Examination Integrity in India: Analysing the Role of Political Influence, Governance Deficits, and Institutional Weaknesses in Examination Paper Leaks
India has one of the world's oldest and largest education systems, where competitive examinations and board assessments play a crucial role in determining academic and career opportunities. However, examination paper leaks, cheating, and the re-conduct of exams undermine the credibility of the education system, affecting deserving aspirants' time, effort, and morale. This study examines how political influence, governance deficits, corruption, and institutional weaknesses contribute to breaches of examination integrity. METHODOLOGY: This study adopts a descriptive and analytical research design based on both primary and secondary sources of data. Primary data were collected through a structured questionnaire administered through Google Forms, with responses from 80 participants. Approximately 62% of respondents were school students, 17–18% were college students from institutions across Delhi NCR, while the remaining participants comprised working professionals from various sectors. Secondary data were collected from government reports, official documents, news articles, policy papers, and published research studies to provide contextual understanding and validate primary findings. RESULT: The findings reveal that most respondents consider examination paper leaks a serious threat to fairness and merit. They identified political influence, corruption, and weak governance as key factors contributing to these incidents. Secondary data further indicate that paper leaks affect millions of candidates, increase public expenditure due to re-conducted examinations, and weaken public trust in the examination system. CONCLUSION: The study concludes that examination paper leaks are not only educational failures but also governance challenges arising from corruption, weak accountability, and institutional shortcomings. Strengthening examination security, transparency, and institutional accountability is essential to safeguard meritocracy, restore public confidence, and protect the integrity of India's education system.
Published by: Divit Batra, Aadit Batra, Amit Gurjar
Author: Divit Batra
Paper ID: V12I4-1176
Paper Status: published
Published: August 2, 2026
Automated Video Generation using Deep Learning
The increasing utilization of multimedia content in education, marketing, and digital communication has created a growing demand for efficient video generation systems. This paper presents an Automated Video Generator that converts textual input into narrated videos using a modular deep learning-based pipeline. The proposed system generates a narrative, retrieves context-relevant images, synthesizes speech using text-to-speech technology, and composes synchronized videos through a web-based Django framework. Experimental results demonstrate improved efficiency, stable performance, and audio-visual synchronization, making the system suitable for educators, marketers, and content creators while reducing manual effort and production time. ``` Batch11 Automated Video Generator Using Deep Learning.pdf
Published by: V. Shiva Kumar, K. Eshwar, M. Raja Laxmi, V. Kavya Sri
Author: V. Shiva Kumar
Paper ID: V12I4-1173
Paper Status: published
Published: August 2, 2026
Strengthening Hospital Disaster Preparedness at District General Hospital Matara, Sri Lanka: A Case Study of Preparedness Assessment and Improvement Strategies
Hospital disaster preparedness is essential for ensuring continuity of healthcare services and minimizing the impact of emergencies and disasters. Despite the availability of national disaster preparedness guidelines, hospitals face challenges in maintaining comprehensive and up-to-date preparedness systems. This study evaluated disaster preparedness at District General Hospital Matara, Sri Lanka, identified key operational challenges, and proposed evidence-based strategies to strengthen organizational resilience. A descriptive case study design was employed using methodological triangulation. Data were collected through document review, key informant interviews, direct observations, and assessment using a structured checklist adapted from the World Health Organization Hospital Emergency Response Checklist and national disaster preparedness guidelines. The checklist comprised 43 indicators across 12 preparedness domains. A study-specific Composite Hospital Disaster Preparedness Score (CHDPS) was developed to summarize preparedness across organizational domains. Operational challenges were prioritized using the Nominal Group Technique, and the highest-priority problem was further analysed through root cause analysis to identify underlying organizational factors. The overall CHDPS was 74.4% (64/86). The highest preparedness scores were observed in Recovery and Termination (100%), External Coordination (83.3%), Security and Access Control (83.3%), and Notification and Activation (80.0%). Lower preparedness scores were identified in Staff Mobilization and Welfare (60.0%), Triage and Patient Management (62.5%), and Debriefing and Quality Improvement (66.7%). The principal operational challenge was an outdated Hospital Disaster Preparedness and Response Plan, with root causes related to governance, organizational processes, human resources, and monitoring mechanisms. The study demonstrates that structured preparedness assessment combined with quality improvement methodologies can effectively identify institutional strengths and operational gaps. The proposed CHDPS provides a practical framework for monitoring hospital disaster preparedness and supporting continuous organizational improvement. The findings offer practical guidance for strengthening disaster preparedness and enhancing health system resilience in Sri Lanka and other comparable resource-constrained
Published by: Sasikumar S, Thotagamuwa T.W.A.N, Maithily B
Author: Sasikumar S
Paper ID: V12I4-1164
Paper Status: published
Published: July 27, 2026
Pain Recognition with Physiological Signals using Hybrid Models
The pain measurement is a very vital aspect of healthcare, but the traditional approaches offer extensive dependence on manual feature extracting through physiological measurements and clinical judgement. These conventional methods involve expert knowledge, they are time consuming and have a tendency to fail to be generalized effectively nor across various groups of patients. To overcome these shortcomings, this paper comes up with a proposal of an automated pain recognition model that processes physiological signals through a hybrid deep learning model. The model combines Convolutional Neural networks, Bidirectional Long short term memory networks, and Gated Recurrent Units with which hierarchical spatial and time representations of raw signals are learned automatically. The architecture captures the local signal properties as well as the long-range contextual dependencies which enhance the difference between pain and no-pain states. Further, a stacking classifier ensemble is used to improve the prediction robustness and generally improve its performance. The proposed method has a high level of reliability as experimental assessment shows that this method is accurate at the level of 99. The system offers scalable and intelligent capability of objective pain monitoring which aids in supporting the making of better clinical decisions and patient care within the contemporary healthcare settings.
