Sobhan Sarkar

Scopus Publications

FGI-CogViT: Fuzzy Granule-based Interpretable Cognitive Vision Transformer for Early Detection of Alzheimer’s Disease using MRI Scan Images
Anima Pramanik, Soumick Sarker, Sobhan Sarkar, Indranil Bose
Information Systems Frontiers, 2026
Developing a reintegration index (RI) for a closed-loop supply chain network in the automobile industry
Shisam Bhattacharyya, Bishal Dey Sarkar, Sobhan Sarkar, Prince Kumar Singh, Ramkrishna Manatkar
Benchmarking, 2026
PurposeContinuous benchmarking of a closed-loop supply chain (CLSC) network is required to achieve circular economic viability for end-of-life vehicle (ELV) recovery programs for original equipment manufacturers (OEMs). This study develops a framework to assess and benchmark CLSC networks in ELV recovery programs, addressing the absence of a standard index and enabling circular economic viability for OEMs.Design/methodology/approachThe study uses a Bayesian evidential reasoning approach (BERA) that helps decision-makers develop a reintegration index (RI) for the automobile CLSC network. To develop the index, a total of 15 factors related to the automobile CLSC are identified from the literature. Bayesian belief network (BBN) is used on those factors to generate conditional probabilities for different nodes of the BBN. With the opinion of 12 domain experts, the ERA is used to generate a score for each node. Finally, the Markovian tree is used on the scores to generate the RI for a particular CLSC network.FindingsThe analysis demonstrates that both operational and strategic actions aimed at ensuring customer satisfaction and retaining core components are quantified using a standardized index value for each alternative amidst uncertainty. Leveraging the BERA model, decision-makers can calculate RI values, providing them with the means to assess and regulate ratings for CLSC networks. This capability serves to bolster circular economic sustainability by facilitating informed decision-making within the automotive industry.Practical implicationsThis framework offers a structured approach for decision-makers to evaluate CLSC networks in ELV recovery programs, allowing for adaptability to specific organizational objectives and facilitating informed decision-making in the automotive industry.Originality/valueThe study’s integration of expert insights and probabilistic modeling fills the gap in the literature by providing a comprehensive framework for assessing CLSC networks in ELV recovery programs, contributing to circular economic viability and strategic decision-making for OEMs.
Soil Fertility Detection Using Reinforcement Learning-Based Recurrent Neural Network
Apurb Srivastava, Sobhan Sarkar, Chawki Djeddi
Lecture Notes in Networks and Systems, 2026
Eye-Tracking-Based Packaging Analysis for Toy Industry Using Bayesian Belief Networks and Evidential Reasoning Approach
Prachi Tulsyan, Amrita Ghosh, Sobhan Sarkar
Lecture Notes on Multidisciplinary Industrial Engineering, 2026
Toward Early Parkinson’s Disease Detection: A Novel RL-CNN-Based Approach
Apurb Srivastava, Sobhan Sarkar, Indranil Bose
Lecture Notes on Multidisciplinary Industrial Engineering, 2026
Social Media Sentiment Analysis of Impacts of COVID-19 on Mothers and Children
Abhishek Kumar, Amrita, Sobhan Sarkar
Lecture Notes on Multidisciplinary Industrial Engineering, 2026
Alzheimer’s Disease Detection Using Gaussian–Bayesian Parameter Optimization-Based Deep Convolution Neural Network
Ansh Varshney, Ishita Luharuka, Sobhan Sarkar, Indranil Bose
Lecture Notes on Multidisciplinary Industrial Engineering, 2026
Enhancing cybersecurity risk assessment using temporal knowledge graph-based explainable decision support system
Subhajit Bag, Sobhan Sarkar, Indranil Bose
Decision Support Systems, 2025
Real-time detection of coke particles in blast furnace operations using machine learning: Case of a steel plant in India
Meenakshi Sabharwal, Harsh Meena, Sobhan Sarkar, Meenu Damani, Neelima Sharma
Ironmaking and Steelmaking, 2025
The efficiency of blast furnace operations in a steel plant relies on the quality of raw materials, including coke. The particle size distribution (PSD) of coke plays a vital role in ensuring the efficiency of the blast furnace. Conventional methods of measuring average particle size are time-consuming and labour-intensive leading to delayed operations. To address the issue, various studies have used different techniques for real-time measurement of coke particle size, including laser diffraction, acoustic sounding, X-ray computed tomography, and computer vision. While these methods have shown successful applications, there have been limitations in their lower prediction accuracy and detection speed. Therefore, our study proposes a practical approach that leverages the integration of computer vision algorithms to enhance accuracy and detection speed. The proposed methodology is compared with the conventional method of measuring particle size in the lab at a blast furnace. Our results reveal that the YOLOv8 algorithm outperforms the conventional method, providing efficient detection of 5.419 frames per second and with a mean absolute error of [Formula: see text]1.77 mm within the lab results. YOLOv8 can perform object segmentation providing much more precise polygon masks of the coke particles instead of simply providing rectangular dimensions using traditional object detection, as explored in previous studies. This approach enables real-time monitoring of PSD and timely alerts to the onsite team, significantly improving the efficiency of blast furnace operations.
