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Intelligent Systems Design and Applications : Machine Learning Solutions, Volume 7
| Intelligent Systems Design and Applications : Machine Learning Solutions, Volume 7 |
| Autore | Abraham Ajith |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (510 pages) |
| Altri autori (Persone) |
BajajAnu
HanneThomas |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 9783031647765 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Comparative Study of Image Compression Methods Using Artificial Neural Networks Based on Semi-log Quantization -- 1 Introduction -- 2 Related Work -- 3 Image Compression by Neural Networks -- 3.1 Image Compression by Back-Propagation Neural Networks -- 3.2 Image Compression by Adaptive Neural Networks -- 3.3 Image Compression by Kohonen Networks -- 4 The Suggested Approach to Improve Compression Based on ANN -- 5 Experimental Study and Discussion -- 6 Conclusion -- References -- Granular Clustering for Maritime Situation Awareness -- 1 Introduction -- 2 Situation Awareness -- 3 Maritime Situation Awareness Based on Granular Clustering -- 3.1 Situation Representation Using Rough K-Means -- 4 Evaluation -- 4.1 Dataset -- 4.2 Results -- 5 Conclusions and Future Work -- References -- Hybrid Approach for Medical Decision-Making: Integrating ResNet-Darknet19 Based Transfer Learning with Radiomics Features for COVID-19 Classification -- 1 Introduction -- 2 ResNet-Darknet19 Transfer Learning -- 3 Radiomics Features -- 4 Hybrid Approach: Integration of ResNet-Darknet19 Transfer Learning with Radiomics Features -- 5 Methods and Materials -- 5.1 Phase 1: Transfer Learning on X-ray Lung Images -- 5.2 Phase 2: Radiomics-Based Feature Extraction and Retraining -- 6 Results and Findings -- 7 Discussion -- 8 Conclusion -- References -- Hate Speech Detection Using Deep Learning Algorithms -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 System Architecture -- 3.2 Modules -- 4 Implementation -- 5 Result and Analysis -- 6 Conclusion and Future Work -- References -- Classification of Cardiac Arrhythmia Using Machine Learning Algorithms -- 1 Introduction -- 1.1 Cardiac Arrhythmia -- 1.2 ECG Signals -- 2 Literature Review -- 3 Research Methodology -- 3.1 Machine Learning -- 3.2 Description of Dataset.
3.3 Pre-processing -- 3.4 Performance Measures -- 4 Machine Learning Algorithms -- 4.1 Decision Tree -- 4.2 K-Nearest Neighbor -- 4.3 Support Vector Machine -- 4.4 XGBoost -- 4.5 Ensemble Algorithm-Random Forest -- 5 Statistical Analysis of Results -- 5.1 Classification Result -- 6 Limitations -- 7 Future Scope -- 8 Conclusion -- References -- Exploring Machine Learning Approaches for Precipitation Prediction: Post Processing of Daily Accumulated North American Forecasts -- 1 Introduction -- 2 Data -- 2.1 Input Weather Models -- 2.2 Data Preprocessing -- 3 Models and Metrics -- 4 Results and Discussion -- 4.1 Discussion -- References -- Deep Learning-Based Classification of Conference Paper Reviews: Accept or Reject? -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 3.1 Dataset Description -- 3.2 Data Cleaning and Preprocessing -- 3.3 Proposed Model -- 3.4 Explainable AI Techniques -- 4 Experimental Results -- 4.1 Performance Evaluations -- 4.2 Explanation of Bi-GRU-LSTM-CNN Model Using XAI Techniques -- 4.3 Response of Proposed RQs -- 5 Conclusions -- References -- A Layout Independent Deep Learning Framework for Recognition of Courtesy-Amount in Bank-Cheque Image -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Mask-RCNN Model-Based Courtesy Field Detection -- 3.2 Refinement of the Mask-RCNN Detection -- 3.3 Handwritten Digit Extraction -- 3.4 CNN-Based Digit Sequence Recognition -- 4 Experimentation, Results and Analysis -- 4.1 Data Set Preparation -- 4.2 Results and Performance Analysis -- 5 Conclusion -- References -- Convolutional Neural Network (CNN) Classifiers Used in Land Use/Land Cover Monitoring and Classification: A Review -- 1 Introduction -- 2 General Architecture -- 3 Datasets -- 4 Evaluation Metrics -- 5 Literature Survey -- 6 Challenges and Issues -- 7 Future Directions and Conclusion. References -- Classification of Obesity Level Using Deep Neural Networks*-8pt -- 1 Introduction -- 2 Related Work -- 3 Background -- 4 Material and Methods -- 4.1 Machine Learnings Models -- 4.2 Dataset Description -- 4.3 Methodology -- 4.4 Metrics -- 5 Simulation Results -- 6 Conclusions -- References -- Analysis of Deepfake Attacks and Detection Techniques in Smart City Applications -- 1 Introduction -- 2 Related Works -- 3 Proposed Models -- 3.1 Convolutional Neural Network (CNN) VGG16 -- 3.2 Recurrent Neural Network (RNN) LSTM -- 3.3 k-Nearest Neighbors (kNN) -- 3.4 Evaluation Metrics -- 4 Data Analysis and Results -- 4.1 The CNN VGG16 Model Using CelebDF Dataset -- 4.2 The CNN VGG16 Model Using DFDC Dataset -- 4.3 The kNN Model Using DFDC Dataset -- 4.4 The RNN LSTM Model Using CelebDF -- 4.5 The RNN LSTM Model Using DFDC -- 5 Conclusions -- References -- Deep-Net: Brain Lesion Segmentation with 3D CNN and Residual Connections -- 1 Introduction -- 2 Proposed Approach -- 3 Experimental Results -- 4 Conclusion -- References -- A Bimodal Autism Spectrum Disorder Detection Using fMRI Images -- 1 Introduction -- 2 Proposed Method -- 2.1 Feature Extraction -- 2.2 Classification -- 3 Experiments and Results -- 3.1 Experimental Settings -- 3.2 Experimental Results -- 4 Conclusion -- References -- Brood Parasitism Identification Using a Deep Learning Model with Mish Activation Function -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Pre-processing of Egg Images -- 3.2 Convolutional Neural Network with Mish Activation Function -- 4 Experimental Study -- 4.1 Dataset -- 4.2 Experimental Results -- 5 Conclusion -- References -- Mobile Application for Diabetic Foot Ulcer Detection -- 1 Introduction -- 2 Related Work -- 3 Software Development Methodology -- 3.1 Software Requirements -- 3.2 Design Patterns and Architecture. 3.3 Languages and Frameworks -- 4 Lesions Detection -- 4.1 Image Dataset -- 4.2 Object Detection Algorithms Evaluated -- 4.3 Assessment Metrics -- 5 Results and Discussion -- 5.1 Application Prototype -- 5.2 Results of Lesion Detection -- 6 Conclusion and Future Work -- References -- Unlocking the Power of LLM-Based Question Answering Systems: Enhancing Reasoning, Insight, and Automation with Knowledge Graphs -- 1 Introduction -- 2 Business Case -- 3 Knowledge Modelling: Ontology Development -- 3.1 Knowledge Graph Queries for Insights -- 3.2 From Insight to Action -- 4 Experimental Setup -- 4.1 Knowledge Graph-Prompting -- 4.2 Knowledge Graph Embedding (KGE) -- 4.3 Translating Text Queries to Graph Queries -- 4.4 Building the Knowledge Graph -- 5 Results -- 6 Discussion and Conclusion -- References -- Comparative Analysis of Machine Learning Models for Breast Cancer Patients' Survival Prediction -- 1 Introduction -- 2 Machine Learning Methods Applied to Survival Analysis -- 2.1 Cox Proportional Hazards -- 2.2 Gradient Boosting Survival -- 2.3 Random Survival Forest -- 2.4 Survival Support Vector Machine -- 3 Material and Methods -- 3.1 Database and Data Preprocessing -- 3.2 Methods, Attributes, and Hyperparameters -- 3.3 Performance Metrics -- 4 Results and Discussion -- 5 Conclusion -- References -- Unsupervised Analysis of Clinical and Laboratory Parameters of Chronic Kidney Disease -- 1 Introduction -- 2 Related Work -- 3 Material and Methods -- 3.1 Clustering Methods -- 3.2 Dataset -- 3.3 Pre-processing -- 3.4 Data Filtering and Analysis -- 3.5 Classification of Exam Values -- 4 Results and Discussion -- 4.1 Class Distribution Analysis by Stage -- 4.2 Computational Experiment -- 4.3 Results from the Clustering Algorithm -- 4.4 Dimensionality Reduction Method -- 5 Conclusion -- References. Use of Deep Learning for the Segmentation of Aquaculture Fishponds in the State of Minas Gerais, Brazil -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Acquisition -- 2.2 YOLO Model -- 2.3 Evalutation Metrics -- 2.4 Calculating the Location and Area of the Fishponds -- 3 Results and Discussion -- 3.1 The Model -- 3.2 Area of the Fishponds -- 4 Conclusions -- References -- Bridging the Mind-Machine Gap: Harnessing AI and ML for EEG Signal Processing and Brainwave Decoding -- 1 Introduction -- 1.1 Decoding the Neuroelectric Lexicon -- 1.2 Applications: Unveiling the Brain's Enigma -- 1.3 The Essence of Feature Extraction -- 1.4 Pioneering Future Frontiers -- 2 Literature Review -- 3 Understanding EEG Data -- 4 Preprocessing of EEG Data: Enhancing Signal Quality for Accurate Analysis -- 4.1 Filtering -- 4.2 Artifact Removal -- 4.3 Referencing -- 4.4 Spatial Features: Visualizing Brain Activity Distribution -- 5 Advanced Analysis Techniques in EEG Signal Processing -- 5.1 Event-Related Potentials (ERPs): Probing Brain Responses -- 5.2 Time-Frequency Analysis: Unveiling Temporal and Frequency Dynamics -- 5.3 Machine Learning and Deep Learning: Decoding Brain Patterns -- 6 Brain-Computer Interfaces (BCIs): A Paradigm of Neurotechnology -- 6.1 Neurofeedback: Training the Brain for Therapeutic Gains -- 6.2 Cognitive Neuroscience: Unraveling Brain Functions and Cognitive Processes -- 6.3 Clinical Diagnosis: Detecting and Addressing Neurological Disorders -- 7 Conclusion -- 7.1 Advanced Techniques in EEG Signal Processing -- 7.2 Applications of EEG Signal Processing -- 7.3 The Future: Advancements and Possibilities -- References -- Analysis of Intelligent Crop Recommendation System -- 1 Introduction -- 2 Literature Review -- 3 Methods and Material -- 4 Results and Discussion -- 5 Conclusion -- References. Multiclass Chest X-Ray Image Classification for Respiratory Diseases: A Deep Learning Framework. |
| Record Nr. | UNINA-9910874686303321 |
Abraham Ajith
|
||
| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Systems Design and Applications : Smart Healthcare, Volume 1
| Intelligent Systems Design and Applications : Smart Healthcare, Volume 1 |
| Autore | Abraham Ajith |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (0 pages) |
| Altri autori (Persone) |
BajajAnu
HanneThomas SiarryPatrick |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 9783031648137 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Identifying Lung Cancer from CT-Scan Images with VGG16 Convolutional Neural Net -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Model Building & -- Training -- 3.4 Results & -- Discussion -- 4 Conclusion -- References -- Cause and Effect of Dementia on Women in Technological Environment -- 1 Introduction -- 2 Literature Survey -- 3 Cause of Dementia -- 4 Comparative Analysis of Dementia -- 5 An Intelligent Dementia Detector -- 6 Conclusion -- References -- Machine Learning Techniques for Pancreatic Cancer Detection -- 1 Introduction -- 1.1 Pancreatic Cancer: A Lethal Challenge -- 1.2 Importance of Early Detection -- 1.3 Role of Machine Learning in Cancer Detection -- 2 Literature Review -- 3 Empowering Cancer Detection with ML -- 3.1 Basic Machine Learning Algorithms for Pancreatic Cancer Detection -- 3.2 Advance Machine Learning Techniques -- 3.3 Deep Learning Methods for Pancreatic Cancer Detection -- 4 Materials and Methods -- 4.1 Data Collection -- 4.2 Data Preprocessing -- 4.3 Machine Learning Algorithms -- 4.4 Interpretability and Explainability -- 4.5 Performance Evaluation -- 5 Results -- 5.1 Performance Evaluation Metrics: -- 5.2 Performance Comparison -- 5.3 Feature Importance Analysis: -- 6 Discussion -- 7 Conclusion -- References -- Integrating Artificial Intelligence and Data Analytics for Enhanced Healthcare Management: Innovations and Challenges -- 1 Introduction -- 2 Background -- 3 Research Methodology -- 4 Applications of AI in Healthcare Industry -- 4.1 AI for Drug Discovery -- 4.2 AI for Clinical Trials -- 5 Challenges of Artificial Intelligence in Healthcare Management -- 5.1 Data Availability and Its Quality -- 5.2 Data Privacy and Security -- 5.3 Interoperability -- 6 Conclusion -- References.
