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Soft Computing : Proceedings of SoCTA 2023, Volume 1
| Soft Computing : Proceedings of SoCTA 2023, Volume 1 |
| Autore | Kumar Rajesh |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (427 pages) |
| Altri autori (Persone) |
VermaAjit Kumar
VermaOm Prakash WadehraTanu |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 9789819720316 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- A Mathematical Approach to Prevent and Control COVID-19 Outbreaks: The Improved M-E Model -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 4 Results and Discussion -- 5 Conclusion -- References -- Implementation of Agricultural Produce Segregation Using Image Processing Algorithm -- 1 Introduction -- 2 Literature Review -- 3 Proposed System -- 3.1 Feature Pyramid Network -- 4 Working Process -- 5 Results and Discussion -- 6 Conclusion -- References -- Detection of Duplicate Question Pairs by Applying Proposed BoW, TF-IDF, and USE Approach -- 1 Introduction -- 2 Related Works -- 3 Dataset and Pre-processing -- 4 Proposed Methodology -- 5 Implementation and Specifics -- 6 Experimental Result and Analysis -- 7 Discussions -- 8 Conclusion and Future Work -- References -- The Hand Glove Enabling Voice and Text Communication -- 1 Introduction -- 2 Existing Methods -- 3 Proposed Method -- 4 Results -- 5 Conclusion -- References -- Advancing Rheumatoid Arthritis Care: Exploring Technological Breakthroughs and Future Directions -- 1 Introduction -- 2 Overviews of Technologies for RA Management -- 2.1 Artificial Intelligence (AI) -- 2.2 Machine Learning (ML) -- 2.3 Deep Learning (DL) -- 2.4 Image Processing -- 3 Prediction and Classification -- 3.1 Predictive Models -- 3.2 Role of Technology in Predicting and Classifying RA -- 4 RA Treatment -- 4.1 Role of Technology in Developing Personalized Treatment Plans -- 4.2 Future Directions for Technology-Based Treatment Options -- 5 RA Diagnosis -- 5.1 Importance of Accurate and Timely Diagnosis of RA -- 5.2 Technology's Impact on Diagnosis Accuracy and Constraints -- 6 Conclusion and Future Directions -- References -- Twitter Trolling Detection Using Machine Learning -- 1 Introduction -- 1.1 Background -- 1.2 Motivation -- 1.3 Objectives.
1.4 Data Cleansing and Feature Extraction -- 2 Literature Review -- 3 Methods -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Feature Extraction -- 3.4 Model Selection -- 4 Results and Discussion -- 4.1 Discussion -- 4.2 Limitations -- 5 Conclusion and Future Work -- References -- HMHDTML: Human Mental Health Detection Using Text and Machine Learning Model -- 1 Introduction -- 2 Literature Survey -- 3 Data Selection -- 4 Methodology -- 4.1 Preprocessing Steps -- 4.2 Feature Extraction -- 4.3 N-Grams Feature -- 4.4 Contradiction Feature -- 4.5 Punctuation and Special Symbols Feature -- 5 Results and Discussion -- 6 Conclusion and Feature Work -- References -- Analyzing the Growth Profile of Brain Tumor with Caputo Fractional Operator via Sumudu Transform -- 1 Introduction -- 2 Basics of Fractional Calculus -- 3 Application of Proposed Technique to FBTM -- 4 Maximum Absolute Error -- 5 Numerical Application -- 6 Numerical Results and Discussion -- 7 Conclusion -- References -- Multi-labelled Topic Classification of Research Articles Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 2.1 Related Study on MLkNN -- 2.2 Related Study on SVM Using Binary Relevance -- 2.3 Related Study on Using GRU -- 2.4 Related Study on Using Attention-BiLSTM -- 2.5 Related Study on Using BERT -- 3 Methodology -- 3.1 Dataset -- 3.2 Data Preprocessing -- 4 Model Selection -- 4.1 MLkNN -- 4.2 SVM-BR -- 4.3 Attention-BiGRU -- 4.4 Attention-BiLSTM -- 4.5 RoBERTa Model -- 5 Data Analysis -- 6 Results and Discussion -- 7 Conclusion -- References -- Security in Mobile Ad Hoc Networks: Impact of Attacks and Countermeasure Approaches -- 1 Introduction -- 1.1 Motivation -- 1.2 Related Work -- 1.3 Research Gaps -- 2 Literature Review -- 3 Impact of Attacks on Network's Performance -- 3.1 Overhead -- 3.2 End-To-End Delay -- 3.3 Packet Delivery Ratio -- 3.4 Energy. 