Manish R Joshi

@nmu.ac.in

Professor, School of Computer Sciences
Kavayitri Bahinabai Chaudhari North Maharashtra University

Manish R Joshi


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https://researchid.co/joshmanish
52

Scopus Publications

1055

Scholar Citations

16

Scholar h-index

32

Scholar i10-index

Scopus Publications

  • A successful recipe for localization: a case of GIMP (GNU image manipulation program)
    Snehalata Bhikanrao Shirude, Manish Ratnakar Joshi
    Journal of Indian Business Research, 2023
    Purpose Free Open Source Softwares (FOSS) witnessed the development of many very good alternatives to proprietary softwares. These free softwares can be localized in several local languages. This paper aims to illustrate a very interesting empirical investigation on FOSS. Several significant benefits of localization are described in introduction and subsequent sections. Design/methodology/approach Although the localization process is standard and well documented for most of the FOSS, it is a more complex task as it involves coordination among developers, linguists and domain experts. Hence, a very few open source softwares are successfully localized in Indian languages. In this paper, the authors present an approach that they have used for GIMP (GNU Image Manipulation Program) software Marathikaran (localization in Marathi language) project of by Rajya Marathi Vikas Sanstha of Maharashtra Government (RMVS), India. Findings This localization project has been described by RMVS as a pilot project that would guide such similar localizations in many other Indian languages for other popular open source softwares. Social implications The localization work overcomes the general misconception that regional languages are good only for communication (Boli Bhasha) but cannot be used for dissemination of knowledge (Gyan Bhasha). This work is notably contributing to language preservation, language revitalization and Digital India Initiative. Originality/value This work is the pioneering work in this domain for Marathi language with respect to GIMP. The authors presented systematic steps used to localize the GIMP software in Marathi language (from 2% to 100%).
  • An extensive review of computational dance automation techniques and applications
    Manish Joshi, Sangeeta Chakrabarty
    Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences, 2021
    Dance is an art and when technology meets this kind of art, it is a novel attempt in itself. Many researchers have attempted to automate several aspects of dance, right from dance notation to choreography; from dance capturing to dance generation. We define and illustrate the concept of ‘Dance Automation’ in this paper. Furthermore, we have encountered several applications of dance automation like e-learning, heritage preservation, medical therapy, etc. Despite decades of continuous attempts by many researchers in various styles of dance all round the world, we found a review paper that portrays the research status in this area of ‘dance and computers’ dating to 1990 (Leonardo 1990 Computers and dance: A bibliography , pp. 87–90). Hence, we decided to compose a comprehensive review article that showcases several aspects of dance automation and document contributions of researchers in marrying creativity with logic. This paper is an attempt to review research work reported in the literature, categorize and group significant research work completed in a span of 1967–2020 in the field of automating dance. We have explicitly identified six major categories corresponding to the use of computers in dance automation, namely, dance representation, dance capturing, dance semantics, dance generation, dance processing approaches and applications of dance automation systems. We classified several research papers under these categories according to their research approach and functionality. With the help of proposed categories and subcategories, one can easily determine the state of research and the new avenues left for exploration in the field of dance automation.
  • Using Sequence Mining to Predict Complex Systems: A Case Study in Influenza Epidemics
    Theyazn H. H. Aldhyani, Manish R. Joshi, Shahab A. AlMaaytah, Ahmed Abdullah Alqarni, Nizar Alsharif
    Complexity, 2021
