J.K Mandal Paramartha Dutta Somnath Mukhopadhyay (Eds.) Communications in Computer and Information Science 776 Computational Intelligence, Communications, and Business Analytics First International Conference, CICBA 2017 Kolkata, India, March 24–25, 2017 Revised Selected Papers, Part II 123 Communications in Computer and Information Science Commenced Publication in 2007 Founding and Former Series Editors: Alfredo Cuzzocrea, Xiaoyong Du, Orhun Kara, Ting Liu, Dominik Ślęzak, and Xiaokang Yang Editorial Board Simone Diniz Junqueira Barbosa Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil Phoebe Chen La Trobe University, Melbourne, Australia Joaquim Filipe Polytechnic Institute of Setúbal, Setúbal, Portugal Igor Kotenko St Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St Petersburg, Russia Krishna M Sivalingam Indian Institute of Technology Madras, Chennai, India Takashi Washio Osaka University, Osaka, Japan Junsong Yuan Nanyang Technological University, Singapore Lizhu Zhou Tsinghua University, Beijing, China 776 More information about this series at http://www.springer.com/series/7899 J.K Mandal Paramartha Dutta Somnath Mukhopadhyay (Eds.) • Computational Intelligence, Communications, and Business Analytics First International Conference, CICBA 2017 Kolkata, India, March 24–25, 2017 Revised Selected Papers, Part II 123 Editors J.K Mandal Department of Computer Science and Engineering University of Kalyani Kalyani, West Bengal India Somnath Mukhopadhyay Department of Information Technology Calcutta Business School Kolkata India Paramartha Dutta Department of Computer and System Sciences Visva Bharati University Bolpur Santiniketan, West Bengal India ISSN 1865-0929 ISSN 1865-0937 (electronic) Communications in Computer and Information Science ISBN 978-981-10-6429-6 ISBN 978-981-10-6430-2 (eBook) DOI 10.1007/978-981-10-6430-2 Library of Congress Control Number: 2017953403 © Springer Nature Singapore Pte Ltd 2017 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer Nature Singapore Pte Ltd The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Foreword Preparing a foreword for the proceedings of an international conference, in the form of an edited volume, cannot but be an intellectual pleasure which I can ill afford to desist myself from Accordingly, I avail myself of an opportunity to write a few words for the foreword of the recently concluded First International Conference on Computational Intelligence, Business Analytics, and Communication (CICBA 2017) It was organized by Calcutta Business School in association with the Computer Society of India, on March 24–25, 2017 at the Calcutta Business School campus The conference was technically sponsored by IEEE Kolkata Chapter, IEEE Young Professionals Kolkata, as well as the IEEE Computational Intelligence Society, Kolkata Chapter The proceedings of the conference have been published by Springer Nature, in their CCIS series With the presence of Prof Dr Sankar Pal, former director, of the Indian Statistical Institute, Padmashri; Prof Dr Edward Tsang, University of Essex, UK; and Dr P.N Suganthan, Nanyang Technological University, Singapore as Keynote speakers, as well as luminaries from leading industries and research/academic institutes as invited speakers, the event could attain the true international standard that it had the intention to achieve With Prof Dr L.M Patnaik, Indian Institute of Science, Bangalore gracing the occasion as the chief guest, it was further praiseworthy to have had representatives from the Indian Institute of Management Kolkata, the Indian Statistical Institute Kolkata, the Defence Research and Development Organization, the Government of India, IBM, Wipro, Capgemini, Tata Consultancy Service, Accenture, Rediff.com, and LinkedIn for invited speeches and panel discussions As per my information, there were 276 papers submitted from across the globe including countries like Australia, the UK, Singapore, Bangladesh, Portugal, Saudi