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Intelligent Systems and Sustainable Computing : Proceedings of ICISSC 2022
| Intelligent Systems and Sustainable Computing : Proceedings of ICISSC 2022 |
| Autore | Reddy V. Sivakumar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2023 |
| Descrizione fisica | 1 online resource (562 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
PrasadV. Kamakshi
WangJiacun Rao DasariNaga Mallikarjuna |
| Collana | Smart Innovation, Systems and Technologies Series |
| ISBN | 981-9947-17-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Conference Committee -- Preface -- Contents -- About the Editors -- 1 Air Pollution Detection and Prediction Using Moving Average in Indian Cities -- 1.1 Introduction -- 1.1.1 Major Air Pollutants -- 1.1.2 The Most Polluted Cities in India -- 1.2 Related Work -- 1.3 Proposed Model -- 1.3.1 AQI Calculation -- 1.4 Conclusion -- References -- 2 Implementation of ResNet-50 with the Skip Connection Principle in Transfer Learning Models for Lung Disease Prediction -- 2.1 Introduction -- 2.1.1 Related Works -- 2.2 Proposed Methods -- 2.2.1 Describe the Dataset -- 2.2.2 Technique for Preprocessing -- 2.2.3 Transfer Learning -- 2.3 Result and Discussion -- 2.4 Conclusion and Future Work -- References -- 3 Performance Analysis of American Sign Language Using Wavelet Transform and CNN -- 3.1 Introduction and Background Study -- 3.2 Methodology and Implementation -- 3.2.1 Database Creation and Image Preprocessing -- 3.2.2 Segmentation and Cropping -- 3.2.3 Feature Extraction and Classification -- 3.3 Results and Discussion -- 3.3.1 Using Wavelet Transform and Feed-Forward Backpropagation Neural Network-Based Classifier -- 3.3.2 Using CNN Classifier -- 3.4 Conclusion -- References -- 4 Image Transmission in Underwater Through Li-Fi -- 4.1 Introduction -- 4.2 Literature Survey -- 4.3 System Design and Implementation -- 4.3.1 System Design -- 4.3.2 Implementation -- 4.4 Results and Discussions -- 4.5 Conclusions and Future Scope -- 4.5.1 Conclusion -- 4.5.2 Future Scope -- References -- 5 Leaf Disease Identification with Multi-label Classification of Various Plants Using Dense CNN Model -- 5.1 Introduction -- 5.2 Literature Survey -- 5.3 Methodology -- 5.3.1 Data Collection -- 5.3.2 Preprocessing -- 5.3.3 Classification: CNN -- 5.4 Experimental Settings -- 5.5 Model Performance -- 5.6 Experimental Results -- 5.7 Comparative Results.
5.8 Conclusion and Future Work -- References -- 6 Enhancing the MANET AODV Forecast of a Broken Link with LBP -- 6.1 Introduction -- 6.1.1 AODV -- 6.1.2 Route Maintenance and Discovery in AODV -- 6.1.3 Link Breakage in MANET -- 6.2 Proposed Solution for Predicting Link Breakages -- 6.2.1 Proposed Architecture -- 6.2.2 Proposed Flowchart -- 6.2.3 Procedure (LBP Algorithm) -- 6.2.4 Methodology -- 6.3 Simulation, Result and Result Analysis -- 6.3.1 Simulation Scenario and Model -- 6.3.2 Simulation Environment -- 6.3.3 Evaluation Metrics -- 6.4 Conclusion -- References -- 7 Educational Innovation Using Augmented Reality: Systematic Literature Review -- 7.1 Introduction -- 7.2 Research Method -- 7.3 Results and Discussion -- 7.3.1 Throughout the Year Publications -- 7.3.2 Multilevel Analysis -- 7.3.3 Geography-Related Contexts -- 7.4 Conclusions -- References -- 8 A Current Survey Trends on Child Safety Devices Using IoT -- 8.1 Introduction -- 8.2 Child Safety Related Factor -- 8.2.1 Location Tracking -- 8.2.2 Notification -- 8.2.3 Sensors -- 8.2.4 Video/Image Capturing -- 8.2.5 Voice Recognition -- 8.3 Child Safety Research Works with the Contribution and Limitations -- 8.4 Conclusion -- References -- 9 Intelligent Children Safety and Security Wearable Shield