    According to the World Health Organisation, three to five million individuals are infected by influenza, and around 250,000 to 500,000 people die of this infectious disease worldwide. Influenza epidemics pose a serious public health threat. Moreover, graver dangers are encountered with influenza subtypes against which there is little or no preexisting human immunity. Such subtypes of influenza have the potential to cause devastating epidemics. Thus, enhancing surveillance systems for the purpose of detecting influenza epidemics in an early stage can quicken response times and save millions of lives. This paper presents three adapting intelligence models: support vector machine regression (SVMR), artificial neural network using particle swarm optimisation (ANNPSO), and our intelligent time series (INTS) to predict influenza epidemics. The novelty of the current study is that it proposes a new intelligent model to predict influenza outbreaks. The INTS model combines clustering with a time series model to enhance the prediction of influenza outbreaks. The innovation of our proposed model integrates the results obtained from the existing weighted exponential smoothing model with centroids obtained from clustering. We developed a surveillance system for influenza epidemics using Google search queries. The current research is based on a weighted version of the Center for Disease Control and Prevention influenza-like illness activity level obtained from the Center for Disease Control and Prevention data, as well as query data obtained from the Goggle search engine in the USA. The influenza-like illness data was collected from January 4, 2009 (week 1), to December 27, 2015 (week 52), stretching across a total time span of 312 weeks. Google Correlate was used to select search queries related to influenza epidemics. In total, 100 search queries were obtained from Google Correlate, 10 of which were better and more relevant search queries selected in this study. The model was evaluated using online Google search queries collected from Google Correlate. Standard measure performance MSE, RMSE, and MAE were employed to estimate the results of the proposed model. The empirical results of the INTS model showed MSE = 0.003, RMSE = 0.036, and MAE = 0.0185, indicating that the errors of the proposed model are very limited. A comparative model of predicting results between the INTS model, alternative Google Flu Trend (GFT), and autoregression with Google search data is also presented. The proposed model outperformed the existing models.
  • Use of Learning Style for Content Delivery Personalization
    Manish Joshi
    2020 International Conference on System Computation Automation and Networking Icscan 2020, 2020
    Personalization in e-services is desirable and large numbers of professional players are ensuring that personalization must be included as a web service for users. Moreover, recommender systems can perform effectively only with the support of personalization. Personalization has gained momentum in the service sector including education. With the advancement of the concept of ‘Teaching with Technology’, industry is inching forward to provide personalized learning contents on e-learning platforms. Personalization can be offered to a learner by ana-lyzing learning behavior, cognitive skills, learning style etc. of a learner. Most of the researchers have attained personalization especially in distance mode of e-learning using Adaptive Educational Hypermedia Systems (AEHS). Different aspects of personalization that demonstrate a paradigm shift from synchronous to adaptive approach of e-learning are being explored and experimented by many researchers. In this paper, we present our experiments of delivering learning objects (LOs) to learners that suits to the learners learning style. A personalized instruction delivery mechanism is developed that matches Learning style of a LO and the learning style of a learner. We demonstrate how such matching is ensured. We present the design of the Intelligent Tutoring System that we have developed and further discussed the learning style driven content delivery personalization.
  • Cluster Driven Candlestick Method for Stock Market Prediction
    Yogita Patil, Manish Joshi
    2020 International Conference on System Computation Automation and Networking Icscan 2020, 2020