An Intelligent Model for Post Covid Hearing Loss -- 1 Introduction -- 2 Mathematical Model -- 3 Non-negativity and Boundedness of the Solutions -- 4 Stability Analysis -- 5 Numerical Simulations -- 6 Result -- 7 Conclusion and Future Work -- References -- Medical Reports Simplification Using Large Language Models -- 1 Introduction -- 2 Materials and Methods -- 2.1 Fine-Tuning T5 -- 3 Results and Discussion -- 4 Conclusion -- References -- Analysis of Magnetic Resonance Imaging for Parkinson's Disease -- 1 Introduction -- 2 Dataset Description -- 3 Methodology -- 4 Simulation Results -- 5 Conclusion -- References -- Study on Health Issue Identification Using Deep Learning and Convolutional Neural Networks -- 1 Introduction -- 1.1 Benefits of Deep Learning in the Medical Field -- 1.2 Enhanced Diagnostics -- 2 Methods -- 3 Conclusion -- References -- Early-Stage Lung Cancer Prediction: A Machine Learning Approach -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset -- 3.2 Pre-processing -- 3.3 Exploratory Data Analysis -- 3.4 Machine Learning Algorithms -- 3.5 Model Evaluation -- 3.6 GridSearchCV -- 3.7 Feature Importance -- 4 Results -- 4.1 Results of EDA -- 4.2 Model Evaluation -- 5 Discussion -- 6 Conclusion -- References -- Convolutional Neural Network-Based Brain Tumor Segmentation Using Detectron2 -- 1 Introduction -- 2 Problem Statement -- 3 Convolutional Neural Networks -- 3.1 Mask R-CNN -- 3.2 Detectron2 -- 4 Results and Discussion -- 4.1 Quantitative Evaluation -- 4.2 Qualitative Evaluation -- 5 Conclusion and Future Works -- References -- Deep Learning-Based Histopathological Analysis for Colon Cancer Diagnosis: A Comparative Study of CNN and Transformer Models with Image Preprocessing Techniques -- 1 Introduction -- 2 Related Works -- 3 Proposed System -- 3.1 Preprocessing -- 3.2 Deep Learning Networks. 4 Results and Discussion -- 4.1 Dataset Description -- 4.2 Data Augmentation -- 4.3 Performance Analysis -- 5 Conclusion -- References -- Detecting Parkinson's Disease at an Early Stage Through Machine Learning Analysis of Brain MRI Images -- 1 Introduction -- 2 Methodology -- 2.1 Data Collection and Pre-processing -- 2.2 Skull Stripping Segmentation -- 2.3 Feature Extraction -- 2.4 Machine Learning Classification -- 2.5 Validation -- 3 Results -- 3.1 Segmentation -- 3.2 Feature Extraction -- 3.3 Brain Shape Analysis -- 3.4 Performance of Machine Learning Classifiers -- 4 Discussion -- 5 Conclusion -- References -- Early-Stage Cervical Cancer Detection via Ensemble Learning and Image Feature Integration -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 Preprocessing Module -- 3.2 Classification Module -- 3.3 Proposed Feature Integration -- 4 Results -- 4.1 Experimental Environment -- 4.2 Dataset -- 4.3 Evaluation Criteria -- 4.4 Experimental Results -- 5 Conclusion -- References -- Comprehensive Comparative Analysis of Breast Cancer Forecasting Using Machine Learning Algorithms and Feature Selection Methods -- 1 Introduction -- 2 Methodology -- 2.1 Dataset Preparation -- 2.2 Machine Learning Model -- 2.3 Dataset -- 3 Result and Discussion -- 4 Conclusion -- References -- Classification of Arrhythmia Using Deep Learning -- 1 Introduction -- 1.1 Motivation -- 1.2 Objectives -- 1.3 Advantages of the Proposed Methodology -- 2 Background -- 2.1 Limitations of the Existing Model -- 3 Proposed Methodology -- 3.1 Dataset Pre-processing: -- 3.2 Terms -- 4 Results -- 5 Future Work -- 6 Conclusion -- References -- An Integrated Machine Learning and IoT Based Approach for Enhanced Healthcare Efficiency and Personalized Treatment -- 1 Introduction -- 2 Methodology -- 2.1 Sensors Used in This Research -- 2.2 Machine Learning Algorithm. 3 Working of the Proposed System -- 4 Result and Discussion -- 5 Conclusion -- References -- CeLaTis: A Large Scale Multimodal Dataset with Deep Region Network to Diagnose Cervical Cancer -- 1 Introduction -- 2 Related Works -- 2.1 Colposcope Image Datasets -- 2.2 Automated Diagnostic Models on Colposcope Images -- 3 CeLaTis Dataset -- 3.1 Data Acquisition -- 3.2 Acquisition Procedure -- 3.3 Features -- 4 Methodology -- 4.1 Segmentation -- 4.2 Lesion Recognition Network -- 4.3 Classification -- 5 Conclusion -- References -- A Deep Learning Approach With Sparse Autoencoder for Alzheimers Disease Classification -- 1 Introduction -- 2 Research Background -- 3 Dataset -- 4 Proposed Methodology -- 4.1 Preprocessing -- 4.2 Feature Extraction and Dimensionality Reduction -- 4.3 Deep Neural Network -- 5 Results and Discussion -- 6 Conclusion -- References -- An Improved Gradient Based Joint Histogram Equalization Technique for Mammogram Image Contrast Enhancement -- 1 Introduction -- 2 Suggested Methodology -- 2.1 Extraction of the Gradient Image -- 2.2 Contrast Enhancement Using Joint Histogram -- 3 Results and Discussion -- 4 Conclusion -- References -- Comparative Performance Analysis of Deep Learning Models in Cervical Cancer Detection -- 1 Introduction -- 2 Related Literature -- 3 Methods -- 3.1 DenseNet -- 3.2 AlexNet -- 3.3 ResNet -- 3.4 Vgg 16 -- 4 Results -- 4.1 Experimental Environment -- 4.2 Dataset -- 4.3 Evaluation Criteria -- 4.4 Experimental Results -- 5 Conclusion -- References -- Comparative Analysis for Feature Selection Approaches for Parkinson's Disease Prediction -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Data -- 3.2 Exploratory Analysis of Data -- 3.3 Feature Selection Methods -- 3.4 Classification Algorithm -- 4 Result Analysis -- 4.1 Metrics -- 4.2 Statistical Analysis -- 5 Conclusion and Future Works. References -- Autism Spectrum Disorder Prediction: A Machine Learning Approach -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset -- 3.2 Pre-processing -- 3.3 Exploratory Data Analysis -- 3.4 Machine Learning Algorithms -- 3.5 Model Evaluation -- 3.6 K-fold Cross-Validation -- 3.7 Feature Importance -- 4 Results -- 4.1 Results of EDA -- 4.2 Model Evaluation -- 5 Discussion -- 6 Conclusion -- References -- Epileptic Seizure Detection on EEG Images Using the Decimal Descriptor Pattern -- 1 Introduction -- 2 Methodology -- 2.1 Database -- 2.2 Feature Extraction -- 2.3 Support Vector Machine (SVM) Classifier -- 2.4 Proposed Approach -- 3 Results and Discussion -- 4 Conclusion -- References -- Influence of Rician Noise on Cardiac MR Image Segmentation Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 MRI Dataset -- 3.2 Rician Noise in MRI Image -- 3.3 AI Segmentation Models -- 3.4 Assessing the Noise Resilience of the Model -- 4 Result -- 5 Discussion -- 6 Conclusion -- References -- A Single-Stage Deep Learning Approach for Multiple Treatment and Diagnosis in Panoramic X-ray -- 1 Introduction -- 2 Material and Methods -- 2.1 Dataset and Annotation -- 2.2 Proposed Method -- 2.3 Experimental Setup -- 3 Results and Discussion -- 4 Conclusion -- References -- Precision Care in Addiction Treatment: A Bayesian-Based Machine Learning Analysis for Adults with Substance Use Disorders -- 1 Introduction -- 2 Related Works -- 2.1 Machine Learning for HealthCare -- 2.2 Machine Learning for SUD Treatment -- 3 Methods -- 3.1 Proposed Structure -- 3.2 Data Pre-Processing and Filtration Criteria -- 4 Results and Discussion -- 4.1 Outcome Obtained Through Cross-Validation Methods -- 5 Conclusion and Future Work -- References. Hybrid Network Model for the Prediction of Retinopathy of Prematurity from Neonatal fundus images. |
| Record Nr. | UNINA-9910878050103321 |
|
Abraham Ajith
|
||
| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Systems Design and Applications : Deep Learning, Volume 2
| Intelligent Systems Design and Applications : Deep Learning, Volume 2 |
| Autore | Abraham Ajith |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2024 |
| Descrizione fisica | 1 online resource (514 pages) |
| Altri autori (Persone) |
BajajAnu
HanneThomas HongTzung-Pei |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 3-031-64836-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Deep Learning Approach for Autonomous Spacecraft Landing -- 1 Introduction -- 2 Related Work -- 3 Simulation Details -- 4 Training a Deep Neural Network -- 5 Results -- 6 Conclusion and Future Scope -- References -- Deep Learning Approach for Flood Mapping Using Satellite Images Dataset -- 1 Introduction -- 2 Related Works -- 3 Proposed Algorithm -- 4 Data Analysis and Results -- 4.1 Sample Output -- 4.2 Performance Analysis -- 4.3 Performance Graph -- 5 Conclusion -- References -- Large Language Models for Named Entity Recognition (NER) of Skills in Job Postings in German -- 1 Introduction -- 2 Problem Description -- 2.1 Problem -- 2.2 Optimization Methods -- 2.3 Implementation and Comparison of Different Optimization Methods -- 3 Models -- 4 Evaluation Methods -- 5 Standard NER Functionality -- 6 Context Model -- 7 Few-Shot Learning Model -- 8 Cost Considerations -- 9 Conclusions -- References -- Machine Learning Approaches for Investing Strategies in Stock Market -- 1 Introduction -- 2 Literature Review -- 3 System Architecture: Enhancing Investing Strategies with Ml -- 3.1 Architecture and System Architecture for Machine Learning Approaches in Investing Strategies for Stock Market -- 3.2 Data Preprocessing -- 3.3 Model Training -- 3.4 Model Evaluation -- 3.5 Model Deployment -- 3.6 System Architecture -- 3.7 Flowchart -- 4 Description of the Experiment -- 4.1 Model Training -- 4.2 DNN Model Training -- 4.3 Evaluation -- 5 Strategic Stock ML Implementation -- 6 Results and Decision Making: Leveraging Machine Learning for Stock Market Investing -- 6.1 Better Prediction -- 6.2 Entry/Exit Points -- 6.3 Data-Driven Decisions -- 6.4 Portfolio Performance -- 6.5 Decision Making -- 7 Comparison of Machine Learning Techniques for Investing Strategies in the Stock Market -- 7.1 Math Foundations.