Using IoT -- 9.1 Introduction -- 9.2 Proposed Design -- 9.3 Results and Discussion -- 9.4 Conclusion -- References -- 10 Software Defects Prediction Using Machine Learning Algorithms -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 Methodology -- 10.3.1 Artificial Neural Network -- 10.3.2 Random Forest -- 10.3.3 Random Tree -- 10.3.4 Linear Regression -- 10.3.5 Gaussian Processes -- 10.3.6 Decision Table -- 10.3.7 SMOreg -- 10.3.8 M5P -- 10.4 Performance Evaluation Measures -- 10.4.1 Accuracy -- 10.4.2 Precession -- 10.4.3 Recall -- 10.4.4 F Measure -- 10.4.5 Cross Validation. 10.5 Experimental Results and Analysis -- 10.6 Conclusion -- References -- 11 Farmers Market-Agricultural Marketing and Management System to Connect Farmers to Retailers -- 11.1 Introduction -- 11.1.1 Objectives -- 11.2 Problems in Current/Existing Models -- 11.3 Proposed System -- 11.3.1 Motivation for Proposed System -- 11.4 Implementation -- 11.4.1 Farmer Module -- 11.4.2 Buyer Module -- 11.4.3 Admin Module -- 11.4.4 Farmers Dashboard -- 11.4.5 Buyer Dashboard -- 11.4.6 Admin Dashboard -- 11.5 Conclusion and Future Scope -- References -- 12 Driver Drowsiness Detection System Based on Behavioral Method, Biological Method and Vehicular Feature-Based Method-A Review -- 12.1 Introduction -- 12.2 Behavioral Method -- 12.3 Biological Method -- 12.4 Vehicular Features-Based Method -- 12.5 Comparison and Discussion -- 12.6 Conclusion -- References -- 13 A Virtual Machine Protection Framework Against Compromised Hypervisor in Cloud Computing -- 13.1 Introduction -- 13.2 Related Work -- 13.3 Methodology -- 13.3.1 The Proposed Framework -- 13.3.2 Hypervisor Stability and Vulnerability Evaluation -- 13.3.3 Proposed Algorithms -- 13.4 Results and Discussion -- 13.4.1 Security Analysis -- 13.4.2 Performance Evaluation -- 13.5 Conclusion and Future Work -- References -- 14 SVM Versus KNN: Prediction of Best Image Classifier -- 14.1 Introduction -- 14.2 Related Works -- 14.3 Basic Concepts -- 14.3.1 Support Vector Machines (SVM) -- 14.3.2 K-Nearest Neighbors (KNN) -- 14.4 Implementation -- 14.5 Results -- 14.5.1 Support Vector Machines (SVM) -- 14.5.2 K-Nearest Neighbors (KNN) -- 14.6 Conclusion -- References -- 15 Developing a SVM Model of Big Data Analytics for Healthcare Recommendation System -- 15.1 Introduction -- 15.2 Literature Survey -- 15.3 SVM Model of Big Data Analytics for Healthcare Recommendation System -- 15.4 Result Analysis. 15.4.1 Comparison Between Methods -- 15.5 Conclusion -- References -- 16 Machine Learning Approach Towards the Breast Cancer Detection with Microwave Imaging -- 16.1 Introduction -- 16.2 Design of Proposed Model in HFSS -- 16.2.1 Basic Antenna Modelling -- 16.2.2 Basic Female Breast Structure Modelling -- 16.3 Simulation of Proposed Model in HFSS -- 16.3.1 Working Procedure of the Proposed Model -- 16.3.2 Dataset Collection for the Classification -- 16.4 Result Analysis -- 16.5 Conclusion -- References -- 17 Initial Intrusion Detection in Advanced Persistent Threats (APT's) Using Machine Learning -- 17.1 Introduction -- 17.2 Background Knowledge -- 17.3 Related Work -- 17.4 Proposed Method -- 17.4.1 Datasets -- 17.5 Experimental Results and Discussion -- 17.5.1 Random Forest -- 17.5.2 Support Vector Machine (SVM) -- 17.5.3 Multilayer Perceptron (MLP) -- 17.6 Conclusion and Future Direction -- References -- 18 Feature Selection with Binary Differential Evolution for Microarray Datasets -- 18.1 Introduction -- 18.2 Review of Literature -- 18.3 Methodology -- 18.3.1 Datasets Preprocessing -- 18.3.2 Adaptive Scaling Factor -- 18.3.3 Feature Correlation-Based Fitness Function -- 18.4 Experimental Analysis -- 18.4.1 Datasets and Parameters -- 18.4.2 Compared