Generative artificial intelligence for management education: applications, benefits, challenges and future research directions
Sreevatsa Bellary, Sobhan Sarkar, Arindra Nath Mishra
International Journal of Educational Management, 2025
Purpose Generative artificial intelligence (GenAI) has received significant traction in recent years for its ability to generate content based on human inputs. The aim of this study is to examine the existing literature on GenAI in management education by conducting a combination of bibliometric analysis and systematic literature review and provide future research directions, which can help management educators to train management students who are potential future managers. Design/methodology/approach Utilizing a total of 141 articles obtained from multiple databases, this study conducts a systematic literature review and synthesizes the existing literature on GenAI across management functions and industries. Further, this study provides future research directions specific to each group that will help in the advancement of context-specific management education. Findings The study synthesized the applications, benefits, challenges and future research directions of GenAI across different management domains, including marketing, finance and accounting, operations and human resource management. Overall, the study found that GenAI can promote academic performance enhancement, personalized learning, programming skills development, improved student motivation and effective learning. Originality/value The study provides an avenue for management education teachers to train their students in multiple management domains to get a comprehensive idea about the current work on GenAI in that particular domain, using which they can proceed to work in the domain. For management students who are potential emerging managers, the results of the study provide a comprehensive overview of the applications of GenAI across various management verticals, which provides a basis for benchmarking against the applications of GenAI.
Real-time fall detection on roads using transfer learning-based granulated Bi-LSTM
Anima Pramanik, Soumick Sarker, Sobhan Sarkar, Sankar K. Pal
Knowledge Based Systems, 2025
Thematic Exploration and Analysis of Cybersecurity Policies of Businesses: An NLP-Based Approach
Abhik Chaudhuri, Sobhan Sarkar, Pradip Kumar Bala
Journal of Organizational Computing and Electronic Commerce, 2025
Scalable Multimodal Misinformation Detection Across Social Media Platforms
Sakshi Singh, Siddhi Khandelwal, Sobhan Sarkar
2025 20th International Joint Symposium on Artificial Intelligence and Natural Language Processing Isai Nlp 2025, 2025
Lightweight Deepfake Detection for Real-World Augmented Images in Social Media
Aryan Kashyap, Mehak, Sobhan Sarkar, Anima Pramanik
2025 20th International Joint Symposium on Artificial Intelligence and Natural Language Processing Isai Nlp 2025, 2025
Influence of leader humility on subordinates’ knowledge-sharing: exploring the boundary conditions
Shivam Upadhyay, Pankaj Singh, Piyali Ghosh, Sobhan Sarkar
Journal of Knowledge Management, 2025
News Media Mining to Explore Speed-Crash-Traffic Association During COVID-19
Subasish Das, Sobhan Sarkar
Transportation Research Record, 2024
A Z-Number Slacks-Based Measure DEA model-based framework for sustainable supplier selection with imprecise information
Sobhan Sarkar, Arup Ratan Paramanik, Biswajit Mahanty
Journal of Cleaner Production, 2024
Risk Modeling Framework for Strategic and Operational Intervention to Enhance the Effectiveness of a Closed-Loop Supply Chain
Shisam Bhattacharyya, Sobhan Sarkar, Bishal Dey Sarkar, Ramkrishna Manatkar
IEEE Transactions on Engineering Management, 2024
NovaNet: A Novel Method for Enhanced Pothole Detection on Road
Soumick Sarker, Abhinav Thakur, Suswan Saha, Sobhan Sarkar
2024 8th International Conference on System Reliability and Safety Icsrs 2024, 2024
Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises
Prasanta Kumar Dey, Soumyadeb Chowdhury, Amelie Abadie, Emilia Vann Yaroson, Sobhan Sarkar
International Journal of Production Research, 2024
