Machine Intelligence for Research and Innovations : Proceedings of MAiTRI 2023, Volume 1

• Autore: Verma Om Prakash
• Pubblicazione: Singapore : , : Springer, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (351 pages)
• Disciplina: 006.3
• Altri autori: WangLipo KumarRajesh YadavAnupam
• Nota di contenuto: Intro -- Preface -- Contents -- Editors and Contributors -- A Simple Algorithm to Secure Data Dissemination in Wireless Sensor Network -- 1 Introduction -- 2 Related Works -- 3 Proposed Encryption Algorithm -- 3.1 Illustration of Proposed Encryption and Decryption -- 4 Results and Discussion -- 5 Conclusion -- References -- Analysis of Pollard Rho Attacks Over ECDLP -- 1 Introduction -- 1.1 Motivation -- 2 Pollard Rho Algorithm -- 2.1 Sequential -- 2.2 Solving for ECDLP Using Parallel Architecture -- 2.3 Experimental Results and Discussion -- 3 Conclusion and Future Direction -- References -- Modelling Networks with Attached Storage Using Perfect Italian Domination -- 1 Introduction -- 2 Perfect Italian Domination of the Join of Two Graphs -- 3 Perfect Italian Domination of the Corona Product -- 4 Conclusion -- References -- Application of Varieties of Learning Rules in Intuitionistic Fuzzy Artificial Neural Network -- 1 Introduction -- 2 Artificial Neural Network and Learning Rules -- 3 ANN Approach to Group Decision-Making with Intuitionistic Fuzzy Information -- 4 Numerical Illustration: Decision-Making of a Customer with Online Shopping -- 5 Numerical Illustration of Solving MAGDM Problem Using ANN with Delta Method and Hidden Layer -- 6 Discussion -- 7 Conclusion -- References -- Automated Tool for Toxic Comments Identification on Live Streaming YouTube -- 1 Introduction -- 2 Related Research -- 3 Methodology -- 4 Experiments -- 4.1 Data Collection -- 4.2 Text Cleaning and Tokenization -- 4.3 Vectorization and Feature Extraction -- 4.4 Model Training -- 4.5 Model Evaluation -- 4.6 Deploying Model -- 5 Implementation -- 6 Results -- 7 Conclusion and Future Work -- References -- Directional Edge Coding for Facial Expression Recognition System -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Compass Masks. ; 3.2 Directional Attributes -- 3.3 Encoding -- 4 Simulation Experiments -- 4.1 Database -- 4.2 Performance Metrics -- 4.3 Results -- 5 Conclusion -- References -- A Cascaded 2DOF-PID Control Technique for Drug Scheduling of Chemotherapy System -- 1 Introduction -- 2 Mathematical Modeling -- 3 Controller Design -- 3.1 Design of Two Degree of Freedom-Proportional-Integral-Derivative (2DOF-PID) Controller -- 3.2 Optimization of Controller Parameters -- 4 Simulation and Results -- 4.1 Uncertainty Analysis -- 5 Conclusion -- References -- Distinguishing the Symptoms of Depression and Associated Symptoms by Using Machine Learning Approach -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset Overview -- 4 Methods Used -- 4.1 Decision Tree Classifier -- 4.2 Random Forest -- 4.3 Stacking -- 4.4 Logistic Regression -- 4.5 K-Nearest Neighbor -- 4.6 Support Vector Machine -- 5 Results -- 6 Conclusion -- References -- Harnessing the Power of Machine Learning Algorithms for Landslide Susceptibility Prediction -- 1 Introduction -- 2 Methodology -- 2.1 Geographical Area -- 2.2 Dataset and Preprocessing -- 2.3 Model Description -- 2.4 Evaluation Metrics -- 3 Experimental Results and Analysis -- 4 Conclusion -- References -- The Effectiveness of GPT-4 as Financial News Annotator Versus Human Annotator in Improving the Accuracy and Performance of Sentiment Analysis -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Corpus -- 3.2 Prompt -- 3.3 GPT-4 -- 3.4 Manual Annotation -- 3.5 GPT Annotation -- 3.6 Experiment -- 3.7 Accuracy -- 4 Conclusion -- 5 Recommendation for Future Studies -- 6 Declaration of Generative AI and AI-Assisted Technologies in the Writing Process -- References -- Machine Learning Method for Analyzing and Predicting Cardiovascular Disease -- 1 Introduction -- 2 Working Model -- 2.1 Collection of Datasets. ; 2.2 Preprocessing Data -- 3 Literature Survey -- 4 Result -- 5 Conclusion -- References -- Rule-Based Learner Competencies Predictor System -- 1 Introduction -- 2 Related Works -- 3 Proposed Model -- 3.1 Rubric Creation -- 3.2 Quiz Conduction for Learners -- 3.3 Partial Scoring According to the Rubric -- 3.4 Learner Categorization Based on Clusters -- 3.5 Rules Generation Using Classification -- 4 Conclusion -- References -- Exploring the Relationship Between Digital Engagement and Cybersecurity Practices Among College Students: A Survey Study -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Research Design and Approach -- 3.2 Sampling Technique and Sample Size Determination -- 3.3 Data Collection Instrument (Survey Questionnaire) and Its Development -- 3.4 Measures and Operationalization of Digital Engagement and Cybersecurity Practices -- 3.5 Data Analysis Techniques -- 4 Data Analysis -- 5 