Manuscripts

Recent Papers

Research Paper

The Bharat Within a National Policy Framework for Youth Well-being, Future-Ready Education, and Nation Building for Generation Z and Generation Alpha

For India to receive a demographic dividend from its demographic window, educational expansion must be matched with the ability to produce resilient and skilled social capital. This secondary-data policy study analyses the “Bharat Within” framework for Generation Z and Generation Alpha. The analysis is based on Indian official data and peer-reviewed literature for the years 2020 to 2025. Since the primary data used in the study existed in a disparate format, descriptive analysis techniques, such as the percentage change, compound annual growth rate (CAGR), and the competition intensity index, were used in the study. India’s education system in the year 2023–24 enrolled 24.8 crore students at 14.72 lakh schools and approximately 4.46 crore in institutions of higher education (provisional figure for 2022–23). NCERT-based findings reported that the surveyed students showed anxiety (11%), extreme emotions (14%), and mood swings (43%). Student suicides reported by the NCRB increased from 12,526 in 2020 to 13,044 in 2022, representing a 4.1% increase and a CAGR of 2.0%. Between the years 2020 and 2024, NEET registrations increased by 50.6%. Additionally, between 2022 and 2025, unique registrations for the JEE Main increased by 50.0%. ASER 2024 reported a gap in rural students’ social media (vs. educational) use of 19 percentage points; rural students also showed near-universal access to smartphones. Based on this evidence, the study advocates that wellness services offered in schools adopt a flexible and tiered system. Furthermore, it recommends first-response training for teachers, regulated competitive exam prep, innovation and community building, AI and digital wellness training, and the National Student Well-Being Index (NSWI) be developed and integrated into Indian schools.

Published by: Dr. Jay Dhruv

Author: Dr. Jay Dhruv

Paper ID: V12I4-1200

Paper Status: published

Published: September 2, 2026

Full Details
Research Paper

A Study to Assess the Knowledge and Attitude Regarding Premenstrual Syndrome and Coping Strategies Among Female Undergraduate Students

Premenstrual syndrome (PMS) is a common cyclical condition among women of reproductive age, characterized by physical, psychological, and behavioural symptoms during the luteal phase of the menstrual cycle. The study aimed to assess the knowledge, attitude, and coping strategies regarding PMS among female undergraduate students. A quantitative approach with a descriptive research design was adopted, and 150 female undergraduate students were selected using convenience sampling from a selected college in Kollam district. The findings revealed that 48.7% (n=73) had average knowledge, 97.3% (n=146) had a positive attitude, and 50% (n=75) adopted moderate coping strategies. There was significant Association between the knowledge regarding premenstrual syndrome and selected Demographic variables and no significant association was found between attitude towards PMS and selected demographic variables. The study concluded that the majority of students had average knowledge, a positive attitude, and moderate coping strategies regarding PMS.

Published by: Gowry P, Ayisha Sharaf, Sangeetha B S, Anitta Babu, Mubashira Rasheed, Adithyan S, Susan George, Shabna Sasidharan

Author: Gowry P

Paper ID: V12I4-1206

Paper Status: published

Published: September 1, 2026

Full Details
Research Paper

Impact of Artificial Intelligence Tools on Academic Performance and Psychological Well-Being Among Undergraduate Students in Selected Colleges in Kollam District

Background & Objectives: The present study was undertaken to assess the impact of Artificial Intelligence (AI) tools on academic performance and psychological well-being among undergraduate students in selected colleges of Kollam district. Methodology: A quantitative research approach with a descriptive research design was used. A sample of 100 undergraduate students was selected from Younus College of Engineering using a non-probability convenience sampling technique. Data were collected through structured questionnaires for measuring AI tool usage, academic performance, and psychological well-being. For the analysis descriptive and inferential statistics were used. Results: The findings revealed that majority of students that is 58% had a high level of AI tool usage, 26% had moderate usage, 13% had very high usage, and 3% had low usage. Regarding the academic performance, 63% achieved excellent level and 37% an average level. Psychological well-being was moderate in 56%, mild in 31%, good in 12%, and poor in 1%. Statistical analysis shows that there is a significant weak positive correlation between AI tool usage and academic performance (r = 0.240, p = 0.016) and a significant weak negative correlation between AI tool usage and psychological well-being (r = -0.270, p = 0.007). Conclusion: The study highlights that the usage of AI tools enhance academic performance of students and higher usage of AI tools is reduces the psychological well-being of the student which emphasizing the need for balanced digital habits.

