Applied Intelligence for Industry 4.0

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 Hossain

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 Rahman

INTRODUCTION
BACKGROUND AND LITERATURE REVIEW
Related Terminologies
Existing Works
Limitations of the Existing Works
PROPOSED APPROACH
Dataset Creation
Data Pre-processing
Model Architecture Design
IMPLEMENTATION
Development Tools
Pre-processing Pipeline
Model Architecture Implementation
RESULTS
Training Results
Parameter Setting
Environment Setting
Evaluation
Limitations of Our Work
CONCLUSION
Bibliography

16. Document Level Comparative Sentiment Analysis on Bangla News Using Long-Short Term Memory and Machine Learning Approaches
Nuren Nafisa, Sabrina Jahan Maisha, and Abdul Kadar Muhammad Masum

INTRODUCTION
LITERATURE REVIEW
SA in Bangla Language
TASK DEFINITION ccxlix
Identifying Sentiment from Bangla news documents
Positive News (PN):
Negative News (NN):
Corpora Development
Data Collection
Data Pre-processing
Data Annotation
METHODOLOGY
Feature Extraction
Supervised ML algorithms
Deep learning approach LSTM
EXPERIMENTS AND RESULT ANALYSIS
Performance Measurement Tools
Experimental Output
Performance Statistics
Error Analysis
CONCLUSION
Bibliography

17. Employee Turnover Prediction Using Machine Learning Approach
Md. Ali Akbar, kamruzzaman Chowdhury, and Mohammed Nazim Uddin

INTRODUCTION
RELATED WORK
METHODOLOGY
System Architecture.
Dataset Collection
Data Preprocessing
Data Cleaning
One Hot Encoding
Feature Selection
Dataset Split
Class Imbalance
Performance Matrix
Selected Classification Methods
Base Rate Model
Logistic Regression Classifier
Decision Tree Classifier
Random Forest Classifier
AdaBoost Classifier
EXPERIMENTAL EVALUATION
Exploratory Data Analysis
Result Analysis
ROC-AUC Graph
Feature Importance
CONCLUSION
Bibliography

18. A Dynamic Topic Identification and Labeling Approach of COVID-19 Tweets
Khandaker Tayef Shahriar, Iqbal H. Sarker, Muhammad Nazrul Islam, and Mohammad Ali Moni

INTRODUCTION
RELATED WORK
METHODOLOGY
Aspect Terms Extraction
Topic Identification
EXPERIMENTS
Dataset
Data Preprocessing
Optimal number of LDA topic selection:
Selecting Top Unigram Feature form aspect terms cluster:
Qualitative Evaluation of Topics
Effectiveness Analysis
DISCUSSION
CONCLUSION AND FUTURE WORK
Bibliography

19. Analyzing IT Job Market and Classifying IT Jobs Using Machine Learning Algorithms
Sharmin Akter, Nabila Nawal, Ashim Dey, and Annesha Das

INTRODUCTION
RELATED WORK
METHODOLOGY
Dataset description
IT job market analysis
Training and testing
OUTCOMES
CONCLUSION
Bibliography

Biography

Nazmul Siddique received the Dipl.-Ing. degree in Cybernetics and Automation from Dresden University of Technology, Dresden, Germany, MSc in Computer Science from Bangladesh University of Engineering and Technology, Dhaka, Bangladesh and the Ph.D in Intelligent Control from the University of Sheffield, England, U.K. He has been a Lecturer with the School of Computing, Engineering and Intelligent Systems, University of Ulster Magee Campus, Londonderry, U.K since 2001. He was previously with the Computer Science and Engineering Discipline, Khulna University, Khulna, Bangladesh. He has been a guest editor of seven special issues of several reputed journals. He has served as committee member and chair of a number of national and international conferences. He is a senior member of IEEE. He is on the Editorial Board of a number of International Journals. Dr. Siddique has published over 170 journal, refereed conference papers, book chapters, and five books (John Wiley, Springer, Taylor & Francis). His research interests are in the fields of intelligent systems, computational intelligence, stochastic systems, and Markov modeling.