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Intelligent Computing for Sustainable Development : First International Conference, ICICSD 2023, Hyderabad, India, August 25-26, 2023, Revised Selected Papers, Part II
Intelligent Computing for Sustainable Development : First International Conference, ICICSD 2023, Hyderabad, India, August 25-26, 2023, Revised Selected Papers, Part II
Autore Satheeskumaran S
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (227 pages)
Altri autori (Persone) ZhangYudong
BalasValentina Emilia
HongTzung-pei
PelusiDanilo
Collana Communications in Computer and Information Science Series
ISBN 3-031-61298-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- A Cognitive Architecture Based Conversation Agent Technology for Secure Communication -- 1 Introduction -- 2 Literature Review -- 3 Evaluation Based on Reputation and Risk Degree -- 4 Information Retrieval for Buyer and Suppler -- 5 Intercession Process -- 6 Negotiation Process -- 7 Conclusion -- References -- Darwinian Lion Swarm Optimization-Based Extreme Learning Machine with Adaptive Weighted Smote for Heart Disease Prediction -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 Data Pre-processing -- 3.2 Feature Selection Using OOA -- 3.3 CVD Prediction Using DLSO-ELM -- 4 Performance Evaluation -- 5 Conclusion -- References -- Alzheimer's Disease Detection Using Convolution Neural Networks -- 1 Introduction -- 2 Literature Review -- 2.1 Issues Identified -- 3 Proposed System -- 4 Result and Discussion -- 4.1 Result Analysis -- 5 Conclusion -- References -- A Comparison Study of Cyberbullying Detection Using Various Machine Learning Algorithms -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Proposed System -- 3.2 Architecture -- 3.3 Modules -- 3.4 UML Diagrams -- 4 Performance Analysis -- 5 Conclusion -- 6 Future Work -- References -- State of the Art Analysis of Word Sense Disambiguation -- 1 Introduction -- 2 Related Work -- 3 Main Approaches and Datasets Used for WSD -- 3.1 Dictionary-Based or Knowledge-Based Approach -- 3.2 Machine Learning Approach -- 4 Evaluation of the Survey -- 4.1 Supervised Approach -- 4.2 Unsupervised Approach -- 4.3 Knowledge-Based Approach -- 4.4 Semi-supervised Approach -- 5 Conclusion and Future Work -- References -- Oral Cancer Classification Using GLRLM Combined with Fuzzy Cognitive Map and Support Vector Machines from Dental Radiograph Images -- 1 Introduction -- 2 Related Works -- 3 Methodology.
3.1 Image Preprocessing -- 3.2 Image Segmentation -- 3.3 Gray Level Run Length Matrix -- 3.4 Fuzzy Cognitive Map -- 3.5 Support Vector Machine -- 4 Results and Discussions -- 5 Conclusion -- References -- Machine Learning Based Delta Sigma Modulator Using Memristor for Neuromorphic Computing -- 1 Introduction -- 2 Memristor for Artificial Neural Network -- 3 Two Stage CMOS Op-Amp Using Memristor -- 3.1 Subtractor -- 3.2 Integrator -- 3.3 Comparator -- 3.4 D Flip-Flop -- 3.5 1-Bit DAC -- 4 Sigma Delta ADC -- 5 Conclusion -- References -- An Effective Framework for the Background Removal of Tomato Leaf Disease Using Residual Transformer Network -- 1 Introduction -- 2 Literature Survey -- 2.1 Related Works -- 2.2 Problem Statement -- 3 Tomato Leaf Disease Classification with Deep Learning Using Background Removal -- 3.1 Dataset Information -- 3.2 Developed Model -- 3.3 Median Blur-Based Image Pre-processing -- 4 The Concept of Background Removal in Tomato Leaf Disease Classification Using Deep Learning -- 4.1 Background Removal Using FCN -- 4.2 Residual Transformer Network-Based Disease Classification -- 5 Result and Discussion -- 5.1 Experimental Setup -- 5.2 Performance Metrics -- 5.3 Resultant Background Removed Images -- 5.4 Analysis of Initiated Model with Conventional Classifiers -- 5.5 Performance Analysis on the Recommended Model -- 6 Conclusion -- References -- An Intelligent Ensemble Architecture to Accurately Predict Housing Price for Smart Cities -- 1 Introduction -- 2 The Literature Review -- 3 Methodology -- 3.1 Research Data Flow Diagram -- 3.2 Data Source and Selection -- 3.3 Data Preprocessing -- 3.4 Model Selection -- 4 Results and Discussions -- 5 Conclusion -- References -- Detection of Leaf Blight Disease in Sorghum Using Convolutional Neural Network -- 1 Introduction -- 2 Research Design and Model Development.