7.2 Predictive Skills -- 7.3 Graphical Representations: -- 8 Conclusion: Embracing the Future of Stock Market Investing with Machine Learning -- 8.1 Data-Driven Decision Making -- 8.2 Future Scope -- References -- OP-FedELM: One-Pass Privacy-Preserving Federated Classification via Evolving Clustering Method and Extreme Learning Machine Hybrid -- 1 Introduction -- 2 Literature Survey -- 3 Preliminaries -- 3.1 Evolving Clustering Machine -- 3.2 Extreme Learning Machine -- 4 Proposed Methodology -- 4.1 Phase I: Generation of the Perturbed Dataset -- 4.2 PHASE II: OP-FedELM -- 5 Dataset Description -- 6 Results and Discussions -- 6.1 Computational Analysis -- 7 Conclusions and Future Directions -- References -- Gamma Corrected Pyramid Pix2pix - Breast Cancer HE to IHC Image Generation -- 1 Introduction -- 2 Existing Solutions and Objective of Present Study -- 3 Methods and Materials -- 3.1 The Programming Environment -- 4 Proposed Methodology -- 5 Results and Discussions -- 5.1 Projection Profile Comparison -- 5.2 Qualitative Validation -- 6 Conclusions and Future Scope -- References -- Unveiling Deepfakes: Convolutional Neural Networks for Detection -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Proposed Method -- 5 Results and Discussion -- 6 Conclusion -- References -- The Nasdaq Composite Index Prediction Using LSTM and Bi-LSTM Multivariate Deep Learning Approaches -- 1 Introduction -- 2 Related Studies -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- PlastOcean: Detecting Floating Marine Macro Litter (FMML) Using Deep Learning Models -- 1 Introduction -- 1.1 Effect of FMML on CO2 Cycle -- 1.2 Effect of FMML on Aquatic Life -- 1.3 Estimation of Plastic Production -- 1.4 Non-AI-Based Estimation Methodologies of FMML Identification -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Constructing Datasets. 3.2 Enhancing PlastOcean Dataset -- 3.3 Building Deep Neural Network for Object Detection -- 4 Results -- 5 Discussion -- 5.1 Previous Results by the Ocean Cleanup -- 5.2 Improving the Dataset -- 6 Conclusion and Future Work -- References -- Data Augmentation Using Generative Neural Networks Based on Fourier Feature Mapping -- 1 Introduction -- 2 Related Work -- 2.1 Data-Level Approaches -- 2.2 Data-Level Approaches -- 2.3 Cost-Sensitive Learning -- 3 Proposed Approach -- 3.1 Basic Concept -- 3.2 Approach Details -- 4 Experiment -- 4.1 Experimental Data and Environment -- 4.2 Experimental Settings -- 4.3 Experimental Results -- 5 Conclusions -- References -- Delay Risk Detection in Road Construction Projects Utilizing Large Language Model -- 1 Introduction -- 2 Related Work -- 2.1 Delay Risk Identification in Construction Projects -- 2.2 Text Mining in Construction Project Management -- 3 Road Construction Delay Risk Detection System -- 4 Experiment and Results -- 4.1 Experiment Setup -- 4.2 Results -- 5 Conclusion -- References -- Unlocking the Potential of Novel LSTM in Airline Recommendation Prediction -- 1 Introduction -- 2 Literature Review -- 2.1 Customer Recommendations -- 2.2 Online Reviews -- 3 Proposed Methodology -- 3.1 Dataset Description -- 3.2 Data Pre-processing -- 3.3 Feature Selection -- 3.4 Machine Learning Methodologies -- 3.5 Model Architecture -- 4 Result Analysis -- 4.1 Training -- 4.2 Testing -- 5 Conclusion -- References -- Pylung: A Supporting Tool for Comparative Study of ViT and CNN-Based Models Used for Lung Nodules Classification -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Dataset -- 3.2 Preparing the Dataset -- 3.3 Models -- 3.4 Pylung Tool -- 4 Results -- 5 Discussion -- 6 Conclusion -- References. Deep Learning Model for Predicting Rice Plant Disease Identification and Classification for Improving the Yield -- 1 Introduction -- 2 Methodology -- 2.1 Dataset Description -- 2.2 Types and Number of Diseases Represented -- 2.3 Description of Neural Architecture Search (NAS) -- 3 Proposed Methodology -- 4 Results and Discussion -- 4.1 Performance of Proposed Method -- 4.2 Comparison with Other Disease Detection Methods -- 5 Conclusion -- References -- Deep Learning-Based Active Fire Detection Using Satellite Imagery -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 Data Source -- 2.3 Approach -- 3 Results -- 4 Conclusion -- References -- Evaluating Time Series Classification with GAN-Generated Synthetic Data -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- Word2Vec-GloVe-BERT Embeddings for Query Expansion -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Word2Vec Term Embeddings Creation and Selection -- 3.2 GloVe Term Embeddings Creation and Selection -- 3.3 BERT Term Embeddings Creation and Selection -- 4 Evaluation -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 5 Conclusion -- References -- A BERT Based Architecture for Detecting Arabic Fake News -- 1 Introduction -- 2 Related Work -- 2.1 Classical Machine Learning Approaches -- 2.2 Deep Learning Approaches -- 2.3 Bidirectional Encoder Representations from Transformer (BERT) Approaches -- 3 Dataset Details -- 4 Proposed Approach -- 4.1 Bidirectional Encoder Representations from Transformers (BERT) -- 4.2 AraBERT -- 4.3 AraBERT V2.0 -- 4.4 Other Models -- 5 Experiments and Results -- 5.1 Experimental Setup -- 5.2 Experimental Results -- 6 Conclusion -- References -- Deep Learning-Based Approaches for Facial Recognition Technology Through Convolutional Neural Networks -- 1 Introduction. 2 Background Details and Related Work -- 3 Proposed Approach -- 4 Implementation of the System -- 5 Conclusions -- References -- Cognizant Prognostication: An In-Depth Comparative Study of Machine Learning Models for Predictive Employee Turnover Analysis in the Realm of Human Resources Analytics -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 3.1 Data Pre-processing -- 3.2 Feature Engineering -- 3.3 Dataset Split and Model Selection -- 4 Model Training and Evaluation -- 4.1 Model Training -- 4.2 Model Evaluation -- 4.3 Results and Comparison -- 5 Discussion -- 6 Results -- 6.1 Model Training -- 6.2 Model Evaluation -- 7 Comparison Table -- 8 Roc Curves -- 9 Discussion -- 10 Conclusion -- References -- Enhancing Road Infrastructure Maintenance Using Deep Learning Approach -- 1 Introduction -- 2 Related Works -- 3 Model Introduction and Improvement -- 4 Dataset -- 5 Design and Implementation -- 5.1 Implementation -- 5.2 Image Dataset -- 5.3 Dataset Preparation -- 5.4 Model Training -- 6 Experimental Results and Discussion -- 6.1 YOLOV8 with Crack Class -- 6.2 YOLOV8 with Pothole Class -- 6.3 YOLOV8 with Two Classes -- 6.4 Visual Analysis -- 7 Conclusion and Future Works -- References -- E-Learning Facial Emotion Recognition Using Deep Learning Models -- 1 Introduction -- 2 Related Work -- 2.1 Approaches to Emotion Recognition (ER) -- 2.2 E-Learnig Emotion Recongition -- 3 Data Collection and Preprocessing -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 4 Methodology -- 4.1 Face Detection -- 4.2 Emotion Recognition (ER) -- 5 Dataset Preparation and Results -- 5.1 Data-Set Preparation -- 5.2 Results -- 6 Comparaison with Others Works -- 7 Conclusion -- References -- Music Recommender Based on the Facial Emotion of the User Identified Using YOLOV8 -- 1 Introduction -- 2 Literature Review -- 3 Proposed Model. 3.1 Dataset Description and Pre-processing. |
| Record Nr. | UNINA-9910878044703321 |
|
Abraham Ajith
|
||
| Cham : , : Springer International Publishing AG, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Systems Design and Applications : Natural Language Processing, Volume 4
| Intelligent Systems Design and Applications : Natural Language Processing, Volume 4 |
| Autore | Abraham Ajith |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2024 |
| Descrizione fisica | 1 online resource (500 pages) |
| Altri autori (Persone) |
BajajAnu
HanneThomas SiarryPatrick |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 3-031-64779-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Automatic Textual Normalization for Hate Speech Detection -- 1 Introduction -- 2 Related Works -- 3 Dataset Creation -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Data Annotation -- 3.4 Error Analysis of Annotation -- 3.5 Dataset Statistics -- 4 Methodology -- 4.1 Normalization Methods -- 4.2 Experimental Settings -- 4.3 Evaluation Metrics -- 4.4 Experimental Results -- 4.5 Error Analysis of Normalization -- 4.6 Leveraging Automatic Textual Normalization for Hate Speech Detection -- 5 Conclusion and Future Direction -- References -- SOTW: Semantics Oriented Tagging of Web Pages -- 1 Introduction -- 2 Related Works -- 3 Proposed System Architecture -- 4 Performance Evaluation and Results -- 5 Conclusion -- References -- Crowdsourcing Applications in Smart Cities -- 1 Introduction -- 2 Overview of MCS in Smart Cities -- 2.1 Outline of Mobile Crowdsourcing -- 2.2 Classification of MCS Systems -- 3 Technologies of Task Scheduling, and Incentive Mechanism -- 3.1 Task Feasibility -- 3.2 Completion Time -- 3.3 Task Pricing -- 3.4 Spacial Factors -- 3.5 Task Complexity -- 4 Task Administration and Assignment -- 4.1 Assigning Subtasks -- 4.2 Participation Information -- 5 Future Challenges -- 5.1 Scarce Resources -- 5.2 Privacy Control -- 5.3 Trustworthy Assessment of Information -- 5.4 Heterogeneity of Hardware and Podiums -- 5.5 Nonparticipator Observation -- 6 Conclusion -- References -- Evaluation of Vendor Analysis Using AHP at TUV Manufacturing Company -- 1 Introduction -- 1.1 Problem Definition -- 1.2 Research Question -- 1.3 Objectives of This Study -- 2 Literature Support -- 3 Research Methodology -- 3.1 AHP Method - Step by Step Procedure -- 3.2 Structural Hierarchy of the Study -- 4 Procurement Department Process in TUV - Chennai, Tamil Nadu -- 4.1 Vendors Analysis.
