Computer Science & Information Management

Computational Intelligence in Analytics and Information Systems, Volume 1
Data Science and AI, Selected Papers from CIAIS-2021

Editors: Hardeo Kumar Thakur, PhD
Manpreet Kaur, PhD
Parneeta Dhaliwal, PhD
Rajeev Kumar Arya, PhD
Joan Lu, PhD

Computational Intelligence in Analytics and Information Systems, Volume 1

Published. Available now.
Pub Date: September 2023
Hardback Price: see ordering info
Hard ISBN: 9781774911440
E-Book ISBN: 9781003332312
Pages: 488pp w/index
Binding Type: Hardback / ebook
Notes: 2 color and 149 b/w illustrations

The new book presents a valuable selection of new and state-of-the-art technological advancements in various application areas using the concepts of AI and machine learning, highlighting the use of predictive analytics of data from various application domains to find timely solutions to various problems. The book focuses on the research developments, limitations, and management of real-time problems using computational intelligence by identifying applicable approaches in order to enhance, automate, and develop effective solutions. The volume introduces empirical research, prospects of theoretical research, and applications in data science and artificial intelligence.
The various novel approaches include applications in healthcare, natural language processing, and smart cities. As such, the book is divided into sections that address:

  • Computational Intelligence in Image Processing
  • Computational Intelligence in Healthcare
  • Techniques for Natural Language Processing
  • Computational Intelligence in Smart Cities
The very diverse range of topics include AI and machine learning applications for
  • In security: For using digital image processing for image fusion (face recognition, feature extraction, object detection as well tracking, moving object identification), for person re-identification for security purposes.

  • In healthcare and medicine: For diagnosis and prediction of breast cancer, other cancers, diabetes, heart disease; for predicting susceptibility to COVID-19; for prediction of mood and anxiety disorders.

  • In agriculture: For prediction of crop profit; for prediction of cropping patterns and recommendation for crop cultivation.

  • In traffic science/smart cities: For understanding road scene images, for detection of traffic signs, for devising a fog-based intelligent traffic phase timing regulation system

  • In language/speech/text: For automatic text summarization, for document indexing for unstructured data, for speech/accent recognition, for sound separation, for American Sign Language interpretation for nonsigners, for emotional recognition and analysis through speech, body postures with facial expressions, and other body movements (to improve the performance of virtual personal assistants / emotion recognition using speech, body postures with facial expressions and other body movements.

This volume offers valuable information for researchers working in interdisciplinary or multidisciplinary areas of healthcare, image analysis, natural language processing, and smart cities. This includes academicians, people in industry, and students with engineering background with research interest in these areas.

These peer-review chapters were selected from the International Conference on Computational Intelligence in Analytics and Information Systems (CIAIS- 2021), held in April 2021 at Manav Rachna University, India.

Click here for Computational Intelligence in Analytics and Information Systems, Volume 2: Advances in Digital Transformation, Selected Papers from CIAIS-2021

Click here for Computational Intelligence in Analytics and Information Systems, 2-volume set

CONTENTS:

Preface

PART I: COMPUTATIONAL INTELLIGENCE IN IMAGE PROCESSING
1. A Study of Issues and Challenges with Digital Image Processing
Urmila Pilania, Ankit Dagar, Sagar Aggarwal, and Aditya Pathak

2. A Methodical View of Prerequisites of Picture Combination, Strategies, Key Indicators with Usage in Real Life and Scientific Domains Facilitating Smart Ubiquitous Environment
Vineeta Singh and Vandana Dixit Kaushik

3. A Study of Emerging Issues and Possibilities for Breast Cancer Diagnosis Using Image Modalities
Ankur Kumar Aggarwal and Mrinal Pandey

4. Pap Smear Image Segmentation Using Chan-Vese Based Adaptive Primal Dual Splitting Algorithm
B. Chitra and S. S.Kumar

5. Satellite Image Compression by Random Forest Optimization Techniques and Performance Comparison Using Multispectral Image Compression Method
Srikanth Bethu, Sanjana Vasireddy, D. Ushasree, Md Asrar Ahmed, and P. Vara Prasad

6. Learning Spatio-Temporal Features for Movie Scene Retrieval Using 3d Convolutional Autoencoder
Vidit Kumar, Vikas Tripathi, and Bhaskar Pant

7. Person Re-Identification Using Deep Learning and Neural Networks
Parneeta Dhaliwal, Riya Sapr, Rishabh Dhiman, and Abhyuday Gupta

PART II: COMPUTATIONAL INTELLIGENCE IN HEALTHCARE
8. A Systematic Literature Review in Health Informatics Using Data Mining Techniques
Anjali Mehta and Dr. Deepa Bura

9. Utilization of Artificial Intelligence Based Methods for Preoperative Prediction in Shoulder Arthroplasty: Survey
Milind Tote and Dr. Shrikant V. Sonekar

10. Role of Computer-Based Intelligence for Prognostication a Social Well-Being and Identifying Frailty and Drawbacks
Sandeep Gupta, Nitin Tyagi, Manjula Jain, Shekhar Singh, and Krishan Kumar Saraswat

11. Health Informatics Support for Occurrence Administration Using Artificial Intelligence and Deep Learning: COVID-19 Pandemic Response
Akshat Jain, Ritu Pal, and Jagdish Chandra Patni

12. Machine Learning Approach for Prediction Analysis of COVID-19
Vaishali Garg, Khushboo Tripathi, and Deepthi Sehrawat

13. Assessment of Generalized Anxiety Disorder and Mood Disorder in Undergraduate Students during the Coronavirus Disease (COVID-19) Pandemic
Devesh Kumar Upadhyay, Subrajeet Mohapatra, and Niraj Kumar Singh

14. Evaluation of Deep Learning Models for Medical Tools Classification
Shweta Bali and S. S Tyagi

15. Cervical Cancer Diagnosis and Prediction: An Application of Machine Learning Techniques
Mamta Arora, Sanjeev Dhawan, and Kulvinder Singh

16. The Working Analysis on Machine Learning Algorithms to Predict Diabetes and Breast Cancer
Srikanth Bethu, Vempati Krishna, Boda Sindhuja, Damarla Lakshmi Rohita, and P Gopala Krishna

17. An Ensemble of AdaBoost with Multilayer Perceptron for Heart Disease Prediction
Syed Heena Andrabi, Mrinal Pandey, and Ram Chatterjee

PART III: TECHNIQUES FOR NATURAL LANGUAGE PROCESSING
18. An Empirical Study of Text Summarization Techniques Using Extractive Approaches
Sumita Gupta and Mohit Gambhir

19. Design and Comparative Analysis of Inverted Indexing of Text Documents
Gunjan Chandwani, Sarika, Narender, and Meena Chaudhary

20. Acoustic Musical Instrument Recognition
Usha Mittal, Pooja Rana, Dilpreet Singh, and Priyanka Chawla

21. Classification of Accented Voice Using RNN and GAN
Archit Prashant Patil, Parikansh Ahluwalia, Siddharth Yadav, and Preeti Kaur

22. Speech Emotion Recognition Using LSTM
Sarika Gaind, Shubham Budhiraja, Deepak Gauba, and Ms. Manpreet Kaur

23. Interpretation of American Sign Language Using a Convolutional Neural Network
Vikas Thada, Utpal Shrivastava, and Apresh Agrawal

24. Emotional Intelligence: An Approach to Analyze Stress Using Speech and Face Recognition
Shambhavi Mishra, Seeripi Naga Surya, and Sumita Gupta

25. Proposed Integrated Framework for Emotion Recognition: A Futuristic Approach
Ramesh Narwal and Dr. Himanshu Aggarwal

PART IV: COMPUTATIONAL INTELLIGENCE IN SMART CITIES
26. A Review on Machine Learning Techniques for Human Actions Recognition
Diana Nagpall and Dr. Rajiv Kumar

27. Fog-Based Intelligent Traffic Phase Timing Regulation System
Sahil and Sandeep Kumar Sood

28. Deep Learning Classification Model for Detection of Traffic Signs
Dr Vikas Thada, Mr. Utpal Shrivastava, Ms Gitika, and Ms Garima

29. Understanding Road Scene Images Using CNN Features
Anamika Maurya and Satish Chand

30. Profitable Crop Prediction for the State of Odisha Using Machine Learning Algorithms
Vaibhav Sinha, Preeti Mishra, and Junali Jasmine Jena

31. CapGAN: IoT-Based Cropping Patterns Prediction and Recommendation for Crop Cultivation
K. Sathya and M. Rajalakshmi

Index


About the Authors / Editors:
Editors: Hardeo Kumar Thakur, PhD
Associate Professor, Department of Computer Science and Technology, Manav Rachna University (MRU), Faridabad, India

Hardeo Kumar Thakur, PhD, is working as an Associate Professor in the Department of Computer Science and Technology of Manav Rachna University (MRU), Faridabad, India. He has more than 10 years of teaching and research experience in leading institutions of India. He earned his PhD (Computer Engineering) from the University of Delhi in 2017 in the field of data mining. His current research interests are data mining, dynamic graph mining, machine learning and big data analytics. He is an active referee for many international journals and conferences.

Manpreet Kaur, PhD
Associate Professor, Department of Computer Science and Technology, Manav Rachna University, India

Manpreet Kaur, PhD, is working as an Associate Professor in the Department of Computer Science and Technology, Manav Rachna University, India. She has more than 14 years of teaching and research experience. She is currently working in the domains of machine learning, deep learning, and natural language processing. She is a Senior Member, IEEE (USA).

Parneeta Dhaliwal, PhD
Associate Professor, Department of Computer Science and Technology, Manav Rachna University, India

Parneeta Dhaliwal, PhD, has over 16 years of experience in teaching and research. Presently, she is working as Associate Professor in the Department of Computer Science and Technology, Manav Rachna University, India. She is also working as Head of the Research Cluster of Computing (RCC) to facilitate students in their research and innovative projects.

Rajeev Kumar Arya, PhD
Assistant Professor, Department of Electronics and Communication Engineering, National Institute of Technology, Patna, India

Rajeev Kumar Arya, PhD, is currently an Assistant Professor with the Department of Electronics and Communication Engineering at National Institute of Technology, Patna, India. His current research interests are in wireless communication, soft computing techniques, cognitive radio, signal processing, communication systems, and circuits design.

Joan Lu, PhD
Professor, Department of Computer Science, Research Group Leader of Information and System Engineering (ISE), Centre of High Intelligent Computing (CHIC), University of Huddersfield, United Kingdom

Joan Lu, PhD, is a Professor in the Department of Computer Science and the Research Group Leader of Information and System Engineering (ISE) in the Centre of High Intelligent Computing (CHIC) at the University of Huddersfield, United Kingdom, having previously been team leader in the IT Department of the publishing company Charlesworth Group.




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