Video surveillance-based fall detection system using object-level feature thresholding and Z−numbers
Anima Pramanik, Sobhan Sarkar, Sankar K. Pal
Knowledge Based Systems, 2023
SENE: A novel manifold learning approach for distracted driving analysis with spatio-temporal and driver praxeological features
Subhajit Bag, Rahul Golder, Sobhan Sarkar, Saptashwa Maity
Engineering Applications of Artificial Intelligence, 2023
A two-stage improved Base Point Slacks-Based Measure of super-efficiency for negative data handling
Arup Ratan Paramanik, Sobhan Sarkar, Bijan Sarkar
Computers and Operations Research, 2023
Quantifying data imbalance using Exponential f-Divergence
Sobhan Sarkar, Anima Pramanik
8th International Conference on Digital Arts Media and Technology and 6th Ecti Northern Section Conference on Electrical Electronics Computer and Telecommunications Engineering Ecti Damt and Ncon 2023, 2023
Impact of operating speed measures on traffic crashes: Annual and daily level models for rural two-lane and rural multilane roadways
Subasish Das, Eun Sug Park, Sobhan Sarkar
Journal of Transportation Safety and Security, 2023
An integrated approach using rough set theory, ANFIS, and Z-number in occupational risk prediction
Sobhan Sarkar, Anima Pramanik, J. Maiti
Engineering Applications of Artificial Intelligence, 2023
A Two-phase Approach to Determine User-Preference and Feature Importance in Pricing of Cryptocurrencies using Twitter Data
Saptashwa Maity, Soujatya Khan, Sobhan Sarkar
Proceedings 2023 IEEE International Conference on E Business Engineering Icebe 2023, 2023
Correction to: An integrated approach using growing self-organizing map-based genetic K-means clustering and tolerance rough set in occupational risk analysis (Neural Computing and Applications, (2022), 34, 12, (9661-9687), 10.1007/s00521-022-06956-5)
Sobhan Sarkar, Numan Ejaz, J. Maiti, Anima Pramanik
Neural Computing and Applications, 2022
Classification and pattern extraction of incidents: a deep learning-based approach
Sobhan Sarkar, Sammangi Vinay, Chawki Djeddi, J. Maiti
Neural Computing and Applications, 2022
OSWMI: An objective-subjective weighted method for minimizing inconsistency in multi-criteria decision making
Arup Ratan Paramanik, Sobhan Sarkar, Bijan Sarkar
Computers and Industrial Engineering, 2022
An integrated approach using growing self-organizing map-based genetic K-means clustering and tolerance rough set in occupational risk analysis
Sobhan Sarkar, Numan Ejaz, J. Maiti, Anima Pramanik
Neural Computing and Applications, 2022
Parametric and Non-Parametric Analyses for Pedestrian Crash Severity Prediction in Great Britain
Maria Rella Riccardi, Filomena Mauriello, Sobhan Sarkar, Francesco Galante, Antonella Scarano, Alfonso Montella
Sustainability Switzerland, 2022
Unsupervised and Categorical Sentiment Segmentation of Customer Product Reviews
Aditya Kumar Singh, Rahul Golder, Sobhan Sarkar
2022 International Conference on Data Analytics for Business and Industry Icdabi 2022, 2022
Handling sparsity and seasonality problems simultaneously in session-based recommender systems using graph collaborative filtering
Subhajit Bag, Anmol Kumar, Sobhan Sarkar
2022 International Conference on Data Analytics for Business and Industry Icdabi 2022, 2022
Crash severity analysis in distracted driving using unlabeled and imbalanced data: A novel approach using Robust Two-Phase Ensemble Predictor
Subhajit Bag, Saptashwa Maity, Sobhan Sarkar
2022 International Conference on Data Analytics for Business and Industry Icdabi 2022, 2022
Identifying spammer groups in consumer reviews using meta-data via bipartite graph approach
Varun Balakrishna, Subhajit Bag, Sobhan Sarkar
2022 International Conference on Data Analytics for Business and Industry Icdabi 2022, 2022
G-AUC: An improved metric for classification model selection
Shashank Sadafule, Sobhan Sarkar, Shaomin Wu
Icsec 2022 International Computer Science and Engineering Conference 2022, 2022
Implementation of a Priority Queue to Optimize Resources during Manual Verification of Fake News
Piran Karkaria, Rahul Golder, Sobhan Sarkar