5 Results and Discussions -- 6 Conclusion -- References -- TESA: Tagging of Educational Videos Using Semantics Oriented Artificial Intelligence -- 1 Introduction -- 2 Related Works -- 3 Proposed System Architecture -- 4 Implementation, Performance Evaluation and Results -- 5 Conclusions -- References -- SISRR: Semantically Inclined Strategic Learning Model for Software Requirement Recommendation Using Artificial Intelligence -- 1 Introduction -- 2 Related Work -- 3 Proposed System Architecture -- 4 Implementation and Result -- 5 Conclusion -- References -- Isolated Word Recognition Based on Power Normalized Cepstrum and Machine Learning Clusters -- 1 Introduction -- 2 Isolated Word Recognition - Experimental Framework -- 2.1 PNCC Extraction -- 2.2 Template Creation Framework -- 2.3 Testing of Speech Recognition System -- 2.4 Results and Discussion -- 3 Conclusion -- References -- A Core Domain Ontology for Specifying the Business View of Enterprise Information Systems -- 1 Introduction -- 2 Related Work: "Three Fit" Problems -- 3 Sensitive Business Process Specification: A Core Domain Ontology -- 3.1 Our Reference Ontological Framework -- 3.2 Overview of COSBP Ontology -- 4 Conclusion and Perspectives -- References -- Data-Driven Exploration of Pandemic's Psychological Impact and Lifestyle Changes Through Clustering Approach -- 1 Introduction -- 1.1 Problem Formulation -- 1.2 Motivation -- 1.3 Objectives -- 2 Literature Review -- 2.1 Exploring Psychological Distress and Mental Health Outcomes -- 2.2 Analyzing Sentiment, Machine Learning, and Mental Health Interventions -- 2.3 Long-Term Psychological Impact and Varied Dimensions -- 2.4 Insights from Indian Studies on Psychological Impact of COVID-19 -- 3 Methodology -- 4 Results and Discussion -- 4.1 Data-Driven Exploration and EDA -- 4.2 Supervised Learning Models -- 4.3 Unsupervised Learning Models. 5 Conclusions -- References -- Explainable Artificial Intelligence for Analytical Customer Relationship Management in Banking and Finance -- 1 Introduction -- 1.1 Overview of LIME -- 1.2 Overview of SHAP -- 2 Literature Review -- 3 Description of Datasets -- 4 Experiments -- 4.1 Node Description -- 4.2 Workflow Description -- 5 Results and Discussions -- 5.1 LIME -- 5.2 SHAP -- 6 Conclusions -- References -- Artificial Intelligence Based Chatbots is Killing Creative Minds: An Effective Discussion on Modern Education -- 1 Introduction - AI Based Chatbots/Tools -- 1.1 Organization of the Work -- 2 Importance of Creativity in Education -- 2.1 Defining Creativity and Its Significance -- 2.2 The Link Between Creativity and Critical Thinking -- 3 AI-Based Chatbots and Their Impact on Creativity -- 3.1 Limitations in Nurturing Creative Problem-Solving -- 3.2 The Role of Educators and AI-Based Chatbots -- 4 Nurturing Creativity in the Digital Age -- 5 Ethical Issues and Challenges Towards AI-Driven Education -- 6 The Future of AI Based Chatbots in Modern Education -- 7 Recommendations for Educators, Institutions, and Policy Makers for AI Driven Education in Today's Smart Era -- 8 Conclusion -- References -- SIGAN: Self-inhibited Graph Attention Network for Text Classification -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Text Graph Construction -- 3.2 Self-inhibited Graph Attention Network -- 3.3 Text Classification -- 4 Experiment -- 4.1 Dataset -- 4.2 Baseline Models -- 4.3 Ablation Experiments -- 5 Conclusoin and Future Work -- References -- Unfolding the Misinformation Spread: An In-Depth Analysis Through Explainable Link Predictions and Data Mining -- 1 Introduction -- 2 Related Works -- 3 Research Methodology -- 4 Research Findings. 4.1 What Are the Most Frequent Relationships? Are the Paths Driven More by Interpersonal Relationships or Affinity Among Ideas? -- 4.2 Analysis on Subnetworks -- 4.3 What Kind of Relationship is this Starting One? How Does the Path Develop Differently from this One? -- 4.4 Additional Analysis -- 5 Conclusion -- References -- Schematic Review of Sentiment Analysis Techniques -- 1 Introduction -- 1.1 Artificial Neural Network -- 1.2 Role of NLP in Opinion Mining -- 1.3 Evolution of Sentiment Analysis -- 2 Existing Researches -- 3 Challenges -- 4 Process Flow of Work -- 5 Conclusion -- References -- How Can Credit Scoring Benefit from Machine Learning? SWOT Analysis -- 1 Introduction -- 2 Literature Review -- 2.1 Statistical Models -- 2.2 Machine Learning Models -- 3 Research Methodology -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Gesture Recognition to Text Conversion for Human-Computer Interaction Through Computer Vision Technology -- 1 Introduction -- 2 Background Details and Related Work -- 3 Proposed Approach -- 4 Implementation of the system -- 5 Conclusions -- References -- Performance Measurement of Reading Teaching-Learning Business Processes: Case of Whole-Word and Syllabic Reading Methods in Primary Schools -- 1 Introduction -- 2 Business Process Management in the Context of Education -- 2.1 BPM and BP Definition -- 2.2 Educational BPM -- 3 KPI in the Context of Education -- 3.1 KPI Definition -- 3.2 KPI in BPM -- 3.3 KPI in the Educational Context -- 4 Approach for Performance Measurement of Languages Learning Business Processes -- 4.1 Step 1: Modeling of Languages' Learning Business Processes -- 4.2 Step 2: Languages Learning KPI Identification - Extraction -- 4.3 Step 3: Business Process Execution Using Identified Learning KPI -- 4.4 Step 4: Business Processes Performance Measurement. 5 Case Study: Primary School - 3rd Year -- 6 Discussion -- 7 Conclusion -- References -- EDULE: An AI-Enhanced Collaborative Learning Platform for Students -- 1 Introduction -- 2 Related Work -- 3 Proposed System Architecture -- 4 Implementation and Results -- 5 Conclusion -- References -- Textual Semantics Analysis Using String Kernels-Based Spectral Clustering with Incremental Hierarchical Topic Clustering -- 1 Introduction -- 2 Related Studies -- 3 Materials and Methods -- 3.1 Datasets -- 3.2 String Kernels -- 3.3 String Similarity Measures -- 4 Proposed Approach -- 5 Experiments -- 6 Results and Discussion -- 7 Conclusions and Future Scope -- References -- Preprocess the Text Based Customer Review Data for Sentiment Analysis -- 1 Introduction -- 2 Review of Literature -- 3 Preprocessing Methods -- 4 Experimental Results -- 5 Conclusion -- References -- Data Warehouse Design to Support Social Media Analysis: The Case of Twitter and Facebook -- 1 Introduction -- 2 Related Works -- 3 Overview of the Proposed Approach -- 4 Data Extraction and Cleaning -- 5 Data Mapping from Social Media -- 6 Multidimensional Schema Concepts -- 7 Experimental Results -- 8 Conclusions -- References -- Machine Learning in Tourism Research: A Bibliometric Analysis Using Dimensions Database -- 1 Introduction -- 2 Methodology -- 2.1 Bibliometric Analysis -- 2.2 Database -- 2.3 Analytical Tool -- 3 Results -- 3.1 Top Contributing Authors -- 3.2 Top Contributing Institutions and Countries -- 3.3 Top Contributing Sources and Top Cited Documents -- 3.4 Keyword Analysis -- 4 Conclusion -- References -- Efficiency of Dropout Regularization in Character Recognition: Introducing the Dropout Efficiency Score Within Intelligent Systems Architectures -- 1 Introduction -- 2 Literature Review -- 3 Background Concepts -- 3.1 Regularization -- 3.2 Challenges -- 4 Methodology. 4.1 Model Architecture. |
| Record Nr. | UNINA-9910878048703321 |
|
Abraham Ajith
|
||
| Cham : , : Springer International Publishing AG, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Systems Design and Applications : Real World Applications, Volume 5
| Intelligent Systems Design and Applications : Real World Applications, Volume 5 |
| Autore | Abraham Ajith |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (523 pages) |
| Altri autori (Persone) |
BajajAnu
HanneThomas SiarryPatrick MaKun |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 3-031-64847-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- ISDA 2023 Preface - Volume 5 -- Organizing Committees -- Contents -- Multi-player Gaming Application Based on Human Body Gesture Control -- 1 Introduction -- 2 Existing System -- 2.1 Traditional Input Devices in Gaming -- 2.2 Enhanced Physical Gaming Systems -- 2.3 Advanced Body Movements in Games -- 3 Proposed System -- 3.1 Dynamic Gameplay -- 3.2 Multiplayer Capability -- 3.3 Physical Activity Promotion -- 3.4 Dashboard with Statical Data -- 3.5 Interaction Among Players -- 3.6 High Level Gaming Experience -- 4 Literature Survey -- 5 Methodology -- 5.1 Objective -- 5.2 Approaches Considered -- 5.3 Gesture Detection and Tracking -- 5.4 Virtual Switches Mechanism -- 5.5 MediaPipe Gesture Fusion -- 5.6 Multiplayer Considerations -- 5.7 Implementation Details -- 5.8 Optimizations and Challenges -- 6 Results -- 7 Conclusion -- References -- Some Novel Fixed Point Findings in Intuitionistic Fuzzy b-Metric Spaces -- 1 Introduction -- 2 Preliminaries -- 3 New Findings -- 4 Conclusion -- References -- Impact Investigation for Gain Flattening Optimization of EDFA-Based Systems for Long-Haul WDM Applications -- 1 Introduction -- 2 Proposed Methodology -- 3 Results and Discussions -- 4 Conclusions -- References -- Modelling Inters Seasonal Variability Impact on Water Demand in a Smart City -- 1 Introduction -- 2 Materials and Method -- 2.1 Study Area Description -- 3 Sample Design and Procedure -- 3.1 Dataset Analyses -- 4 Results and Discussion -- 5 Conclusions -- 6 Limitations of the Study -- References -- Eco-designed Recirculating Vertical Aquaponic Lettuce Production System Through Mamdani Fuzzy Logic-Based Adaptive Fertigation -- 1 Introduction -- 2 Materials and Methods -- 3 Results and Discussion -- 4 Conclusion and Future Works -- References -- Video Codec Using Machine Learning Image Compression Techniques -- 1 Introduction.