2.1 Proposed Model Development -- 3 Research Methodology -- 3.1 Dataset -- 4 Experiment Evaluation and Discussion -- 4.1 Dataset -- 4.2 Training Model -- 4.3 Hyper Parameters -- 4.4 Experimental Results -- 5 Conclusion -- References -- Data Security for Internet of Things (IoT) Using Lightweight Cryptography (LWC) Method -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Light Weight Cryptography (LWC) -- 3.2 Elliptic Curve Cryptography (ECC) -- 3.3 Security Analysis -- 4 Results and Discussion -- 5 Conclusion -- References -- A Hybrid Optimization Driven Deep Residual Network for Sybil Attack Detection and Avoidance in Wireless Sensor Networks -- 1 Introduction -- 2 Proposed ECMVRO Enabling Assault Detection Method Based on DRN -- 2.1 Evaluation of WSN -- 2.2 Cluster Head Selection Using LEACH Protocol -- 2.3 Routing Using FABC -- 2.4 Attack Detection Using Proposed ECMVRO-DRN -- 2.5 Guiding of (DRN) Deep Residual Network -- 2.6 Attack Mitigation with Data Rates -- 2.7 Developed Sybil attack detection Model-Flow Chart -- 3 Simulation Results -- 4 Conclusion -- References -- Feature Engineering Techniques for Stegware Analysis: An Extensive Survey -- 1 Introduction -- 2 Related Study -- 3 Overview of Feature Engineering -- 3.1 Feature Selection Techniques -- 3.2 Feature Extraction Techniques -- 4 Comparative Analysis of Feature Engineering Techniques -- 5 Challenges and Future Directions -- 5.1 Challenges -- 5.2 Scope and Future Directions -- 6 Conclusion -- References -- Text Summarization Using Deep Learning: An Empirical Analysis of Various Algorithms -- 1 Introduction -- 2 Related Works -- 3 Model Architecture -- 3.1 Seq2seq Model -- 3.2 Transformers -- 4 Experiment and Result -- 5 Conclusion -- References -- An Improved Detection of Fetal Heart Disease Using Multilayer Perceptron -- 1 Introduction -- 2 Related Work.
3 Dataset -- 3.1 CHD Dataset -- 4 Methodology and Models -- 5 Data Pre-processing -- 5.1 Feature Selection -- 5.2 Image Classification -- 6 Fetal Heart Anatomical Findings -- 7 Performance Metrics Estimation -- 7.1 Accuracy -- 7.2 Precision -- 7.3 Recall -- 7.4 F1-Score -- 8 Results Analysis -- 9 Conclusion -- References -- Application of Deep Learning Techniques for Coronary Artery Disease Detection and Prediction: A Systematic Review -- 1 Introduction -- 2 Deep Learning Architectures and Applications -- 3 Performance Metrics -- 3.1 Accuracy -- 3.2 Sensitivity or P (+/Disease) -- 3.3 Specificity or P (-/Disease) -- 3.4 Prevalence -- 3.5 Positive Predict Value (PPV) -- 3.6 Negative Predict Value (NPV) -- 3.7 Confusion Matrix -- 3.8 ROC Curve -- 3.9 F-Score or F-Measure -- 4 Deep Learning for CAD Prediction -- 5 Conclusion -- References -- Author Index.
Record Nr. UNINA-9910864192403321
Satheeskumaran S  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Computing for Sustainable Development : First International Conference, ICICSD 2023, Hyderabad, India, August 25-26, 2023, Revised Selected Papers, Part I
Intelligent Computing for Sustainable Development : First International Conference, ICICSD 2023, Hyderabad, India, August 25-26, 2023, Revised Selected Papers, Part I
Autore Satheeskumaran S
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (428 pages)
Altri autori (Persone) ZhangYudong
BalasValentina Emilia
HongTzung-pei
PelusiDanilo
Collana Communications in Computer and Information Science Series
ISBN 3-031-61287-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Transfer Learning Based Bi-GRU for Intrusion Detection System in Cloud Computing -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Pre-processing -- 3.2 Feature Extraction -- 3.3 Optimization Based Classification -- 4 Results and Discussion -- 4.1 Dataset Details -- 4.2 Performance Measures -- 5 Conclusion -- References -- Text to High Quality Image Generation Using Diffusion Model and Visual Transformer -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Algorithm -- 5 Results and Discussions -- 6 Experimentation -- 7 Comparison with Existing Models -- 8 Conclusion -- References -- Bequeathing the Blockchain Wallet in Public Blockchain Securing Wallet Sensitive Data -- 1 Introduction -- 1.1 Motivation of Research -- 1.2 Contribution -- 2 Preliminary -- 2.1 Blockchain -- 2.2 Encryption Algorithms Used -- 3 Proposed Method for Public Blockchain -- 4 Security Analysis -- 4.1 Comparison with Proposed Framework -- 4.2 Analysis on System Security -- 5 Conclusion -- References -- Few Shot Domain Adaptation Using Transformer and GNN-Based Fine Tuning -- 1 Introduction -- 2 Literature Review -- 3 Methodology/Experimental -- 3.1 Dataset -- 3.2 Preprocessing -- 3.3 Model -- 4 Algorithm -- 5 Results and Discussion -- 6 Conclusion -- References -- Prediction of Diabetic Retinopathy Using Deep Learning -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Data Collection -- 3.2 Image Pre-processing -- 3.3 Data Visualization -- 3.4 Training the Data -- 3.5 Evaluating The Data -- 4 Results and Discussion -- 5 Conclusion -- References -- Maritime Vessel Segmentation in Satellite Imagery Using UNET Architecture and Multiloss Optimization -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing.