4 Countermeasures to MANETs' Security Threats -- 4.1 Authentication and Access Control -- 4.2 Cryptography and Encryption Techniques -- 4.3 Denial-of-Service Prevention Techniques -- 4.4 Network Segmentation and Firewalls -- 4.5 Intrusion Detection and Prevention Systems -- 4.6 Network Monitoring and Auditing -- 4.7 Redundancy and Backup Systems -- 4.8 Secure Routing Protocols -- 4.9 Traffic Analysis and Anomaly Detection -- 4.10 Trust-Based and Reputation-Based Systems -- 5 Conclusion -- References -- Optimization of Vibrational Frequencies for Orthotropic Parallelogram Plates With Circular Variations in Tapering at Simply Supported Boundary -- 1 Introduction -- 2 Method of Solution -- 3 Numerical Work and Discussion -- 4 Comparative Analysis -- 5 Conclusions -- References -- Drowsiness Detection Using Adaboost Method and Haar Cascade Classifier to Improve Safety of Drivers -- 1 Introduction -- 2 Review of Literature -- 3 Proposed Methodology -- 3.1 Physiological Level Approach -- 3.2 Behavioral-Based Approach -- 3.3 Face Detection -- 3.4 Eye Detection -- 3.5 Recognition of the Eye's State -- 3.6 Eye State Determination -- 3.7 Drowsiness Detection -- 4 Results -- 5 Conclusion -- References -- Early Detection of Colorectal Cancer from Polyps Images Using Deep Learning -- 1 Introduction -- 2 Research Review -- 3 Methodology -- 4 Material and Method -- 4.1 Dataset -- 4.2 Model Selection for CRC Classification -- 4.3 Tools -- 4.4 Model Evaluation -- 5 Experiment and Results -- 5.1 Model Implementation -- 5.2 Model Performance on Datasets -- 5.3 Limitations of the Present Study -- 6 Conclusion -- References -- Motion Control of Underactuated Cart-Double-Pendulum System Via Fractional-Order Sliding Mode Controller -- 1 Introduction -- 2 Dynamics of Cart-Double-Pendulum System -- 3 Controller Structure -- 3.1 Fractional-Order Sliding Surface -- 3.2 RBFNN. 3.3 Adaptive Bound -- 4 Stability Analysis -- 4.1 Asymptotical Convergence of Tracking Error and Boundedness of Signals -- 5 Simulation -- 6 Conclusions -- References -- A Comparative Study of Pedestrian Detection Techniques Over the Last Decade -- 1 Introduction -- 2 State-of-the-Art Methods for Pedestrian Detection -- 2.1 Region-Based CNN (R-CNN) -- 2.2 Fast R-CNN -- 2.3 Faster R-CNN -- 2.4 Single Shot Detectors -- 2.5 Scale-Aware Fast R-CNN for Pedestrian Detection -- 3 Evaluation Criteria for Pedestrian Detection -- 4 Evaluation Benchmark Datasets -- 4.1 Evaluation Results for Pedestrian Detection -- 5 Conclusion -- References -- Approximation Properties of Modified-Bernstein Operators Having Szász Weight Functions -- 1 Introduction -- 2 Preliminaries -- 3 Moment Estimation -- 4 Approximation Properties of Sn(. -- t) -- 4.1 Local Approximation -- 4.2 Rate of Convergence -- 4.3 Voronovskaya-Type Asymptotic Result -- 5 Graphical Analysis -- 6 Conclusion -- References -- Fourier-Laguerre Expansion of Signals by Composite Summable Technique -- 1 Introduction -- 2 Preliminaries -- 3 Main Result -- 4 Graphical Analysis -- References -- A Multiple Linear Regression Model to Estimate Global, Direct and Diffuse Irradiance in Gurugram, India, Using Python -- 1 Introduction -- 2 Data Acquisition -- 3 Multiple Linear Regression Model for Estimation of Solar Radiation -- 4 Results and Discussions -- 4.1 Multiple Linear Regression Model for Global Horizontal Irradiance (GHI) -- 4.2 Multiple Linear Regression Model for Direct Normal Irradiance (DNI) -- 4.3 Multiple Linear Regression Model for Diffuse Horizontal Irradiance (DHI) -- 5 Evaluating Model Performance -- 5.1 Model Validation for Global Horizontal Irradiance -- 5.2 Model Validation for Direct Normal Irradiance -- 5.3 Model Validation for Diffuse Horizontal Irradiance -- 6 Conclusions -- References. Supervised Machine Learning Approaches for Customer Reviews Sentiment Analysis -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Customer