2 Artificial Intelligence for Image Encoding -- 3 Artificial Intelligence to Generalize Image-Encoding Technique to Video Encoding -- 4 The Experiment -- 5 Conclusion -- References -- mRMR Feature Selection to Handle High Dimensional Datasets: Vertical Partitioning Based Iterative MapReduce Framework -- 1 Introduction -- 2 Theoretical Discussion on mRMR -- 3 Analysis of the Extant MapReduce Approaches for mRMR -- 3.1 SparkVIFS -- 3.2 SparkInfo-Theoretic -- 4 Proposed Methodology -- 5 Results and Discussions -- 5.1 Cluster Configuration -- 5.2 Computational Gain -- 5.3 Comparative Analysis Between VMRmRMR with SparkVIFS -- 5.4 Comparative Analysis Between VMRmRMR and SparkInfo-Theoretic -- 5.5 Comparative Analysis Between HMRmRMR and VMRmRMR -- 6 Conclusion -- References -- Design and Development of Low-Cost Smart Safety System for Residence -- 1 Introduction -- 2 Background Study -- 2.1 Related Work -- 3 Proposed Model and Design -- 3.1 System Architecture/3D Model -- 3.2 Block Diagram and Algorithm of Proposed Model -- 4 Simulation Analysis -- 5 Hardware Implementation and Result Analysis -- 5.1 Result Analysis -- 6 Conclusions -- References -- Teaching Service-Oriented Architectures Using a Two-Player Online Game -- 1 Introduction -- 2 Context -- 3 The Project -- 3.1 Service Endpoints -- 3.2 Client Frontend -- 3.3 Security and Penetration Testing -- 3.4 Reflection -- 4 Project Execution -- 5 Evaluation -- 6 Summary and Conclusion -- References -- Distribution Methodology for Objects Extraction from Complex Network and Colorization -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 3.1 AVI Header -- 3.2 Cellular Automata -- 3.3 PageRank Algorithm -- 4 Proposed Method -- 5 Experiments -- 6 Discussion and Conclusions -- References -- Multiparameter Physiological Estimation Based on Multi-electrodes and Bioimpedance Measurement Method. 1 Introduction -- 2 Materials and Methods -- 2.1 Design the Block Diagram of the System -- 2.2 Algorithm Flow Chart -- 3 Experiments -- 3.1 Experiment with Resistance -- 3.2 Determine Locations for Positioning the Electrodes on the Body -- 3.3 Testing with Volunteers -- 4 Results and Discussion -- 4.1 Measurements on Several Volunteers Results -- 5 Discussion -- 6 Conclusion -- References -- Solar Power Production Forecasting Model Using Random Forest Algorithm -- 1 Introduction -- 2 Related Work -- 2.1 Random Forest Algorithm Application -- 2.2 Solar Power Production Forecast using Random Forest -- 3 Research Method -- 4 Result Analysis -- 5 Conclusion -- References -- Requirements Analysis in a Systems Engineering Process Approach to the Design of Gas Detection Systems for the Philippine Industries -- 1 Introduction -- 2 Philippine Regulation Settings -- 3 Gas Detection Operation -- 4 Gas Detection Design -- 5 Practical Considerations -- 5.1 Systems Engineering Processes - Standards -- 5.2 Safety Considerations -- 5.3 Gas Detection Requirements, Maintenance and Reliability -- 5.4 Economic Considerations -- 6 System Engineering Based Gas Detection Design -- 7 Conclusions and Recommendations -- References -- A Graph Partitioning Approach to Optimize Test Patterns -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Test Pattern Generator -- 3.2 Kernighan Lin (KL) Algorithm -- 3.3 Prim's Algorithm -- 3.4 PCB Design -- 4 Results and Discussion -- 5 Conclusion -- References -- DNA Computing: Challenges and Opportunities for Future -- 1 Introduction -- 1.1 Fundamentals of DNA Computing -- 1.2 DNA as a Computational Medium -- 1.3 DNA Encoding and Manipulation -- 1.4 Key Concepts in DNA Computing -- 1.5 Organization of the Work -- 2 Background and Scope of DNA Computing -- 3 Applications of DNA Computing. 4 Issues and Challenges in DNA Computing -- 4.1 Privacy and Security Issues in DNA Computing -- 5 Future Opportunities/Future Directions Towards in DNA Computing -- 5.1 Future of DNA Computing with Other Emerging Technology -- 5.2 The Future of DNA Computing with Quantum Computing -- 6 Current Status Towards Practical Implementations of DNA Computing in Real World's Sectors -- 7 Conclusion -- References -- Early Warning System for Flood Disaster Risk Reduction Using Predictive Analytics -- 1 Introduction -- 2 Background -- 3 Proposed Flood Early Warning Predictive Analytics -- 3.1 Study Area and Data Pre-processing -- 3.2 Training of the LSTM Model -- 3.3 Evaluation Metrics -- 4 Discussion -- 5 Conclusion -- References -- Machine Learning Techniques for VLSI Circuit Design: A Review -- 1 Introduction -- 2 ML-AI for VLSI Circuit Design and Simulation -- 3 Bibliometric Analysis -- 4 Current State of VLSI Design Using ML/AI -- 5 Conclusion -- References -- Rice Leaf Disease Diagnosis Using Dense EfficientNet Model -- 1 Introduction -- 2 Literature Survey -- 3 Proposed System -- 3.1 Image Acquisition -- 3.2 Preprocessing -- 3.3 Image Segmentation -- 3.4 Image Classification -- 4 Performance Evaluation and Analysis -- 4.1 Validation and Results -- 4.2 Performance Evaluation -- 5 Conclusion -- References -- A Cooperative Machine Learning-Based Algorithm: The Case of Max-Min Knapsack Problem with Multiple Scenarios -- 1 Introduction -- 2 Background -- 3 A Cooperative Algorithm for Solving PMSKP -- 3.1 Application of Q-Table -- 3.2 Strategy for Exploitation -- 3.3 Diversification Operator -- 3.4 Framework of the Designed Cooperative Method -- 4 Results and Discussions -- 4.1 Effect of the Strategies Employed by the Algorithm -- 4.2 CA's Results Versus Published Bounds -- 5 Conclusion -- References. Performance Enhancement of a Film Bulk Acoustic Resonator Using Taguchi DoE and ANOVA Techniques -- 1 Introduction -- 2 Conclusions -- References -- Enhanced Learning in IoT-Based Intelligent Plant Irrigation System for Optimal Growth and Water Management -- 1 Introduction -- 2 Methodology -- 2.1 Cloud Storage -- 2.2 Machine Learning Algorithm -- 2.3 Support Vector Machine -- 2.4 Artificial Neural Network -- 2.5 Convolutional Neural Network -- 3 Result and Discussion -- 4 Conclusion -- References -- A Real-Time Based System for Personalized Processing Using Fog Computing: A Complete Architecture -- 1 Introduction -- 2 Related Works -- 3 Architecture of Fog Recommender Model for Real Time Processing -- 3.1 Mobile User Profile -- 3.2 Process of Ubiquitous and Fog Personalized Recommendations -- 3.3 Mobile User Interface -- 3.4 Fog Data Processing -- 3.5 Recommendation Algorithms -- 4 Experiments -- 4.1 Data Preprocessing -- 4.2 Fog Content Cache Recommendation Experiment -- 5 Conclusion -- References -- Automatic Group Labeling Using Attribute Information Gain Filters and Unsupervised Learning -- 1 Introduction -- 2 Theoretical Framework -- 2.1 Related Works -- 2.2 Feature Selection Algorithms Evaluated -- 3 Proposed Method -- 3.1 Clustering -- 3.2 Attribute Selection -- 3.3 Discretization -- 3.4 Labeling -- 4 Results and Discussion -- 5 Conclusion -- References -- Solar Intensity Classification with Imbalanced Data -- 1 Introduction -- 2 Classification Models -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Data Preprocessing -- 4 Results and Discussion -- 4.1 Case Study 1 - Benchmarking Case -- 4.2 Case Study 2 - Imbalanced Data -- 4.3 Case Study 3 - Undersampling -- 4.4 Case Study 4 - Sequencial Oversampling -- 4.5 Case Study 5 - Iterative Oversampling -- 4.6 Case Study 6 - Random Oversampling -- 5 Conclusion -- References. DNA Transcription and Translation Inspired Deep Features for Classification-Based CBIR. |
| Record Nr. | UNINA-9910878065103321 |
|
Abraham Ajith
|
||
| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Systems Design and Applications : Industrial Applications, Volume 6
| Intelligent Systems Design and Applications : Industrial Applications, Volume 6 |
| Autore | Abraham Ajith |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (526 pages) |
| Altri autori (Persone) |
BajajAnu
HanneThomas SiarryPatrick MaKun |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 3-031-64850-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Optimizing Energy Consumption in Android Mobile Devices Based on User Recommendations -- 1 Introduction -- 2 Related Work -- 3 Method and Prototyping -- 3.1 Data Collect -- 3.2 Selection of Features for Analysis -- 3.3 Technical Details -- 3.4 Saving Time -- 3.5 Notifications and Feedback -- 4 Results and Discussions -- 4.1 Energy Consumption Analysis -- 5 Final Considerations -- References -- Identification and Analysis of Barriers for In-Service Pressure Vessel and Piping Inspection Using DEMATEL Approach -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 4 Application of Proposed Approach -- 5 Result and Discussions -- 6 Managerial Implications -- 7 Conclusions and Scope for Future Research -- Appendix A -- References -- Micro Expression Recognition - Contemporary Challenges, Options and Analysis -- 1 Introduction -- 2 MEs Recognition -- 3 Factors Affecting MEs Recognition -- 3.1 Emotional Context -- 3.2 Duration of Expression -- 3.3 Annotation Biasness -- 4 Methods of MEs Recognition -- 4.1 Facial Feature Extraction -- 4.2 Classification -- 4.3 Existing MEs Datasets -- 5 Challenges Occurs, Open Issues and Future Direction -- 5.1 Challenges -- 5.2 Open Issues -- 5.3 Future Directions -- References -- Traffic Signal Timing Optimization on Superstreet Using Ecology-Based Optimization -- 1 Introduction -- 2 Methodology -- 3 Numerical Example -- 4 Conclusion -- References -- IntelliFarmAssist - A Novel Machine Learning integrated Genetic Algorithm Based Optimal Crop Recommendation System -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Work - Intelligence Assisted Crop Recommendation System -- 3.1 Proposed Methodology -- 3.2 Proposed Framework -- 3.3 Proposed GA Based Optimization Algorithm -- 4 Proposed GA Algorithm -- 5 Experimentation and Result Analysis.