to Conventional Feature Selection Techniques -- 18.4.3 Compared to Sophisticated Feature Selection Techniques -- 18.4.4 Biomarker Analysis -- 18.5 Conclusion -- References -- 19 Survey on Imbalanced Dataset Classification-Machine Learning -- 19.1 Introduction -- 19.2 Problem Statement -- 19.3 Impacts on Classification by Imbalanced Data -- 19.4 Techniques for Classification of Unbalanced Data -- 19.5 Summary -- 19.6 Learning Objectives and Assessment Measures -- 19.7 Conclusion -- References -- 20 AI-Based Smart Farming Technology Using IoT -- 20.1 Introduction. 20.1.1 The Various Ways in Which AI Has Contributed in the Agricultural Sector Are as Follows -- 20.2 Issues in Farming -- 20.3 Proposed Solution -- 20.3.1 Methodology and Work Plan -- 20.4 Results and Discussion -- 20.5 Conclusions -- References -- 21 Deep Learning Approach for Auto Counting Complex Plants -- 21.1 Introduction -- 21.2 Collection of Data -- 21.3 Methodology -- 21.3.1 Image Phenotyping System -- 21.4 Experimental Results -- 21.4.1 Regression with Density Maps -- 21.4.2 Regression Using a Classifier -- 21.4.3 Extracting the Foreground -- 21.4.4 Slider Window -- 21.5 Conclusion -- References -- 22 A Survey on Smart Contract Vulnerabilities Including Auditing Tools -- 22.1 Introduction -- 22.2 Smart Contracts and Solidity -- 22.2.1 Smart Contracts -- 22.2.2 Solidity -- 22.3 Vulnerabilities in Smart Contracts -- 22.3.1 Re-entrancy -- 22.3.2 Transaction Origin (tx.origin) -- 22.3.3 Integer Overflow/Underflow -- 22.3.4 Timestamp Dependence -- 22.3.5 Transaction Ordering Dependence -- 22.3.6 Unsafe Delegate Call -- 22.3.7 Insecure Source of Randomness -- 22.4 Smart Contract Auditing Tools -- 22.5 Conclusion -- References -- 23 Breast Cancer Prediction by Levaraging Machine Learning Algorithm and Using Adaptive Voting Ensemble Method -- 23.1 Introduction -- 23.2 Literature Survey -- 23.3 Method of Materials -- 23.4 Result and Discussion -- 23.5 Conclusion and Future Scope -- References -- 24 Vulnerability Classification Based on Fine-Tuned BERT and Deep Neural Network Approaches -- 24.1 Introduction -- 24.2 Literature Review -- 24.3 Implementation -- 24.3.1 Dataset -- 24.3.2 Evaluation Measures -- 24.3.3 Implementation of Proposed Work Flow -- 24.4 Results and Discussion -- 24.4.1 Experimental Setup -- 24.4.2 Result Analysis on Different Machine Learning Approach -- 24.4.3 Result Analysis on Different Deep Learning and Transformer Approaches. 24.5 Conclusion and Future Scope. |
| Record Nr. | UNINA-9910746968203321 |
Reddy V. Sivakumar
|
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| Singapore : , : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Soft Computing and Signal Processing : Proceedings of 5th ICSCSP 2022 / / edited by V. Sivakumar Reddy, V. Kamakshi Prasad, Jiacun Wang, K. T. V. Reddy
| Soft Computing and Signal Processing : Proceedings of 5th ICSCSP 2022 / / edited by V. Sivakumar Reddy, V. Kamakshi Prasad, Jiacun Wang, K. T. V. Reddy |
| Autore | Reddy V. Sivakumar |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (669 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
PrasadV. Kamakshi
WangJiacun ReddyK. T. V |
| Collana | Smart Innovation, Systems and Technologies |
| Soggetto topico |
Computational intelligence
Artificial intelligence Signal processing Cooperating objects (Computer systems) Internet of things Computational Intelligence Artificial Intelligence Signal, Speech and Image Processing Cyber-Physical Systems Internet of Things |
