Journals/conferences/chapters

Publications in SCI indexed Journals
  1. Pandey, A. K and Roy S.S(2024), “Extractive Question Answering over Ancient scriptures Texts using Generative AI and Natural Language Processing Techniques,” in IEEE Access, doi: 10.1109/ACCESS.2024.3431282.(Impact Factor :3.9)
  1. Ramesh, H., Shariaty, F., & Roy, S. S. (2024, July). IFDRF: Advancing anomaly detection with a hybrid machine learning model. Optical Memory and Neural Network. Springer,(accepted).( Impact Factor 1)..
  2. Pandey, A. K and Roy S.S (2024), CANBLWO: A Novel Hybrid Approach for Semantic Text Generation , International Arab Journal of Information Technology, (accepted). (Impact factor 1).
  3. Kumar, P., Samui, P., Armaghani, D. J., & Roy, S. S. (2024). Second-Order Reliability Analysis of an Energy Pile with CPT Data. Journal of Building Engineering, 110165.(Impact factor 6.7)
  4. Turki, T.,Taguchi, YH and Roy, S. S. (2023). Optimized Tensor Decomposition and PCA Outperforming State-of-the- Art Methods When Analyzing Histone Modification ChIP-seq Profiles, Algorithms, MDPI(accepted, SCI IF : 2.3).
  5. Pandey, A.K., Roy, S.S (2023) Natural Language Generation Using Sequential Models: A Survey. Neural Process Letter, 1-34, https://doi.org/10.1007/s11063-023-11281-6.
    (SCI Impact factor: 3.1)
  6. Shukla, A., Das, T. K., & Roy, S. S. (2023). TRX Cryptocurrency Profit and Transaction Success Rate Prediction Using Whale Optimization-Based Ensemble Learning Framework. Mathematics, MDPI 11(11), 2415. (SCI IF : 2.4), https://doi.org/10.3390/math11112415
  7. Roy, S. S., Roy A., Gandoni, M, Samui, P and Gandoni A(2023). Hateful Sentiment Detection in Real-time Tweets: An LSTM-Based Comparative Approach, IEEE Transactions on Computational Social Systems, DOI: 10.1109/TCSS.2023.3260217., [SCI IF: 4.74]
  8. Samui, P., Yesilyurt, S. N., Dalkilic, H. Y., Yaseen, Z. M., Roy, S. S., & Kumar, S. (2023). Comparison of different optimized machine learning algorithms for daily river flow forecasting. Earth Science Informatics, 16(1), 533-548.[SCI IF: 2.4], DOI: 10.1007/s12145-022-00896-3
  9. Roy, S. S., Awad, A. I., Amare, L. A., Erkihun, M. T., & Anas, M. (2022). Multimodel Phishing URL Detection Using LSTM, Bidirectional LSTM, and GRU Models. Future Internet, 14(11), 340. [SCI IF: 0.23], https://doi.org/10.3390/fi14110340
  10. Roy S S, Hsu C h, Samaran A, Goyal R, Pande A, Balas V E(2022) Vessels Segmentation in Angiograms Using Convolutional Neural Network: A Deep Learning Based Approach, Computer Modeling in Engineering & Sciences, volume 136, issue 1,P241-255, ISSN:1526-1492[SCI IF: 2.02]
  11. Chakraborty, C., Bhattacharya, M., Sharma, A. R., Roy, S. S., Islam, M. A., Chakraborty, S & Dhama, K. (2022). Deep learning research should be encouraged for diagnosis and treatment of antibiotic resistance of microbial infections in treatment associated emergencies in hospitals. International Journal of Surgery, 106857. [SCI IF: 13], DOI: 10.1016/j.ijsu.2022.106857
  12. Chakraborty C, Bhattacharya M, Dhama K, Roy S S, Sharma A R, Ranjan K. Mohapatra R K, Lee S S(2022) , Deep learning research should be encouraged more and more in different domains of surgery: An open call – Correspondence, International Journal of Surgery, Volume 104, 2022, 106749, ISSN 1743-9191, https://doi.org/10.1016/j.ijsu.2022.106749. [SCI IF: 13]
