12317nam 22007215 450 991087899160332120240801130627.0981-9738-17-210.1007/978-981-97-3817-5(MiAaPQ)EBC31576133(Au-PeEL)EBL31576133(CKB)33587038400041(OCoLC)1450835500(DE-He213)978-981-97-3817-5(EXLCZ)993358703840004120240801d2024 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierInnovative Computing and Communications Proceedings of ICICC 2024, Volume 4 /edited by Aboul Ella Hassanien, Sameer Anand, Ajay Jaiswal, Prabhat Kumar1st ed. 2024.Singapore :Springer Nature Singapore :Imprint: Springer,2024.1 online resource (694 pages)Lecture Notes in Networks and Systems,2367-3389 ;1024981-9738-16-4 Intro -- Preface -- Steering Committee -- Contents -- Editors and Contributors -- Low Voice Speech Conversion Analysis Using Novel Convolutional Neural Network Compared with K-Nearest Neighbor with Enhanced Accuracy -- 1 Introduction -- 2 Materials and Methods -- 2.1 Convolutional Neural Networks -- 2.2 K-Nearest Neighbors -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- ML Models for Energy Efficiency in Office Buildings: A Comprehensive Comparative Analysis -- 1 Introduction -- 2 System Architecture -- 3 Study Method -- 4 Machine Learning Models -- 4.1 Logistic Regression -- 4.2 SVM -- 4.3 Decision Trees -- 4.4 Random Forest -- 4.5 Gradient Bossting -- 4.6 Multi-layer Perceptron (MLP) -- 5 Comparison of ML Models -- 5.1 Learning Curve -- 5.2 Validation Curve -- 6 Conclusion -- References -- Breast Cancer Prediction and Detection: Comparison of the Latest Machine Learning Techniques -- 1 Introduction -- 1.1 Contribution and Novelty -- 1.2 Limitations -- 2 Literature Review -- 2.1 Embryonic Stages-Texture Analysis -- 2.2 Deep Learning-A New Dawn -- 2.3 Transfer Learning-Bridging Past and Present -- 2.4 Computer-Aided Diagnosis (CAD)-The Modern Frontier -- 2.5 A Departure-Embracing Artificial Intelligence in a Novel Manner -- 2.6 Support Vector Machines (SVMs) -- 2.7 Deep Learning Advancements -- 3 Research Design and Methodology -- 3.1 Dataset -- 3.2 Algorithm Selection and Model Design -- 3.3 Machine Learning Framework and Tools -- 3.4 Infrastructure Limitations -- 3.5 Ethical Considerations -- 4 Results and Discussion -- 4.1 Machine Learning Algorithm -- 4.2 CNNs -- 4.3 ResNet -- 4.4 VGGNet -- 5 Conclusion and Future Works -- 5.1 Future Works -- References -- GIS-Based Identification and Representation of Particulate Matters Using Ontology and SPARQL -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods.3.1 Description of the Case Study -- 3.2 Field Study -- 3.3 Equipment Used in the Investigation -- 4 Proposed System -- 4.1 Creation of Knowledge Base in the Form of Ontology -- 4.2 Execution of SPARQL Query -- 5 Results and Discussion -- 5.1 PM 2.5 Concentration -- 5.2 PM 10 Concentration -- 6 Conclusion and Future Scope -- References -- Advancements in Arrhythmia Classification: A Comprehensive Survey of AI Techniques -- 1 Introduction -- 2 Related Work -- 3 Observations from the Literature -- 3.1 Conventional Machine Learning Methods -- 3.2 Deep Learning Models -- 3.3 Hybrid Techniques -- 3.4 Classification Techniques Application and Clinical Impact -- 4 Methodological Approach -- 4.1 Inclusion Criteria -- 4.2 Exclusion Criteria -- 4.3 Techniques Selection Criteria -- 4.4 Databases of ECG Datasets -- 5 Importance of Cardiac Arrhythmia Diagnosis Using Deep Learning -- 5.1 Automated Feature Learning in Deep Neural Networks -- 5.2 Addressing Challenges in ECG Signal Analysis -- 5.3 Handling Signal Variability -- 6 Challenges -- 7 Conclusion -- References -- Survey on VANET Authentication Scheme Based on Cryptographic Protocols -- 1 Introduction -- 1.1 Key