Kooperativer Bibliotheksverbund

UID:

Format: XII, 531 p. 273 illus., 205 illus. in color. , online resource.

Edition: 1st ed. 2024.

ISBN: 9783031614712

Series Statement: Information Systems Engineering and Management, 3

Content: This book presents a comprehensive collection of research chapters focusing on innovative solutions to energy and sustainability challenges. It reflects the collaborative efforts of researchers worldwide, showcasing novel approaches to complex problems. Topics discussed range from securing cyber-physical systems to revolutionizing healthcare with AI and robotics, emphasizing sustainable research. The book emphasizes smart and sustainable energy solutions, highlighting advancements in solar panel efficiency, fault analysis, and fuzzy-controlled converters for grid-tied photovoltaic systems. Additionally, it explores AI's transformative potential in water solutions, agriculture, and renewable energy technologies across domains like smart cities, transportation, and healthcare. The insights shared aim to inspire further research, foster discussions, and drive real-world impact toward a resilient, inclusive, and sustainable future. · Discusses issues and offers sustainable solutions to meet the challenges faced by today's economy and industry. · Presents recent research in the sustainable transformation of engineering and technological systems. · Serves as a valuable resource for both academic researchers and industry practitioners interested in Artificial Intelligence (AI) and smart energy sectors.

Note: Chapter 1. A Hybrid Machine Learning Approach for Enhanced Prediction of Breast Cancer with Lasso Method for Feature Extraction -- Chapter 2. A Comparative Overview of Deep Learning Aided Image Generation. Chapter 3. Enhancing Pneumonia Detection in Chest X-Rays: A Combined GAN and CNN Approach -- Chapter 4. A Data Driven AI Framework for Conversational Bot by Vision Transformers in Health Care Systems -- Chapter 5. Predictive Modelling of Cardiac Disease: Enhancing Accuracy through Machine Learning Algorithms and Borderline-SMOTE Technique -- Chapter 6. An AI-Driven Model for Decision Support Systems -- Chapter 7. Exploring Music Genres through Facial Emotions: Intelligent Data Processing and Machine Learning -- Chapter 8. Optimizing Cloud Task Scheduling through Innovative Metaheuristic Algorithm and Impulsive Fuzzy C-Means -- Chapter 9. Cirrhosis Patient Survival Prediction Analysis using Ml Algorithms -- Chapter 10. Learnable Discrete Wavelet(LDW) Pooling in CNN for Multidisciplinary Disease Prediction in Healthcare -- Chapter 11. Autonomous Human Computer Interaction System in Windows Environment using YOLO and LLM -- Chapter 12. Deep Learning based Animal Intrusion Detection System -- Chapter 13. Sustainable Crop Monitoring and Management for Enhanced Agricultural Productivity through IoT, AI & ML: Case Studies and Innovations -- Chapter 14. Design of an Auto Evaluation Model for Subjective Answers using Natural Language Processing and Machine Learning Techniques -- Chapter 15. Navigating the Radiological Landscape: A Cutting-Edge Hybrid VGG16-EfficientNet Model for Improved CT Scan Interpretation -- Chapter 16. Optimized Scene Text Detector and Paddle Optical Character Recognizer Techniques to Extract Text from Images -- Chapter 17. A Cost-Sensitive Sparse Auto-Encoder based Feature Extraction for Network Traffic Classification using CNN.-....etc.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783031614705

Additional Edition: Printed edition: ISBN 9783031614729

Additional Edition: Printed edition: ISBN 9783031614736

Language: English

DOI: 10.1007/978-3-031-61471-2

URL: https://doi.org/10.1007/978-3-031-61471-2

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: 1 online resource (0 pages)

Edition: 1st ed.