  13. Turki, T., & Roy, S. S. (2022). Novel Hate Speech Detection Using Word Cloud Visualization and Ensemble Learning Coupled with Count Vectorizer. Applied Sciences, 12(13), p1-13.[SCI IF: 2.8], https://doi.org/10.3390/app12136611
  14. Roy, S. S., Mihalache, S. F., Pricop, E., & Rodrigues, N. (2022). Deep convolutional neural network for environmental sound classification via dilation. Journal of Intelligent & Fuzzy Systems, 1-7. ISSN 1064- 1246 ,(SCI IF : 2), https://doi.org/10.3233/JIFS-219283
  15. Roy, S. S., Goti, V., Sood, A., Roy, H., Gavrila, T., Floroian, D. & Mohammadi-Ivatloo, B. (2022). L2 regularized deep convolutional neural networks for fire detection. Journal of Intelligent & Fuzzy Systems, 1-12, p1827-1833 (SCI IF : 2)
  16. Moradzadeh, A., Mohammadi-Ivatloo, B., Abapour, M., Anvari-Moghaddam, A., & Roy, S. S. (2021). Heating and Cooling Loads Forecasting for Residential Buildings Based on Hybrid Machine Learning Applications: A Comprehensive Review and Comparative Analysis. IEEE Access.p 2196 – 2215, ISSN 2169-3536[SCI IF : 3.4], DOI:10.1109/ACCESS.2021.3136091
  17. Bose, A., Hsu, C. H., Roy, S. S., Lee, K. C., Mohammadi-ivatloo, B., & Abimannan, S. (2021). Forecasting stock price by hybrid model of cascading Multivariate Adaptive Regression Splines and Deep Neural Network. Computers & Electrical Engineering, 95, 107405. [SCI IF 4.1], DOI:10.1016/j.compeleceng.2021.107405
  18. Roy, S.S., Taguchi, YH. Identification of genes associated with altered gene expression and m6A profiles during hypoxia using tensor decomposition based unsupervised feature extraction. Sci Rep 11, 8909 (2021). https://doi.org/10.1038/s41598-021-87779- [SCI IF 4.3].
  19. Roy SS, Rodrigues N, Taguchi Y-h. Incremental Dilations Using CNN for Brain Tumor Classification. Applied Sciences. 2020; 10(14):4915. https://doi.org/10.3390/app10144915 [SC IIF: 2.8]
  20. Roy S S, Balas Valentina E, Popa M, Ramona Lile, Ishan Nagtode (2020) Prediction of Air-Pollutant Concentrations using Hybrid Model of Regression and Genetic Algorithm, Journal of Intelligent & Fuzzy Systems,IOS Press(SCI IF : 1.7), ISSN 1064- 1246. vol. 38, no. 5, pp. 5909-5919, 2020, [SCI & Scopus].
  21. Biswas R, Vasan A and Roy S S* (2019) Dilated Deep Neural Network for Segmentation of Retinal Blood Vessels in Fundus Images, Iranian Journal of Science and Technology, Transactions of Electrical Engineering, ISSN: 2228-6179,(SCI IF : 0.6), pp 1-14. [SCI & Scopus]. https://doi.org/10.1007/s40998-019-00213-7
  22. Roy S S*, Sikaria R and Susan A(2019) A deep learning based CNN approach on MRI for Alzheimer’s disease detection, IOS PRESS , ISSN872-4981. [ESCI & Scopus], DOI 10.3233/IDT-190005
  23. Roy S S*, Samui P, Nagtode I , Jain H, and Shivaramakrishnan V, Mohammadi-ivatloo B(2019) Forecasting Heating and Cooling Loads of Buildings: A Comparative Performance Analysis, Journal of Ambient Intelligence and Humanized Computing(SCI IF 1.9),11(3) ISSN: 1868-5145.pp. 1-12. [SCI & Scopus].
  24. Roy S S*, Chopra R, Lee K C, Spampinato C, Mohammadi-ivatloo B (2019) Random Forest, Gradient Boosted Machines and Deep Neural Network for Stock Price Forecasting: A Comparative Analysis on South Korean Companies, International Journal of Ad Hoc and Ubiquitous Computing (SCI IF 0.7) , Vol. 33, No. 1, 2020, ISSN 1743-8233. [SCI & Scopus].