Review Dataset -- 3.2 Workflow of Sentiment Analysis -- 3.3 Evaluation Parameters -- 4 Comparative Analysis -- 4.1 Comparing the Vectorization Techniques -- 4.2 Comparing the Classifiers -- 5 Conclusion -- References -- Stock Price Prediction on Indian Share Market Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Evaluation Metrics -- 5 Results -- 6 Conclusion -- References -- Transparent Price Forecasting for Basic Food Commodities in a Developing Economy -- 1 Introduction -- 2 Background and Motivation -- 3 Research Contribution -- 4 Methodology -- 5 Results and Discussion -- 5.1 Dataset Description -- 5.2 Exploratory Data Analysis -- 5.3 Data Cleaning and Preprocessing -- 5.4 Data Splitting -- 5.5 Training the Model -- 5.6 Results Before Model Tuning -- 5.7 Explainable AI Results -- 5.8 Final Results -- 6 Conclusion -- 7 Limitations of the Model -- 8 Future Works -- References -- Parallel Deep Convolution Neural Network (P-DCNN) Prediction of Paddy Crop Disease -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Image Data Collection -- 3.2 Classification Phase -- 3.3 ResNet Model -- 3.4 YOLO Classifier -- 3.5 Learning Rate (LR) and Epochs -- 4 Results and Discussion -- 4.1 Performance Analysis -- 5 Conclusion -- References -- Convolutional-LSTM Network for Emotion Recognition Using EEG Data in Valence-Arousal Dimension -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Wavelet Transform -- 3.2 Convolutional-LSTM Network -- 4 Experiments -- 4.1 Dataset -- 4.2 Model Implementation -- 5 Results and Analysis -- 6 Conclusion -- References -- Analysis of Multiply-Accumulate (MAC) Unit Using Convolution Neural Networks (CNN). 1 Introduction. |
| Record Nr. | UNINA-9910874686603321 |
Kumar Rajesh
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Soft Computing : Proceedings of SoCTA 2023, Volume 2
| Soft Computing : Proceedings of SoCTA 2023, Volume 2 |
| Autore | Kumar Rajesh |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (472 pages) |
| Altri autori (Persone) |
VermaAjit Kumar
VermaOm Prakash WadehraTanu |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN |
9789819720897
9789819720880 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- An Extensive Review on Designing of Blood Bank Management System -- 1 Introduction -- 2 Literature Survey -- 2.1 Development of a Blood Bank Management System -- 2.2 Blood Bank Management and Inventory Control Database Management System -- 2.3 Effective Blood Bank Management Based on RFID in Real-Time Systems -- 2.4 Computerized Central Blood Bank Management System (CCBBMS) -- 2.5 Web Based Blood Donation Management System (BDMS) and Notifications -- 2.6 A Secure Cloud Computing-Based Framework for the Blood Bank -- 3 Methodology -- 4 Conclusion -- References -- Ensemble Models for Vulnerability Prediction Using Code Metrics -- 1 Introduction -- 2 Related Research -- 3 Methodology -- 3.1 Dataset Preparation -- 3.2 Ensemble Model -- 4 Experiment -- 5 Results and Discussion -- 6 Conclusion -- References -- Echo State Networks for Cryptography: A Novel Framework for Key Generation and Secure Communication -- 1 Introduction -- 2 Echo State Networks -- 3 Literature Review on Cryptography -- 4 ESN-Based Cryptography -- 5 Proposed Framework -- 5.1 System Architecture -- 5.2 Key Generation Unit (KGU) -- 5.3 Encryption Processing Unit (EPU) -- 5.4 Decryption Processing Unit (DPU) -- 5.5 System Robustness and Adaptability -- 5.6 Detailed Operation of the Proposed Framework -- 5.7 Computational Considerations and Practical Implications -- 6 Security Analysis -- 6.1 Resistance to Brute-Force Attacks -- 6.2 Resistance to Side-Channel Attacks -- 6.3 Resistance to Cryptanalysis Attacks -- 6.4 Key Space Analysis -- 6.5 Complexity Analysis -- 6.6 Theoretical Robustness and Adaptability -- 7 Discussion and Future Directions -- 7.1 Theoretical Contributions and Implications -- 7.2 Potential Practical Applications -- 7.3 Challenges and Future Directions -- 8 Conclusion -- References.