    Trend prediction of the volatile stock market has been an interesting and challenging task for many researchers over many years. In this paper, we present how rough set-based BIRCH clustering can be used to develop stock data prediction model. The proposed model augments clustering with a popular technical analysis method called candlestick. BIRCH clustering algorithm is used to group stocks of varied sectors by taking into consideration the previous few days volatility. Further cluster analysis is carried out to predict stocks movement for next trading day. The proposed prediction model is different from existing models as it works on all NSE stocks from varied sector. Our model outperforms models that merely using clustering or candlestick techniques.
  • KBCNMUJAL@HASOC-Dravidian-CodeMixFIRE2020: Using machine learning for detection of hate speech and offensive code-mixed social media text
    Ceur Workshop Proceedings, 2020
  • Relevance feedback mechanism for resolving transcription ambiguity in SMS based literature information system
    Varsha M. Pathak, Manish R. Joshi
    Smart Innovation Systems and Technologies, 2019
  • Clustering with polar coordinates system: Exploring possibilities
    Yogita S. Patil, Manish R. Joshi
    Smart Innovation Systems and Technologies, 2019
  • Clustering to enhance network traffic forecasting
    Theyazn H. H. Aldhyani, Manish R. Joshi
    Lecture Notes in Networks and Systems, 2018
  • Automatic Sub Classification of Benign Breast Tumor
    Aparna Bhale, Manish Joshi
    Lecture Notes in Networks and Systems, 2018
  • Use of Learning Style Based Approach in Instructional Delivery
    Ravindra Vaidya, Manish Joshi
    Lecture Notes in Networks and Systems, 2018
  • Study of dimensionality reduction techniques for effective investment portfolio data management
    Swapnaja Gadre-Patwardhan, Vivek Katdare, Manish Joshi
    Smart Innovation Systems and Technologies, 2018
  • Integration of time series models with soft clustering to enhance network traffic forecasting
    Theyazn H. H. Aldhyani, Manish R. Joshi
    Proceedings 2016 2nd IEEE International Conference on Research in Computational Intelligence and Communication Networks Icrcicn 2016, 2017
  • Quantitative estimation of time interval of 3-sequences
    Gajendra Wani, Manish Joshi
    2016 5th International Conference on Reliability Infocom Technologies and Optimization Icrito 2016 Trends and Future Directions, 2016
  • Analysis of change in coordinate system on clustering
    Manish R. Joshi, Yogita S. Patil
    2016 IEEE International Conference on Current Trends in Advanced Computing Icctac 2016, 2016
  • An integrated model for prediction of loading packets in network traffic
    Theyazn H. H. Aldhyani, Manish R. Joshi
    ACM International Conference Proceeding Series, 2016
  • Handling ambiguous packets in intrusion detection
    Theyazn Hassn Hadi, Manish R. Joshi
    2015 3rd International Conference on Signal Processing Communication and Networking Icscn 2015, 2015
  • Art to SMart: An automated bharatanatyam dance choreography
    Sangeeta Jadhav, Manish Joshi, Jyoti Pawar
    Applied Artificial Intelligence, 2015
  • Natural language query refinement scheme for indic literature information system on mobiles
    Varsha M. Pathak, Manish R. Joshi
    Advances in Intelligent Systems and Computing, 2015
  • Role of clinical attributes in automatic classification of mammograms
    Aparna Bhale, Manish Joshi, Yogita Patil
    Advances in Intelligent Systems and Computing, 2015
  • An automated stick figure generation for bharatanatyam dance visualization
    Sangeeta Jadhav, Anwaya Aras, Manish Joshi, Jyoti Pawar
    ACM International Conference Proceeding Series, 2014
  • Towards automation and classification of BharataNatyam dance sequences
    International Journal of Computer Science and Applications, 2014
  • Clustering-based stability and seasonality analysis for optimal inventory prediction
    Manish Joshi, Pawan Lingras, Gajendra Wani, Peng Zhang
    Global Trends in Intelligent Computing Research and Development, 2013
  • A review of paradigm shift from conventional to personalized e-learning
    Manish Joshi, Ravindra Vaidya
    Proceedings of the 2013 International Conference on Advances in Computing Communications and Informatics Icacci 2013, 2013
  • Soft clustering to determine ambiguous regions during medical images segmentation
    Manish Joshi, Monica Mundada
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013