Arabia, Taiwan, Nepal, Thailand, Russia, and the USA – out of which 90 papers were accepted and presented There were technical tracks at the conference, each chaired by experts in the respective domains, as well as 18 technical sessions, where the authors presented their respective research work in front of the session chairs from academia and industry The three best papers were awarded by Springer Nature with prizes worth € 250, € 200, and € 150 respectively Some more awards were also offered by Calcutta Business School, the host, and IEEE Young Professionals Kolkata From my experience in general and by virtue of being present in person for some hours during the event, I strongly believe that it was undoubtedly commendable on the part of the organizers of the conference to have made it a grand success, especially this being the first one in the series I am sure that subsequent events of this conference series will definitely be able to prove its standing as a successful series within the research community in the years ahead VI Foreword Last but not the least, I want to avail myself of this opportunity to express my heartfelt thanks to the chairs of the Program Committee of CICBA 2017, along with all my good wishes for the upcoming CICBA series of conferences With best wishes July 2017 Sushmita Mitra Preface Calcutta Business School, in collaboration with the Computer Society of India, organized the First International Conference on Computational Intelligence, Communication, and Business Analytics (CICBA 2017), during 24–25 March 2017 at the Calcutta Business School campus This is the first activity of the Computer Society of India in the eastern region with Springer Nature as the publication partner This mega event covered all aspects of computational intelligence, communications, and business analytics, where by the scope was not only limited to various engineering disciplines, such as computer science, electronics, and electrical, mechanical, or biomedical engineering, but also included work from allied communities like general science, educational research, and management science, etc The volume constitutes a collection of high-quality peer-reviewed research papers received from all over the world CICBA 2017 attracted a good number of submissions from the different areas spanning eight tracks in various cutting-edge technologies of specialized focus, which were organized and chaired by eminent professors The eight special sessions focused on computational intelligence, data science and advanced data analytics, signal processing and communications, microelectronics, sensors, intelligent networks, computational forensics (privacy and security), computational intelligence in bio-computing, computational intelligence in mobile & quantum computing, and intelligent data mining & data warehousing After a rigorous peer-review process, with the help of our Program Committee members and external experts as reviewers (from inland as well as abroad), top-quality papers could be identified for presentation and publication The review process was extremely stringent with a minimum of three reviews for each submission and occasionally up to six reviews duly supplemented by checks on similarity and overlaps as well Submitted papers geographically encompass countries like Australia, the UK, Singapore, Bangladesh, Portugal, Saudi Arabia, Taiwan, Nepal, Thailand, Russia, and the USA Out of the pool of papers submitted, only 30% have been included in these final proceedings The Organizing Committee of CICBA 2017 consisted of international academic and industrial luminaries, and the Program Committee comprised around 200 technical experts These proceedings are published in one volume of Springer’s Communications in Computer and Information Science (CCIS) series We, in the capacity of the volume editors, convey our sincere gratitude to Springer for providing the opportunity to publish the proceedings of CICBA 2017 Representatives