  25. Roy SS*, Reetika Roy,Valentina Balas (2017), Estimating Heating Load in Buildings using Multivariate Adaptive Regression Splines, Extreme Learning Machine, a Hybrid Model of MARS and ELM, Renewable and Sustainable Energy Review, Elsevier, IF=16.70,Volume 82, Part 3, February 2018, Pages 4256-4268, DOI 10.1016/j.rser.2017.05.249, ISSN: 1364-0321. [Scopus].
  26. Samui P, Kim D; Jagan J;Roy S S(2018) Determination of uplift capacity of suction caisson using Gaussian Process Regression, Minimax Probability Machine Regression and Extreme Learning Machine, Iranian Journal of Science and Technology, Transactions of Civil Engineering (SCI IF 0.8), Volume 40,pp.1-7, ISSN: 2228-6160. [SCI & Scopus].
  27. Chakraborty C,Roy SS,Agoramoorthy G (2013) Transcription Factors of Nuclear Reprogramming and Network Analysis of Induced Pluripotent Stem (iPS) Cell using Bioinformatics, International Journal of Fertility and Sterility (SCI IF=0.4),ISSN : 2008- 0778. [SCI & Scopus].
  28. Chakraborty C, Roy SS, Hsu M J, A Govindasamy(2012) Can computational biology improve the phylogenetic analysis of insulin? Computer Methods and Programs in Biomedicine, 108(2), pp.860-872, ISSN 0169-2607, Elsevier (SCI-IF 1.2). [SCI & Scopus].
  29. Roy SS, Hsu CH, Wen ZH, Lin CS, Chakraborty C (2010) A hypothetical relationship between the nuclear reprogramming factors for induced pluripotent stem (iPS) cells generation- bioinformatics and algorithmic approach. Medical Hypotheses, Elsevier, Vol 76 (2011), pp.507-511(SCI IF 1.6),ISSN:0306-9877. [SCI & Scopus].
  30. Roy SS, Hsu CH, Wen ZH, Lin CS, Chakraborty C (2010) Understanding hematopoietic stem cell mobility pattern through mathematics.Rivista Di Biologia / Biology Forum(SCI IF 0.5), ISSN:0035-6050. [SCI & Scopus].
  31. Chakraborty C, Roy SS, Hsu CH, Wen ZH, Lin CS. (2010) Network building of proteins in a biochemical pathway: a computational biology related model for target discovery and drug- design, Current Bioinformatics 5(4): 290-295 (SCI-IF 1.7), ISSN : 1574-8936. [SCI & Scopus].

Publications in scopus indexed journals

  1. Samui, P., Palsapure, A., & Roy, S. S. (2023). Reliability analysis of shallow foundation based on settlement criteria. International Journal of Advanced Intelligence Paradigms, 24(3-4), 369-379. ISNN : 17550386
  2. Biswas, R., Rai, B., Samui, P., & Roy, S. S. (2020). Estimating Concrete Compressive Strength Using MARS, LSSVM and GP. Engineering Journal, 24(2), 41-52, DOI: https://doi.org/10.4186/ej.2020.24.2.41.
  3. Roy S S*, Singh P, Manuja G, Raghav S and Parekh M (2019) Prediction of Airfoil Self- Noise using Polynomial Regression, Multivariate Adaptive Regression Splines, Gradient Boosting Technique and Deep Learning Technique, International Journal of Advanced Intelligence Paradigms, InPress, ISSN: 1755-0394, [Scopus].
    .
  4. Roy S S*,Chakraborty,P V Krishna,Abraham(2017) Predicting and Analyzing Breast Cancer tumors by adopting Hybrid Neuro Fuzzy approach, International Journal of Functional Informatics and Personalised Medicine, ISSN : 1756-2112, Inderscience. [Scopus].
  5. Samui P,Palsapure A, Roy S S* (2023)Reliability Analysis Of Shallow Foundation Based On Settlement Criteria, International Journal of Advanced Intelligence Paradigms, Inderscience, 10.1504/IJAIP.2023.129184, Vol.24 No.3/4, pp.369 – 379 ,ISSN: 1755-0394, [Scopus].