Discussion -- 6 Conclusion -- References -- Secure and Energy Efficient Routing in VANETs Using Nature Inspired Hybrid Optimization -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Fitness Function -- 3.2 Proposed Hybrid Optimization Algorithm -- 4 Results and Analysis -- 5 Conclusion -- References -- Performance Evaluation of Machine Learning Models for Intrusion Detection in Wireless Sensor Networks: A Case Study Using the WSN DS Dataset -- 1 Introduction -- 2 Related Works -- 3 Machine Learning Models Considered -- 4 Dataset Description, Results, Discussions, and Performance Evaluation -- 4.1 Performance Metrics -- 4.2 Results, Discussions, and Performance Evaluation -- 5 Conclusion -- References -- Arduino Controlled 3D Object Scanner and Image Classification -- 1 Introduction -- 2 Methodology -- 2.1 A System Overview -- 2.2 Image Classification -- 2.3 2D Image to 3D Mesh Reconstruction -- 3 Mathematical Analysis. ; 3.1 3D Scanner Design -- 3.2 Texture Analysis Using Gabor Features -- 4 Result and Discussion -- 5 Conclusion -- References -- Anomaly Detection for IoT-Enabled Kitchen Area Network Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 MQTT Broker-Based Anomaly Detection Model -- 3.2 KNN-Based Machine Leaning Model -- 3.3 Data Pre-processing -- 3.4 Label Defining and Mapping IoT Network Traces -- 3.5 Resolving the Imbalance Data Problem -- 3.6 Features Selection and Extraction -- 3.7 Training and Testing -- 4 Experimental Setup -- 4.1 IoT-Flock Framework -- 4.2 MQTT Broker -- 4.3 IoT Network Traffic Sniffer -- 4.4 Kitchen Area Network (KAN) Use-Case Creation -- 4.5 Normal Traffic Generation -- 4.6 Malicious Traffic Generation -- 5 Performance Evaluation -- 6 Conclusion and Future Directions -- References -- Character-Level Bidirectional Sign Language Translation Using Machine Learning Algorithms -- 1 Introduction -- 2 Literature Survey -- 3 Dataset and Methods -- 3.1 Dataset -- 3.2 Sign to Text Translation -- 3.3 Text to Sign Translation -- 4 Results -- 5 Conclusion -- 6 Future Scope -- References -- Enhancing Performance of Noise-Robust Gujarati Language ASR Utilizing the Hybrid Acoustic Model and Combined MFCC + GTCC Feature -- 1 Introduction -- 2 Literature Review -- 3 Proposed Method -- 3.1 Dataset Preparation -- 3.2 Speech Feature Extraction -- 3.3 CNN-BiGRU Hybrid Acoustic Architecture -- 3.4 Text Decoding -- 4 Experiment Setup and Results -- 4.1 Multi-person ASR Performance Analysis -- 4.2 Multi-person Model Loss Graph -- 4.3 Comparison of Proposed Methods with Existing Works -- 5 Conclusion -- References -- Random Forest (RF) Assisted and Support Vector Machine (SVM) Algorithms for Performance Evaluation of EDM Interpretation -- 1 Introduction -- 2 Methodology -- 2.1 Support Vector Machine (SVM). ; 2.2 Random Forest (RF) -- 2.3 Proposed Approach -- 3 Results -- 3.1 Accuracy -- 3.2 Recall -- 3.3 Precision -- 3.4 F1 Score -- 4 Discussion and Conclusion -- References -- COVID-19 Classification of CT Lung Images Using Intelligent Wolf Optimization Based Deep Convolutional Neural Network -- 1 Introduction -- 1.1 Challenges -- 2 Proposed Methodology -- 2.1 Data Collection -- 2.2 Image Pre-processing -- 2.3 Feature Extraction -- 2.4 Intelligent Wolf Optimization Based Deep CNN Classifier for COVID-19 Classification Using the Texture CT Features -- 2.5 Mathematical Modeling of the Intelligent Wolf Optimization -- 3 Experimental Setup and Results -- 3.1 Comparative Analysis -- 4 Conclusion -- References -- Parallelization of Molecular Dynamics Simulations Using Verlet Algorithm and OpenMP -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Organization -- 2 Literature Review -- 3 Proposed Research -- 3.1 Working Methodology -- 3.2 Computation of Atomic Forces -- 4 Experiment Result and Analysis -- 5 Conclusion -- References -- Prediction of HDFC Bank Stock Price Using Machine Learning Techniques -- 1 Introduction -- 2 Dataset Description -- 3 Experiments and Result Analysis -- 3.1 System Architecture -- 3.2 Visualizations -- 4 Conclusion -- References -- Real-Time Applicability Analysis of Lightweight Models on Jetson Nano Using TensorFlow-Lite -- 1 Introduction -- 2 Background -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- An Efficient Fog Computing Platform Through Genetic Algorithm-Based Scheduling -- 1 Introduction -- 2 System Model -- 2.1 System Environment -- 2.2 Application Environment -- 2.3 Optimization Goal -- 3 Methodology -- 3.1 Genetic Algorithm-Based Scheduler. -- 4 Experimental Evaluation -- 4.1 Dataset Description -- 4.2 Performance Metrics -- 5 Conclusion and Future Work -- References. ; Development of a Pixhawk-Based Quadcopter: A Bottom-Up Approach.
• Titolo autorizzato: Machine Intelligence for Research and Innovations
• ISBN: 981-9981-29-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910842300203321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Networks and Systems Series