10767nam 22004693 450 991087468660332120240726080302.09789819720316(CKB)33388411500041(MiAaPQ)EBC31552521(Au-PeEL)EBL31552521(EXLCZ)993338841150004120240726d2024 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierSoft Computing Proceedings of SoCTA 2023, Volume 11st ed.Singapore :Springer,2024.©2024.1 online resource (427 pages)Lecture Notes in Networks and Systems Series ;v.9709789819720309 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.Lecture Notes in Networks and Systems SeriesKumar Rajesh437573Verma Ajit Kumar1062272Verma Om Prakash1732023Wadehra Tanu1749540MiAaPQMiAaPQMiAaPQ9910874686603321Soft 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