  6. Roy SS*, Samui P (2021) Predicting longitudinal dispersion coefficient in natural streams using Minimax Probability Machine Regression and Multivariate Adaptive Regression Spline, International Journal of Advanced Intelligence Paradigms. Inderscience, https://doi.org/10.1504/IJAIP.2021.115244, Vol 19, No 2, ISSN: 1755-0394, [Scopus].
  7. Pijush S, Kumar R,Kumari S and Roy SS(2018) Determination of Reliability Index of Cantilever Retaining Wall by RVM, MPMR and MARS, International Journal of Advanced Intelligence Paradigms. Inderscience , ISSN: 1755-0394, [Scopus].
  8. Roy S*S,Madhu Viswanatham(2016),Classifying Spam emails using artificial intelligent techniques,International Journal of Engineering Research in Africa(JERA), Vol. 22, pp. 152-161, ISSN No 1663-4144.[Scopus].
  9. Roy SS*; Madhu,V Viswanatham;Krishna,P.V(2017), An Ensemble Design approach based on Bagging Technique for filtering Email SPAM,International Journal of Autonomous and Adaptive Communications Systems,Inderscience, Vol.10, No.3, 247-260 SCOPUS- indexed,ISSN No 1754-8640. [Scopus].

Roy SS*; Madhu V Viswanatham, P Venkata Krishn,(2016) Spam detection using hybrid model of rough set and Decorate Ensemble, International Journal of Computational Systems Engineering,Inderscience,Vol 2,No.3,2016, ISSN No 2046-3405.

  1. Rohit Ramesh,Roy SS*,Anvesha Sinha(2013) Applicability of rough set theory for analysis of phishing threats, Anale. Seria Informatic. Vol. XI fasc. 2.
  2. Roy SS*, V Madhu Viswanatham, P Venkata Krishna,(2012) Intrusion Detection Data Analysis Using Dominance Based Rough Set , Annals. Computer Science Series, 10th vol, issue 1.
  3. Roy SS (2010) Probability method of reliability for cooperative neural network (2010), Annals. Computer Science Series, 8th vol, issue 2. ISSN:1930-2940.

Book Chapters

  1. Ghoshal, N., Anas, M., & Roy, S. S. (2023). Chest X-Ray Image Classification of Pneumonia Disease Using EfficientNet and InceptionV3. In Deep Learning Applications in Image Analysis (pp. 173-186). Singapore: Springer Nature Singapore.
  2. Anas, M., Roy, S. S., Srivastava, K. S., & Chakraborty, J. (2023). Plant Diseases Classification Using Neural Network: AlexNet. In Deep Learning Applications in Image Analysis (pp. 133-147). Singapore: Springer Nature Singapore.
  3. Khoria V, Singh A, and Roy S S(2021) Leukaemia Classification using Machine Learning and Genomics, Handbook of machine learning applications for genomics,Springer,2020-21(Accepted).
  4. Panday A and Roy S S(2021) Protein sequence classification using Convolutional Neural Network and Natural Language Processing, Handbook of machine learning applications for genomics,Springer,2020-21(Accepted).
  5. Mitra, S., Roy, S. S., & Srinivasan, K. (2021). Classifying CT scan images based on contrast material and age of a person: ConvNets approach. In Data Analytics in Biomedical Engineering and Healthcare (pp. 105-118). Academic Press.
  6. Wadhwa, A., & Roy, S. S. (2021). Driver drowsiness detection using heart rate and behavior methods: A study. Data Analytics in Biomedical Engineering and Healthcare, 163-177.
