Applied intelligence for Industry 4.0. (2022)

• Record Type: Book
• Further Information: Note: Edited by Nazmul Siddique, Mohammad Shamsul Arefin, M. Shamim Kaiser, ASM Kayes.
• Editors: Siddique, N. H; Arefin, Mohammad Shamsul; Kaiser, M. Shamim; Kayes, ASM
• Contents: 1. Multi-labelled Bengali Public Comments Sentiment Analysis with Bidirectional Recurrent Neural Networks (Bi-RNN) ; Promila Ghosh, M. Raihan, Nishat Tasnim Tonni, Himadri Sikder Badhon, Sayed Asaduzzaman, and Hasin Rehana INTRODUCTION; RELATED WORK; METHODOLOGY; Data Preprocessing; Bidirectional RNN Implementation; OUTCOMES; CONCLUSION; Bibliography 2. Machine Learning and Blockchain Based Privacy-Aware: Cognitive Radio Internet of Things; Md Shamim Hossain, Kazi Mowdud Ahmed, Md Khairul Islam, Md MahbuburRahman, and Md Sipon Miah INTRODUCTION; SYSTEM MODEL; Blockchain based CR-IoT Network; The Protocol Structure; SENSING-CLUSTERING-BIDING-MINING POLICY; Sensing-Mining Energy Efficiency; SIMULATION RESULTS AND DISCUSSION; CONCLUSION; Bibliography 3. Machine Learning Based Models for Predicting Autism Spectrum Disorders; S. M. Mahedy Hasan, Md. Fazle Rabbi, Arifa Islam Champa, Md. Rifat Hossain, and Md. Asif Zaman INTRODUCTION; MATERIALS AND METHODS; Dataset Description; Methods; Classification Techniques; Evaluation Measures and Experimental Setup; EXPERIMENTAL RESULTS ANALYSIS; Analysis of Toddlers Dataset; Analysis of Adults Datasets; Discussion; CONCLUSION; Bibliography 4. Implementing Machine Learning Through the Neural Network for the Time Delay SIR Epidemic Model for the Future Forecast; Sayed Allamah Iqbal, Md. Golam Hafez, and A.N.M. Rezaul Karim INTRODUCTION; TIME DELAY SIR EPEDIMIC MODEL; Neural Networks for time-delay SIR model; DISCUSSION; SUMMARY; Bibliography 5. Prediction of PCOS Using Machine Learning and Deep Learning Algorithms; Syed Mohd. Farhan, Maimuna Manita Hoque, and Mohammed Nazim Uddin INTRODUCTION; RELATED WORK; METHODOLOGY; Dataset Collection; Data Preprocessing; Data Cleaning; Feature Engineering; Feature Selection; Feature Scaling; Dataset Split; Handling Imbalanced Data; Modelling Process; Hyperparameter Optimization; Logistic Regression Classifier; Random Forest Classifier; AdaBoost Classifier; Naĺȷve Bayes Classifier; Artificial Neural Network; Voting Classifier; Performance Evaluation; Selecting Best Model; Validating Final Model; Deploying Final Model into PCOS Predictor; EXPERIMENTAL RESULTS; Statistical Results; Model Visualization; CONCLUSION AND FUTURE WORKS; Bibliography 6. Malware Detection: Performance Evaluation of ML Algorithms Based on Feature Selection and ANOVA; Nazma Akther, Md. Neamul Haque, and Khaleque Md. Aashiq Kamal INTRODUCTION; RELATED WORK; PROBLEM STATEMENT; RESEARCH METHODOLOGY; Data set; Weka Tool; Feature Selection Technique; RESULT ANALYSIS; STATISTICAL ANALYSIS; Statistical Analysis of Feature Selection Technique; Statistical Analysis of Machine Learning Algorithm; CONCLUSION; Bibliography 7. An Efficient Approach to Assess the Soil Quality of Sundarbans Utilizing Hierarchical Clustering; Diti Roy, Md. Ashiq Mahmood, and Tamal Joyti Roy INTRODUCTION; RELATED WORK; PROPOSED METHODOLOGY; RESULTS AND DISCUSSION; CONCLUSION; Bibliography 8. A Machine Learning Approach to Clinically Diagnose Human Pyrexia Cases ; Dipon Talukder and Md. Mokammel Haque INTRODUCTION; RELATED HEALTHCARE RESEARCH; DATASET DESCRIPTION; Dataset Collection; Data Analysis and Deductions; FEATURE SELECTION; Primary Feature Selection; Final Feature Selection; MODEL EVALUATION; RESULT ANALYSIS; CONCLUSION AND FUTURE WORKS; Bibliography 9. Prediction of