Exploration of Coarse-Graining and Threshold Selection of Lempel-Ziv Complexity on Vibroarthrographic Signals -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Lempel-Ziv Complexity -- 2.3 Various Coarse-Graining Techniques Applied to VAG Signals -- 2.4 Benchmark Indices and Statistical Test -- 3 Result -- 4 Conclusion -- References -- Image Super Resolution Using Extensive Residual Network (ERN) for Orange Fruit Disease Detection -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Super Resolution Model Using ERN -- 3.2 Classification of Orange Fruit Disease -- 3.3 Dataset -- 3.4 Experimentation -- 4 Results -- 4.1 Qualitative Analysis -- 4.2 Quantitative Analysis -- 5 Conclusion -- References -- A Powerful High-Order B-Spline Galerkin Technique for Numerical Solutions of Advection-Diffusion Equation -- 1 Introduction -- 2 A Higher-Order B-Spline Function with Galerkin Approach -- 3 Numerical Examples -- 3.1 Test Example 1 -- 3.2 Test Example 2 -- 4 Conclusions -- References -- Some Explicit Formulas for Changhee-Genocchi Polynomials and Numbers -- 1 Introduction -- 2 The Changhee-Genocchi Polynomials -- 3 Conclusion -- References -- Numerical Simulations of Third-Order Singularly Perturbed Boundary Value Problems -- 1 Introduction -- 1.1 The QTBS Functions -- 2 The Technique -- 3 Numerical Simulations -- 3.1 Problem-1 -- 3.2 Problem 2 -- 3.3 Problem 3 -- 4 Conclusion -- References -- A Study on lamdaλ-Analogue Type of Degenerate Daehee Polynomials and Numbers -- 1 Introduction -- 2 lamdaλ-Analogue Type of Degenerate Daehee Polynomials and Numbers -- 3 Conclusion -- References -- Water Quality Prediction Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Research Methodology -- 3.1 Machine Learning Methods' Applied -- 3.2 About Dataset -- 4 Experimental Results and Discussion -- 4.1 Training and Testing. 4.2 The Performance Measurement Factors -- 5 Conclusion, Limitations, and Future Scope -- References -- Single Smart Card for Identity and Authentication Using Data Analytics -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Block Diagram -- 3.2 Implementation -- 4 Results and Discussions -- 5 Conclusion -- References -- Strategic Utilization of ChatGPT in Teaching and Learning -- 1 Introduction -- 1.1 Background and Motivation -- 1.2 Our Contributions -- 2 ChatGPT -- 2.1 Brief History of ChatGPT -- 2.2 Understanding Open AI and Current Research Focus on ChatGPT -- 2.3 Technical Setup and Operation of ChatGPT -- 3 Methodology -- 4 Results and Discussion -- 4.1 Benefits of ChatGPT for Teaching and Learning -- 4.2 Risks of ChatGPT in Teaching and Learning -- 4.3 Opportunities Arising from the Need to Optimize and Utilize ChatGPT for Teaching and Learning -- 4.4 Simple Practical Use Cases of ChatGPT for Teaching and Learning -- 5 Conclusion -- References -- Particle-Based Swarm Fuzzy Optimization Approach in Vague Measurement of the Distance in Transportation Problems -- 1 Introduction -- 2 Primary Definitions -- 2.1 Fuzzy Set -- 2.2 Fuzzy Number -- 2.3 Particle Swarm Optimization (PSO) -- 3 Proposed Methodology -- 4 Implementation in a Problem Using MATLAB -- 5 Results and Discussion -- 6 Conclusion and Future Aspect of the Work -- References -- Design and Implementation of Network Coverage Area in WSN Using Swarm Optimization Techniques -- 1 Introduction -- 2 WSN Node Network -- 3 Particle Swarm Optimization and Discussion -- 4 Conclusion -- References -- Divergence Models in Fuzzy Environment and Their Solicitations for the Development of Fuzzy Information Improvement Models -- 1 Introduction -- 2 A New Non-parametric Fuzzy Divergence Model -- 3 Information Improvement Models for Discrete Fuzzy Distributions -- 4 Conclusion. References -- ViT-ALZ: Vision Transformer with Deep Neural Network for Alzheimer's