Proceedings of Fifth Doctoral Symposium on Computational Intelligence : DoSCI 2024, Volume 4

• Autore: Swaroop Abhishek
• Pubblicazione: Singapore : , : Springer, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (613 pages)
• Disciplina: 006.3
• Altri autori: KansalVineet FortinoGiancarlo HassanienAboul Ella
• Nota di contenuto: Intro -- DoSCI-2024 Steering Committee Members -- Preface -- Contents -- Editors and Contributors -- A Comprehensive Examination of Machine Learning Models in Predicting 16 Personality Traits -- 1 Introduction -- 2 Literature Review -- 3 Dataset -- 4 Implementation -- 5 Result and Discussion -- 6 Conclusion -- References -- A Historical Analysis of Chatbots from Eliza to Google Bard -- 1 Introduction -- 2 History -- 2.1 Early Chatbots (1960-2001) -- 2.2 Late Chatbots (2000-2010) -- 2.3 Modern Chatbots (2020-Present) -- 3 Chatbot Approaches -- 3.1 Rule-Based -- 3.2 Retrieval-Based -- 3.3 Generative-Based Approach -- 3.4 Hybrid-Based Approach -- 4 Large Language Model in ChatGPT and Google Bard -- 4.1 ChatGPT with GPT-3.5 -- 4.2 Google Bard with LaMDA -- 5 Chatbots Programming Languages and Summary of Chatbot Journey -- 6 Conclusion -- References -- A Cutting-Edge Approach to Forest Fire Region Identification Through Deep Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Proposed Approach -- 3.2 Image Pre-processing -- 4 Feature Extraction -- 4.1 Convolutional Neural Network -- 5 Image Classification -- 5.1 Visual Geometry Group-19 or VGG-19 -- 6 Object Detection -- 6.1 You Only Look Once (YOLOv6) -- 7 Spatial Feature Extraction -- 8 Temporal Feature Extraction -- 9 Discussion -- 9.1 Dataset Description -- 10 Results -- 11 Conclusion -- 12 Future Scope -- References -- Brain Tumor MRI Segmentation Using Deep Instance Segmentation with Bioinspired Optimization Algorithm -- 1 Introduction -- 2 Related Works -- 3 Proposed Model -- 4 Results and Discussion -- 5 Conclusion -- References -- Cloud-Based Tool for Node.js Project Generation Using Abstract Syntax Trees -- 1 Introduction -- 2 Basic Concepts and Related Work -- 2.1 Abstract Syntax Trees -- 2.2 Webpack -- 2.3 Babel -- 2.4 Related Research -- 3 Architecture and Design. ; 3.1 Component Identification -- 3.2 System Interaction -- 3.3 DSG Service -- 3.4 Cloud Provider -- 4 Enhancements -- 4.1 Advanced AST Manipulation -- 4.2 AST Analysis and Manipulation -- 4.3 AST Optimization -- 5 Results -- 6 Limitations -- 7 Conclusion -- References -- Complex Network Traffic Prediction Method Under Graph Neural Network -- 1 Introduction -- 2 Dataset -- 3 Graph Neural Network -- 4 Experiment and Results -- 5 Conclusions -- References -- Enhanced Holistically Nested Edge Detection (eHED) Algorithm: A Reliable Edge Detection in Unconstrained Scenarios -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Multi-stream Architecture -- 3.2 Skip-Layer Network Architecture -- 3.3 Multiple Scale Input into a Single Model -- 3.4 Training Distinct Networks Independently -- 3.5 Enhanced Holistically Nested Edge Detection (eHED) -- 4 Formulation -- 5 Experimental Results -- 5.1 Dataset -- 5.2 Histogram of Oriented Gradients -- 5.3 Contour Algorithm -- 5.4 Canny -- 5.5 EHED -- 5.6 Comparison with Canny and eHED -- 6 Conclusion -- 7 Future Research -- References -- Toward Effective Suggestion Mining in Game Reviews: Introducing an Aspect-Based Multiclass Multilevel Dataset -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 3.1 Background -- 3.2 Annotation Scheme -- 3.3 Expert Annotation -- 3.4 Characteristics of Dataset -- 4 Experimental Setup -- 4.1 TCN -- 4.2 LSTM -- 4.3 DRC_Net -- 4.4 GPT-3 -- 4.5 TCN with Machine Learning -- 5 Results -- 5.1 Suggestion Extraction (Superclass) -- 5.2 Evaluation of Sentiments -- 5.3 Evaluation of Subclass -- 5.4 Evaluation of Receiver and Suggestion Type -- 5.5 Evaluation of Aspects -- 6 Conclusion -- References -- Server-Enabled Information Transmission Through Networks Using Federated Learning Approach -- 1 Introduction -- 1.1 Applications of Federated Learning. ; 2 Federated Learning in Healthcare -- 3 Literature Review -- 4 Proposed Model -- 5 Result Analysis -- 6 Conclusion -- References -- Object Detection for Efficient Lighting: Comparing Models -- 1 Introduction -- 2 Related Works -- 3 System Architecture -- 4 Devices and Methods -- 4.1 Hardware -- 4.2 Software -- 4.3 Methodology -- 5 Analysis -- 5.1 YOLOv5 -- 5.2 Faster RCNN -- 5.3 SSD (Single-Shot Multi-Box Detector) -- 6 Discussion -- 7 Conclusion -- References -- Intelligent Adaptive Control Algorithm Based on Reinforcement Learning in the Field of Robotics -- 1 Background -- 2 Intelligent Adaptive Control Algorithm -- 3 Design of Intelligent Adaptive Control Algorithm in the Field of Robotics -- 3.1 Principles of Adaptive Control -- 3.2 Adaptive Control in Reinforcement Learning -- 4 Experimental Results of Response Time -- 5 Stability Test Results -- 6 Tracking Error Experimental Results -- 7 Conclusions -- References -- Multi-factor Authentication and Data Integrity for WBAN Using Hash-Based Techniques -- 1 Introduction -- 1.1 Motivation -- 1.2 The Main Contributions of the Research Work Are -- 1.3 Structure of the Article -- 2 Extensive Literature Survey -- 3 Research Gaps -- 4 Proposed Hypothesis -- 5 Proposed Methodology -- 5.1 WBAN Creation -- 5.2 Analysis and Update -- 5.3 Prediction and Diagnosis -- 6 Results and Discussion -- 6.1 Formal Security Analysis Using BAN Logic -- 6.2 Other Informal Security Analysis Over -- 6.3 Limitation of the Proposed Work -- 7 Expected Contribution to the Literature -- 8 Conclusion -- References -- Monitoring and Evaluating ECU Communication Data for Vulnerabilities Detection -- 1 Introduction -- 2 Related Works -- 3 Proposed Model -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Anomaly Detection and Result Discussion -- 3.4 Evaluation -- 4 Conclusion -- References. ; Animal Species Classification Using Deep Learning -- 1 Introduction -- 1.1 Need of the Model -- 2 Literature Survey -- 3 Methodology and Working -- 3.1 About the Dataset -- 3.2 Preprocessing of Data -- 3.3 (CNN)_ -- 3.4 EffecientNetB3 -- 3.5 Working of the Model -- 4 Result -- 4.1 Confusion Matrix -- 4.2 Accuracy -- 4.3 Precision -- 4.4 Recall -- 4.5 F1-Score -- 5 Conclusion -- 5.1 Model Applied to Input User Image -- 5.2 Implementation of the Model -- 5.3 Outcome -- 6 Recommendation for Future -- 6.1 Application in Veterinary -- 6.2 Zoological Parks -- 6.3 Sanctuaries -- 6.4 Roads Near Forests -- 6.5 Villages in National Parks -- References -- Comparative Analysis of Machine Learning and Deep Learning Classifiers for Crack Classification -- 1 Introduction -- 1.1 Motivation -- 1.2 Our Contribution -- 2 Methodology -- 2.1 Data Collection -- 2.2 Data Augmentation -- 2.3 Classification Models -- 2.4 Testing and Evaluation -- 3 Results -- 3.1 Performance Evaluation of ML Classifiers -- 3.2 Performance Evaluation of Pre-trained Deep Learning Classifiers -- 3.3 Performance Comparison with Existing Similar Models -- 4 Discussion -- 5 Conclusion -- References -- Design of Computer Network Security Defense System Based on Big Data -- 1 Introduction -- 2 Methods of CN SD System Design -- 2.1 Network Data Collection and Storage -- 2.2 Data Preprocessing and Feature Engineering -- 2.3 LSTM Model Construction -- 2.4 Real-Time Data Stream Processing -- 3 CN SD Performance Evaluation -- 3.1 Experimental Environment -- 3.2 Evaluation Indicators -- 4 Results -- 4.1 Threat Detection Accuracy Performance -- 4.2 Real-Time Results -- 5 Conclusions -- References -- Validation of Object-Oriented Metrics Against Standard Properties -- 1 Introduction -- 2 Literature Review -- 3 Proposed Object-oriented Metric Set for Reusability Assessment -- 3.1 Inherited Class Count (ICC). ; 3.2 Inherited Attribute Count (IAC) -- 3.3 Inherited Method Count (IMC) -- 3.4 Depth of Inheritance Hierarchy (DIH) -- 3.5 Degree of Reusability (DOR) Metric -- 4 Object-Oriented Metric Set Validation -- 4.1 Theoretical Validation -- 4.2 Through Measurement Theory -- 4.3 Through Kaner's Framework -- 5 Result and Discussion -- 6 Conclusion and Future Scope -- References -- A Personalized Health-Care Framework for Health-Care Service -- 1 Introduction -- 2 Machine Intelligence and Personalized Health Care -- 3 Computational Approach for Personalized Spine Care -- 4 Implementation Results -- 5 Conclusion -- References -- Comparative Analysis of Machine-Learning and Deep Learning Algorithms Using Manta Ray Foraging Optimization for the Detection of Hate Speech -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Methodology -- 4.1 Data Collection and Preprocessing -- 4.2 Feature Extraction and Representation -- 4.3 ML Models Used -- 4.4 Manta Ray Foraging Optimization -- 5 Results and Discussion -- 6 Conclusion and Future Work -- References -- Bangladeshi Currency Authentication Checking System Using Convolutional Neural Networks -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preparation -- 3.3 Model Development -- 4 Results and Discussion -- 4.1 Result -- 4.2 Discussion -- 5 Conclusion -- References -- CLASH: A Contrastive Learning Approach for Few-Shot Classification of Histopathological Images -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 3.1 Architecture -- 4 Experimental Results -- 4.1 Experiment Setup -- 4.2 Evaluation Metrics -- 4.3 Experiment Data -- 4.4 Performance Evaluation with Histopathology Dataset -- 4.5 Limitation of the Proposed Work -- 5 Conclusion -- References -- Data-Driven Air Quality Prediction with Batch Normalization in Long Short-Term Memory Networks. ; 1 Introduction.
• Titolo autorizzato: Proceedings of Fifth Doctoral Symposium on Computational Intelligence
• ISBN: 981-9767-26-1
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910903790603321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Networks and Systems Series