the Dengue Incidence in Bangladesh Using Machine Learning; Md. Al Mamun, Abu Zahid Bin Aziz, Md. Palash Uddin, and Md Rahat Hossai n INTRODUCTION; LITERATURE REVIEW; METHODOLOGY; Dataset Collection; Data Preprocessing; Machine Learning Algorithms; Method Evaluation Metrics; RESULT AND DISCUSSION \; Parameter Tuning; Result Analysis; ACKNOWLEDGEMENT; CONCLUSION; Bibliography 10. Detecting DNS over HTTPS Traffic Using Ensemble Feature Based Machine Learning; Sajal Saha, Moinul Islam Sayed, and Rejwana Islam INTRODUCTION; LITERATURE REVIEW; METHODOLOGY; Dataset; Data Preprocessing; Feature Engineering; Machine Learning Models; Proposed DOH Detection Model; Ensemble Feature Selection; Software and Hardware Preliminaries; Evaluation Metrics; RESULTS AND DISCUSSION; CONCLUSION; Bibliography 11. Development of Risk-Free COVID-19 Screening Algorithm from Routine Blood Test Using Ensemble Machine Learning; Md. Mohsin Sarker Raihan, Md. Mohi Uddin Khan, Laboni Akte, and Abdullah Bin Shams INTRODUCTION; RELATED WORKS; METHODOLOGY; Dataset Collection; Data Pre-processing; Missing Data Handling; SMOTE Analysis; Data Splitting; Feature Scaling; Stacked Ensemble Machine Learning; Machine Learning Algorithms; K-Nearest Neighbors (KNN); Support Vector Machine (SVM); Random Forest (RF); XG-Boost (XGB); AdaBoost (ADB); Compute Statistical Metrics; OUTCOMES; CONCLUSION; SUPPLEMENTARY WEBLINK; Bibliography 12. A Transfer Learning Approach to Recognize Pedestrian Attributes; Saadman Sakib, Anik Sen, and Kaushik Deb INTRODUCTION; RELATED WORKS; METHODOLOGY; Overview; Mask RCNN Object Detector; Preprocessing; Spatial Feature Extraction; Transfer Learning Approach; Classifier; OUTCOMES; Dataset Description; Experiments on the Proposed CNN Architecture; Results and Discussion; CONCLUSION; Bibliography 13. TF-IDF Feature-Based Spam Filtering of Mobile SMS Using Machine Learning Approach ; Syed Md. Minhaz Hossain, Khaleque Md. Aashiq Kamal, Anik Sen, and Iqbal H. Sarker INTRODUCTION; RELATED WORK; MATERIALS AND METHODS; Preprocessing; Redundant character removal; Removal of stop words; Tokenization; Lemmatization; Feature Extraction; Classifiers; Support Vector Machine; Multinomial Naĺȷve Bayes; RESULT AND OBSERVATIONS; Dataset; Classification using SVM and Multinomial Naĺȷve Bayes; Performance Measure; Performance Evaluation for Different Feature Extraction; Methods using Various Classifiers Performance Representation for the best classifier Using AUC and Confusion Matrix; Computational Time Analysis for Classifying spam; Comparison among the benchmark spam detection method; Critical Evaluation; CONCLUSION; Bibliography 14. Content-Based Spam Email Detection Using N-gram Machine Learning Approach; Nusrat Jahan Euna, Syed Md. Minhaz Hossain, Md. Musfique Anwar, and Iqbal H. Sarker INTRODUCTION; RELATED WORKS; METHODOLOGY; Preprocessing; Special character removal; Stop words removal; Tokenization; Lemmatization; Feature extraction; N-gram; Word2vec; Training; Support Vector Machine; Logistic Regression; Decision Tree; Multinomial naĺȷve bayes; RESULT AND OBSERVATIONS; CONCLUSION; Bibliography 15. AI Poet: A Deep Learning Based Approach to Generate Artificial Poetry in Bangla; Hasan Murad and Rashik
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2022
• Extent: 1 online resource
• Subjects: 658.4038028563; Industry 4.0; Artificial intelligence -- Industrial applications
• Languages: English
• ISBNs: 9781000804270; 9781000804232
• Related ISBNs: 9781032164151
• Notes: Note: Description based on CIP data; resource not viewed.
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