6 Conclusion and Future Work -- References -- Real-Time ETL for Multimedia Sources: A Systematic Literature Review -- 1 Introduction -- 2 Planning the Review on Real-Time ETL for Multimedia Sources -- 2.1 Fixing Research Objectives -- 2.2 Identifying the Research Questions on Real-Time ETL for Multimedia Sources -- 3 Study Selected Related to Real-Time ETL -- 3.1 Electronic Sources and Search String -- 3.2 The Selection of Relevant Studies Related to Real-Time ETL -- 4 Data Extraction and Mapping of Relevant Studies -- 5 Data Synthesis and Overview of Selected Studies -- 6 Conclusion -- References -- Wastewater Monitoring and Control Using Cloud Based IoT System -- 1 Introduction -- 2 Literature Review -- 3 System for Monitoring and Controlling Wastewater Currently in Place -- 4 Existing System Components -- 5 Existing System Limitations -- 6 Proposed System -- 6.1 System Overview -- 6.2 System Architecture -- 6.3 Hardware Components -- 6.4 The Software Components -- 7 Conclusion -- References -- Multimodal Emotion Classification: Implications for Cognitive Science and Human Behaviour -- 1 Introduction -- 2 Related Work -- 3 MAHNOB-HCI Dataset -- 3.1 Data Modalities -- 4 Proposed Methodology -- 4.1 Data Preprocessing -- 4.2 Feature Extraction and Selection -- 4.3 Unimodal Classification -- 4.4 Multimodal Classification -- 5 Gender-Specific Analysis -- 6 Results and Discussions -- 7 Conclusion -- References -- Uniting Optimization and Deep Learning for Complex Problem Solving: A Comprehensive Review -- 1 Introduction -- 2 Literature Survey -- 3 Optimization Techniques -- 3.1 Particle Swarm Optimization (PSO) -- 3.2 Bat Algorithm (BA) -- 3.3 Cuckoo Algorithm (COA) -- 3.4 Whale Optimization Algorithm (WOA) -- 3.5 Firefly Algorithm (FA) -- 4 Conclusion -- References. Novel Predictive Machine Learning Approach for Identification of Microbial Niche and Microbial Communities from Omics Dataset of Kaveri River, Tamil-Nadu, India -- 1 Introduction -- 2 Methodology -- 2.1 Feature Selection -- 2.2 Microbial Community Classification -- 3 Experimental Results -- 4 Conclusion -- References -- A Review of Path Planning Algorithms -- 1 Introduction -- 2 Path Planning Approaches Classification -- 2.1 Classical Approaches -- 2.2 Heuristic Approaches -- 2.3 Metaheuristic Approaches -- 2.4 Machine Learning Approaches -- 2.5 Hybrid Approaches -- 3 Path Planning Approaches Challenges -- 4 Analytic Comparison -- 5 Conclusion -- References -- Application of WASPAS Method on Selecting Best Deemed University in India -- 1 Introduction -- 2 Literature Support -- 3 Research Methodology -- 4 Application - Selection of Best Deemed University -- 5 Results -- 5.1 Comparative Study -- 6 Conclusions -- References -- Valuation of Trash Management in Railway Compartment Using ENTROPY - A MCDM Method -- 1 Introduction -- 2 Literature Support -- 3 Research Methodology -- 4 Case Study - Trip from Chennai to Mangalore -- 5 Application of ENTROPY Method -- 6 Results and Discussions -- 7 Conclusion -- References -- Adaptive Windowing (ADWIN3) to Learning from Time-Changing Data Stream -- 1 Introduction -- 1.1 Adaptive Stream Mining Methodology -- 1.2 Time Change Predictors and Detectors -- 1.3 HoeffdingTrees (HT) Incremental Decision Trees -- 1.4 Adaptive Windowing Algorithm (ADWIN) -- 1.5 CVFDT -- 1.6 Hoeffding Adaptive Trees (HAT) -- 1.7 Early Drift Detection Method (EDDM) -- 2 Related Works -- 3 Proposed Method -- 3.1 ADWIN3 -- 4 Results and Discussion -- 5 Conclusion -- References -- Towards Enhancing Driver's Perceived Safety in Autonomous Driving: A Shield-Based Approach -- 1 Introduction -- 2 Background -- 2.1 Reinforcement Learning. 2.2 Shielding -- 3 Related Work -- 4 Personalized Perceived Safety Shielding -- 4.1 Autonomous Driving Module -- 4.2 Human Interaction Module -- 5 Evaluation -- 5.1 Experiment Setting -- 5.2 Experiment Result -- 5.3 Discussion -- 6 Conclusion and Future Work -- References -- A Uniplanar Asymmetric Circular Slotted Patch Antenna for 5.8 GHz Applications -- 1 Introduction -- 2 Uniplanar Asymmetric Circular Slotted Antenna-Design -- 3 Result Discussions on Uniplanar Asymmetric Circular Slotted Antenna -- 4 Conclusion -- References -- A Discrete Event Formalism for Fast Simulation of On-Demand Transportation Systems -- 1 Introduction -- 1.1 Related Work -- 1.2 Problem Statement -- 1.3 Contribution -- 2 System Theory -- 2.1 Intersections, Segments and Locations -- 2.2 Charging Stations, Demands and Vehicles -- 3 Discrete Events -- 3.1 Vehicle-Intersection Location Events -- 3.2 Vehicle-Charging Station Location Events -- 3.3 Vehicle-Demand Location Events -- 3.4 Vehicle-Vehicle Location Events -- 3.5 Demand Events -- 3.6 Speed Events -- 3.7 Battery Events -- 4 Conclusion -- References -- Algorithm for Boycotting Behavior for Fake Goods -- 1 Introduction -- 2 Method -- 2.1 Sample Size -- 2.2 Blinding -- 2.3 Datasets -- 2.4 Model Choice -- 3 Results -- 3.1 Regression -- 3.2 AIC -- 4 Conclusion -- References -- Assessing for Online Teaching Effectiveness Using VIKOR Method During Covid Pandemic Times -- 1 Introduction -- 2 Literature Support -- 3 Research Methodology -- 4 Survey - Deemed University Students in South India -- 5 Application of VIKOR Method -- 6 Results and Discussions -- 7 Conclusion -- References -- ChronoEdgeMiner: A Novel Algorithm for Extracting Frequent Temporal Graphs from Data -- 1 Introduction -- 2 Problem Definitions -- 3 ChronoEdgeMiner -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Analysis of ChronoEdgeMiner. 5 Conclusion and Future Work -- References -- A Survey on Educational Processes Based on Agile, BPM, and PM -- 1 Introduction -- 2 Methodology -- 3 Literature Review -- 3.1 Agility -- 3.2 BPM (Business Process Management) -- 3.3 Process Mining (PM) -- 4 Obtained Results for Educational Processes -- 4.1 The Educational Process -- 4.2 Overview of the Proposed Framework -- 5 Conclusion -- References -- Telecom Churn Movement Prediction Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Data Collection and Preprocessing -- 3.2 Model Development -- 4 Results and Discussion -- 4.1 Parameters for Evaluation -- 4.2 Performance -- 5 Conclusion -- References -- Tracking Sigmoid Regression with Multicollinearity in Phase I: An Approach Incorporating Control Charts -- 1 Introduction -- 2 Sigmoid Regression Model-Based Control Charts -- 2.1 Multicollinearity -- 2.2 Principal Component -- 2.3 Iterative Re-Weighted Least Square Algorithm -- 2.4 Sigmoid Regression -- 3 Intended Control Charts -- 3.1 Control Chart Based on Ordinary Residuals, Deviance Residuals, and Pearson's Residuals -- 4 Illustration of the Application of the Control Chart in Phase I -- 5 Discussion and Findings -- References -- AR-Driven Smart Homes: Enhancing Automation and User Experience -- 1 Introduction -- 2 Related Works -- 2.1 AR-Based Smart Home Control -- 2.2 AR and IoT Integration -- 2.3 AR for Access Control and Security -- 2.4 AR and AI Synergy -- 2.5 Mixed Reality for IoT Control and Monitoring -- 3 Methodology -- 3.1 Contribution -- 3.2 Proposed Methodology -- 4 Results -- 4.1 Target Image and Virtual Button -- 4.2 IoT Setup -- 5 Conclusion and Inference -- 6 Future Works -- References -- Overview of Vehicular Resource Allocation: Review and Future Directions -- 1 Introduction -- 1.1 Related Surveys and Scope of the Paper. 1.2 Contributions. |
| Record Nr. | UNINA-9910878980603321 |
|
Abraham Ajith
|
||
| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Systems Design and Applications : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 2 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
| Intelligent Systems Design and Applications : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 2 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj |
| Autore | Abraham Ajith |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (614 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
PllanaSabri
CasalinoGabriella MaKun BajajAnu |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| Soggetto non controllato | Science |
| ISBN | 3-031-35507-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910728934703321 |
|
Abraham Ajith
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Systems Design and Applications : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 4 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
| Intelligent Systems Design and Applications : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 4 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj |
| Autore | Abraham Ajith |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (631 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
PllanaSabri
CasalinoGabriella MaKun BajajAnu |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| Soggetto non controllato | Science |
| ISBN | 3-031-35510-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- ISDA 2022-Organization -- Contents -- Machine Learning Approach for Detection of Mental Health -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Proposed Model -- 5 Results and Discussion -- 6 Conclusion and Future Scope -- References -- U-Net as a Tool for Adjusting the Velocity Distributions of Rheomagnetic Fluids -- 1 Introduction -- 2 Theoretical Basics -- 2.1 Physics-Based Loss -- 2.2 Rheomagnetic Fluids -- 3 Simulation Modeling -- 4 Results and Discussion -- 5 Conclusions -- References -- Detection of Similarity Between Business Process Models with the Integration of Semantics in Similarity Measures -- 1 Introduction -- 2 Similarity Measures -- 2.1 Syntactic Measures -- 2.2 Semantic Measures -- 2.3 Structural Measures -- 2.4 Behavioral Measures -- 3 Problem Illustration -- 3.1 Similarity Measures -- 3.2 Dimensions of Semantic Similarity -- 3.3 Cardinality Problem -- 3.4 Genetic Algorithm -- 4 Related Work -- 5 Our Approach -- 5.1 Steps of Genetic Algorithm -- 6 Conclusion -- References -- Efficient Twitter Sentiment Analysis System Using Deep Learning Algorithm -- 1 Introduction -- 2 Literature Review -- 3 Proposed Method -- 3.1 Pre-processing -- 3.2 User-Mention -- 3.3 EMOJ Positive and Negative -- 3.4 Feature Selection -- 3.5 Classification -- 4 Experimental Results and Discussion -- 5 Conclusion -- References -- An Efficient Deep Learning-Based Breast Cancer Detection Scheme with Small Datasets -- 1 Introduction -- 1.1 Contributions -- 2 Proposed Method -- 2.1 Preprocessing -- 2.2 CNN Architecture -- 3 Datasets -- 4 Results and Discussion -- 5 Conclusion -- References -- Comparative Analysis of Machine Learning Models for Customer Segmentation -- 1 Introduction -- 2 Problem Statement -- 3 Literature Review -- 4 Algorithms for Customer Segmentation -- 4.1 Customer Segmentation Using K-Means.