Disease Detection -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset and Dataset Preparation -- 2.2 Proposed Vision Transformer and Deep Neural Network Model (ViT-ALZ)) -- 3 Experimental Setups -- 3.1 Implementation Details -- 3.2 Performance Metrics -- 4 Result -- 5 Conclusion -- References -- Edge-Ward Computational Offloading for Smart Waste Management System -- 1 Introduction -- 2 Background History -- 3 System Architecture -- 4 Experimental Setup -- 4.1 Network Topology for Cloud-Word Computational Offloading Architecture -- 4.2 Network Topology for Edge-Word Computational Offloading Architecture -- 5 Experimental Results and Discussion -- 5.1 Latency-Response Time -- 5.2 Network Usage -- 6 Conclusion and Future Work -- References -- AMPpred-CNN: Prediction of Antimicrobial Peptide by Using 1D Convolution Neural Network and Composition/Transition/Distribution (CTD) Encoding -- 1 Introduction -- 2 Material and Methods -- 2.1 Dataset Description -- 2.2 Overview of AmpPred-CNN -- 2.3 Performance Metric -- 3 Results and Discussion -- 3.1 Analyzing the Distribution of Sequence Lengths of AMPs and Non-AMPs in Different Datasets -- 3.2 Investigating Length Dependency of Antimicrobial Activity -- 3.3 Investigating Existence of Linearly Separable Features -- 3.4 Evaluating the Proposed Model on Benchmark Dataset -- 3.5 Comparative Performance on XUAMP Independent Dataset -- 3.6 Comparative Performance on DBAASP Independent Dataset -- 3.7 Performance of the Proposed Model with PCA -- 3.8 Performance of the Proposed Model with Top K Features and RFE -- 3.9 Performance of the Proposed Model with Different Ratios of AMPs and Non-AMPs -- 4 Conclusion -- References -- A Hybrid System for Detection of Stress Using Human Emotions Through Voice -- 1 Introduction. 2 Material and Method -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusions -- References -- Quasi-oppositional-Based Whale Optimization Applied to Multilevel Image Thresholding -- 1 Introduction -- 2 Problem Formulation -- 2.1 Whale Optimization Algorithm -- 2.2 Encircling Prey -- 2.3 Bubble Net Feeding -- 2.4 Looking for Prey -- 2.5 Quasi-oppositional-Based Learning (QOBL) -- 2.6 Quasi-opposite Number -- 3 QOWOA in Multilevel Image Thresholding -- 4 Experiments and Results -- 5 Conclusion -- References -- Enhanced Georeferencing by Adapting Improvised Lens Distortion Correction in Stationary Drone Video Frames -- 1 Introduction -- 1.1 Existing Projective Transformation (Homography) -- 1.2 Traditional Lens Distortion Correction -- 2 Proposed Projective Transformation Methodology -- 2.1 Lens Distortion Correction -- 3 Optimal Polynomial Order Selection Approach -- 4 Experimental Evaluation -- 4.1 Dataset Selection Criteria -- 4.2 Dataset Features -- 4.3 Radial Distortion Coefficient Calculations -- 5 Result Analysis -- 5.1 Radial Distortion Calculations-Traditional -- 5.2 Radial Distortion Calculations-Improvised -- 5.3 Comparative Data Analysis-Traditional and Improvised Approach -- 5.4 Comparative Complexity Analysis -- 5.5 Conclusion and Future Scope -- References -- Feature Selection and Classification to Detect Fetal Abnormalities -- 1 Introduction -- 2 Feature Selection -- 2.1 Feature Classification -- 3 Proposed System -- 3.1 SVM-Based LDA -- 3.2 PNN-Based MLE -- 4 Results and Discussions -- 5 Conclusion -- References -- Adoption of Blockchain Technologies into Forensic Accounting Practices -- 1 Introduction -- 2 Literature Review -- 3 Conceptual Framework -- 4 Hypotheses Development -- 5 Research Methodology -- 6 Structural Model Assessment and Result Interpretation -- 6.1 Model Assessment -- 6.2 Result Interpretation. 7 Recommendations. |
| Record Nr. | UNINA-9910882886203321 |
|
Kumar Rajesh
|
||
| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||