Machine Learning and Computational Intelligence Techniques for Data Engineering

1. Front Matter

   Pages i-xiv

   PDF

2. A Review on Rainfall Prediction Using Neural Networks

   • Sudipta Mandal, Saroj Kumar Biswas, Biswajit Purayastha, Manomita Chakraborty, Saranagata Kundu

   Pages 1-12

3. Identifying the Impact of Crime in Indian Jail Prison Strength with Statical Measures

   • Sapna Singh kshatri, Deepak Singh

   Pages 13-22

4. Visual Question Answering Using Convolutional and Recurrent Neural Networks

   • Ankush Azade, Renuka Saini, Dinesh Naik

   Pages 23-33

5. Brain Tumor Segmentation Using Deep Neural Networks: A Comparative Study

   • Pankaj Kumar Gautam, Rishabh Goyal, Udit Upadhyay, Dinesh Naik

   Pages 35-46

6. Predicting Bangladesh Life Expectancy Using Multiple Depend Features and Regression Models

   • Fatema Tuj Jannat, Khalid Been Md. Badruzzaman Biplob, Abu Kowshir Bitto

   Pages 47-58

7. A Data-Driven Approach to Forecasting Bangladesh Next-Generation Economy

   • Md. Mahfuj Hasan Shohug, Abu Kowshir Bitto, Maksuda Akter Rubi, Md. Hasan Imam Bijoy, Ashikur Rahaman

   Pages 59-70

8. A Cross Dataset Approach for Noisy Speech Identification

   • A. K. Punnoose

   Pages 71-79

9. A Robust Distributed Clustered Fault-Tolerant Scheduling for Wireless Sensor Networks (RDCFT)

   • Sandeep Sahu, Sanjay Silakari

   Pages 81-93

10. Audio Scene Classification Based on Topic Modelling and Audio Events Using LDA and LSA

    • J. Sangeetha, P. Umamaheswari, D. Rekha

    Pages 95-103

11. Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine Tuning Approach

    • Tejas Shelatkar, Urvashi Bansal

    Pages 105-114

12. Comparative Study of Loss Functions for Imbalanced Dataset of Online Reviews

    • Parth Vyas, Manish Sharma, Akhtar Rasool, Aditya Dubey

    Pages 115-126

13. A Hybrid Approach for Missing Data Imputation in Gene Expression Dataset Using Extra Tree Regressor and a Genetic Algorithm

    • Amarjeet Yadav, Akhtar Rasool, Aditya Dubey, Nilay Khare

    Pages 127-138

14. A Clustering and TOPSIS-Based Developer Ranking Model for Decision-Making in Software Bug Triaging

    • Pavan Rathoriya, Rama Ranjan Panda, Naresh Kumar Nagwani

    Pages 139-150

15. GujAGra: An Acyclic Graph to Unify Semantic Knowledge, Antonyms, and Gujarati–English Translation of Input Text

    • Margi Patel, Brijendra Kumar Joshi

    Pages 151-160

16. Attribute-Based Encryption Techniques: A Review Study on Secure Access to Cloud System

    • Ashutosh Kumar, Garima Verma

    Pages 161-170

17. Fall Detection and Elderly Monitoring System Using the CNN

    • Vijay Mohan Reddy Anakala, M. Rashmi, B. V. Natesha, Ram Mohana Reddy Guddeti

    Pages 171-182

18. Precise Stratification of Gastritis Associated Risk Factors by Handling Outliers with Feature Selection in Multilayer Perceptron Model

    • Brindha Senthil Kumar, Lalhma Chhuani, Lalrin Jahau, Madhurjya Sarmah, Nachimuthu Senthil Kumar, Harvey Vanlalpeka et al.

    Pages 183-196

19. Portfolio Selection Using Golden Eagle Optimizer in Bombay Stock Exchange

    • Faraz Hasan, Faisal Ahmad, Mohammad Imran, Mohammad Shahid, Mohd. Shamim Ansari

    Pages 197-206

20. Hybrid Moth Search and Dragonfly Algorithm for Energy-Efficient 5G Networks

    • Shriganesh Yadav, Sameer Nanivadekar, B. M. Vyas

    Pages 207-218

This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves to be a valuable resource for those in academia and industry.

• Machine Intelligence
• Signal Processing
• Brain Computing Interface
• Computational Intelligence
• Pattern Classification
• Ensemble Models
• Deep Learning
• Human Computer Interaction
• Biomedical Imaging
• Diagnosis of Mental Disorder
• MISP 2022
• MISP Proceedings

• Department of Computer Science and Engineering, National Institute of Technology Raipur, Raipur, India

  Pradeep Singh, Deepak Singh

• Department of Computer Science and Engineering, International Institute of Information Technology, Naya Raipur, India

  Vivek Tiwari

• Østfold University College, Halden, Norway

  Sanjay Misra

Dr. Pradeep Singh received a Ph.D. in Computer science and Engineering from the National Institute of Technology, Raipur, and an M.Tech. in Software engineering from the Motilal Nehru National Institute of Technology, Allahabad, India. Dr. Singh is an Assistant Professor in the Computer Science & Engineering Department at the National Institute of Technology. He has over 15 years of experience in various government and reputed engineering institutes. He has published over 80 refereed articles in journals and conference proceedings. His current research interests areas are machine learning and evolutionary computing and empirical studies on software quality, and software fault prediction models.

Dr. Deepak Singh completed his Bachelor of Engineering from Pt. Ravi Shankar University, Raipur, India, in 2007. He earned his Master of Technology with honors from CSVTU Bhilai, India, in 2011. He received a Ph.D. degree from the Department of Computer Science and Engineering at the National Institute of Technology (NIT) in Raipur, India, in 2019. Dr. Singh is currently working as an Assistant Professor at the Department of Computer Science and Engineering, National Institute of Technology Raipur, India. He has over 8 years of teaching and research experience along with several publications in journals and conferences. His research interests include evolutionary computation, machine learning, domain adaptation, protein mining, and data mining.

Dr. Vivek Tiwari is a Professor in Charge of the Department of Data Science and AI and Faculty of Computer Science and Engineering at IIIT Naya Raipur, India. He received B.Eng. from the Rajiv Gandhi Technical University, Bhopal, in 2004 and M.Tech. from SATI, Vidisha (MP), in 2008. He obtained a Ph.D. degree from the National Institute of Technology, Bhopal (MA-NIT), India, in 2015 in data mining and warehousing. Dr. Tiwari has over 65 research papers, 2 edited books, and one international patent published to his credit. His current research interest is in machine/deep learning, data mining, pattern recognition, business analytics, and data warehousing.

Dr. Sanjay Misra Sr. Member of IEEE and ACM Distinguished Lecturer, is Professor at Østfold University College (HIOF), Halden, Norway. Before coming to HIOF, he was Professor at Covenant University (400-500 ranked by THE (2019)) for 9 years. He holds a Ph.D. in Information & Knowledge Engineering (Software Engineering) from the University of Alcala, Spain, and an M.Tech. (Software Engineering) from MLN National Institute of Tech, India. Total around 600 articles (SCOPUS/WoS) with 500 co-authors worldwide (-130 JCR/SCIE) in the core & appl. area of Software Engineering, Web engineering, Health Informatics, Cybersecurity, Intelligent systems, AI, etc.