RECENT SCHOLAR PUBLICATIONS

  • Optimization of placement of continuous air monitors in a radiological facility
    J Chakraborty, MK Sureshkumar, M Joshi, S Anand, MS Kulkarni
    Aerosol Science and Engineering 9 (3), 413-425 , 2025
    2025
  • Seasonal variability of 222 Rn and 220 Rn equilibrium factors in indoor environment of Kumaun Himalaya, India
    T Ahamad, OP Nautiyal, M Joshi, P Singh, AS Rana, AA Bourai, ...
    Journal of Radioanalytical and Nuclear Chemistry 333 (6), 2881-2890 , 2024
    2024
    Citations: 2
  • Frontogenesis-inspired efficient synthesis of dense SWCNT fiber through in-situ boosting of catalyst re-nucleation
    A Kaushal, R Alexander, M Joshi, J Singh, K Dasgupta
    Chemical Engineering Journal 484, 149254 , 2024
    2024
    Citations: 8
  • Size-segregated aerosol measurements during Diwali festival in an elevated background location
    A Buwaniwal, M Joshi, V Sharma, G Gupta, A Khan, S Kansal, BK Sapra
    Atmospheric Environment 314, 120078 , 2023
    2023
    Citations: 5
  • Personalized Recommendation after Classification of Tweets to Predict Depression using Sentiment Analysis
    M Joshi, J Bhuvana
    2023 International Conference on Advances in Computation, Communication and … , 2023
    2023
    Citations: 2
  • Port-based classification of network traffic analysis using the ColasoftCapsa tool for enhanced cybersecurity
    S Jebaraj, M Joshi
    2023 International Conference on Communication, Security and Artificial … , 2023
    2023
    Citations: 3
  • Sentiment analysis from social media data in code-mixed indian languages using machine learning classifiers with TF-IDF and weighted word features
    PA Joshi, VM Pathak, MR Joshi
    International conference on data science and big data analysis, 203-222 , 2023
    2023
    Citations: 5
  • A successful recipe for localization: a case of GIMP (GNU image manipulation program)
    SB Shirude, MR Joshi
    Journal of Indian Business Research 15 (2), 227-242 , 2023
    2023
    Citations: 1
  • Effective dose estimation of radon, thoron and their progeny concentrations in the environs of Himalayan belt, India
    P Semwal, TK Agarwal, M Joshi, A Kumar, K Singh, RC Ramola
    International Journal of Environmental Science and Technology 20 (4), 4127-4138 , 2023
    2023
    Citations: 9
  • Assessment of natural radiation levels due to 222Rn, 220Rn and progeny in indoor environment of outer Himalayan region, India
    T Ahamad, AS Rana, OP Nautiyal, M Joshi, P Singh, AA Bourai
    2022
  • Comprehensive Review on the Selection of Materials in City Gas Distribution Value Chain
    B Shingan, M Harshita, N Verma, M Joshi, H Vishwakarma
    International Conference on Materials for Energy Storage and Conservation, 7-14 , 2022
    2022
  • Experimental estimates of hygroscopic growth of particulate fission product species (mixed CsI–CsOH) with implications in reactor accident safety research
    M Joshi, A Khan, G Mishra, SN Tripathi, BK Sapra
    Progress in Nuclear Energy 148, 104216 , 2022
    2022
    Citations: 6
  • Quick laboratory methodology for determining the particle filtration efficiency of face masks/respirators in the wake of COVID-19 pandemic
    M Joshi, A Khan, BK Sapra
    Journal of Industrial Textiles 51 (5_suppl), 7622S-7640S , 2022
    2022
    Citations: 21
  • Improving the accuracy of charge size distribution measurement using electrical low pressure impactor
    Mariam, M Joshi, A Khan, BK Sapra
    Particulate Science and Technology 40 (3), 290-295 , 2022
    2022
    Citations: 5
  • Comparative study of two different water sources in the aspect of radiological exposure to the local population of Bageshwar, India
    A Kumar, D Singh, P Semwal, T Kandari, K Singh, M Joshi, P Singh
    Journal of Radioanalytical and Nuclear Chemistry 331 (4), 1941-1949 , 2022
    2022
    Citations: 7
  • Aerosol generation from graphite at high temperature: Role of heating rate and air flow rate
    SK Yadav, M Joshi, P Shukla, A Khan
    Annals of Nuclear Energy 167, 108792 , 2022
    2022
    Citations: 2
  • Dosimetry of indoor alpha flux belonging to seasonal radon, thoron and their EECs
    A Kaushal, M Joshi, A Sarin, N Sharma
    Environmental monitoring and assessment 194 (2), 119 , 2022
    2022
    Citations: 1
  • Welding studies on dissimilar magnesium alloys for improving corrosion behaviour
    SK Maurya, R Kumar, SK Mishra, H Shukla, AK Dahayat, AK Jain, M Joshi
    Materials Today: Proceedings 63, 623-629 , 2022
    2022
    Citations: 8
  • Comparative structural analysis of CNC milling machine bed using Al-SIC/graphite, al alloy and Al-SIC composite material
    R Kumar, A Jain, SK Mishra, M Joshi, K Singh, R Jain
    Materials Today: Proceedings 51, 735-741 , 2022
    2022
    Citations: 15
  • Evaluation of natural radioactivity levels and 222 Rn, 220 Rn exhalation rate in the soil of the Himalayan belt of Uttarakhand, India
    P Semwal, A Kumar, K Singh, M Joshi, TK Agarwal, RC Ramola
    Journal of Radioanalytical and Nuclear Chemistry 330 (3), 1589-1599 , 2021
    2021
    Citations: 3