Published by: Sajna Sajeer, Prof. Amal James, Asha Raichal Sam, Jeena Varghese, Mahima Murali, Irfana Hussain, Devika, Alan Lalal

Author: Sajna Sajeer

Paper ID: V12I4-1191

Paper Status: published

Published: August 25, 2026

Full Details
Thesis

A study to assess the effectiveness of structured teaching program on knowledge regarding home maneuver for foreign body ingestion among mothers of toddlers in selected villages of district Mandi, Himachal Pradesh

Foreign body ingestion is a common and potentially life-threatening emergency among toddlers. Mothers play a vital role in prevention and immediate management, and adequate knowledge of home manoeuvres can help reduce complications and improve child safety. The main aim of the study was to assess the effectiveness of a structured teaching programme on knowledge regarding home manoeuvres for foreign body ingestion among mothers of toddlers in selected villages of District Mandi, Himachal Pradesh. A quantitative research approach with quasi-experimental non-randomized control group design was used. The study was conducted on 60 mothers of toddlers, with 30 in the experimental group and 30 in the control group. Samples were selected using non-probability convenient sampling technique from selected villages of District Mandi, Himachal Pradesh. Data were analyzed using descriptive and inferential statistics and presented through tables and bar diagrams. The pretest mean knowledge score was 10.13 in the experimental group and 10.03 in the control group, whereas the posttest mean scores were 19.76 and 10.46, respectively. The calculated paired 't' value in the experimental group was 14.82, higher than the table value of 2.05 at p≤0.05, while in the control group it was 1.12, lower than 2.05. Thus, the structured teaching programme had a significant impact on mothers' knowledge. A significant association was also found between posttest knowledge score and selected socio-demographic variables in the experimental group at p≤0.05 level of significance.

Published by: Yamini Sharma, Shephali Walia, Pallavi Mehra, Priyanka Sharma

Author: Yamini Sharma

Paper ID: V12I4-1187

Paper Status: published

Published: August 25, 2026

Full Details
Research Paper

Detection of Eye Diseases Using Machine Learning Techniques

Eye disorders have become one of the leading causes of vision loss around the globe. This highlights the importance of early accurate diagnosis of these disorders. Most of the current methods for diagnosing eye diseases use manual examination of retinal images and depend primarily on experienced ophthalmologists. These manual methods can take a lot of time to examine each eye(s) and can also be highly subjective in their determination of a diagnosis.In this project, we will develop an automated framework that uses machine-learning techniques to automatically detect and classify multiple eye disorders from retinal images.We only used traditional machine-learning methods in this work and did not consider using deep-learning models. The proposed framework includes systematic image preprocessing for standardising input images, automated feature extraction using feature extraction methods, and dataset balancing using the synthetic minority oversampling technique (SMOTE) to adjust for class imbalance in each of the datasets used for training and testing our classification system. The proposed framework includes the use of supervised machine-learning algorithms for the classification of all images in each class. The performance of the proposed machine-learning framework was evaluated thoroughly using various performance metrics including confusion matrices, ROC curves, precision–recall analysis, learning curve graphs, PCA visualisation, and cross-validation stability analysis. The results from the experimental evaluations indicated that the proposed machine-learning framework can generate very high classification accuracy and good generalisability for the various types of diseases evaluated using the proposed machine-learning classification system. Overall, the experimental results show that the proposed machine-learning framework can provide good quality decision support tools to use for early eye disorder diagnosis in clinical settings.

Published by: Vaishali Ashok Barse, Dr. Kavita Yogesh Suryawanshi

Author: Vaishali Ashok Barse

Paper ID: V12I4-1190

Paper Status: published

Published: August 19, 2026

Full Details
Research Paper

Altered Pattern of Calcium, Phosphorus, and Calcium/Phosphorus Ratio in Serum and Synovial Fluid of Rheumatoid Arthritis Patients

Abstract Rheumatoid Arthritis is a systemic autoimmune inflammatory disease characterized by synovitis and serositis (inflammation of the linning surfaces of the joints, pericardium, pleura and rheumatoid nodules). This study was carried to determine the status of biochemical parameters i.e. calcium, phosphorus and calcium/phosphorus ratio in serum and synovial fluid of RA patients. A total of 66 RA patients were included in the study. Out of which 48(72.7%) were female patients of RA and 18(27.3%) were male patients of RA. Some normal individuals (n=25) were also investigated. The levels of serum calcium and phosphorus were found to be significantly (p<0.001) lowered as compared to normal individuals. A significant (p<0.001) decrease in levels of calcium and phosphorus in synovial fluid of RA patients was observed. Calcium/phosphorus ratio was also found to be lowered in RA patients. It was also observed that calcium/phosphorus ratio was more decreased in females as compared to males.

Published by: Bhanoo Priya, Jai Bharti

Author: Bhanoo Priya

Paper ID: V12I4-1175

Paper Status: published

Published: August 18, 2026

Full Details