Biswas, Subrata
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Accumulation of Biological and Behavioral Data of Female Sex Workers Using Respondent-Driven Sampling Around the World: Systematic Review Bhatta, Mihir; Majumdar, Agniva; Ghosh, Piyali; Banerjee, Sitikantha; Chakraborty, Debjit; Biswas, Subrata; Sahoo, Srijan; Dutta, Shanta
Epidemiology and Society Health Review (ESHR) Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/eshr.v6i2.9845

Abstract

Background: Respondent-Driven Sampling (RDS) is generally used to study hidden or hard-to-reach populations. The objective of the present work is to describe the initiation, implementation, and complications that arise during RDS of female sex workers (FSWs) around the world. Method: Behavioural and biological data of FSWs collected through RDS was mined from peer-reviewed articles, published during 2010-2022. Review protocol was developed and registered in the PROSPERO (registration number CRD42022346470) and published separately. Results: It was found that most of the RDS (69 articles, globally) were largely successful in the recruitment of FSWs, with varying response rates. Conclusion: Present outcomes supports the application of RDS in surveillance for any such population by providing a minimal set of parameters of testing procedures (methodology) including methods to evaluate the quality also.
Methodology for incisive foraging of high-risk junctions and elimination of injected false data in smart grid Ghosh, Poulami; Biswas, Subrata; Purkait, Prithwiraj
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i2.pp347-358

Abstract

The present work represents a method for identification of the vulnerable nodes in smart grid as well as assessment of the performance of voltage stability indicator technique with the help of weighted least square scheme. in today’s smart grid system, false data injection (FDI) is the major issue to supply uninterruptedly at demand side in advanced metering infrastructure (AMI). The recent blackouts are the consequence of non-identifying FDI as research on FDI is not considered under power system analysis. In our research, vulnerable nodes of a power system network have been identified and a state estimation method was used to eliminate superfluous data for those identified nodes. Voltage stability indicator (VSI) based state estimation have been used successfully to make the smart grid system error free as possible. VSI method has been used first to find the vulnerable nodes of the grid after that the efficient state estimation method i.e. optimal weighted least square (optimal WLS) have been employed to get refined result. Results show that VSI based technique in concurrence with optimal WLS has potential to eliminate undesirable data with sensible level of precision.