from the Indian Institute of Management Kolkata, the Indian Statistical Institute Kolkata, the Indian Institute of Science Bangalore, the Defence Research Development Organization, the Government of India, IBM, Wipro, Capgemini, TCS, Accenture, Rediff.com, and LinkedIn participated in the panel discussions, keynote addresses, and invited talks The conference included many distinguished keynote addresses by eminent speakers such as Prof Dr Sankar Pal, Indian Statistical Institute, Dr P.N Suganthan, Nanyang Technological University, Singapore, VIII Preface Prof Dr L.M Patnaik, Indian Institute of Science Bangalore, and Prof Dr Edward Tsang, University of Essex, UK Speakers for panel discussions included luminaries from academia and industry, such as Dr Gautam Mahapatra, RCI Labs, Defence Research Development Organization, Hyderabad; Mr Lawrence Mohanraj, IBM India Pvt Ltd., Chennai; Mr Somnath Chatterjee, Capgemini, Kolkata; Mr Ajit Balakrishnan, Rediff.com; Dr Arindam Pal, Data and Decision Sciences Group, TCS Innovation Labs Kolkata, India; Mr Rajeev Ranjan Kumar, Virtual Desk, Wipro Tech Hyderabad, etc Invited talks were delivered by Ms Suvira Srivastav, Springer Nature and Prof Dr Sushmita Mitra, Machine Intelligence Unit, Indian Statistical Institute, Kolkata The editors would like to express their sincere gratitude to Prof Dr Kalyanmoy Deb, Michigan State University, for taking the time to inaugurate the Call for Papers of CICBA 2017 They also thank the International Advisory Committee and the Chief Guest of CICBA 2017, Prof Dr L.M Patnaik, for providing valuable guidance and inspiration to overcome various difficulties in the process of organizing the conference We moreover want to avail ourselves of this opportunity to extend our heartfelt thanks to the Honorary Chair of this conference, Prof Dr Anirban Basu, Computer Society of India, for his active involvement from the very beginning till the end of the conference, without whose support this conference could never have assumed such a successful shape Sincerest thanks are due to Prof Dr P.K Roy, APIIT, India, for his valuable suggestions regarding enhancing the editorial review process The editors also thank the Best Paper Award Committee of CICBA 2017 for taking the trouble to select the best papers from a pool so many formidable acceptances The conference was sponsored by Calcutta Business School and IEEE Young Professionals Special words of appreciation are due to the Calcutta Business School, for coming forward to host the conference, which incidentally was the first in the series It was indeed heartening to note the enthusiasm of all faculty, staff, and students of Calcutta Business School to organize the conference in a professional manner Involvement of faculty coordinators and student volunteers are particularly praiseworthy in this regard The editors also thank technical partners and sponsors for providing all the support and financial assistance It is needless to mention the role of the contributors But for their active support and participation, the question of organizing a conference is bound to fall through The editors take this opportunity to thank the authors of all the papers submitted as a result of their hard work, more so because all of them considered the conference as a viable platform to ventilate some of their latest findings, not to speak of their adherence to the deadlines and patience with the lengthy review process The quality of a refereed volume primarily depends on the expertise and dedication of the reviewers who volunteer their efforts with a smiling face The editors are further indebted to the Program Committee members and external reviewers, who not only produced excellent reviews but also did these in short timeframes, in spite of their very busy schedules It is because of their quality work that it has been possible to maintain the high academic standard of the proceedings A conference is only complete when it has