2022 International Conference on Data Analytics for Business and Industry Icdabi 2022, 2022
Deep Network-based Slow Feature Analysis for Human Fall Detection
Anima Pramanik, Kavya Venkatagiri, Sobhan Sarkar, Sankar K. Pal
Proceedings 2022 International Conference on Computational Modelling Simulation and Optimization Iccmso 2022, 2022
Real-Time Detection of Traffic Anomalies Near Roundabouts
Anima Pramanik, Sobhan Sarkar, Chawki Djeddi, J. Maiti
Communications in Computer and Information Science, 2022
A Novel Optimized Method for Feature Selection Using Non-linear Kernel-Free Twin Quadratic Surface Support Vector Machine
Saptashwa Maity, Arjav Rastogi, Chawki Djeddi, Sobhan Sarkar, J. Maiti
Communications in Computer and Information Science, 2022
COVID-19 outbreak: A data-driven optimization model for allocation of patients
Sobhan Sarkar, Anima Pramanik, J. Maiti, Genserik Reniers
Computers and Industrial Engineering, 2021
RT-GSOM: Rough tolerance growing self-organizing map
Anima Pramanik, Sobhan Sarkar, J. Maiti, Pabitra Mitra
Information Sciences, 2021
A real-time video surveillance system for traffic pre-events detection
Anima Pramanik, Sobhan Sarkar, J. Maiti
Accident Analysis and Prevention, 2021
Personality Traits Identification Through Handwriting Analysis
Tahar Mekhaznia, Chawki Djeddi, Sobhan Sarkar
Communications in Computer and Information Science, 2021
Text Mining-Based Association Rule Mining for Incident Analysis: A Case Study of a Steel Plant in India
Sobhan Sarkar, Sammangi Vinay, Chawki Djeddi, J. Maiti
Communications in Computer and Information Science, 2021
A kernel-free support vector machine with Q-margin
Smarak Pradhan, Sagar Kumar, Sobhan Sarkar, J. Maiti
2021 International Conference on Data Analytics for Business and Industry Icdabi 2021, 2021
DiPSVM: A Polynomial Kernel-free Support Vector Machine
Soumadip Saha, Meghashrita Das, Baishali Sow Mondal, Sobhan Sarkar, J. Maiti
2021 International Conference on Data Analytics for Business and Industry Icdabi 2021, 2021
Semi-automated Ontology Creation and Upgradation for Rail-Road Incidents: A Case of a Steel Plant in India
Anima Pramanik, Sobhan Sarkar, V. Sai Siddharth, J. Maiti, Pabitra Mitra
Lecture Notes in Networks and Systems, 2021
Machine learning in occupational accident analysis: A review using science mapping approach with citation network analysis
Sobhan Sarkar, J. Maiti
Safety Science, 2020
Region proposal and object detection using HoG-based CNN feature map
Anima Pramanik, Harshvardhan, Chawki Djeddi, Sobhan Sarkar, J Maiti
2020 International Conference on Data Analytics for Business and Industry Way Towards A Sustainable Economy Icdabi 2020, 2020
Predicting and analyzing injury severity: A machine learning-based approach using class-imbalanced proactive and reactive data
Sobhan Sarkar, Anima Pramanik, J. Maiti, Genserik Reniers
Safety Science, 2020
An Investigation of the Effects of Missing Data Handling Using ‘R’-Packages
Sobhan Sarkar, Anima Pramanik, Nikhil Khatedi, J. Maiti
Advances in Intelligent Systems and Computing, 2020
Pattern Extraction Using Proactive and Reactive Data: A Case Study of Contractors’ Safety in a Steel Plant
Sobhan Sarkar, Numan Ejaz, C. S. Promod, J. Maiti
Lecture Notes in Electrical Engineering, 2020
An Ensemble Learning-Based Undersampling Technique for Handling Class-Imbalance Problem
Sobhan Sarkar, Nikhil Khatedi, Anima Pramanik, J. Maiti
Lecture Notes in Electrical Engineering, 2020
Root Cause Analysis of Incidents Using Text Clustering and Classification Algorithms
Sobhan Sarkar, Numan Ejaz, Mehul Kumar, J. Maiti
Lecture Notes in Electrical Engineering, 2020
GSEL: A Genetic Stacking-Based Ensemble Learning Approach for Incident Classification
Sobhan Sarkar, Anima Pramanik, Nikhil Khatedi, A. S. M. Balu, J. Maiti
Lecture Notes in Electrical Engineering, 2020
A Structural Topic Modeling-Based Machine Learning Approach for Pattern Extraction from Accident Data
Sobhan Sarkar, Suvo Gaine, Aditya Deshmukh, Nikhil Khatedi, J. Maiti
Advances in Intelligent Systems and Computing, 2020
An optimization-based decision tree approach for predicting slip-trip-fall accidents at work
