The increasing reliance on automation and data-driven decision-making is transforming industries. As technology advances, the need for more intelligent and efficient systems is growing. This book explores how data-driven approaches are being applied in various fields to solve real-world challenges.
With contributions from researchers and professional, the chapters discuss practical applications of modern computational techniques. Topics range from optimizing industrial processes to improving predictive systems in different sectors. The book also emphasizes the importance of responsible and interpretable technology to ensure fairness and transparency.
This book is a valuable resource for students, researchers, and professionals looking to understand the evolving role of data in industry. It provides insights into emerging trends and encourages further exploration in the field of intelligent systems and automation.
The increasing reliance on automation and data-driven decision-making is transforming industries. This book explores how data-driven approaches are being applied in various fields to solve real-world challenges.
1. A System that Analyzes Bengali Text on Facebook Posts Using Machine
Learning to Spot Suspicious Content.
2. A Reversible Transformer Based Bangla
Conversational Agent.
3. URL Based Website Classification Using Deep Learning
and Word Based Multiple N-gram Models.
4. BN-HTRd: A Benchmark Dataset for
Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line
Segmentation.
5. RiceNet: Accurate Classification of Rice Varieties using
Convolutional Neural Networks.
6. Vehicle Name Plate Detection and Blurring
from social media images using image processing and Deep learning.
7.
DCNN-SMD: A Deep Convolutional Neural Network Model to Diagnosis, Prognosis,
and Characterise Sperm Morphology.
8. Muslim Salat Gesture Recognition
Framework: Integrating Deep Transfer Learning and Machine Learning.
9.
BHSGR-Net: A Light-Weight Convolutional Neural Architecture for Recognition
of Bengali Hand Sign Gestures.
10. Can Machine Learning Help Identify
Suicidal Tweets? An Ensemble Classifier Approach.
11. An Interpretable
Systematic Review of Machine Learning Models for Predictive Maintenance of
Aircraft Engine.
12. Multichannel Attention Networks with Ensembled Transfer
Learning to Recognize Bangla Handwritten Charecter.
13. Development of a Deep
Learning Classification Model for Improved Rainfall Prediction in Ireland.
14. Defect Detection of Casting Products Using Deep Learning: A Method Based
on Convolutional Neural Networks.
15. OLD-TL: Offensive Language Detection in
Gaming Live Stream using Transfer Learning.
16. Predicting Stress in
Bangladeshi University Students: A LIMEInterpretable Machine Learning
Approach.
17. Early detection of system failure using machine learning
techniques.
18. Churn Prediction Using Machine Learning in the Tours and
Travel Industry.
Dr. Nazmul Siddique is a researcher at the School of Computing, Engineering, and Intelligent Systems, Ulster University. He has published over 170 research papers and several books on cybernetics and computational intelligence. His editorial roles in top journals highlight his academic influence and contributions.
Dr. Mohammad Shamsul Arefin is a professor at the Department of CSE, CUET, and Dean of Electrical and Computer Engineering. He has over 170 publications in journals and conferences on data mining, distributed computing, and machine learning. His leadership has significantly fostered research growth and academic excellence in many aspects.
Dr. K. M. Azharul Hasan, Professor, Department of CSE, KUET, has served as the Head of CSE and Dean of EEE, making significant contributions to engineering education in Bangladesh. He earned the University Gold Medal at Khulna University, completed his M.Eng. at AIT, Thailand, and obtained a Ph.D. from the University of Fukui, Japan, specializing in flexible data warehouse design. Currently, his research focuses on Big Data and Natural Language Processing, driving advancements in data management, computational intelligence, and AI.
Dr. M Shamim Kaiser is a professor and Chairman at the Institute of Information Technology, Jahangirnagar University. He has authored over 100 research papers on machine learning, cyber security, and cognitive radio networks. His leadership at IIT has driven academic and research excellence in ICT.