managed to attract a high level of participation A conference with good papers accepted and devoid of any participants is perhaps the worst form of curse that may be imagined The editors therefore thank the participants for attending the conference Preface IX Last but not the least, the editors would offer cognizance to all the volunteers for their tireless efforts in meeting the deadlines and arranging every minute detail meticulously to ensure that the conference achieved its goals, academic or otherwise J.K Mandal Paramartha Dutta Somnath Mukhopadhyay 616 A.M Chaudhari et al The pseudo-code of A* algorithm is as follow: function find_path( Source, Destination) { OPEN_List = [Source]; CLOSED_List = []; Current_Node = null; Neighbours = []; Path = []; Source.Parent = null; while ( OPEN_List is not Empty ) { Current_Node = OPEN_List.remove_least_node(); if( Current_Node == Destination ) break; CLOSED_List.add(Current_Node); Neighbours = Map.search_neighbours( Current_Node ); foreach (n in Neighbours) { examine(n); //The F, G and H cost of n is calculated n.Parent = Current_Node; OPEN_List.add(n); } } while( Current_Node is not null ) { Path.add( Current_Node ); Current_Node = Current_Node.Parent; } } The A* algorithm maintains two lists (OPEN List and CLOSED List) to keep track of examined/traversed nodes The OPEN list contains the nodes, which have been discovered but yet to examine Whereas, the CLOSED list contains the nodes, which have been discovered as well as examined [7] In the OPEN list, the nodes are kept in a sorted manner with respect to the Cost value of the Node While finding the path, the A* algorithm add the Source Node to OPEN list, and then repeatedly remove the node Improved A-star Algorithm with Least Turn 617 with least cost value from the OPEN list and add their walkable neighbour nodes to OPEN list, until the destination node is removed from the OPEN list Due to sorted order of nodes in OPEN list, the removal of node with least cost value become very much faster and optimal The removed node from OPEN list is then examined If the removed node is the destination node then A* algorithm will be terminated Otherwise, the walk‐ able neighbour nodes of current node are discovered and then added to OPEN list after calculating cost value of each neighbour node by cost function of A* algorithm And after adding each walkable neighbour node to OPEN list, the current node is added to CLOSED list [2] Heuristic Cost and Heuristic Function in A* The Heuristic cost can be calculated by using Heuristic function This Heuristic function uses the distance metric used to calculate the movement cost The choice of distance metric is done according to the requirements The two most popular distance metrics are: a Euclidean distance b Manhattan distance The Euclidean distance [3] between two n-dimensional vectors x and y can be defined as: d(x, y) = √∑ n i=1 ( )2 xi − yi (1) And the Manhattan distance [3] between two n-dimensional vectors x and y can be defined as: d(x, y) = ∑n i=1 |x − y | i| | i (2) The heuristic cost is estimated by considering that there is no obstacle between the current node and the destination node The Accuracy and Speed of A* algorithm depend on this heuristic cost If the heuristic cost is zero then the A* algorithm will work similar to Dijkstra’s algorithm, which will give very accurate output but it will be slow in performance If the heuristic cost is greater than the cost of moving from current node to destination node, then A* will not guarantee to find the shortest path but it will run faster, i.e the accuracy will be reduced and the speed will be increased If the Heuristic cost is equal to the cost of moving from current node to destination node then the A* will only follow the correct path/nodes and avoid exploring irrelevant nodes, making it very fast For the accurate (or shortest path) the Euclidean distance can be used And for faster path-finding, the Manhattan distance can be