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All Journal International Journal of Advances in Applied Sciences Bulletin of Electrical Engineering and Informatics
Madake, Jyoti
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Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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A gamified online learning environment with comprehensive assessments and software integration Shilaskar, Swati; Bhatlawande, Shripad; Deshpande, Rupali; Shinde, Shivam; Madake, Jyoti; Solanke, Anjali
International Journal of Advances in Applied Sciences 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/ijaas.v14.i2.pp416-429

Abstract

The National Achievement Survey (NAS), conducted by the Ministry of Education, India, highlighted a concerning decline in mathematics proficiency among students in Maharashtra as they advance through grades. This trend is further aggravated by the limited availability of online resources in Marathi, hindering their learning progress. To address this, a pilot study was proposed to develop a specialized online platform tailored for Marathi medium students, integrating gamification and artificial intelligence (AI)-driven feedback to enhance engagement and comprehension. The pilot project, conducted at a Marathi medium school with approval from the principal, focused on polynomial division tests for 8th-grade students over four days. Results revealed that despite the easy level test's higher difficulty, students scored higher on the medium level test, possibly due to an adjustment period to the online platform. Notably, some students performed better on the hard-level test, indicating the platform's potential to improve performance. While promising, the study's limitations, including a small sample size, highlight the need for further research with a larger cohort and the integration of automatic suggestions for concept-specific games and assessments in future iterations to optimize the platform's effectiveness.
Automated real-time cervical cancer diagnosis using NVIDIA Jetson Nano Mulmule, Pallavi; Shilaskar, Swati; Bhatlawande, Shripad; Mulmule, Vedant; H Kamble, Vaishali; Madake, Jyoti
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.10169

Abstract

Cervical cancer is a global health concern, making early detection critical for ensuring effective treatment outcomes. Screening technique, the Papanicolaou test (Pap test), has been adopted globally for timely detection. Nevertheless, the process of screening is subjective. The current study aims to advance the development of an automated real time framework for cervical cell analysis for early-stage diagnosis using supervised classification on NVIDIA Jetson Nano platform. Our approach, leveraging adaptive fuzzy k-means (AFKM) clustering and k-means clustering, extracts distinctive features from cervical cell images for accurate classification. Utilizing multilayer perceptron (MLP) and support vector machine (SVM) classifiers, we achieved a classification accuracy of 97%, highlighting the potential of our system for real-time applications in cervical cancer investigation. Validation by two expert pathologists further supports the system’s practical utility.
Co-Authors Bhatlawande, Shripad Deshpande, Rupali H Kamble, Vaishali Mulmule, Pallavi Mulmule, Vedant Shilaskar, Swati Shinde, Shivam Solanke, Anjali