Aspects of VANETs -- 1.2 Architecture of VANETs -- 1.3 Applications of VANETs -- 1.4 Privacy Issue of VANETs -- 2 Background Information -- 2.1 Traditional Digital Signature Scheme -- 2.2 Group Signature Scheme -- 2.3 Ring Signature Scheme -- 2.4 Conditional Privacy-Preserving Authentication Scheme (CPPA) -- 2.5 Blockchain-Based Authentication Schemes -- 3 Literature Survey -- 3.1 Traditional Digital Signature Scheme -- 3.2 Group Signature-Based Authentication Scheme -- 3.3 Ring Signature-Based Authentication Scheme -- 3.4 Threshold Signature-Based Authentication Scheme -- 3.5 Conditional Privacy-Preserving Authentication Scheme -- 4 Discussion -- 5 Conclusion and Future Work -- References.Exploring Machine Learning Models for Age Recognition -- 1 Introduction -- 2 Related Work -- 3 Material and Methods -- 3.1 Dataset -- 4 Building a Balance Dataset -- 4.1 Feature Extraction from the Image -- 5 Implementation of Age Detection Models -- 6 Evaluation and Model Performance -- 6.1 Comparison Using Confusion Matrix -- 6.2 Summary of the Performance of Three Models -- 6.3 Performance of the Convolutional Neural Networks -- 6.4 Summary of Supervise Learning Models -- 7 Conclusion -- 8 Future Works and Recommendations -- References -- Novel Authentication Scheme to Increase Security of Vehicular Ad Hoc Networks -- 1 Introduction -- 1.1 Security Architecture -- 1.2 Technologies for Security Improvement -- 2 Literature Review -- 3 Research Methodology -- 4 Result and Discussion -- 5 Conclusion -- References -- A Study on the Working of Swarm-Based Metaheuristic Algorithms Using Theoretical Framework -- 1 Introduction -- 2 Swarm Intelligence -- 3 Proposed Theoretical Framework -- 4 Swarm-Based Metaheuristic Algorithms -- 4.1 Spotted Hyena Optimization (SHO) [7] -- 4.2 Harris Hawk Optimization (HHO) [12] -- 4.3 Seagull Optimization Algorithm (SeOA) [8] -- 4.4 Sailfish Optimizer (SO) [29] -- 4.5 Sooty Tern Optimization Algorithm (STOA) [6] -- 4.6 Sandpiper Optimization Algorithm (SOA) [16] -- 4.7 Golden Eagle Optimizer (GEO) [22] -- 4.8 Northern Goshawk Optimization (NGO) [5] -- 4.9 Red Fox Optimization (RFO) [25] -- 4.10 Chameleon Swarm Algorithm (CSO) [2] -- 4.11 Gannet Optimization Algorithm (GOA) [24] -- 5 Limitations of the Proposed Framework -- 6 Challenges -- 6.1 Swarm Size -- 6.2 Exploration-Exploitation Trade-Off -- 6.3 Parameter Tuning Using Sensitivity Analysis -- 6.4 Applicability Toward Large-Scale Real-World Problems -- 6.5 Lack of Theoretical Understanding -- 7 Conclusion and Future Directions -- References.Financial Fortunes: A Stock Price Prediction Using LSTM -- 1 Introduction -- 2 Background -- 2.1 FINVIZ -- 2.2 Reddit API -- 3 Literature Review -- 4 System Design and Solution -- 4.1 Methods and Methodology -- 4.2 Algorithm -- 5 Implementation -- 6 Results and Discussion -- 7 Conclusions and Future Scope -- References -- Utilization of Data Mining in Spatial Analysis of Displacement Crisis in Iraq -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results and Discussion -- 4.1 Spatial Analysis of the Displacement Crisis in Iraq Between 2014 and 2017 -- 5 Conclusion and Future Scope -- References -- Integrating Multimodal Data for Parkinson's Disease Prediction: An Ensemble Approach -- 1 Introduction -- 2 Related Works -- 2.1 Application of CNNs for Advanced Drawing Analysis -- 2.2 The Synergy of AI and the Spiral Test for PD Diagnosis -- 2.3 AI-Driven Drawing Evaluation for Disease Detection -- 3 System Design -- 3.1 Parkinson's Disease Speech Dataset Analysis -- 3.2 Parkinson's Disease Drawings Dataset Analysis -- 3.3 Multimodal Ensemble Approach -- 4 