3.3 Model Architecture -- 3.4 Algorithm -- 3.5 Model Training -- 4 Result Analysis -- 5 Conclusion -- References -- A Blockchain-Based Ad-Hoc Network to Provide Live Updates to Navigation Systems -- 1 Introduction -- 2 Literature Survey -- 3 Relevant Use Cases -- 3.1 Sports Car with Low Ground Clearance -- 3.2 ATM Status -- 4 Blockchain-Based Ad-Hoc Network -- 4.1 Hardware -- 4.2 Framework -- 4.3 Workflow -- 5 Implementation and Results -- 6 Conclusion -- 7 Future Work -- References -- Recognition of Facial Expressions Using Geometric Appearance Features -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 MUG Dataset -- 3.2 Data Pre-processing -- 3.3 Feature Extraction -- 3.4 Classification -- 4 Experimental Results -- 5 Conclusion -- References -- Facial Emotion Recognition Using Deep Learning -- 1 Introduction -- 2 Background of the Work -- 3 Background -- 4 Methodology -- 4.1 Software Narrative -- 4.2 Open CV -- 4.3 NumPy -- 5 Problem Delineation -- 5.1 Flow Diagram of the Proposed Work -- 5.2 Algorithmic Steps -- 5.3 Dataset -- 5.4 Face Registraton -- 6 Results -- 7 Conclusion -- References -- Graph Based Semantically Extractive Tool for Text Summarization Using Similarity Score -- 1 Introduction -- 1.1 Abstractive Text Summarization -- 1.2 Extractive Text Summarization -- 1.3 Problem statement -- 2 Related Works -- 3 Proposed Methodology -- 4 Implementation -- 5  Results -- 6 Conclusion and Future Works -- References -- Cloud Based Attendance Management System Using Face Recognition with Haar Cascade Classifier and CNN -- 1 Introduction -- 1.1 The major face recognition algorithms discussed as: -- 2 Literature Study -- 3  Existing Solution -- 4 Methodology -- 4.1  CNN Architecture -- 4.2 Haar Cascades -- 5  Results and Discussion -- 6 Conclusion -- References.
An Efficient Early Detection of Lung Cancer and Pneumonia with Streamlit -- 1 Introduction -- 2 Related Works -- 3 Methodologies of the Proposed Work -- 3.1 Methodology for Lung Cancer Detection -- 3.2 Methodology for Pneumonia -- 3.3 System Design -- 4 Results -- 4.1 Results and Discussion on Lung Cancer -- 4.2 Results and Discussion on Pneumonia -- 4.3 Results and Discussion on Streamlit Web Application -- 5 Conclusion -- References -- An Improved Filter Based Feature Selection Model for Kidney Disease Prediction -- 1 Introduction -- 2 Literature Review -- 2.1 Research Gap -- 3 Methods -- 3.1 Working Principle -- 3.2 Significant Feature Selection -- 3.3 Statement of the Problem -- 3.4 Proposed Approach -- 4 Result -- 4.1 Dataset Description -- 4.2 Discussion -- 4.3 Significant Feature Selection -- 5 Conclusion -- References -- A Novel Approach to Address Concept Drift Detection with the Accuracy Enhanced Ensemble (AEE) in Data Stream Mining -- 1 Introduction -- 2 Literature Review -- 2.1 Ensemble Drift Detection Methods -- 2.2 Problem Statement -- 3 Proposed Methodology -- 3.1 Proposed Method Steps -- 4 Possible Outcomes -- 5 Conclusion -- References -- Intelligent Computing Techniques for Sustainable Cybersecurity: Enhancing Threat Detection and Response -- 1 Introduction -- 1.1 Types of Cyber Security -- 1.2 Study's Contribution -- 2 Literature Review -- 3 Methodology -- 3.1 Data Description -- 3.2 Data Pre-processing -- 3.3 Feature Selection -- 3.4 Indices of Performance -- 4 Results and Discussion -- 5 Conclusion -- References -- Parkinson's Disease Progression: Comparative Analysis of ML Models and Embedded Algorithm -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Pre-processing -- 3.2 Dataset Split -- 3.3 Selection of ML Models -- 3.4 Hyperparameter Tuning -- 3.5 Model Evaluation -- 4 Results -- 5 Discussion -- 6 Conclusion.