ISBN: 9783031614712

Series Statement: Information Systems Engineering and Management Series ; v.3

Note: Intro -- Preface -- Contents -- A Hybrid Machine Learning Approach for Enhanced Prediction of Breast Cancer with Lasso Method for Feature Extraction -- 1 Introduction -- 2 Related Work -- 3 Dataset Description -- 3.1 Dataset -- 3.2 System Architecture -- 4 Methodology -- 4.1 Data Preprocessing -- 4.2 Handling Missing Values -- 4.3 Selection Operator and Minimum Absolute Shrinkage (Lasso) -- 4.4 Evaluation Metrics -- 5 Result Discussion -- 5.1 Random Forest Algorithm -- 5.2 Artificial Neural Network Algorithm -- 5.3 Hybrid Approach -- 6 Results and Discussions -- 6.1 Result Using ANN -- 6.2 Result Using RF -- 6.3 Result Using Hybrid Model -- 7 Conclusion -- References -- A Comparative Overview of Deep Learning Aided Image Generation -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 DCGAN -- 3.2 SDXL -- 3.3 CVAE-GAN -- 3.4 ANI-GAN -- 3.5 CycleGAN -- 4 Result and Discussion -- 5 Conclusion and Future Scope -- References -- Enhancing Pneumonia Detection in Chest X-Rays: A Combined GAN and CNN Approach -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 GAN -- 3.2 AC GAN -- 3.3 Data Augmentation -- 3.4 CNN -- 4 Result Analysis -- 4.1 Feature Extraction and Classification Process -- 4.2 Data Augmentation -- 4.3 AC GAN -- 5 Conclusion -- References -- A Data Driven AI Framework for Conversational Bot by Vision Transformers in Health Care Systems -- 1 Introduction -- 2 Literature Review -- 3 Datasets -- 3.1 Indian Medicinal Plants Dataset -- 3.2 Floramed Data -- 4 Methodology -- 4.1 Proposed Framework -- 4.2 Vision Transformers (ViT) -- 4.3 Large Language Model- Mistral-7B-V0.1 -- 4.4 Frontend Framework -- 4.5 Implementation -- 5 Comparison and Results -- 6 Conclusion -- References -- Predictive Modelling of Cardiac Disease: Enhancing Accuracy Through Machine Learning Algorithms and Borderline-SMOTE Technique. , 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Data Balancing Technique -- 3.4 Feature Selection -- 4 ML Models -- 4.1 LR -- 4.2 SVC -- 4.3 RF -- 4.4 KNN -- 4.5 GNB -- 4.6 AdaBoost Classifier -- 4.7 CatBoost Classifier -- 4.8 Gradient Boosting -- 5 Model Evaluation -- 5.1 Accuracy (A) -- 5.2 Precision (P) -- 5.3 Recall (R) -- 5.4 F1 Score (F1) -- 5.5 Specificity (S) -- 5.6 ROC-AUC Curve -- 6 Results and Discussions -- 7 Conclusion and Future Work -- References -- An AI-Driven Model for Decision Support Systems -- 1 Introduction -- 2 Related Work -- 3 AI in Management -- 4 MCDM and GP -- 5 Experimental Results -- 6 Conclusion -- References -- Exploring Music Genres Through Facial Emotions: Intelligent Data Processing and Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Existing System -- 4 Proposed System -- 5 Methodology -- 5.1 Identification of Emotions on the Face -- 5.2 Classifying Music Genres -- 5.3 Integration and Recommendations -- 6 Results and Discussion -- 7 Conclusion -- 8 Future Work -- References -- Optimizing Cloud Task Scheduling Through Innovative Metaheuristic Algorithm and Impulsive Fuzzy C-Means -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Credit Task Length -- 3.2 Credit Makespan -- 3.3 Credit Task Priority -- 3.4 Credit Deadline -- 3.5 Credit Degree of Imbalance -- 3.6 Execution Cost of the Task -- 4 IGFCM Clustering Method -- 4.1 Impulsive Genetic FCM Algorithm -- 4.2 Impulsive Technique in GA Design -- 4.3 IGA Operation -- 4.4 Clustering with FCM Method -- 5 Load Balancing Using Proposed Deep Q-Learning -- 5.1 Metaheuristic Elements - Fire Hawk Optimization (FHO) Algorithm -- 5.2 Deep Q-Learning Algorithm -- 5.3 Experimental Setup -- 5.4 Makespan Comparison Results -- 5.5 Response Time Comparison Results. , 5.6 Resource Utilization Comparison Results -- 5.7 Average Waiting Time Comparison Results -- 5.8 Total Cost Comparisons Results -- 5.9 Degree of Imbalance Performance Comparisons -- 6 Scalability and Applicability in Real-World Cloud Environment -- 6.1 Scalability -- 6.2 Applicability -- 7 Conclusion and Future Work -- References -- Cirrhosis Patient Survival Prediction Analysis Using ML Algorithms -- 1 Introduction -- 2 Literature Survey -- 3 Methods -- 3.1 Supervised Machine Learning Algorithm -- 3.2 Logistic Regression Algorithm -- 3.3 Support Vector Machine (SVM) -- 3.4 Decision Tree Algorithm -- 3.5 Random Forest Algorithm -- 4 Experiment -- 4.1 Experiment Environment -- 4.2 Cirrhosis Disease Dataset -- 4.3 Data Visualization -- 4.4 Imputing Missing Values in Numerical Features -- 4.5 Encoding Categorical Variables -- 4.6 Encoding Target Variable for Training and Test Datasets. -- 5 Experimental Results -- 