| ISBN | 981-19-8669-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Microservice Architecture Observability Tool Analysis -- Chapter 2. Decentralized payment architecture for e-commerce and utility transactions with Government verified identities -- Chapter 3. Detection of Phishing Website using Intelligent Machine Learning Classifiers -- Chapter 4. Bidirectional Gated Recurrent Unit (BiGRU) based Bitcoin Price Prediction by News Sentiment Analysis -- Chapter 5. How AI Algorithms are being used in Applications -- Chapter 6. A Framework for Identifying Theft Detection using Multiple-instance Learning -- Chapter 7. An Efficient Reversible Data Hiding Based on Prediction Error Expansion -- Chapter 8. Deriving Insights from COVID-19 -- Chapter 9. Smoke Detection in Forest Using Deep Learning -- Chapter 10. Pneumothorax Segmentation using Feature Pyramid Network and MobileNet Encoder through Radiography Images -- Chapter 11. Visual Learning with Dynamic Recall -- Chapter 12. Machine learning for drug discovery using ag-glomerative hierarchical clustering -- Chapter 13. Automated Photomontage Generation with Neural Style Transfer -- Chapter 14. Machine Learning Model Development Using Computational Neurology -- Chapter 15. Graph Theory based user profile extraction and community detection in Linkedin- A study. etc. |
| Record Nr. | UNINA-9910734863003321 |
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Reddy V. Sivakumar
|
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Soft Computing and Signal Processing : Proceedings of 3rd ICSCSP 2020, Volume 2
| Soft Computing and Signal Processing : Proceedings of 3rd ICSCSP 2020, Volume 2 |
| Autore | Reddy V. Sivakumar |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2021 |
| Descrizione fisica | 1 online resource (663 pages) |
| Altri autori (Persone) |
PrasadV. Kamakshi
WangJiacun ReddyK. T. V |
| Collana | Advances in Intelligent Systems and Computing Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN | 981-16-1249-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Conference Committee -- Preface -- Contents -- About the Editors -- Artificial Intelligence with New Approach of Concrete Ingredients Changing in the Exact Proportions -- 1 Introduction -- 2 Literature Review -- 3 Materials Used -- 3.1 Admixture -- 3.2 Cement -- 3.3 Fine Aggregate -- 3.4 Course Aggregate -- 3.5 Water -- 3.6 Super Plasticizer -- 4 Methodology -- 4.1 Reading for Specimens -- 4.2 Calculation -- 5 Experimental Result -- 6 Conclusion -- References -- A New Approach in Cloud Environment to Improve Data Security Using Multiple Bits -- 1 Introduction -- 2 Literature Review -- 3 Proposed Technique -- 3.1 Algorithm for Embedding of Message -- 3.2 Algorithm for Repossession of Message -- 4 Experimental Results and Analysis -- 5 Conclusion and Future Scope -- References -- Clustering Text: A Comparison Between Available Text Vectorization Techniques -- 1 Introduction -- 2 Previous Literature -- 3 Dataset -- 3.1 Collection -- 3.2 Filtering -- 3.3 Pre Processing -- 4 Methodology -- 4.1 TFIDF -- 4.2 Doc2Vec -- 4.3 Clustering Techniques -- 4.4 Performance Evaluation -- 5 Results -- 6 Conclusion -- References -- Evaluating Deep Neural Network Ensembles by Majority Voting Cum Meta-Learning Scheme -- 1 Introduction -- 2 Combining the Results of Independent Learners -- 3 Proposed Ensemble Approach -- 4 Results -- 5 Conclusion -- References -- Virtual Mouse Control Using Finger Action -- 1 Introduction -- 2 Existing System -- 3 Proposed System -- 4 Proposed Algorithm -- 4.1 Actions Performed Using Speech Recognition -- 4.2 Task Performed Using Speech Reorganization -- 5 Implementation -- 6 Conclusion -- References -- A Hybrid Model for Combining Neural Image Caption and k-Nearest Neighbor Approach for Image Captioning -- 1 Introduction -- 2 Related Work -- 3 Proposed Hybrid Model -- 3.1 Methodology -- 3.2 Feature Extraction and Normalization.