Ensemble Method of Averaging -- 4.1 Drawing Dataset -- 4.2 Multimodal Ensemble Approach -- 5 Conclusion -- References -- Mental Health Assessment Using EEG Sensor and Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Utilization of Machine Learning for Heart Failure Prediction and Diagnosis -- 4 Datasets and Evaluation Metrics -- 5 Results and Discussion -- 6 Conclusion -- References -- Enhancing Patterns Accessibility for Visually Impaired Programmers -- 1 Introduction -- 2 Related Work -- 3 Development Process of Pattern Reader -- 3.1 Problem Identification -- 3.2 Design -- 4 Experiment Design -- 4.1 Procedure -- 4.2 Analysis -- 4.3 Result -- 4.4 Participant Experience -- 5 Future Work -- 6 Conclusion -- References.Lung and Colon Cancer Detection: Advancing Automated Diagnosis Through Deep Learning -- 1 Introduction -- 2 Literature Survey -- 3 LC25000: De-identified Lung and Colon Tissue Images for Cancer Research -- 4 Research Proposal -- 5 Scope and Objective of Research -- 6 Conclusion -- References -- Detection of Micro and Macro Nutrient Deficiency in Okra (Abelmoschus Esculentus L) Plant Leaves Using Machine Learning Approach -- 1 Introduction -- 2 Background -- 3 Work Plan -- 4 Results and Discussion -- 5 Future Scope -- 6 Conclusion -- References -- Empowering Aspiring Artists: A Machine Learning-Powered Carnatic Music Tutor -- 1 Introduction -- 2 Related Work -- 2.1 Raga Classification Methods -- 2.2 Other Audio Analysis Techniques -- 3 Proposed Methodology -- 3.1 Pre-processing -- 3.2 Note Identification -- 3.3 Raga Identification -- 3.4 Lyric Extraction -- 3.5 Video Generation -- 3.6 Evaluation -- 4 Experimental Results and Discussion -- 4.1 Note Identification -- 4.2 Raga Identification -- 4.3 Lyrics Extraction -- 5 Conclusion -- References -- Image Denoising Using Autoencoder: Utilizing Deep Learning and Autoencoder Techniques to Enhance Natural Images by Eliminating Noisy Pixels and Grains -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Dataset -- 3.2 Image Denoising Using CNN -- 3.3 Network Architecture -- 4 Experimental Results and Analysis -- 5 Conclusion -- References -- An IoT-Based Animal Health Monitoring System -- 1 Introduction -- 2 Background -- 3 Proposed Methodology -- 3.1 Block Diagram -- 3.2 Hardware Requirements -- 3.3 Software Requirements -- 4 Results -- 5 Conclusion -- References -- Experimental Analysis of Four Gamma Correction Variants on Brain Tumor Images -- 1 Introduction -- 2 Variants of Gamma Correction -- 2.1 Adaptive Gamma Correction Image Enhancement (AGCIE).2.2 Adaptive Gamma Correction and Color Preserving Framework (AGCCPF).This book includes high-quality research papers presented at the Seventh International Conference on Innovative Computing and Communication (ICICC 2024), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on 16–17 February 2024. Introducing the innovative works of scientists, professors, research scholars, students, and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.Lecture Notes in Networks and Systems,2367-3389 ;1024TelecommunicationCooperating objects (Computer systems)Internet of thingsArtificial intelligenceCommunications Engineering, NetworksCyber-Physical SystemsInternet of ThingsArtificial IntelligenceTelecommunication.Cooperating objects (Computer systems).Internet of things.Artificial intelligence.Communications Engineering, Networks.Cyber-Physical Systems.Internet of Things.Artificial Intelligence.621.382Hassanien Aboul Ella846730Anand Sameer1379088Jaiswal Ajay1379089Kumar Prabhat1758603MiAaPQMiAaPQMiAaPQBOOK9910878991603321Innovative Computing and Communications4196819UNINA