  7. Bose A, Roy S S, Balas V, Pijush P(2019),Deep Learning for Brain Computer Interfaces, Handbook of Deep Learning Applications, Smart Innovation, Systems and Technologies Publisher, Springer Nature Switzerland AG.[ Scopus]
  8. Roy S S, Pulkit Kulshrestha and Pijush Samui(2016). Classifying Images of drought affected area using Deep Belief Network,kNN and Random Forest Learning Techniques., Deep Learning Innovations and their Convergence with Big Data, IGI-GLOBAL, 10.4018/978-1-5225-3015-2.ch006. [ Scopus]
  9. Samui P, Roy S S, Kurup P and Dalkiliç Y(2016) Modeling of seismic liquefaction data using extreme learning machine, Earthquakes: Monitoring Technology, Disaster Management and Impact Assessment, NovaPublishers(published).
  10. Roy S S, Biba M,Kumar R,Kumar R,Samui P(2016) A New SVM Method for Recognizing Polarity of Sentiments in Twitter, in “Web Data Mining and the Development of Knowledge-Based Decision Support Systems”,” Handbook of Research on Soft Computing and Nature-Inspired Algorithms”, IGI-GLOBAL, BOOK Chapter(published)”,2017. DOI: 10.4018/978-1-5225-2128-0.ch009. [ Scopus].International Conference Publications (peer reviewed& scopus indexed)

Conferences

  1. Pandey A K, Roy S S(2023). Attention-Based Bidirectional Lstm Model For Data To Text Generation. International conference on Advances in Computational Intelligence and its Applications (ICACIA) (accepted).
  2. Roy, S. S., Ranjan, A., & Tomasiello, S. (2021). Link prediction in social networks by variational graph autoencoder and similarity-based methods: A brief comparative analysis. In Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings, Part IV (pp. 422-429). Springer International Publishing.
  3. Khandelwal, P., Srinivasan, K., & Roy, S. S. (2019, May). Surgical education using artificial intelligence, augmented reality and machine learning: A review. In 2019 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW) (pp. 1-2). IEEE.
  4. Chopra, R., & Roy, S. S. (2020). End-to-end reinforcement learning for self-driving car.
    In Advanced Computing and Intelligent Engineering: Proceedings of ICACIE 2018,
    Volume 1 (pp. 53-61). Springer Singapore.
  5. Bondhu A, Roy S S (2017), Classifying multi-category images using Deep Learning: A Convolutional Neural Network Model, 2017 2nd IEEE International conference on recent trends in electronics, information & communication technology, SBN: 978-1-5090- 37049.
  6. Roy, S. S., Kaul, D., Roy, R., Barna, C., Mehta, S., & Misra, A. (2018). Prediction of customer satisfaction using naive bayes, multiclass classifier, k-star and ibk. In Soft Computing Applications: Proceedings of the 7th International Workshop Soft Computing Applications (SOFA 2016), Volume 2 7 (pp. 153-161). Springer International Publishing.
  7. Roy, S. S., Pratyush, C., & Barna, C. (2018). Predicting ozone layer concentration using multivariate adaptive regression splines, random forest and classification and regression tree. In Soft Computing Applications: Proceedings of the 7th International Workshop Soft Computing Applications (SOFA 2016), Volume 2 7 (pp. 140-152). Springer International Publishing.
  8. Roy, S. S., Sinha, A., Roy, R., Barna, C., & Samui, P. (2018). Spam email detection using deep support vector machine, support vector machine and artificial neural network. In Soft Computing Applications: Proceedings of the 7th International Workshop Soft Computing Applications (SOFA 2016), Volume 2 7 ( ). Springer International Publishing..
  9. Roy, S. S., Mallik, A., Gulati, R., Obaidat, M. S., & Krishna, P. V. (2017). A deep learning based artificial neural network approach for intrusion detection. In Mathematics and Computing: Third International Conference, ICMC 2017, Haldia, India, January 17-21, 2017, Proceedings 3 (pp. 44-53). Springer Singapore.
  10. Mittal.D,Gaurav D and Roy,S.S(2015) An Effective Hybridized Classifier for Breast Cancer Diagnosis, 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM),Busan,South Korea,IEEE Xplore, ISBN: 978-1-4673-9107-8
  11. Received Best Paper Award: Basu, A., Roy, S. S., & Abraham, A. (2015, February). A novel diagnostic approach based on support vector machine with linear kernel for classifying the erythemato-squamous disease. In 2015 international conference on computing communication control and automation (pp. 343-347). IEEE.