MOST CITED SCHOLAR PUBLICATIONS

  • A review of network traffic analysis and prediction techniques
    M Joshi, TH Hadi
    arXiv preprint arXiv:1507.05722 , 2015
    2015
    Citations: 200
  • An extensive review of computational dance automation techniques and applications
    M Joshi, S Chakrabarty
    Proceedings of the Royal Society A 477 (2251), 20210071 , 2021
    2021
    Citations: 52
  • Kbcnmujal@ hasoc-dravidian-codemix-fire2020: Using machine learning for detection of hate speech and offensive code-mixed social media text
    V Pathak, M Joshi, P Joshi, M Mundada, T Joshi
    arXiv preprint arXiv:2102.09866 , 2021
    2021
    Citations: 46
  • NATURAL LANGUAGE INT ERFACE USING SHALLOW PARSING
    R Akerkar, M Joshi
    International Journal of Computer Science & Applications 5 (3), 70-90 , 2008
    2008
    Citations: 30
  • A review of artificially intelligent applications in the financial domain
    S Gadre-Patwardhan, VV Katdare, MR Joshi
    Artificial Intelligence in Financial Markets: Cutting Edge Applications for … , 2016
    2016
    Citations: 26
  • Classification and clustering
    M Joshi
    1977
    Citations: 26
  • Quantification of 222 Rn/ 220 Rn exhalation rates from soil samples of Champawat region in Kumaun Himalaya, India
    T Ahamad, P Singh, OP Nautiyal, M Joshi, AA Bourai, AS Rana, K Singh
    Journal of Radioanalytical and Nuclear Chemistry 330 (3), 1485-1495 , 2021
    2021
    Citations: 23
  • Integration of time series models with soft clustering to enhance network traffic forecasting
    THH Aldhyani, MR Joshi
    2016 Second International Conference on Research in Computational … , 2016
    2016
    Citations: 23
  • Quick laboratory methodology for determining the particle filtration efficiency of face masks/respirators in the wake of COVID-19 pandemic
    M Joshi, A Khan, BK Sapra
    Journal of Industrial Textiles 51 (5_suppl), 7622S-7640S , 2022
    2022
    Citations: 21
  • Art to SMart: an evolutionary computational model for BharataNatyam choreography
    S Jadhav, M Joshi, J Pawar
    2012 12th International Conference on Hybrid Intelligent Systems (HIS), 384-389 , 2012
    2012
    Citations: 21
  • CFD simulations to study the effect of ventilation rate on 220Rn concentration distribution in a test house
    TK Agarwal, BK Sahoo, M Joshi, R Mishra, O Meisenberg, J Tschiersch, ...
    Radiation Physics and Chemistry 162, 82-89 , 2019
    2019
    Citations: 20
  • Intelligent time series model to predict bandwidth utilization
    THH Aldhyani, MR Joshi
    Int. J. Comput. Sci. Appl 14 (2), 130-141 , 2017
    2017
    Citations: 20
  • Art to SMart: an automated BharataNatyam dance choreography
    S Jadhav, M Joshi, J Pawar
    Applied Artificial Intelligence 29 (2), 148-163 , 2015
    2015
    Citations: 20
  • Assessment of physicochemical and radon-attributable radiological parameters of drinking water samples of Pithoragarh district, Uttarakhand
    P Singh, OP Nautiyal, M Joshi, A Kumar, T Ahamad, K Singh
    Journal of Radioanalytical and Nuclear Chemistry 330 (3), 1559-1570 , 2021
    2021
    Citations: 19
  • Correlating Fuzzy and Rough Clustering
    M Joshi, P Lingras, CR Rao
    Fundamenta Informaticae 115 ((2-3)), 233-246 , 2012
    2012
    Citations: 19
  • Algorithms to improve performance of natural language interface
    MR Joshi, RA Akerkar
    International Journal of Computer Science and Application 5 (2) , 2008
    2008
    Citations: 18
  • A review of paradigm shift from conventional to personalized e-learning
    M Joshi, R Vaidya
    2013 International Conference on Advances in Computing, Communications and … , 2013
    2013
    Citations: 16
  • Modeling BharataNatyam dance steps: art to SMart
    S Jadhav, M Joshi, J Pawar
    Proceedings of the CUBE International Information Technology Conference, 320-325 , 2012
    2012
    Citations: 16
  • Comparative structural analysis of CNC milling machine bed using Al-SIC/graphite, al alloy and Al-SIC composite material
    R Kumar, A Jain, SK Mishra, M Joshi, K Singh, R Jain
    Materials Today: Proceedings 51, 735-741 , 2022
    2022
    Citations: 15
  • Data mining approach to predict and analyze the cardiovascular disease
    A Bhatt, SK Dubey, AK Bhatt, M Joshi
    Proceedings of the 5th International Conference on Frontiers in Intelligent … , 2017
    2017
    Citations: 15