used 618 A.M Chaudhari et al Speed-Accuracy Trade-off in A* Algorithm Due to this Speed-Accuracy trade-off, the A* have ability to change its behavior according to the requirements i.e if path needs to be found in the situations (like video games), where just finding the path in less time is important than optimal path, then the Heuristic cost can be kept greater or equal to the cost of moving from current node to destination node But, if the path needs to be found in the situations (like rescue opera‐ tions), where the path should be accurate as well as should be found in less time, then the Heuristic cost should be equal to the cost of moving from current node to destination node [5] The Speed-Accuracy trade-off of the A* algorithm with respect to Heuristic cost can be given as follow: Notation: d(n) is the cost of moving from current node to destination As shown in Fig 1, as the value of heuristic function h(n) increases from to infinity, the speed of the algorithm increases i.e time required by algorithm decreases and the accuracy of algorithm decreases i.e Path length computed by algorithm increases Since, at h(n) = 0, the A* algorithm will act like Dijkstra’s algorithm and will provide accurate result but with less speed And at h(n) > d(n), the A* algorithm will act like Greedy Best-First-Search algorithm and will provide high speed but with less accurate result Fig Speed-Accuracy trade-off Improved A-star Algorithm with Least Turn 619 Problem The A* algorithm is heuristic and hence one cannot predict the path computed by it, since there can be multiple paths of same length Consider the following example: Figure shows the open maze, in which the path needs to be found The cost of moving from one node to other node is And the shortest path between them is of length 11 The path from the Source Node and the Destination Node can be given as follow: Fig Open maze The Figs 3, 4, and shows the few possible paths, that can be obtained by tradi‐ tional A* algorithm Let’s consider that the path is needed to be followed by a robot And the cost of moving the robot in forward direction is Cm and the cost of rotating the robot in left or right direction is CR So the total cost of moving robot from Source to Destination for each path can be given as follow: Cost(Path 1) = 11Cm + CR Cost(Path 2) = 11Cm + 2CR Cost(Path 3) = 11Cm + 4CR Cost(Path 4) = 11Cm + 8CR 620 A.M Chaudhari et al Fig Path Fig Path Fig Path Fig Path So even if the A* finds the optimal path by taking a sufficient amount of time, the cost of movement of the robot may or may not be optimal To find the optimal path with optimal movement cost, the cost function f(n) of the A* algorithm need to be modified Proposed Work In order to reduce the number of rotations taken by the A* algorithm, the cost function needs to be modified As the heuristic cost function not consider any obstacle in between the current node and destination node, it may or may not consider any rotation But in the case of actual cost function, it takes care of cost of moving from source to current nodes And by adding a cost to actual cost value for each turn taken by that path, the more accurate result i.e path with less turn can be achieved The actual cost function g(n) of the A* algorithm g(n) = g(parent) + movement_cost can be modified as follow: Improved A-star Algorithm with Least Turn g(n) = g(parent) + movement_cost + R 621 (3) Where, R is the cost of changing the direction i.e the cost of rotating left or rotating right The value of R can be defined as follow: If turn is detected then R = CR Otherwise R = Where, CR is the cost of rotation The Cost of Rotation depends on the size of Grid The larger the grid size, the higher value of rotation cost required Due to this, after taking each turn the cost value of the node will be increased And hence, as algorithm chooses the nodes with least cost value from OPEN list, it will also select the nodes with less number of turns, which may result