Saikat Deb

@scmhrd.edu

Assistant Professor
Symbiosis Centre for Management and Human Resource Development (SCMHRD), Pune, Symbiosis International (Deemed University), Pune



                 

https://researchid.co/saikatdeb25

RESEARCH, TEACHING, or OTHER INTERESTS

Transportation, Civil and Structural Engineering, Waste Management and Disposal, Urban Studies

12

Scopus Publications

Scopus Publications

  • Harnessing machine learning models and explainable AI to understand MOOC continuance intention
    Vinod Sharma, Yogesh Mahajan, Manohar Kapse, and Saikat Deb
    Emerald
    Purpose This study aims to investigate factors that influence individuals’ continuance intention to use massive open online courses (MOOCs) by using machine learning models. Design/methodology/approach Data was collected from 702 MOOC users from major metropolitan cities in India through a network-based sampling and recruitment via various social media outlets (e.g. LinkedIn and Facebook). Various machine learning algorithms along with explainable artificial intelligence (XAI) were employed using Python PyCaret. Findings Results confirm that pedagogy value, content value, interface value, ubiquity value, teacher presence and learning satisfaction have positive effects on the continuous intention of MOOCs. Furthermore, pedagogy value is a chief driving force of CI of MOOCs. XAI helps clarify intricate patterns in learner data, thus allowing more appropriate interventions. Practical implications The findings of the study would be useful for MOOC developers to formulate better value propositions for ensuring a sustainable business and higher growth rate in the market. Originality/value This study bridges the gap in the existing literature by providing a novel approach. To the best of the authors’ knowledge, this is the first study using machine learning and XAI earlier in identifying factors leading to continuous intentions of MOOCs, so this research adds value to the existing method of exploring factors enhancing retention rates among learners.

  • Reuse of Brick Waste in the Construction Industry
    Saikat Deb, Mriganka Mazumdar, and Rakesh A. Afre
    Informatics Publishing Limited
    Demolition work produces a lot of waste or demolition waste made up of different materials like concrete, wood, metals, bricks, glass, plastics and asphalt. To maintain environmental sustainability this waste must be managed. This study offers a sustainable solution for the construction industry by providing a thorough analysis of demolition waste management with a focus on the reuse of brick aggregate and brick dust. Samples from a controlled demolition site were collected for the study. The brick samples from the demolition site were found through laboratory testing to have greater compressive strength than regular bricks, making them an acceptable building material. Brick dust was also discovered to be a superior void filler. These waste materials were used to create lean concrete, which was stronger than regular concrete and thus suitable for building. Cost comparisons revealed significant cost savings, making this strategy appealing from an economic standpoint. The study emphasises how using bricks made from demolition debris could lower carbon emissions. Responsible demolition waste management can also prevent priceless land resources from being turned into landfills, enhance soil quality and advance in building a circular economy. In conclusion, improving demolition waste management, particularly by recycling brick waste, offers a long-term solution for the building sector. It contributes to a greener and more sustainable future by minimising environmental impact, conserving resources, lowering construction costs and promoting a circular economy.

  • The Role of GPT and Data Fusion in improving Disaster Prediction
    Saikat Deb and Mriganka Mazumdar
    World Researchers Associations
    The application of data fusion for disaster prediction using GPT (Generative Pre-trained Transformer) is covered in this study. Data fusion is the process of merging information from several sources including social media, sensor data, and simulation data, in order to increase the precision of catastrophe prediction models. Through the utilization of GPT, an artificial intelligence language model, data fusion enables a thorough examination and amalgamation of data from disparate fields, hence producing more resilient forecasts. GPT models may be used to recognize geographical descriptions from social media postings and identify cell kinds using information about marker genes. Proactive communication with impacted people in times of catastrophe is made possible by the integration of GPT with social media monitoring. GPT models may significantly enhance disaster preparedness, response, prediction, and recovery by gathering pertinent data from many sources and modelling various situations.

  • Assessment of Changes in Brahmaputra River Course at the Pagladia Confluence Point using Remote Sensing and GIS Techniques
    Mriganka Mazumdar and Saikat Deb
    World Researchers Associations
    The river Brahmaputra is a large alluvial river that is prone to frequent bank erosion and channel pattern changes, leading to significant shifts in its course. This study aimed to analyze these changes along a 56-kilometer stretch of the river using a combined approach of remote sensing and GIS techniques. This study utilized USGS and Landsat 8 satellite imagery to map the river's channel configuration from 1985 to 2022, providing valuable insights into the river's morphology and the stability of its banks. Additionally, the analysis provided information on changes in the river's main channel which can help in predicting future behavior and mitigating the impact of these changes. The findings of this study have significant implications for river management, allowing for informed decision-making and improved strategies for protecting communities and infrastructure located along the river's course.



  • District-level assessment of changes in extreme rainfall indices in Barak and other basins in Indian Himalayan states: risks and opportunities
    Gilbert Hinge, Mriganka Mazumdar, Saikat Deb, and Mintu Kumar Kalita
    Springer Science and Business Media LLC


  • Model for Estimating On-street Parking Demand in Urban CBD
    Debasish Das, Mokaddes Ali Ahmed, and Saikat Deb
    Springer International Publishing

  • Quality assessment of city bus service based on subjective and objective service quality dimensions: Case study in Guwahati, India
    Saikat Deb and Mokaddes Ali Ahmed
    Emerald
    Purpose The purpose of this paper is to estimate and compare the service quality of the city bus service measured by two different approaches which are subjective service quality dimensions and objective service quality dimensions. Design/methodology/approach The objective service quality dimensions have been estimated based on the benchmarking technique provided by the Ministry of Urban Development, India. For the analysis of subjective service quality dimensions, a questionnaire survey has been conducted to measure the users’ satisfaction and dissatisfaction about the service. The questionnaire consists of users’ socioeconomic characteristics and 23 questions related to city bus service quality dimensions. Questionnaire data have been analyzed by factor analysis, regression analysis and path analysis to find out the indicators representing subjective service quality dimensions. Finally, the overall service quality of the bus service has been determined based on both the measures. Findings The study indicates that the overall service quality of the bus service is different for subjective and objective analyses. While the objective measures show that the service quality is very good, the subjective measures indicate that the service is not doing well. Research limitations/implications The analysis of the subjective dimensions is complicated. Analysis of the subjective dimensions needed more expertise and resources than the objective analysis. Originality/value In this study, the estimated service quality of the bus service is more reliable than the other methods as it comprises of both operators’ perspective and passengers’ expectations from the service.


  • Variability Of the perception about safety, comfort, accessibility and reliability of city bus service across different users groups


RECENT SCHOLAR PUBLICATIONS

    Publications

    Das, Jayanta Kumar, Saikat Deb, and Biswadeep Bharali. "Prediction of aggregate impact values and aggregate crushing values using light compaction Journal of Applied Engineering Sciences 11.2 (2021): 93-100.