networksArtificial IntelligenceDatabase Management SystemMachine LearningComputer and Information Systems ApplicationsComputer Engineering and NetworksComputer Communication NetworksArtificial intelligence.Database management.Machine learning.Application software.Computer engineering.Computer networks.Artificial Intelligence.Database Management System.Machine Learning.Computer and Information Systems Applications.Computer Engineering and Networks.Computer Communication Networks.006.3Aurelia Sagaya1680150J Chandra1680151Immanuel Ashok1680152Mani Joseph1680153Padmanabha Vijaya1680154MiAaPQMiAaPQMiAaPQBOOK9910831008003321UNINA