  12. Roy,S.S., Mittal, D., Basu, A., & Abraham, A. (2015). Stock Market Forecasting Using LASSO Linear Regression Model. In Afro-European Conference for Industrial Advancement (pp. 371-381).Springer International Publishing, ISBN 978-3-319-13572- 4.
  13. Roy, S. S., Krishna, P. V., & Yenduri, S. (2014, December). Analyzing intrusion detection system: an ensemble based stacking approach. In 2014 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (pp. 000307-000309). IEEE.
  14. Roy, S. S., Viswanatham, V. M., Rawat, S. S., & Shah, H. (2013, January). Multicriteria decision examination for electrical power grid monitoring system. In 2013 7th International Conference on Intelligent Systems and Control (ISCO) (pp. 26-30). IEEE.
  15. Roy,S.S. and Charaborty, S. and Sourav, S. and Abraham (2013) A Rough Set Theory Approach for Filtering Spams from boundary messages in a Chat System pp.28- 34,ISDA,Malaysia,(IEEE Xplore), ISBN: 978-1-4799-3516-1.
  16. Gupta, A., Sabharwal,S.,Roy,S.S &Gupta,R.(2013) Investigating the factors responsible for hepatitis disease using rough set theory. In Computing, Communications and Networking Technologies (ICCCNT), 2013 Fourth International Conference on (pp. 1-6). IEEE.(IEEE Xplore),, ISBN: 978-1-4799-3926-8.
  17. Tiwari, S., Roy,S.S.,Charaborty, S., & Kumar, A. (2013). A novel hybrid model for network intrusion detection. In Green Computing, Communication and Conservation of Energy (ICGCE), 2013 International Conference on (pp. 685-688). IEEE,(IEEE Xplore), ISBN: 978-1-4673-6126-2.
  18. Rawat, S. S., Mor, D. D., Roy, S. S., Kumar, A., & Ramesh, R. (2013, December). Improving circuit miniaturization and its efficiency using Rough Set Theory. In 2013 International Conference on Machine Intelligence and Research Advancement (pp. 374-378). IEEE.
  19. Saxena, S., Kumar, A., & Roy, S. S. (2013, February). Determination of network vulnerability factor using rough set. In 2013 International Conference on Signal Processing, Image Processing & Pattern Recognition (pp. 263-268). IEEE. ISBN: 978-1- 4673-4862-1.
  20. Roy, S. S., Viswanatham, V. M., Krishna, P. V., Saraf, N., Gupta, A., & Mishra, R. (2013). Applicability of rough set technique for data investigation and optimization of intrusion detection system. In Quality, Reliability, Security and Robustness in Heterogeneous Networks: 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers 9 (pp. 479-484). Springer Berlin Heidelberg.
  21. Kumar, A., Roy,S.S., Rawat,S.S.,&Saxena,S.(2013). Phishing Detection by determining reliability factor using rough set theory. arXiv preprint arXiv:1312.2709.
  22. Tiwari, S., Roy, S. S., & Viswanatham, V. M. (2012, February). Using rough sets for optimal cost evaluation in supply chain management. In 2012 International Conference on Computing, Communication and Applications (pp. 1-5). IEEE.ISBN: 978-1-4673-0273-9.
  23. Roy, S. S., Gupta, A., Sinha, A., & Ramesh, R. (2012, October). Cancer data investigation using variable precision Rough set with flexible classification. In Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology (pp. 472-475).ISBN: 978-1-4673-0272-2.
  24. Roy,S.S., Omsai Jadhav, Saptarshi Chakraborty,Swapnil Saurav and Madhu Viswanatham(2012) Multicriteria Decision Analysis for Intrusion Detection Data, Advances in Intelligent Systems and Computing, Volume 174, (Springer link), ISBN 978- 81-322-0740-5.
  25. Tiwari, S., Khandelwal, S., & Roy, S. S. (2011, December). E-learning tool for Japanese language learning through English, Hindi and Tamil: A computer assisted language learning (CALL) based approach. In 2011 Third International Conference on Advanced Computing (pp. 52-55). IEEE.ISBN: 978-1-4673-0671-3.
Scroll to Top