5.1 Results of Each Model -- 5.2 Accuracy of All Models -- 5.3 Final Results -- 6 Conclusion -- 7 Future Research Directions -- References -- Learnable Discrete Wavelet (LDW) Pooling in CNN for Multidisciplinary Disease Prediction in Healthcare -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Structuring the Paper -- 4 Experimental Study -- 5 Result and Analysis -- 6 Conclusions and Future Scope -- References -- Autonomous Human Computer Interaction System in Windows Environment Using YOLO and LLM -- 1 Introduction -- 2 Methodology -- 2.1 Data Collection -- 2.2 YOLO V8 Model Training -- 2.3 Tesseract OCR Implementation -- 2.4 Edge and Contour Detection -- 2.5 Large Language Model (LLM) GPT-4 with Instruction Fine-Tuning -- 3 Implementation and Algorithm -- 3.1 Screen Image Pre-processing -- 3.2 Large Language Model (LLM) Integration and Its Capabilities -- 3.3 User Command and Screen Image Processing. , 3.4 Integrate Large Language Model -- 4 Results and Discussion -- 4.1 Optical Character Recognition (OCR) Performance -- 4.2 Edges and Contours Detection -- 4.3 You Only Look Once (YOLO V8) Results -- 4.4 Large Language Model (LLM) Performance and Interpretation -- 4.5 Discussion -- 5 Conclusion and Future Work -- References -- Deep Learning Based Animal Intrusion Detection System -- 1 Introduction -- 2 Problem Statement -- 3 Related Work -- 4 Methodology -- 4.1 Process Involved in Designing -- 5 Performance Analysis -- 6 Conclusion -- References -- Sustainable Crop Monitoring and Management for Enhanced Agricultural Productivity Through IoT, AI& -- ML: Case Studies and Innovations -- 1 Introduction -- 1.1 Study of Agriculturalist -- 1.2 Agricultural Landscape -- 1.3 Importance to Livelihood -- 1.4 Problems and Challenges -- 1.5 Governmental Programs -- 1.6 Technological Acceptance -- 1.7 Agricultural Exports -- 1.8 Prospects for the Future -- 1.9 Sustainability and Organic Agricultural -- 2 Agrıcultural Integratıon of Internet of Thıngs and the Artıfıcıal Intellıgence -- 2.1 Agriculture and IoT -- 2.2 AI in Agriculture -- 3 Problem Statement -- 4 Lıterature Revıew of Contrıbutıons -- 5 Materıals and Methods -- 6 Frame Work -- 6.1 Results -- 7 Conclusion -- References -- Design of an Auto Evaluation Model for Subjective Answers Using Natural Language Processing and Machine Learning Techniques -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Proposed Methodology for Student Module -- 3.2 Proposed Methodology for Teacher Module -- 4 Results -- 5 Conclusion -- References -- Navigating the Radiological Landscape: A Cutting-Edge Hybrid VGG16-EfficientNet Model for Improved CT Scan Interpretation -- 1 Introduction -- 2 Related Works -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Data Pre-processing -- 3.3 Data Augmentation. , 3.4 Model Evaluation -- 4 Proposed Methodology -- 4.1 Working Process of Proposed Model -- 4.2 VGG16-EfficientNet Model -- 5 Results and Discussion -- 6 Conclusion -- References -- Optimized Scene Text Detector and Paddle Optical Character Recognizer Techniques to Extract Text from Images -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusion and Future Scope -- References -- A Cost-Sensitive Sparse Auto-encoder Based Feature Extraction for Network Traffic Classification Using CNN -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Pre-processing -- 3.2 Feature Extraction Using Sparse Autoencoder -- 3.3 Deep Learning Based Traffic Classification Using CNN -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Evaluation Measures -- 4.3 Results and Comparisons -- 5 Conclusion -- References -- Comparative Analysis of Deep Learning Architectures for Rice Crop Image Classification -- 1 Introduction -- 2 Design and Methodology -- 3 Result Analysis -- 4 Discussions -- 5 Conclusion and Future Scope -- References -- A Comprehensive Survey on Real-Time Animal (Dog) Detection System Using Artificial Intelligence Methods -- 1 Introduction -- 2 Literature Review -- 2.1 Objectives (OBJ) of the Review -- 2.2 Observation Table -- 2.3 Major Techniques Used -- 3 Observations and Outcomes of the Survey -- 4 Limitations of the Survey -- 5 Conclusion -- References -- Natural Language Processing Approach to Real-Time Multilingual Speech Conversion -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Proposed System -- 5 Results -- 6 Future Scope -- 7 Conclusion -- References -- Automatic Road Accident Detection Using Deep Learning -- 1 Introduction -- 2 Related Works -- 3 Dataset -- 3.1 Dataset Description -- 3.2 Dataset Preparation for YOLO Model -- 3.3 Dataset Preparation for CNN Model -- 4 Implementation. , 4.1 Architecture for Accident Detection.