Sobhan Sarkar, Rahul Raj, Sammangi Vinay, J. Maiti, Dilip Kumar Pratihar
Safety Science, 2019
Application of optimized machine learning techniques for prediction of occupational accidents
Sobhan Sarkar, Sammangi Vinay, Rahul Raj, J. Maiti, Pabitra Mitra
Computers and Operations Research, 2019
Oil spill detection using image processing technique: An occupational safety perspective of a steel plant
Anima Pramanik, Sobhan Sarkar, J. Maiti
Advances in Intelligent Systems and Computing, 2019
Decision support system for prediction of occupational accident: A case study from a steel plant
Sobhan Sarkar, Mainak Chain, Sohit Nayak, J. Maiti
Advances in Intelligent Systems and Computing, 2019
A novel feature extraction-based human identification approach using 2D ear biometric
Anima Pramanik, Apurba Gorai, Sobhan Sarkar, Phalguni Gupta
Proceedings of 2018 IEEE Applied Signal Processing Conference Aspcon 2018, 2018
Text-clustering based deep neural network for prediction of occupational accident risk: A case study
Sobhan Sarkar, Vaibhav Lodhi, J. Maiti
2018 International Joint Symposium on Artificial Intelligence and Natural Language Processing Isai Nlp 2018 Proceedings, 2018
Application of hybrid clustering technique for pattern extraction of accident at work: A case study of a steel industry
Sobhan Sarkar, Numan Ejaz, J. Maiti
Proceedings of the 4th IEEE International Conference on Recent Advances in Information Technology Rait 2018, 2018
An integrated fuzzy multiple criteria supplier selection approach and its application in a welding company
Sobhan Sarkar, Dilip Kumar Pratihar, Bijan Sarkar
Journal of Manufacturing Systems, 2018
Application of rough set theory in accident analysis at work: A case study
Sobhan Sarkar, Soumyadeep Baidya, J Maiti
Proceedings 2017 3rd IEEE International Conference on Research in Computational Intelligence and Communication Networks Icrcicn 2017, 2017
Application of Bayesian network model in explaining occupational accidents in a steel industry
Sobhan Sarkar, Anindra Kumar, Sunil Kumar Mohanpuria, J Maiti
Proceedings 2017 3rd IEEE International Conference on Research in Computational Intelligence and Communication Networks Icrcicn 2017, 2017
Predictive model for incident occurrences in steel plant in India
Sobhan Sarkar, Vishal Pateshwari, J Maiti
8th International Conference on Computing Communications and Networking Technologies Icccnt 2017, 2017
Segmented point process models for work system safety analysis
Saurabh Gautam, J. Maiti, A. Syamsundar, Sobhan Sarkar
Safety Science, 2017
Study of optimized SVM for incident prediction of a steel plant in India
Sobhan Sarkar, Sammangi Vinay, Vishal Pateshwari, Jhareswar Maiti
2016 IEEE Annual India Conference Indicon 2016, 2017
Prediction of occupational accidents using decision tree approach
Sobhan Sarkar, Atul Patel, Sarthak Madaan, Jhareswar Maiti
2016 IEEE Annual India Conference Indicon 2016, 2017
Modelling safety of gantry crane operations using Petri nets
Karmveer Singh, Navneet Raj, S.K. Sahu, R.K. Behera, Sobhan Sarkar, J. Maiti
International Journal of Injury Control and Safety Promotion, 2017
Genetic algorithm-based association rule mining approach towards rule generation of occupational accidents
Sobhan Sarkar, Ankit Lohani, Jhareswar Maiti
Communications in Computer and Information Science, 2017
Supplier selection in uncertain environment: A fuzzy MCDM approach
Sobhan Sarkar, Vishal Lakha, Irshad Ansari, Jhareswar Maiti
Advances in Intelligent Systems and Computing, 2017
Text mining based safety risk assessment and prediction of occupational accidents in a steel plant
Sobhan Sarkar, Sammangi Vinay, Jhareswar Maiti
2016 International Conference on Computational Techniques in Information and Communication Technologies Icctict 2016 Proceedings, 2016
Measurement and modeling of job stress of electric overhead traveling crane operators
Obilisetty B. Krishna, Jhareswar Maiti, Pradip K. Ray, Biswajit Samanta, Saptarshi Mandal, Sobhan Sarkar
Safety and Health at Work, 2015

Sobhan Sarkar

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