into the path with less number of turns Experimental Setup We have used Raspberry Pi – Model B (1.2 GHz 64-bit quad-core ARMv8 CPU) on three 500 × 250 blocks grids We have used JavaScript programming to achieve the worst case performance, as the JavaScript get less system resources than other program‐ ming languages like C, C++ or Java, due to browser restrictions We have executed the algorithm for 10,000 times to achieve more accurate performance, as the JavaScript’s performance may vary according to CPU usage The Figs 7, and show the Grids used for testing traditional A* algorithm and Improved A* algorithm Fig Grid 622 A.M Chaudhari et al Fig Grid Fig Grid Experimental Result To find the path from the Source to the Destination, if the traditional A* algorithm is applied The following results were obtained (Figs 10, 11, 12 and Table 1) Improved A-star Algorithm with Least Turn Fig 10 Grid Fig 11 Grid Fig 12 Grid 623 624 A.M Chaudhari et al Table Result of traditional A* algorithm Grid Grid Grid Grid Time required (in milliseconds) 0.2504 0.3744 0.441 Path length Number of rotations 70 70 112 44 32 To find the path from the Source to the Destination, if the improved version of A* algorithm is applied The following results were obtained (Figs 13, 14 and 15) Fig 13 Grid Fig 14 Grid Improved A-star Algorithm with Least Turn 625 Fig 15 Grid Rotation Cost: See Table Table Result of improved A* algorithm Grid Time required (in milliseconds) 0.3082 0.4852 0.5446 Grid Grid Grid Path length Number of rotations 70 70 112 Result Comparison See Table Table Result comparison Grid Grid Grid Grid Time required (in milliseconds) A* Improved A* 0.2504 0.3082 0.3744 0.4852 0.4410 0.5446 Number of rotations A* Improved A* 44 32 The traditional A* algorithm takes less time (in milliseconds) to find the path, but the number of turns in path are more, whereas the improved A* algorithm take few more milliseconds but give less number of turns As the rotation cost increases gradually, the value of cost function of A* algorithm also increases, as result, the accuracy of algorithm increases, i.e number of turns taken reduces While doing so, few extra numbers of node could be also discovered The Figs 16 and 17 shows that, as the rotation cost increases gradually, the number of turns decreases, whereas the node space required increases, until the threshold rotation cost is achieved Whereas the Fig 18 shows that, as the rotation cost increases gradually, the number of nodes discovered also increases, for those extra discovered nodes, the A* algorithm requires little bit more time, due to this the time required by algorithm also increases gradually 626 A.M Chaudhari et al Fig 16 Effect of rotation cost on number of turns Fig 17 Effect of rotation cost on number of nodes discovered Fig 18 Effect of rotation cost on time required Improved A-star Algorithm with Least Turn 627 Conclusion Keeping in view the threatening situations, the design of Path-finding algorithm become more crucial in rescue operations We have modified the actual cost function of the traditional A* algorithm As the rotation cost is added in the cost function, the output of traditional A* algorithm can be improved efficiently The new cost function will help to find the shortest path with less number of turns, but in doing so, due to Speed-Accuracy trade-off, the time required by the algorithm will be bit more Due to this, the robot will need more time (in milliseconds) to compute the path, but it will require less time (in seconds/minutes) to reach to the trapped person and bring him/her to a safer place References Algfoor, Z., Sunar, M., Kolivand, H.: A comprehensive study on pathfinding techniques for robotics and video games Int J Comput Games Technol (2015) doi:10.1155/2015/736138 Dong, Z., Li, M.: A routing method of ad hoc networks based on A-star algorithm In: International Conference on Networks Security, Wireless Communications and Trusted Computing (2009) doi:10.1109/NSWCTC.2009.21 Han, J., Kamber, M.: Data Mining: Concepts and Techniques Morgan Kaufmann Publisher, San Francisco (2001) Joshi, H., Shinde, J.: An image based path planning using A-star algorithm Int J Emerg Res Manag Technol 3(5), 127–131 (2014) Liu, X., Gong, D.: A comparative study of A-star algorithms for search and rescue in perfect maze In: Electric Information and Control Engineering (ICEICE) (2011) doi:10.1109/ ICEICE.2011.5777723 Terzimehic, T., Silajdzic, S., Vajnberger, V., Velagic, J., Osmic, N.: Path finding simulator for mobile robot navigation In: International Symposium on Information, Communication and Automation Technologies (2011) doi:10.1109/ICAT.2011.6102086 Yao, J., Lin, C., Xie, X., Wang, A., Hung, C.: Path planning for virtual human motion using improved A* algorithm In: Seventh International Conference on Information Technology (2010) doi:10.1109/ITNG.2010.53 Zhang, Z., Zhao, Z.: A multiple mobile robots path planning algorithm based on A-star and Dijkstra algorithm Int J Smart Home 8(3), 75–86 (2014) Author Index Adhikari, Sudip Kumar II-323 Ahlawat, Khyati I-118 Amaratunga, Gehan A.J I-22 Apsangi, Minal R II-614 Babu, Ravi I-335 Bag, Pranab I-349 Bag, Soumen II-297 Bandyopadhyay, Rajib I-407 Banerjee, Avishek II-336 Banerjee, Mahuya Bhattacharyya I-407 Banerjee, Titir I-440 Banka, Haider I-525 Barik, Ranjan Kumar I-363 Barman, Subhas II-65 Basak, Piyali II-17 Basu, Anamika II-17 Basu, Saurabh I-296 Basu, Subhadip II-3 Bera, Somnath I-349 Bhakta, Ishita I-253 Bhattacharjee, Debotosh II-30, II-371 Bhattacharjee, Debraj I-72 Bhattacharya, Animesh I-281 Bhattacharya, Hindol II-336 Bhattacharya, Indrajit I-230 Bhattacharya, Indrani II-137 Bhattacharya, Samar II-197 Bhattacharyya, Nabarun I-407 Bhola, Prabha I-72 Bhowmick, Shib Sankar II-30 Bhowmik, Showmik II-599 Biswas, Animesh II-153 Biswas, Bikram I-431 Biswas, Biswajit II-256 Biswas, Neepa II-242 Biswas, Papun II-423 Biswas, Sanket II-65 Biswas, Suparna I-217 Biswas, Tanmay I-397 Bose, Anirban I-240 Chaki, Jyotismita II-197 Chakrabarti, Amlan I-397, II-371 Chakraborti, Debjani II-423 Chakraborty, Rajdeep I-485 Chakraborty, Sanjay II-44 Chakraverty, Shampa I-84 Chakravortty, Somdatta I-179 Chandra, Girish II-57 Chandrakar, Preeti I-537 Charernmool, Piyanuch I-93 Chatterjee, Moumita I-266 Chatterjee, Piyali II-3 Chatterjee, Rajeev I-141 Chatterjee, Santanu II-242 Chatterjee, Soma II-552 Chatterjee, Sujoy II-504 Chattopadhyay, Matangini II-336 Chattopadhyay, Samiran I-59, II-226, II-242, II-336 Chaudhari, Ashok M II-614 Chaudhuri, Tamal Datta II-475 Chiu, Tien-Lung I-416 Chowdhuri, Partha I-511 Chowdhury, Srijit I-308 Dalela, Pankaj Kumar I-296 Dan, Pranab K I-72 Das Chakladar, Debashis II-44 Das, Amita II-411 Das, Biplab II-108, II-121 Das, Jadav Chandra II-108, II-121 Das, Piyali I-253 Das, Rama Krushna II-488 Das, Sayan II-212 Das, Srirupa I-179 Das, Sujit II-540 Das, Sujoy Kumar I-495 Dash, Sanghamitra II-488 Datta, Kakali II-75 De, Debashis II-108, II-121 Deb, Kalyanmoy I-3 Dev, Deep Suman II-307 Devapriya, M I-193 Dey, Anup I-431 Dey, Chanchal I-372, I-453 Dhar, Tapobrata I-495 630 Author Index Dhebar, Yashesh I-3 Dutta, Paramartha II-75, II-85 Ghosh, Amal K I-281 Ghosh, Manosij II-599 Ghosh, Mili II-85 Ghosh, Shreya II-358, II-577 Ghosh, Susmita I-322 Ghoshal, Ranjit II-212 Giri, Chandan I-308 Gladston Raj, S II-384 Goswami, Saptarsi I-150 Goswami, Trishita II-358 Gowri, S I-206 Guha, Siddhartha II-466 Gupta, Diotima Dutta II-577 Gupta, Indrajeet II-97 Gupta, Priti II-65 Gurung, Bijay II-168 Halder, Amiya II-466 Hassan, Khondekar Lutful I-349 Hiriyannaiah, Srinidhi I-35 Hui, Nirmal Baran II-585 Jabez, J I-206 Jaiswal, Abeg Kumar I-525 Jaiswal, Himanshu II-307 Jana, Biswapati I-511 Jana, Prasanta K II-97 Jana, Susovan II-184 Jauhari, Anisha I-84 Joshi, Basanta II-168 K., Perumal I-582 Kahali, Sayan II-323 Kalitin, Denis II-398 Kantha, Bijoy I-431 Kar, Abhishek II-585 Kar, Sadhu Prasad I-141 Kaswan, Amar II-97 Khamrui, Amrita