Published by: A. Harsha Vardhan Reddy, Dr. Burla Srinivas, Venkata Lakshmi
Author: A. Harsha Vardhan Reddy
Paper ID: V12I4-1172
Paper Status: published
Published: July 27, 2026
Copper (II) Schiff Base Complex: Synthesis, Characterization, Enhanced Antibacterial Activity and Electrochemical Drug Detection
A novel Schiff base ligand (L), namely (E)-N-(1-(2,4,5-trimethylphenyl)ethylidene)-1H-1,2,4-triazol-3-amine, derived from a substituted phenolic precursor, and its copper(II) complex were successfully synthesized and characterized using various spectroscopic techniques, including FTIR, NMR, and elemental analysis. Spectral investigations confirmed the coordination of the ligand to the Cu(II) ion through the azomethine nitrogen and phenolic oxygen atoms, indicating bidentate chelation and the formation of a stable metal complex. The antimicrobial activity of the synthesized compounds was evaluated against Escherichia coli using the agar well diffusion method. The Cu(L)₂ complex exhibited significantly enhanced antibacterial activity compared to the free ligand, as evidenced by larger zones of inhibition. A concentration-dependent increase in inhibition diameter was observed, demonstrating improved efficacy at higher concentrations. The enhanced biological performance of the metal complex can be attributed to chelation-induced increases in lipophilicity, which facilitate better penetration through the bacterial cell membrane, along with possible metal-mediated interference in essential cellular processes. In addition to its antimicrobial properties, the Cu(L)₂ complex was investigated as an electrochemical sensing material for the detection of Naproxen (NPR). The modified electrode exhibited a linear response over the concentration range of 1–10 μM, demonstrating excellent sensing capability toward the target analyte. The sensor showed a sensitivity of 0.13 μA μM⁻¹ and achieved a limit of detection (LOD) of 1 μM. The enhanced electrochemical performance is attributed to the redox-active Cu(II) center and the efficient electron-transfer characteristics of the Schiff base framework, which promote rapid and sensitive analyte detection.
Published by: Pawan R. Jagnit, Satish V. Jadhav, Yogesh I. Biradar, Dr. Sandip R. Kelode
Author: Pawan R. Jagnit
Paper ID: V12I4-1157
Paper Status: published
Published: July 17, 2026
Ramana Pada Pancharatnam
Ramana Pada Pancharatnam lays the spiritual journey of Sivaprakasam Pillai. Pillai was the first to receive written instructions about self – enquiry from Ramana Maharshi. There were questions by Sivaprakasam Pillai and Ramana’s replies to them forming the foundation to the text ‘Nan Yaar’ (Who am I?), a ready reckoner to all Spiritual seekers. His experiences of meeting Ramana, his guidance to him and many other instances have been documented in the works – Anugraha Ahaval, Sri Ramana Charitra Ahaval and Ramana Pada Malai. Smt. Sulochana Natarajan inspired by this work of Sivaprakasam Pillai has composed music and presented the Ramana Pada Malai similar to the lines of Thyagaraja Swamy’s Pancharatna Kritis using ragas Nattai, Goula, Arabhi, Varali and Sri. The pallavi is aptly chosen as Ramanan Padam Vazhgave. The attempt to translate to Kannada has also happened here, giving the english meaning along with the verse. The text also includes stories related to the verses showing Ramana’s life – his compassion towards devotees, animals, and even sinners by reminding everyone about Self enquiry and emphasising on liberating oneself from this world or the cycle of birth and death, resting in the truth of the Self.
Published by: Revathi Sankar, Dr. Ambika Kameshwar
Author: Revathi Sankar
Paper ID: V12I4-1145
Paper Status: published
Published: July 14, 2026