4 Results -- 5 Conclusion -- References -- Neural Abstractive Text Summarizer for Telugu Language -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Recurrent Neural Network Encoder-Decoder -- 4 Training -- 5 Evaluation -- 6 Conclusions -- References -- OCR-Based Assistive System for Blind People -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 4 Workflow -- 5 Hardware Components -- 6 Software Used -- 7 OCR -- 8 Tesseract -- 9 Text to Speech (TTS) -- 10 Results -- 11 Billing Description and Output -- 12 Conclusion -- References -- Modern Privacy Risks and Protection Strategies in Data Analytics -- 1 Introduction -- 1.1 Privacy and Privacy Threats -- 2 Privacy Preservation Methods -- References -- An Approach Toward Deep Learning-Based Facial Expression Recognition in Wavelet Domain -- 1 Introduction -- 2 Related Works -- 3 The Proposed Framework -- 3.1 Face Processing -- 3.2 Feature Representation Using DWT -- 3.3 Expression Recognition Using CNN -- 4 Experimental Results and Discussions -- 5 Conclusions -- References -- Modified UNet Architecture with Less Number of Learnable Parameters for Nuclei Segmentation -- 1 Introduction -- 2 Methodology -- 2.1 UNet -- 2.2 Segnet -- 3 Experiments and Results -- 3.1 Dataset Description -- 3.2 Results and Discussions -- 4 Conclusion -- References -- Classification of Diseases Using CBC -- 1 Introduction -- 2 Review of Literature -- 3 Implementation -- 3.1 Data Pre-Processing -- 3.2 Model Training -- 3.3 Evaluation of Model -- 3.4 Machine Learning Algorithms -- 3.5 Analysis of the Model -- 4 Experimental Results and Performance Analysis -- 5 Conclusion and Future Scope -- References -- Post-earthquake Building Damage Detection Using Deep Learning -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 3.1 Preprocessing -- 3.2 Network Architecture -- 3.3 Jaccard Index. 3.4 Dice Coefficient -- 4 Experiments and Setup -- 4.1 Dataset -- 4.2 Setup -- 4.3 Parameters -- 4.4 Analysis -- 5 Conclusion -- References -- Ensemble of Deep Transfer Learning Models for Parkinson's Disease Classification -- 1 Introduction -- 2 Methodology -- 2.1 Architectural Performance -- 2.2 Ensemble Method -- 2.3 Dataset -- 3 Results and Discussion -- 3.1 Experimental Results from Commonly Used Deep Learning Architectures -- 3.2 Experimental Results from the Proposed Ensemble Model -- 4 Conclusion -- References -- Energy-Efficient Clustering in Real-World Wireless Sensor Networks: Implementation -- 1 Introduction -- 2 Literature Survey -- 3 Clustering in Real-World WSNs -- 4 Energy Efficient Clustering: Optimal Cluster Head Selection -- 5 Hopcount Matrix: Properties -- 6 Implementation, Results and Discussions -- 7 Conclusions -- References -- Customer Feedback Through Facial Expression Recognition System Using Neural Network -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Image Data Collection -- 3.2 Data Preprocessing -- 3.3 Model Selection and Training -- 4 Models for Facial Expression Recognition -- 4.1 CNN -- 4.2 VGG16 -- 4.3 VGG19 -- 5 Transfer Learning -- 6 Result and Analysis -- 6.1 Final Results on Real-Time Faces -- 7 Conclusion -- References -- Taxi Demand Prediction Using LSTM and Optimized Taxi Geo-distribution -- 1 Introduction -- 2 Related Work -- 3 Implementation of Location and Time-Based Taxi Demand Prediction -- 3.1 Data Preparation -- 3.2 Time Binning -- 3.3 Feeding the Input to the LSTM Model -- 3.4 Training the Model -- 3.5 Testing the Model -- 4 Proposed Rank-Based Optimized Algorithm for Driver Mapping -- 4.1 Driver-Demand Check -- 4.2 Construction of Rank Table -- 4.3 Driver Mapping Using Rank Table -- 4.4 Mapping Optimization -- 5 Results -- 6 Conclusion -- References. Container ID Detection and Recognition -- 1 Introduction -- 2 Related Works -- 3 Technical Details -- 3.1 Architecture of the System -- 3.2 Data Collection -- 