II-577 Khan, Saif Ayan II-347 Khataniar, Beauti I-467 Kisku, Dakshina Ranjan II-307 Koley, Santanu I-552 Kudale, Akshay B II-614 Kulkarni, Raghavendra V II-451 Kumar, Manoj I-467 Kumar, Mohit I-150 Kumar, Sachin II-398 Kumar, Samir II-153 Kundu, Riyanka II-65 Kushwaha, Niraj Kant I-296 Landge, Irfan A I-567 Lodh, Nilanjana II-137 Lohani, Ankit II-517 Mahapatra, Gautam II-242 Mahapatra, Priya Ranjan Sinha II-284 Maiti, Jhareswar II-517 Maitra, Sayantan II-65 Maity, Goutam Kr I-281, I-416 Maity, Mrinmoy I-230 Maity, Santi P I-217, I-240, I-322, I-382 Maity, Satyabrata II-371 Majumdar, Sabyasachi I-296 Majumder, Koushik I-253 Malakar, Samir II-599 Mandal, Ankita II-284 Mandal, Himadri I-416 Mandal, J.K I-485, II-475 Mandal, Jyotsna Kumar I-141 Mandal, Kunal Kumar I-552 Mandal, Sudhindu Bikash I-397 Manna, Suvojit II-65 Midya, Sadip I-253 MingKhwan, Anirach I-93 Mishra, B.K I-567 Mishra, Rabindra Kishore II-488 Mitra, Pabitra II-531 Mitra, Somosmita II-531 Mondal, Anindita Sarkar II-226 Mondal, Kartick Chandra II-226, II-242 Mondal, Ranjan Kumar II-256 Mondal, Sanjana I-161 Mondal, Tamal I-230 Mudi, Rajani K I-372 Mukherjee, Himadri I-129 Mukhopadhyay, Anirban II-504 Mukhopadhyay, Debarka II-75, II-85 Mukhopadhyay, Somnath II-475 Nandi, Enakshmi II-256 Nandy, S II-577 Narnoli, Harshita II-284 Nasipuri, Mita II-3, II-599 Author Index Naskar, Indrajıt II-567 Nath, Subhrapratim I-440 Nath, Ujjwal Manikya I-372 Obaidullah, Sk Md I-129 Om, Hari I-537 P., Mohana Chelvan I-582 Pal, A.K II-567 Pal, Bijay Baran II-423 Pal, Pabitra I-511 Pal, Somnath II-358 Panda, Manisha II-488 Panda, S.S II-411 Pandey, Manjusha I-103 Parekh, Ranjan II-184, II-197 Patil, Kiran Kumari I-335 Patnaik, L.M I-35 Paul, Anal I-382 Paul, Avijit Kumar II-121 Pensiri, Fuangfar II-271 Phadikar, Amit I-416 Phadikar, Santanu I-129, I-253 Phupittayathanakorn, Chayute II-271 Pradhan, Manoranjan I-363 Pramanik, Ankita I-322 Pramanik, Rahul II-297 Pramanik, Sabari II-440 Prasad, Abhimanyu II-3 Qiu, Xueheng I-22 Rai, Mehang II-168 Rakshit, Somnath II-65 Rato, Luis II-30 Rautaray, Siddharth Swarup I-103 Ray, Payel II-256 Ray, Sumanta II-347 Ray, Utpal Kumar I-495 Raychaudhuri, Amlan II-371 Roy, Asmita I-253 Roy, Jaydeep I-230 Roy, Kaushik I-129 Roy, Runu Banerjee I-407 Roy, Subhashis I-431 Saha, Indrajit II-30 Saha, Sourav II-284 Saha, Sovan II-3 Samaddar, Ankita II-358 Sandeep, Jayapalan I-193 Sanyal, Madhupa II-226 Sanyal, Manas Kumar II-256 Sarddar, Debabrata II-256 Sarkar, Anasua II-17 Sarkar, Anindita I-59 Sarkar, Kamal II-552 Sarkar, Ram II-599 Sarkar, Sagar II-108 Sarkar, Sobhan II-517 Sarkar, Subir Kumar I-431, I-440 Sarvamangala, D.R II-451 Seal, Arnab I-440 Sen, Jaydip I-161 Sengupta, Aritro I-495 Sengupta, Reshma I-453 Seth, Runa I-485 Setua, S.K II-440 Setua, Sanjit K I-266 Shakya, Ayush II-168 Sharma, Srishti I-84 Shenoy, Udaya Kumar K I-335 Sheth, Paras II-284 Si, Amalendu II-540 Sil, Jaya I-217, II-137 Sing, Jamuna Kanta II-323 Singh, Amit Prakash I-118 Sinha, Ranu I-150 Suganthan, P.N I-22 Suresh, Hima II-384 Thapa, Mahendra Singh II-168 Tiwari, Prayag II-398 Tripathi, Sudhakar II-57 Tripathy, Snigdha Subhadarshinee Tsang, Edward P.K I-45 Tudu, Bipan I-407 Tyagi, Vipin I-296 Umadevi, Murugesan I-193 Visutsak, Porawat Sabut, Sukanta II-411 Sachdev, Smriti I-296 Saha, Aditya II-212 Saha, Debasri I-397 Yadav, Kusum Zhu, Huilin I-93, II-271 I-103 I-22 I-363 631 ... http://www.springer.com/series/7899 J.K Mandal Paramartha Dutta Somnath Mukhopadhyay (Eds.) • Computational Intelligence, Communications, and Business Analytics First International Conference,... aspects of computational intelligence, communications, and business analytics, where by the scope was not only limited to various engineering disciplines, such as computer science, electronics, and. .. were organized and chaired by eminent professors The eight special sessions focused on computational intelligence, data science and advanced data analytics, signal processing and communications,