4.2 Customer Segmentation Using DBSCAN -- 4.3 Agglomerative Clustering (Using PCA) -- 4.4 K-Means Using PCA -- 5 Results and Discussion -- 5.1 K-Means Model -- 5.2 DBSCAN -- 5.3 Agglomerative Clustering with PCA -- 5.4 Kmeans with PCA -- 6 Conclusion -- References -- An Intelligent Approach to Identify the Eggs of the Insect Bemisia Tabaci -- 1 Introduction -- 2 Overview of Proposed Approach -- 2.1 Deep Learning Algorithm -- 2.2 Auto-encoder -- 2.3 Stacked Auto-encoder for Egg Classification -- 3 Results and Discussion -- 3.1 Databases Used -- 3.2 Result -- 3.3 Test Phase -- 4 Conclusion -- References -- Overview of Blockchain-Based Seafood Supply Chain Management -- 1 Introduction -- 2 Blockchain Technology: Overview and Adoption in Supply Chains Management -- 3 An Overview of Blockchain Based Seafood Supply Chain Management Systems -- 4 Discussion and Research Challenges -- 5 Conclusion -- References -- Synthesis of a DQN-Based Controller for Improving Performance of Rotor System with Tribotronic Magnetorheological Bearing -- 1 Introduction -- 2 System Description and Modeling -- 2.1 Rotor Model -- 2.2 Bearing Model -- 3 Model Verification -- 4 Designing a DQN Controller -- 5 Results and Discussion -- 6 Conclusion -- References -- Card-Not-Present Fraud Detection: Merchant Category Code Prediction of the Next Purchase -- 1 Introduction -- 2 State of the Art -- 2.1 What is a Card-Not-Present Transaction? -- 2.2 Card not Present Fraud Scenario -- 2.3 What is the Merchant Category Code? -- 2.4 Prediction of Merchant Category Code for the Next Buy -- 3 Related Works -- 3.1 Online Payment Fraud Detection AI Proposals -- 4 Conclusion -- References -- Fast Stroke Lesions Segmentation Based on Parzen Estimation and Non-uniform Bit Allocation in Skull CT Images -- 1 Introduction -- 2 Related Works: classical and Deep Learning Approaches. 3 Materials and Methods -- 3.1 Level Set -- 3.2 Parzen Window -- 3.3 Non-uniform Bit Allocation: -law and A-law Algorithms -- 3.4 Datasets and Evaluation Metrics -- 4 LSBRD: An Approach Based on Parzen Estimation and Non-uniform Bit Allocation via -law and A-law -- 5 Results and Discussions -- 5.1 Algorithm Performance Analysis -- 6 Conclusion and Future Works -- References -- Methods for Improving the Fault Diagnosis Accuracy of Rotating Machines -- 1 Introduction -- 2 Intellectual Diagnostic Methods -- 2.1 Fully Connected Neural Networks -- 2.2 Generative Adversarial Network -- 3 Results and Discussion -- 3.1 Data Collection -- 3.2 Fully Connected Neural Networks to Rotor Diagnostic Defects -- 3.3 Generative Adversarial Network to Increasing the Volume and Variety of Training Data -- 4 Conclusion -- References -- Heuristics Assisted by Machine Learning for the Integrated Production Planning and Distribution Problem -- 1 Introduction -- 2 Problem Definition -- 3 Proposed Algorithms -- 3.1 Decoding Algorithms -- 3.2 Initial Solution -- 3.3 Neighborhood Search Heuristics -- 3.4 Framework -- 4 Computational Experiments -- 4.1 Computational Results -- 5 Conclusions -- References -- LSTM-Based Congestion Detection in Named Data Networks -- 1 Introduction -- 2 Background and Related Works -- 2.1 Long Short Term Memory Background -- 2.2 Related Works -- 3 LSTM-Based Congestion Detection -- 4 Performance Evaluation -- 5 Conclusion -- References -- Detection of COVID-19 in Computed Tomography Images Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Image Acquisition -- 3.2 Pre-processing -- 3.3 Data Augmentation -- 3.4 Evaluated Architectures -- 3.5 Proposed Method -- 4 Experimental Results -- 4.1 Transfer Learning Results -- 4.2 Fine-Tuning Results -- 5 Discussion -- 6 Conclusion -- References. Abnormal Event Detection Method Based on Spatiotemporal CNN Hashing Model -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Spatiotemporal Stream -- 3.2 Network Architecture -- 4 Experiments Results -- 4.1 Network Architecture -- 4.2 Datasets -- 4.3 Evaluation -- 5 Conclusion -- References -- A Multi-objective Iterated Local Search Heuristic for Energy-Efficient No-Wait Permutation Flowshop Scheduling Problem -- 1 Introduction -- 2 Problem Description -- 3 Multi-objective Iterated Local Search Heuristic -- 3.1 Multi-objective Local Search and Perturbation -- 4 Computational Experiments -- 4.1 Obtained Results -- 5 Conclusions -- References -- An Elastic Model for Virtual Computing Labs Using Timed Petri Nets -- 1 Introduction -- 2 Cloud Computing -- 2.1 Cloud Service Models -- 2.2 Cloud Deployement Models -- 2.3 Benefits and Challenges of Cloud Computing -- 3 Related Works -- 4 Background -- 4.1 Timed and Colored Petri Nets -- 4.2 Cloud Elasticity -- 5 Proposed Approach -- 5.1 The Challenge for Moving to VCL -- 5.2 Model Description -- 5.3 Vertical Elasticity Algorithm -- 5.4 Proposed Solution -- 5.5 Support Tools -- 6 Conclusion -- References -- A Decision Support System Based Vehicle Ontology for Solving VRPs -- 1 Introduction -- 2 Literature Review -- 2.1 Classification of Vehicle Routing Problems -- 2.2 Ontologies for Vehicle Domain -- 3 Decision Support System -- 4 Proposed VRP-Vehicle Ontology -- 5 Conclusion -- References -- Web API Service to RDF Mapping Method for Querying Distributed Data Sources -- 1 Introduction -- 2 Related Work -- 2.1 Smart City Platforms -- 2.2 Relational Databases -- 3 Accident Card Analysis System -- 3.1 R2RML Mapping -- 3.2 Data Quality -- 4 Web API Service to RDF Mapping Method Description -- 4.1 Weather Data Sources Specific -- 4.2 W2RML Scheme -- 5 Conclusion -- References. Risk Management in the Clinical Pathology Laboratory: A Bayesian Network Approach -- 1 Introduction -- 2 Research Design -- 3 Results -- 3.1 Literature Review -- 3.2 Risk Model -- 4 Conclusions -- References -- Leveraging Sequence Mining for Robot Process Automation -- 1 Introduction -- 2 Related Works -- 3 The Proposed Approach -- 3.1 FEM-M: Frequent Episode Miner -- 3.2 TEF-M: Target Episode Finder -- 4 Experimental Results -- 5 A Case Study -- 6 Conclusions -- References -- Intelligent Agents System for Intention Mining Using HMM-LSTM Model -- 1 Introduction and Motivation -- 2 Related Works -- 3 Architecture of Multi Intelligent Agents System Approach -- 3.1 Description of Agents -- 3.2 Hybrid Model -- 4 Experimentation and Validation -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Result -- 5 Conclusion -- References -- Unsupervised Manipulation Detection Scheme for Insider Trading -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Feature Characterisation -- 3.2 Kernel Principal Component Analysis (KPCA) -- 4 Results and Discussion -- 5 Conclusion -- References -- A Comparative Study for Modeling IoT Security Systems -- 1 Introduction -- 1.1 Originality and Objectives -- 1.2 Outline -- 2 IoT and Modeling Languages -- 2.1 IoT Background -- 2.2 Overview of UML -- 2.3 Overview of SysML -- 3 Related Works -- 4 Proposed New IoT Security Modeling -- 4.1 IoT Architecture and Security Requirements -- 4.2 Modeling the Security of the Physical Layer and the Network Layer of IoT Systems with UML Language: Use Case Diagram -- 4.3 Modeling IoT Security Systems Using SysML Language: Requirement Diagram -- 5 Analysis and Discussion -- 6 Conclusion -- References -- Improving the Routing Process in SDN Using a Combination of the Evidence Theory and ML -- 1 Introduction -- 2 Related Work -- 3 Overview of the Trust-Based Routing Scheme. 4 Global Trust (GT) Vector Computation. |
| Record Nr. | UNINA-9910728932903321 |
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Abraham Ajith
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent Systems Design and Applications : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 3 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
| Intelligent Systems Design and Applications : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 3 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj |
| Autore | Abraham Ajith |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (602 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
PllanaSabri
CasalinoGabriella MaKun BajajAnu |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| Soggetto non controllato | Science |
| ISBN | 3-031-35501-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910728946403321 |
|
Abraham Ajith
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent Systems Design and Applications : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 1 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj
| Intelligent Systems Design and Applications : 22nd International Conference on Intelligent Systems Design and Applications (ISDA 2022) Held December 12-14, 2022 - Volume 1 / / edited by Ajith Abraham, Sabri Pllana, Gabriella Casalino, Kun Ma, Anu Bajaj |
| Autore | Abraham Ajith |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (592 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
PllanaSabri
CasalinoGabriella MaKun BajajAnu |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| Soggetto non controllato |
Artificial Intelligence
Engineering Computers Technology & Engineering |
| ISBN | 3-031-27440-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- ISDA 2022-Organization -- Contents -- KMetaTagger: A Knowledge Centric Metadata Driven Hybrid Tag Recommendation Model Encompassing Machine Intelligence -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Results and Performance Evaluation -- 5 Conclusion -- References -- KCReqRec: A Knowledge Centric Approach for Semantically Inclined Requirement Recommendation with Micro Requirement Mapping Using Hybrid Learning Models -- 1 Introduction -- 2 Related Works -- 3 Proposed System Architecture -- 4 Implementation and Performance Evaluation and Results -- 5 Conclusion -- References -- Object Classification Using ECOC Multi-class SVM and HOG Characteristics -- 1 Introduction -- 1.1 Background -- 1.2 Research Objectives -- 1.3 Paper Organization -- 2 Proposed Scheme for Object Classification -- 3 System Description -- 3.1 Image Datasets -- 3.2 ECOC Based Multi-class SVM -- 3.3 Appropriate Cell Size Selection for HOG Feature -- 4 Results and Discussions -- 5 Conclusion -- References -- GA Evolved Configuration Data for Embryonic Architecture with Built-in Self-test -- 1 Introduction -- 2 Embryonic Digital Circuit Architecture Using CGP Data -- 3 Novel Parallel GA Design for CGP Configuration Data Generation -- 3.1 Optimum Individual Monogenetic GA-OIMGA -- 3.2 Parallel HsClone GA -- 4 Embryonic Cells with Built-in Self-Test Design -- 5 Embryonic Adder and Comparator Cell Fault Detection -- 6 Conclusion and Scope for Future Work -- References -- A Multi-layer Deep Learning Model for ECG-Based Arrhythmia Classification -- 1 Introduction -- 2 Related Work -- 3 Material and Method -- 3.1 Dataset -- 3.2 Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- Analyzing Electoral Data Using Partitional and Hierarchical Clustering Algorithms -- 1 Introduction -- 2 The Municipal Human Development Index (MHDI).
