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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science Asian Journal of Science, Technology, Engineering, and Art
Yadav, Neelam
Unknown Affiliation
Arts Computer Science & IT Engineering Social Sciences

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Developing standard criteria for robotic process automation candidate process selection Yadav, Neelam; P. Panda, Supriya
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i4.pp4291-4300

Abstract

Robotic process automation (RPA) is a cutting-edge technology that provides software robots to repeat and mimic the repeatable tasks that a human user earlier performed. The use of software robots is encouraging because of their cost efficiency and easy implementation. Selecting and prioritizing a candidate process for automation is always challenging as all the business processes in an organization are not equally suitable for RPA implementation. Various studies have highlighted several criteria found in the literature for determining, prioritising, and selecting a business process for RPA. Nevertheless, there are no set standards for evaluating and analyzing a certain process or its tasks to determine whether they may be automated to use RPA. This paper aims to develop standard criteria and propose a consistent model to select and prioritize candidate process for RPA projects. To assess these criteria's applicability in the context of RPA, surveys among subject matter experts (SMEs) are used to validate them. Principal component analysis (PCA) and correlation are used to identify the top 20 criteria. Naïve Bayes algorithm is applied on the collected data for decision-making. The developed multi-criteria model exhibits strong precision and recall measures, with training and validation accuracy of 96% and 90%, respectively.
Machine learning-based intelligent result compilation RPA bot for higher education institutions Yadav, Neelam; Panda, Supriya P.
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp587-594

Abstract

Educators are essential for societal progress, and well-educated students are pivotal for a promising future. Higher education faces challenges such as budget constraints, limited time, and a shortage of trained personnel, leading to faculty stress. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and block chain provide solutions, with robotic process automation (RPA) bots a notable advanced AI subfield-automating repetitive tasks, thereby freeing teachers to focus on more essential responsibilities. RPA bots automate various educational processes, including examinations, admissions, marks updating, student record management, result compilation, human resources, resume screening, and administration. This research examines robotic automation in higher education institutions (HEIs), selecting and prioritizing RPA tasks through a survey involving subject matter experts (SMEs) from different HEIs, including professors and RPA experts. The research aims to develop a “virtual software bot” for automating “result compilation” post-examination. Using tools like XPATH, Whisper, and the web-based automation program Selenium web in Python, the bot automates this process. The ML library “Whisper” addresses the reCAPTCHA problem. The automated bot generates comma separated values (CSV) files in specific formats, completing the task 58 times faster than humans and saving 43 man-hours by compiling results for 653 students in 45 minutes.
Unleashing Effective Models of Collaboration for Rainwater Harvesting: Experiences from Nepal Yadav, Maheshwar Prasad; Aithal, P. S.; Yadav, Neelam; Karki, Tej Bahadur
Asian Journal of Science, Technology, Engineering, and Art Vol 2 No 4 (2024): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v2i4.3660

Abstract

Background: Rainwater harvesting (RWH) is an age-old practice of a localized renewable and alternate source of water supply to meet the growing demand of people in developing countries like Nepal. Thus, the effective models of collaboration for providing water services through RWH is a pathway to the sustainable water management of the nation leading to achieving SDGs. Purpose: The paper aims at unleashing effective models of collaboration for RWH in the context of the rural areas of Nepal. Methodology: The study comprises a descriptive cum analytical research design based on both primary and secondary data. The necessary primary data were collected by conducting a field survey using a semi-structured questionnaire on a sample of 38 communities/projects having RWH systems while the secondary data were collected through relevant publications. The csollected data were analyzed using statistical tools through SPSS to derive results leading to major findings of the study. Analysis/Results: The study concluded that a collaborative plan provides a ground to get contributions from different stakeholders and increase their sense of ownership. The collaboration with the local government ensures co-financing and involvement in planning and monitoring and increases prospects for support to required rehabilitation in the future. Community engagement from planning to implementation to managing the systems ensures the system's functionality and sustainability, leading to caretakers’ management and promoting income-generating activities using waste/overflow water from the system. The multiple uses of water services (MUS) provide a basis for livelihood enhancement leading to regular payment of tariffs. The caretakers’ management ensures to fix minor repairs promptly as needed. A combination of monitoring and eval_uation with different stakeholders during implementation and afterward ensures efficient and effective implementation and sustainability of the RWH system. Originality/Value: No such study uses recent data related to effective models of collaboration for RWH in the context of the rural areas of developing countries like Nepal is accessible. The paper, therefore, is valuable for users’ committees, development actors, academia, and policymakers to create effective models of collaboration for RWH. This work may potentially be useful to academia for future studies. Future avenue: The extension of this study can be made by incorporating an analysis of diverse applications of artificial intelligence (AI) in the water management sector in future studies.
Co-Authors Aithal, P. S. Karki, Tej Bahadur P. Panda, Supriya Panda, Supriya P. Yadav, Maheshwar Prasad