3.3 Data Preprocessing -- 4 Detection Module -- 4.1 Container Detection -- 4.2 Text Detection -- 4.3 Character Detection -- 5 Classification Module -- 6 Experimental Results -- 7 Performance Analysis -- 8 Summary -- References -- Autonomous Flying Using Deep Reinforcement Learning -- 1 Introduction -- 2 Literature Survey -- 3 Experimental Setup -- 3.1 Virtual Environment -- 3.2 Quadcopter -- 3.3 Deep Deterministic Policy Gradient -- 4 Workflow -- 5 Results and Conclusion -- References -- Detecting Surface Cracks on Buildings Using Computer Vision: An Experimental Comparison of Digital Image Processing and Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Acquisition -- 3.2 Building the Classifier -- 3.3 Evaluation -- 3.4 Interpretation -- 4 Experimental Results -- 4.1 The DIP-Based Approach Performance -- 4.2 The Deep Learning-Based Approach -- 4.3 Performance on Dataset 4 -- 5 Conclusion -- 6 Future Scope of Work -- 7 Declaration -- References -- A Survey on Preserving Data Confidentiality in Cloud Computing Using Different Schemes -- 1 Introduction -- 2 Literature Survey -- 3 The Objective of the Study -- 4 Results and Comparisons -- 5 Conclusion -- References -- Deep Learning-Based Approach for Human Activity Recognition -- 1 Introduction -- 2 Literature Survey -- 3 Problem Definition -- 4 Proposed System -- 4.1 Mathematical Foundation -- 4.2 Proposed Model -- 5 Performance Analysis and Result -- 6 Conclusion and Future Scope -- References -- Vuln-Check: A Static Analyzer Framework for Security Parameters in Web -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Work -- 3.1 Recon Phase -- 3.2 Scanning -- 3.3 Enumeration -- 3.4 Static Analyzer Phase. 3.5 Reporting -- 4 Experimental Setup and Results -- 5 Comparative Analysis -- 6 Conclusion -- References -- Concept Drift Detection Using Minimum Prediction Deviation -- 1 Introduction -- 2 Related Work -- 3 Minimum Prediction Deviation -- 3.1 Bootstrapping Samples -- 3.2 Uncertainty -- 3.3 Minimum Prediction Deviation Score -- 4 Methodology -- 5 Experiments -- 5.1 Datasets -- 5.2 Experimental Setup -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- An Interactive System for Assessing Emotional Wellness -- 1 Introduction -- 2 Related Works -- 3 Architecture Overview -- 4 Implementation -- 4.1 Anxiety Test Questionnaire -- 4.2 Fuzzification -- 4.3 Rule base -- 4.4 Rule Evaluation and Aggregation -- 4.5 Defuzzification -- 5 Results -- 6 Conclusion and Future Scope -- References -- Performance Analysis of Genetic Algorithm for Function Optimization in Multicore Platform Using DEAP -- 1 Introduction -- 2 Literature Survey -- 3 Genetic Algorithm for Function Optimization Using Multicore Platform -- 3.1 Multicore Platform -- 3.2 Distributed Evolutionary Algorithms in Python (DEAP) -- 3.3 Genetic Algorithm for Function Optimization Using Multicore Platform -- 3.4 Benchmark Functions and Parameter Settings -- 4 Experimental Analysis -- 4.1 Experimental Setup and Parameter Setting -- 4.2 Performance Analysis of Genetic Algorithm for Function Optimization in Single and Multicore Platforms for Function with Fixed Variables -- 4.3 Performance Analysis of Genetic Algorithm for Function Optimization in Single and Multicore Platforms for Function with Variable Dimensions -- 5 Conclusion -- References -- Various Image Modalities Used in Computer-Aided Diagnosis System for Detection of Breast Cancer Using Machine Learning Techniques: A Systematic Review -- 1 Introduction -- 2 Methodology -- 2.1 Data Extraction -- 3 Results. 3.1 Imaging Modalities. |
| Altri titoli varianti | Soft Computing and Signal Processing |
| Record Nr. | UNINA-9910497108703321 |
|
Reddy V. Sivakumar
|
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| Singapore : , : Springer Singapore Pte. Limited, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||