3 Data Used in the Experiments -- 4 Methodology and Experiments -- 5 Conclusions -- References -- Medical Decision Making Based 5D Cardiac MRI Segmentation Tools -- 1 Introduction -- 2 Methods and Materials -- 3 Theory -- 3.1 Concept of the 5D Segmentation and Medical Issue -- 3.2 Goals and Contributions -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- India Post Service Facility Layout Design Selection and Evaluation Using MCDM Approach -- 1 Introduction -- 2 Literature Support -- 3 Research Methodology -- 4 Application - NSH Mangalore -- 5 Results -- 5.1 Finding the Weightage Criteria -- 5.2 Calculation Method -- 6 Conclusions -- References -- Weighted Pathfinding in the Paparazzi Problem with Dynamic Obstacles -- 1 Introduction -- 2 Problem Statement -- 3 Background Information -- 3.1 A* Algorithm -- 3.2 Extended A* Algorithm -- 3.3 Heuristics -- 3.4 Dynamic Obstacles -- 4 Implementation and Testing -- 4.1 Code Structure -- 4.2 Pathfinding -- 5 Results and Discussion -- 5.1 Data Distribution -- 5.2 Pathfinding -- 5.3 Diagonal Movement -- 5.4 Overall Heuristic Performance -- 6 Conclusions -- References -- A Rapid Review on Ensemble Algorithms for COVID-19 Classification Using Image-Based Exams -- 1 Introduction -- 2 Ensemble Algorithms -- 3 Methodology -- 3.1 Inclusion Criteria -- 3.2 Exclusion Criteria -- 4 Results and Discussion -- 4.1 Q1 - Ensemble Technique -- 4.2 Q2 - Number of Classes -- 4.3 Q3 - Machine Learning Algorithms and Models -- 4.4 Q4 - Datasets -- 5 Conclusions -- References -- Indian Postal Service Quality Assessment Using Graph Theoretic Approach - A Quantitative Decision-Making Tool -- 1 Introduction -- 1.1 Importance of the Study -- 2 Literature Review -- 2.1 Graph Theoretical (GT) Model -- 3 Research Methodology -- 3.1 Graph-Theoretic Model Approach -- 4 Analysis and Results -- 4.1 Graph Theory Calculation. 5 Conclusions -- References -- Analyzing the Critical Success Factors of Lean System Implementation in India Post Using DEMATEL Method -- 1 Introduction -- 1.1 Rationale of the Study -- 2 Literature Support -- 3 Research Methodology -- 3.1 Steps for DEMATEL Method -- 4 Case Application: Indian Postal NSH Mangalore, India -- 5 Conclusions -- References -- Application of Artificial Intelligence in Mental Health -- 1 Introduction to Artificial Intelligence in Healthcare -- 2 Mental Health -- 2.1 AI in Healthcare -- 2.2 Ethics and AI Mental Health Research -- 2.3 AI Research on the Involvement of Patient and Public Mental Health -- 2.4 Well-Being and Educational Performance -- 2.5 Internet-Based Mental Health Care -- 2.6 Mental Healthcare Chatbots -- 3 Literature Survey -- 4 Constraints of AI and Mental Health Care Research -- 5 Statistics Scenario in the Area of AI in Mental Health Care Research -- 6 Conclusion -- References -- Cold Rolling Mill Energy Consumption Prediction Using Machine Learning -- 1 Introduction -- 2 Cold Rolling Mill and Energy Consumption -- 3 Proposed Approach -- 4 Results and Analysis: Model Training and Energy Prediction -- 5 Conclusions and Future Work -- References -- Virtual Reconstruction of Adaptive Spectral and Spatial Features Based on CNN for HSI Classification -- 1 Introduction -- 2 Proposed Approach -- 2.1 Extraction of Spectral Data Vectors and Fusions of Pixels to Obtain a Single Spatial-Spectral Band -- 2.2 Apply Five Algorithms to Create Five Virtual Layers -- 2.3 3D Image Reconstruction -- 2.4 Edge-Adaptive Spatial Data Extraction -- 2.5 Convolution and Processing of Each Block Until Recognition of the pixel -- 2.6 Placing Pixels in Their Positions, Merging the Five Spectral Bands and Labeling -- 3 Experiences and Results -- 3.1 Tests -- 3.2 Results and Discussions -- 4 Conclusion -- References. Enhancing Rental Bike Count and Availability Prediction Using Regression Modelling -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Multiple Linear Regression -- 3.2 Polynomial Regression -- 4 Results -- 5 Conclusion and Fututre Enhancement -- References -- Application of WASPAS Method for the Evaluation of Tamil Nadu Private Travels -- 1 Introduction -- 2 Literature Support -- 3 Research Methods -- 4 Case Study - Chennai, Tamilnadu, Southern India -- 4.1 Application of WASPAS Method -- 5 Comparative Study -- 6 Conclusion -- References -- Time Series Forecast Applied to Electricity Consumption -- 1 Introduction -- 2 Related Work -- 3 BackGround of Study -- 3.1 Definitions -- 3.2 Machine Learnings Models -- 4 Material and Methods -- 4.1 Dataset Description -- 4.2 Performance Indices -- 5 Simulation Results -- 5.1 Regression Models - Data with Daily Periodicity -- 5.2 Regression Models - Data with Daily Periodicity (Outlier Removal) -- 5.3 Regression Models - Data with Monthly Periodicity -- 5.4 Regression Models - Data with Daily Periodicity (Outlier Removal) - Moving Average -- 5.5 Multi Layer Perceptron (MLP) - Data with Monthly Periodicity -- 5.6 Recurrent Neural Network (RNR) - Data with Monthly Periodicity -- 6 Conclusions -- References -- A Survey on Text Processing Using Deep Learning Techniques -- 1 Introduction -- 2 Sentiment Analysis is Divided into Numerous Categories -- 2.1 Sentiment with a Finer Granularity -- 2.2 Sentiment Analysis for Emotion Identification -- 2.3 Analyses Based on Aspects -- 2.4 Sentiment Analysis Based on Intent -- 3 Approaches to Sentiment Analysis -- 3.1 Rule-Based Approach -- 3.2 Machine Learning Approach -- 3.3 Lexicon Based Approach -- 4 All Approaches Advantages and Limitations -- 5 Text-Based Emotion Detection (TBED) -- 5.1 Datasets for Text-Based ED (Emotion Detection) Research -- 6 Feature Set. 6.1 Extraction of Feature -- 6.2 Feature Selection -- 7 Comparison Analysis -- 7.1 Lexicon Based Approach -- 7.2 Dictionary-Based Classification -- 7.3 Corpus-Based Classification -- 7.4 Machine Learning Based Classification -- 7.5 Support Vector Machine -- 7.6 Comparative Table for Different Classification Algorithm -- 7.7 Naïve Bayes -- 7.8 K-Nearest Neighbor -- 7.9 Maximum Entropy -- 7.10 Decision Tree Learning -- 7.11 Semantic Orientation Approach -- 7.12 Keyword-Based Classification -- 7.13 Emotions Based Classifications -- 8 Issues in Text Sentiment Analysis -- 9 Conclusion -- References -- RePI: Research Paper Impact Analysis -- 1 Introduction -- 2 Literature Survey -- 2.1 Previous Works -- 2.2 Impact Metrics -- 2.3 Keyword Extraction -- 3 Dataset Creation -- 4 Methodology and Architecture -- 5 Design and API Integration -- 5.1 RAKE -- 5.2 Implementation -- 6 Impact Metric Calculation -- 7 Results -- 7.1 Visualizations -- 7.2 Impact Metric Ratio -- 8 Conclusion -- References -- Human-Centred Artificial Intelligence in Sound Perception and Music Composition -- 1 Introduction -- 2 Melody and Musical Grammar -- 3 Formalization of Musical Grammar Rules -- 4 Obtained Results -- 5 Discussion and Conclusions -- References -- Multi-objective Optimization for Sensor Networks Based Smart Parking Systems -- 1 Introduction -- 2 Related Works -- 3 Real Time Smart Parking System Description -- 4 Mathematical Formulation -- 4.1 Poisson Process -- 4.2 Linear Programming Formulation -- 5 Performance Evaluation -- 6 Open Research Issue: Sensor Networks and Artificial Neural Networks (ANN) -- 7 Conclusion -- References -- Process Automation with Digital Robots Under Smart University Concept -- 1 Introduction -- 2 Literature Review -- 3 Digital Transformation of Processes -- 3.1 Digital Transformation -- 3.2 Process Automation -- 3.3 Human Path and Robot Path. 4 Case Study. |
| Record Nr. | UNINA-9910728933403321 |
|
Abraham Ajith
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||