References -- System Evaluation of Team and Winner Prediction in One Day International Matches with Scenario Based Questionnaire -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection and Understanding -- 3.2 Feature Selection and Optimization -- 3.3 Hybrid CS-PSO -- 3.4 Learning Algorithms/Model Selection -- 3.5 Training and Testing -- 3.6 Parameter Tuning and Model Evaluation -- 4 Result Analysis -- 4.1 Result for Winner Prediction (Model 1, 2, and 3) -- 4.2 Result: Player Selection for Team Formation -- 5 System Evaluation -- 5.1 Manual Evaluation of Winner Prediction System -- 5.2 Manual Evaluation of Team Prediction System -- 6 Conclusion and Future Work -- References -- Data-Driven Precision: Machine Learning's Impact on Thyroid Disease Diagnosis and Prediction -- 1 Introduction -- 2 Implementation -- 2.1 Exploring Its Role and Diagnostic Techniques -- 2.2 Unveiling the Power of Classification and Regression -- 2.3 Unraveling Multinomial Logistic Regression: Considerations, Applications, and Interpretation -- 2.4 Simultaneous Approach -- 2.5 Support Vector Machine (SVM) Variants and Extensions -- 2.6 Gradient Boosting -- 3 Conclusion and Future Work -- References -- Modeling and Design of an Autonomous Amphibious Vehicle with Obstacle Avoidance for Surveillance Applications -- 1 Introduction -- 2 Related Work -- 3 Proposed Solution -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- Prediction of Cardio Vascular Diseases Using Calibrated Machine Learning Model -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Gaussian Naïve Bayes (GNB) -- 3.2 Calibration -- 3.3 Sigmoid Calibration -- 3.4 Isotonic Calibration -- 3.5 Brier Score -- 4 Dataset -- 5 Experimental Results -- 5.1 Preprocessing -- 5.2 Input and Output Selection -- 5.3 Model Fitting -- 6 Conclusion -- References.
Alzheimer's Disease Detection Using Resnet -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Proposed Model -- 3.2 Model Details -- 4 Result and Discussion -- 5 Conclusion -- References -- Dysarthria Speech Disorder Assessment Using Genetic Algorithm (GA)-Based Layered Recurrent Neural Network -- 1 Introduction -- 1.1 Motivation -- 2 Related Work -- 3 Methodology -- 3.1 Clustered Cuckoo Search Optimized Feature Subset Selection -- 3.2 Speech Signal Energy-Based Lung Capacity Estimation -- 3.3 GA-Based Layered Recurrent Neural Networks -- 4 Results and Discussions -- 4.1 Performance Measure of Accuracy -- 4.2 Performance Measure of Precision -- 4.3 Performance Measure of RMSE -- 5 Conclusion -- References -- Plant Disease Diagnosis with Novel Segmentation and Multiple Feature Selection Based on Machine Learning -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Crop Image Acquiring and Pre-processing Techniques -- 3.2 Segmentation Color and Shape Elements -- 3.3 Feature Extraction Color and Shape Elements -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- An Integrated Method to Monitor Indoor Air Quality Using IoT for Enhanced Health of COPD Patients -- 1 Introduction -- 2 Indoor Air Quality and Improved Living Environment -- 3 Related Works -- 4 Proposed Methodology - Materials and Methods -- 4.1 Thingsboard -- 4.2 Flutter Framework -- 5 Results and Discussions -- 6 Conclusion -- References -- Design and Development of Computational Methodologies for Agricultural Informatics -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 A Novel Data Mining Technique for Accurate Prediction of Leaf Diseases with Soil Characteristics -- 3.2 The Prediction of Leaf Disease and Soil Properties Using Multi-channel Convolutional Neural Network.
3.3 Multi-channel Multi-modal Concatenation-Based Deep Learning Model for Leaf Infection and Soil Property Prediction.
Record Nr. UNINA-9910864194203321
Satheeskumaran S  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui