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Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications [Pehme köide]

Edited by , Edited by (Visva Bharati University, West Bengal, India), Edited by (Department of Computing and Information Technologies, Rochester Institute of Technology, Republic of Kosovo), Edited by (RCC Institute of Inf), Edited by (VSB Technical University of Ostrava, Czech Republic)
  • Formaat: Paperback / softback, 418 pages, kõrgus x laius: 276x216 mm, kaal: 450 g
  • Ilmumisaeg: 05-Aug-2021
  • Kirjastus: Academic Press Inc
  • ISBN-10: 012822844X
  • ISBN-13: 9780128228449
Teised raamatud teemal:
Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and ApplicationsSuurem pilt
  • Formaat: Paperback / softback, 418 pages, kõrgus x laius: 276x216 mm, kaal: 450 g
  • Ilmumisaeg: 05-Aug-2021
  • Kirjastus: Academic Press Inc
  • ISBN-10: 012822844X
  • ISBN-13: 9780128228449
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128228449.html
Märksõnad:

The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few.

Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing.

  • Provides insights into the theory, algorithms, implementation, and application of computational intelligence techniques
  • Covers a wide range of applications of deep learning across various domains which are researching the applications of computational intelligence
  • Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques
List of contributors
xiii
Preface xv
1 Optimization in the sensor cloud: Taxonomy, challenges, and survey
1(22)
Prashant Sangulagi
Ashok Sutagundar
1.1 Introduction
1(3)
1.2 Background and challenges in the sensor cloud
4(2)
1.2.1 Key definitions
4(1)
1.2.2 Challenges/issues
5(1)
1.3 Taxonomy for optimization in the sensor cloud
6(10)
1.3.1 Load balancing
7(3)
1.3.2 Information classification
10(1)
1.3.3 Information transmission
11(2)
1.3.4 Information processing
13(2)
1.3.5 Limitations of existing work
15(1)
1.4 Discussion and future research
16(3)
1.4.1 Discussion
16(2)
1.4.2 Future research
18(1)
1.5 Conclusion
19(1)
References
19(4)
2 Computational intelligence techniques for localization and clustering in wireless sensor networks
23(18)
Basavaraj M. Angadi
Mahabaleshwar S. Kakkasageri
Sunilkumar S. Manvi
2.1 Introduction
23(1)
2.2 Wireless sensor networks
24(2)
2.2.1 Characteristics
24(1)
2.2.2 Research issues/challenges
25(1)
2.3 Localization and clustering in wireless sensor networks
26(1)
2.3.1 Localization
26(1)
2.3.2 Clustering
26(1)
2.4 Computational intelligence techniques
27(10)
2.4.1 Computational intelligence techniques for localization
30(4)
2.4.2 Computational intelligence techniques for clustering
34(3)
2.5 Future research directions
37(1)
References
38(3)
3 Computational intelligent techniques for resource management schemes in wireless sensor networks
41(20)
Gururaj S. Kori
Mahabaleshwar S. Kakkasageri
Sunilkumar S. Manvi
3.1 Introduction
41(1)
3.2 Wireless sensor networks
42(4)
3.2.1 Characteristics
42(2)
3.2.2 Applications
44(1)
3.2.3 Issues/challenges
45(1)
3.3 Resource management in wireless sensor networks
46(9)
3.3.1 Computational intelligence techniques
47(1)
3.3.2 Literature survey
47(8)
3.4 Future research directions and conclusion
55(1)
References
56(5)
4 Swarm intelligence based MSMOPSO for optimization of resource provisioning in Internet of Things
61(22)
Daneshwari I. Hatti
Ashok V. Sutagundar
4.1 Introduction
61(3)
4.1.1 Related work
62(2)
4.1.2 Our contributions
64(1)
4.2 Proposed method
64(6)
4.2.1 Network environment
64(6)
4.3 Agency
70(3)
4.3.1 Device agency
70(1)
4.3.2 Fog agency
71(1)
4.3.3 Example scenario
72(1)
4.4 Simulation
73(8)
4.4.1 Simulation inputs
73(1)
4.4.2 Simulation procedure
74(1)
4.4.3 Performance measures
74(2)
4.4.4 Results
76(5)
4.5 Conclusion
81(1)
Acknowledgment
81(1)
References
81(2)
5 DNA-based authentication to access internet of things-based healthcare data
83(12)
Sreeja Cherillath Sukumaran
5.1 Introduction
83(1)
5.2 Literature survey
83(5)
5.2.1 Internet of things generic architecture
84(1)
5.2.2 Challenges in the internet of things
84(1)
5.2.3 Security challenges in internet of things layers
85(1)
5.2.4 Authentication schemes in the internet of things
86(2)
5.2.5 DNA cryptography
88(1)
5.3 Methodology
88(1)
5.4 Security analysis
88(4)
5.4.1 Password file compromise attack
88(3)
5.4.2 Dictionary attack
91(1)
5.4.3 Replay attack
91(1)
5.5 Scyther analysis
92(1)
5.6 Conclusion
92(1)
References
92(3)
6 Computational intelligence techniques for cancer diagnosis
95(16)
Nimrita Koul
Sunilkumar S. Manvi
6.1 Introduction
95(1)
6.2 Background
95(2)
6.2.1 Cancer research data
95(1)
6.2.2 Genomic data for cancers
96(1)
6.2.3 Imaging data for cancers
97(1)
6.3 Approaches to computational intelligence
97(2)
6.3.1 Evolutionary computation
98(1)
6.3.2 Learning theory
98(1)
6.3.3 Artificial neural networks
98(1)
6.3.4 Probabilistic methods
99(1)
6.4 Computational intelligence techniques for feature selection in cancer diagnosis
99(8)
6.4.1 Advantages of feature selection
100(1)
6.4.2 Rough sets for feature selection
100(1)
6.4.3 Genetic algorithms for feature selection
101(1)
6.4.4 Adaptive network fuzzy inference system
102(1)
6.4.5 Deep learning for cancer diagnosis
103(2)
6.4.6 Autoencoders for feature extraction
105(1)
6.4.7 Particle swarm optimization for feature selection
105(2)
6.5 Computational intelligence methods for cancer classification
107(1)
6.5.1 Classification methods
107(1)
6.6 Conclusion
108(1)
Acknowledgment
108(1)
References
108(3)
7 Security and privacy in the internet of things: computational intelligent techniques-based approaches
111(18)
Poornima M. Chanal
Mahabaleshwar S. Kakkasageri
Sunil Kumar S. Manvi
7.1 Introduction
111(1)
7.2 Internet of things
112(2)
7.2.1 Architecture
112(2)
7.3 Characteristics
114(1)
7.4 Research issues/challenges
115(1)
7.5 Applications
116(2)
7.6 Security and privacy in the internet of things
118(1)
7.6.1 Security
118(1)
7.6.2 Privacy
119(1)
7.7 Computational intelligent techniques
119(3)
7.7.1 Artificial intelligence
120(1)
7.7.2 Neural networks
120(1)
7.7.3 Evolutionary computation
120(1)
7.7.4 Artificial immune systems
121(1)
7.7.5 Fuzzy system
121(1)
7.7.6 Machine learning
121(1)
7.7.7 Bio-inspired algorithm
121(1)
7.8 Computational intelligent techniques to provide security and privacy for the internet of things
122(2)
7.8.1 Confidentiality
122(1)
7.8.2 Integrity
122(1)
7.8.3 Authentication
123(1)
7.8.4 Availability
123(1)
7.9 Future research direction
124(1)
References
124(5)
8 Automatic enhancement of coronary arteries using convolutional gray-level templates and path-based metaheuristics
129(26)
Miguel-Angel Gil-Rios
Ivan Cruz-Aceves
Fernando Cervantes-Sanchez
Igor Guryev
Juan-Manuel Lopez-Hernandez
8.1 Introduction
129(2)
8.2 Background
131(8)
8.2.1 Iterated local search
131(4)
8.2.2 Tabii search
135(2)
8.2.3 Simulated annealing
137(1)
8.2.4 Univariate marginal distribution algorithm
138(1)
8.3 Proposed method
139(3)
8.3.1 Automatic generation of convolutional gray-level template
139(2)
8.3.2 Binary classification of the gray-level filter response
141(1)
8.3.3 Image postprocessing
141(1)
8.4 Computational experiments
142(4)
8.4.1 Results of vessel imaging enhancement
142(1)
8.4.2 Postprocessing procedure
143(3)
8.5 Concluding remarks
146(1)
Appendix 1 Matlab code of the tabu search for the traveler salesman problem
147(5)
References
152(3)
9 Smart city development: Theft handling of public vehicles using image analysis and cloud network
155(16)
Himadri Biswas
Vaskar Sarkar
Priyajit Sen
Debabrata Sarddar
9.1 Introduction
155(1)
9.2 Motivation scenario
155(1)
9.3 Issues and challenges of image authentication through Internet of Things-based cloud framework
156(10)
9.3.1 Biometric system
156(4)
9.3.2 Internet of Things
160(3)
9.3.3 Cloud computing
163(1)
9.3.4 Different cloud management services
164(2)
9.3.5 Cloud-enabled Internet of Things
166(1)
9.4 Proposed facial recognition system implementation for theft handling
166(2)
9.4.1 Algorithm
167(1)
9.4.2 Flow chart
168(1)
9.4.3 Simulation result
168(1)
9.5 Conclusion
168(1)
References
168(3)
10 Novel detection of cancerous cells through an image segmentation approach using principal component analysis
171(26)
Joy Bhattacharjee
Soumen Santra
Arpan Deyasi
10.1 Introduction
171(1)
10.1.1 Principal component analysis
172(1)
10.1.2 Objective of the work
172(1)
10.2 Algorithm for analysis
172(1)
10.2.1 Binarized masked segmentation image
172(1)
10.2.2 Confusion matrix
172(1)
10.2.3 Image assessment using PCA
172(1)
10.2.4 Selection of highest probability
173(1)
10.3 Methodology
173(2)
10.4 Results and discussions
175(19)
10.4.1 Detection of cancerous cell from brain MRI
175(14)
10.4.2 Detection of cancerous cells from a breast mammogram
189(5)
10.5 Conclusion
194(1)
References
195(2)
11 Classification of the operating spectrum for the RAMAN amplifier embedded optical communication system using soft computing techniques
197(14)
Arup Kumar Bhattacharjee
Soumen Mukherjee
Rajarshi Dhar
Arpan Deyasi
11.1 Introduction
197(1)
11.2 Soft computing approaches in the optimization procedure
198(1)
11.3 Objective of the present problem
198(1)
11.4 Result analysis
199(1)
11.5 Practical implications
199(9)
11.6 Conclusion
208(1)
11.7 Limitations of research
208(1)
11.8 Future research
208(1)
References
208(3)
12 Random walk elephant swarm water search algorithm for identifying order-preserving submatrices in gene expression data: a new approach using elephant swarm water search algorithm
211(22)
Joy Adhikary
Sriyankar Acharyya
12.1 Introduction
211(2)
12.2 Problem description
213(1)
12.2.1 Order-preserving submatrices
213(1)
12.2.2 Solution generation
213(1)
12.2.3 Cost function
214(1)
12.3 Method
214(3)
12.3.1 Elephant swarm water search algorithm
215(1)
12.3.2 Random walk elephant swarm water search algorithm
216(1)
12.4 Numerical experiments
217(13)
12.4.1 Parameter settings
218(1)
12.4.2 Benchmark functions
218(2)
12.4.3 Convergence analysis
220(1)
12.4.4 Comparison with other metaheuristic algorithms
221(1)
12.4.5 Performance of random walk elephant swarm water search algorithm with the change in the objective function dimension
221(1)
12.4.6 Effectiveness of context switch probability
221(4)
12.4.7 Impact of random inertia weight strategy
225(1)
12.4.8 Success rate
226(2)
12.4.9 Statistical analysis
228(1)
12.4.10 Results on a real-life problem
229(1)
12.4.11 Biological relevance
229(1)
12.5 Conclusion
230(1)
References
230(3)
13 Geopositioning of fog nodes based on user device location and framework for game theoretic applications in an fog to cloud network
233(12)
Anjan Bandyopadhyay
Utsav Datta
Antara Banik
Pratyay Biswas
Vaskar Sarkar
13.1 Introduction
233(1)
13.2 System model
234(1)
13.3 Literature review
234(1)
13.4 Problem formulation
235(1)
13.5 Proposed method
235(5)
13.5.1 Geopositioning of fog nodes
235(1)
13.5.2 Applications of the proposed fog to cloud network
236(1)
13.5.3 Allocation of device requests to the processing resources
236(1)
13.5.4 User-to-user data transfer using fog nodes
237(1)
13.5.5 Determining the cost of edges
238(1)
13.5.6 Physical address of FNL2S
239(1)
13.5.7 Packet flow inside the network
239(1)
13.6 Simulation and discussion
240(4)
13.6.1 Geopositioning of fog nodes
240(1)
13.6.2 Request allocation to processing resources
240(1)
13.6.3 User-to-user data transfer
241(3)
13.7 Conclusions and future research
244(1)
References
244(1)
14 A wavelet-based low frequency prior for single-image dehazing
245(18)
Subhadeep Koley
Hiranmoy Roy
Soumyadip Dhar
14.1 Introduction
245(1)
14.2 Literature survey
245(1)
14.3 Motivation and contribution
246(1)
14.4 Proposed method
247(7)
14.4.1 Low-frequency prior
247(2)
14.4.2 Noise removal in high frequency
249(1)
14.4.3 Dehazing in low frequency
249(3)
14.4.4 Fuzzy contrast enhancement
252(2)
14.5 Analysis of results and discussion
254(7)
14.5.1 Qualitative assessment
254(2)
14.5.2 Quantitative assessment
256(2)
14.5.3 Time complexity evaluation
258(3)
14.6 Conclusions
261(1)
References
261(2)
15 Segmentation of retinal blood vessel structure based on statistical distribution of the area of isolated objects
263(16)
Rajat Suvra Nandy
Rohit Kamal Chatterjee
Abhishek Das
15.1 Introduction
263(2)
15.2 Related works
265(3)
15.2.1 Matched filter method
265(1)
15.2.2 Technique related to the region growing after the scale-space analysis
265(1)
15.2.3 Method related to the curvature estimation using mathematical morphology
266(1)
15.2.4 B-COSFIRE method
267(1)
15.2.5 Supervised approach
267(1)
15.3 Basic morphological operations
268(1)
15.4 Proposed algorithm
269(2)
15.4.1 Preprocessing of the fundus image
269(1)
15.4.2 Initial vessel-like structure determination
269(1)
15.4.3 Locally adaptive line structuring element generation and blood vessel segmentation
269(1)
15.4.4 Enhancement of vessel structure using difference of Gaussians
270(1)
15.4.5 Binarization using local Otsu's threshold
270(1)
15.4.6 Elimination of noisy objects from a binary image
270(1)
15.5 Experiment
271(4)
15.5.1 Database
271(1)
15.5.2 Experimental results
272(2)
15.5.3 Performance measurement
274(1)
15.6 Conclusions
275(2)
References
277(2)
16 Energy-efficient rendezvous point-based routing in wireless sensor network with mobile sink
279(16)
Priyanjana Mitra
Sanjoy Mondal
Khondekar Lutful Hassan
16.1 Introduction
279(1)
16.2 Problem statement
280(1)
16.3 Literature survey
280(3)
16.3.1 Cluster-based routing protocol with static sink
280(1)
16.3.2 Cluster-based routing protocol with mobile sink
281(2)
16.4 System model
283(2)
16.4.1 Network model
283(1)
16.4.2 Energy model
284(1)
16.5 General structure of a genetic algorithm
285(1)
16.5.1 Encoding
285(1)
16.5.2 Initial population
285(1)
16.5.3 Fitness function
285(1)
16.5.4 Selection
285(1)
16.5.5 Crossover
285(1)
16.5.6 Mutation
285(1)
16.6 Proposed method
285(3)
16.6.1 Cluster head selection
286(1)
16.6.2 Rendezvous point selection
286(2)
16.6.3 Tour formation for the mobile sink
288(1)
16.7 Simulation environment and results analysis
288(3)
16.7.1 Number of alive nodes
288(2)
16.7.2 Cumulative energy consumption
290(1)
16.7.3 Cumulative data packet received at base station
290(1)
16.7.4 Changing the base station location
290(1)
16.7.5 Packet drop ratio and packet delay
290(1)
16.8 Statistical analysis
291(1)
16.9 Conclusions and future work
291(1)
References
292(3)
17 An integration of handcrafted features for violent event detection in videos
295(12)
B.H. Lohithashva
V.N. Manjunath Aradhya
D.S. Guru
17.1 Introduction
295(1)
17.2 Proposed method
296(3)
17.2.1 Global histograms of oriented gradients feature descriptor
296(1)
17.2.2 Histogram of optical flow orientation feature descriptor
297(1)
17.2.3 GIST feature descriptor
297(1)
17.2.4 Fusion feature descriptors
298(1)
17.2.5 Classifier
298(1)
17.2.6 Postprocessing
299(1)
17.3 Experimental results and discussion
299(5)
17.3.1 Data sets
299(1)
17.3.2 Experimental setting
299(1)
17.3.3 Evaluation parameter
300(1)
17.3.4 Results and analysis
301(2)
17.3.5 Space and time computation
303(1)
17.4 Conclusion
304(1)
Acknowledgment
304(1)
References
304(3)
18 Deep learning-based diabetic retinopathy detection for multiclass imbalanced data
307(10)
Shukla Mondal
Kaniz Fatima Mian
Abhishek Das
18.1 Introduction
307(1)
18.2 Related works
307(1)
18.3 Data set and preprocessing
308(1)
18.4 Methodology
308(3)
18.4.1 Convolutional neural networks
310(1)
18.4.2 Training (transfer learning)
311(1)
18.4.3 Steps to train the proposed model
311(1)
18.5 Experimental results and discussion
311(3)
18.6 Conclusion and future work
314(1)
References
315(1)
Further reading
316(1)
19 Internet of Things e-health revolution: secured transmission of homeopathic e-medicines through chaotic key formation
317(22)
Joydeep Dey
Arindam Sarkar
Sunil Karforma
19.1 Introduction
317(1)
19.2 Related works
318(2)
19.3 Complication statements
320(1)
19.4 Proposed frame of work
320(1)
19.5 Work flow diagram of the proposed technique
321(1)
19.6 Novelty of the proposed technique
322(1)
19.7 Result section
322(13)
19.7.1 Statistical key strength
322(1)
19.7.2 Histogram and autocorrelation analysis
323(2)
19.7.3 Chi-square comparison
325(1)
19.7.4 Differential attacks
325(1)
19.7.5 Security analysis
326(7)
19.7.6 Analysis of the session key space
333(1)
19.7.7 Analysis of the information entropy
333(1)
19.7.8 Encryption--decryption process time
334(1)
19.7.9 Time needed for an intrusion
335(1)
19.7.10 Comparative study with earlier works
335(1)
19.8 Conclusion
335(1)
Acknowledgments
336(1)
References
336(3)
20 Smart farming and water saving-based intelligent irrigation system implementation using the Internet of Things
339(16)
Sagnick Biswas
Labhvam Kumar Sharma
Ravi Ranjan
Sayak Saha
Arpita Chakraborty
Jyoti Sekhar Banerjee
20.1 Introduction
339(1)
20.2 Related studies
340(1)
20.3 System model
341(3)
20.3.1 Hardware operation
342(1)
20.3.2 Software operation
343(1)
20.4 Application of machine learning model
344(1)
20.5 Step-by-step procedure of the proposed methodology
345(2)
20.6 Results and discussion
347(5)
20.7 Comparative study among various Internet of Things based smart agriculture systems
352(1)
20.8 Conclusion
352(1)
Acknowledgments
352(1)
References
353(1)
Further reading
354(1)
21 Intelligent and smart enabling technologies in advanced applications: recent trends
355(12)
Mayurakshij Ana
Suparna Biswas
21.1 Introduction
355(1)
21.2 Enabling intelligent technologies used in recent research problems
355(7)
21.2.1 Internet of Things
355(1)
21.2.2 Machine learning
355(2)
21.2.3 Deep learning
357(1)
21.2.4 Metaheuristics
357(1)
21.2.5 Classification of various smart applications
358(2)
21.2.6 Smart home
360(1)
21.2.7 Smart transport
361(1)
21.2.8 Smart parking
362(1)
21.2.9 Smart agriculture
362(1)
21.3 Issues and challenges
362(1)
21.4 Case study
363(1)
21.5 Open research issues
364(1)
21.6 Conclusion
364(1)
References
364(3)
22 Leveraging technology for healthcare and retaining access to personal health data to enhance personal health and well-being
367(10)
Ayan Chatterjee
Ali Shahaab
Martin W. Gerdes
Santiago Martinez
Pankaj Khatiwada
22.1 Introduction
367(2)
22.1.1 Blockchain technology: a brief overview
368(1)
22.1.1 The work summary
368(1)
22.2 Patient stories and identified challenges
369(2)
22.2.1 Patient story 1
369(1)
22.2.2 Patient story 2
370(1)
22.2.3 Patient story 3
370(1)
22.2.4 Patient story 4
370(1)
22.3 Electronic health record, its security, and portability
371(1)
22.3.1 Electronic health record
371(1)
22.3.2 Electronic health record data-sharing challenges and opportunities
372(1)
22.3.3 Blockchain and electronic health record
372(1)
22.4 Discussion
372(2)
22.4.1 Censorship resistance
373(1)
22.4.2 Enhanced integrity and security
374(1)
22.4.3 Data aggregation and identity basis
374(1)
22.4.4 Ownership and access control
374(1)
22.5 Conclusion
374(1)
Acknowledgments
374(1)
References
374(3)
23 Enhancement of foveolar architectural changes in gastric endoscopic biopsies
377(12)
Mousumi Gupta
Om Prakash Dhakal
Amlan Gupta
23.1 Introduction
377(2)
23.1.1 Importance of gland and nuclei segmentation on clinical diagnosis
378(1)
23.1.2 Traditional gland segmentation computational models
379(1)
23.2 Current state of the art
379(2)
23.3 Source of images and image processing
381(4)
23.3.1 Description of the data set
382(1)
23.3.2 Segmentation approach
382(1)
23.3.3 Numerical definitions
383(2)
23.4 Outcomes and discussion
385(1)
23.5 Future possibilities and challenges
386(1)
23.6 Conclusion
387(1)
Acknowledgment
387(1)
References
387(2)
Index 389
Siddhartha Bhattacharyya is a Senior Researcher in the Faculty of Electrical Engineering and Computer Science of VSB Technical University of Ostrava, Czech Republic. He is also serving as the Scientific Advisor of Algebra University College, Zagreb, Croatia. Prior to this, he served as the Principal of Rajnagar Mahavidyalaya, Rajnagar, Birbhum. He was a professor at CHRIST (Deemed to be University), Bangalore, India, and also served as the Principal of RCC Institute of Information Technology, Kolkata, India. He is the recipient of several coveted national and international awards. He received the Honorary Doctorate Award (D. Litt.) from the University of South America and the SEARCC International Digital Award ICT Educator of the Year in 2017. He was appointed as the ACM Distinguished Speaker for the tenure 2018-2020. He has been appointed as the IEEE Computer Society Distinguished Visitor for the tenure 2021-2023. He has co-authored six books, co-edited 75 books, and has more than 300 research publications in international journals and conference proceedings to his credit. Dr. Paramartha Dutta did his Bachelors and Masters in Statistics from the Indian Statistical Institute, Calcutta in the years 1988 and 1990 respectively. He afterwards completed his Master of Technology in Computer science from the same Institute in the year 1993 and Doctor of Philosophy in Engineering from the Bengal Engineering and Science University, Shibpur in 2005 respectively. He has served in the capacity of research personnel in various projects funded by Govt. of India, which include DRDO, CSIR, Indian Statistical Institute, Calcutta etc. Dr. Dutta is now a Professor in the Department of Computer and system Sciences of the Visva Bharati University, West Bengal, India. Prior to this, he served Kalyani Government Engineering College and College of Engineering in West Bengal as full time faculty members. He has coauthored four books and has also one edited book to his credit. He has publishedabout hundred fifty papers in various journals and conference proceedings, both international and national. Presently, he is supervising four students for their Ph. D program registered with Visva Bharati University and West Bengal University of Technology. Dr. Dutta is a Life Fellow of the Optical Society of India (OSI), Computer Society of India (CSI), Indian Science Congress Association (ISCA), Indian Society for Technical Education (ISTE), Indian Unit of Pattern Recognition and Artificial Intelligence (IUPRAI) - the Indian affiliate of the International Association for Pattern Recognition (IAPR), Senior Member of Associated Computing Machinery (ACM), IEEE Computer Society, USA and IACSIT. Debabrata Samanta is an Assistant Professor & Program Head, at the Department of Computing and Information Technologies, Rochester Institute of Technology, Kosovo, Europe. He obtained his Ph.D. in Computer Science and Engg. in the area of SAR Image Processing. He is keenly interested in Interdisciplinary Research and development and has experience spanning fields of SAR Image Analysis, Video surveillance, a Heuristic algorithm for Image Classification, Deep Learning Framework for Detection and Classification, Blockchain, Statistical Modelling, Wireless Adhoc Networks, Natural Language Processing. He has successfully completed six Consultancy Projects. He owns 22 Patents (4 Design Indian Patents and 2 Australian patents Granted, 16 Indian Patents published) and 2 copyrights. He has authored or co-authored over 224 research papers; he has co-authored 13 books and co-edited 13 books. He has presented various papers at international conferences and received Best Paper awards. He is an IEEE Senior Member, an Associate Life Member of the Computer Society of India (CSI), and a Life Member of the Indian Society for Technical Education (ISTE). Dr. Anirban Mukherjee did his Bachelors in Civil Engineering in 1994 from Jadavpur University, Kolkata. While in service he achieved a professional Diploma in Operations Management (PGDOM) in 1998 and completed his PhD on Automatic Diagram Drawing based on Natural Language Text Understanding from Indian Institute of Engineering, Science and Technology (IIEST), Shibpur in 2014. Serving RCC Institute of Information Technology (RCCIIT), Kolkata since inception (in 1999), he is currently an Associate Professor and Head of the Department of Engineering Science & Management at RCCIIT. Before joining RCCIIT he served as an Engineer in the Scientific & Technical Application Group in erstwhile RCC, Calcutta for 6 years. His research interest includes Computer Graphics, Computational Intelligence, Optimization and Assistive Technology. He has co-authored two UG engineering textbooks: one on Computer Graphics and Multimedia and another on Engineering Mechanics. He has also co-authored more than 18 books on Computer Graphics/Multimedia for distance learning courses BBA/MBA/BCA/MCA/B.Sc (Comp. Sc.)/M.Sc (IT) of different Universities of India. He has international journal, book chapters and conference papers to his credit. He is on the editorial board of the International Journal of Ambient Computing and Intelligence (IJACI). Dr. Indrajit Pan, Associate Professor, Department of Information Technology, RCC Institute of Information Technology, Kolkata, India