Additional Edition: Print version: Manoharan, S. Proceedings of 4th International Conference on Artificial Intelligence and Smart Energy Cham : Springer,c2024 ISBN 9783031614705

Language: English

UID:

Format: 1 online resource (0 pages)

Edition: 1st ed. 2024.

ISBN: 9783031614712

Series Statement: Information Systems Engineering and Management, 3

Content: This book presents a comprehensive collection of research chapters focusing on innovative solutions to energy and sustainability challenges. It reflects the collaborative efforts of researchers worldwide, showcasing novel approaches to complex problems. Topics discussed range from securing cyber-physical systems to revolutionizing healthcare with AI and robotics, emphasizing sustainable research. The book emphasizes smart and sustainable energy solutions, highlighting advancements in solar panel efficiency, fault analysis, and fuzzy-controlled converters for grid-tied photovoltaic systems. Additionally, it explores AI's transformative potential in water solutions, agriculture, and renewable energy technologies across domains like smart cities, transportation, and healthcare. The insights shared aim to inspire further research, foster discussions, and drive real-world impact toward a resilient, inclusive, and sustainable future. · Discusses issues and offers sustainable solutions to meet the challenges faced by today's economy and industry. · Presents recent research in the sustainable transformation of engineering and technological systems. · Serves as a valuable resource for both academic researchers and industry practitioners interested in Artificial Intelligence (AI) and smart energy sectors.

Note: Chapter 1. A Hybrid Machine Learning Approach for Enhanced Prediction of Breast Cancer with Lasso Method for Feature Extraction -- Chapter 2. A Comparative Overview of Deep Learning Aided Image Generation. Chapter 3. Enhancing Pneumonia Detection in Chest X-Rays: A Combined GAN and CNN Approach -- Chapter 4. A Data Driven AI Framework for Conversational Bot by Vision Transformers in Health Care Systems -- Chapter 5. Predictive Modelling of Cardiac Disease: Enhancing Accuracy through Machine Learning Algorithms and Borderline-SMOTE Technique -- Chapter 6. An AI-Driven Model for Decision Support Systems -- Chapter 7. Exploring Music Genres through Facial Emotions: Intelligent Data Processing and Machine Learning -- Chapter 8. Optimizing Cloud Task Scheduling through Innovative Metaheuristic Algorithm and Impulsive Fuzzy C-Means -- Chapter 9. Cirrhosis Patient Survival Prediction Analysis using Ml Algorithms -- Chapter 10. Learnable Discrete Wavelet(LDW) Pooling in CNN for Multidisciplinary Disease Prediction in Healthcare -- Chapter 11. Autonomous Human Computer Interaction System in Windows Environment using YOLO and LLM -- Chapter 12. Deep Learning based Animal Intrusion Detection System -- Chapter 13. Sustainable Crop Monitoring and Management for Enhanced Agricultural Productivity through IoT, AI & ML: Case Studies and Innovations -- Chapter 14. Design of an Auto Evaluation Model for Subjective Answers using Natural Language Processing and Machine Learning Techniques -- Chapter 15. Navigating the Radiological Landscape: A Cutting-Edge Hybrid VGG16-EfficientNet Model for Improved CT Scan Interpretation -- Chapter 16. Optimized Scene Text Detector and Paddle Optical Character Recognizer Techniques to Extract Text from Images -- Chapter 17. A Cost-Sensitive Sparse Auto-Encoder based Feature Extraction for Network Traffic Classification using CNN.-....etc.

Additional Edition: Print version: Manoharan, S. Proceedings of 4th International Conference on Artificial Intelligence and Smart Energy Cham : Springer,c2024 ISBN 9783031614705

Language: English

DOI: 10.1007/978-3-031-61471-2