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Research Paper

Computational Study on Airfoil Flow Control Using Gurney Flap

Enhancing the performance of airfoils can help in improving the performance of many devices such as Darrieus Vertical Axis Wind Turbines (VAWTs.) Several methods have been proposed in the literature to control the flow over airfoils. These included using Gurney flap, using leading edge flap, slotted airfoils as well as others. The Gurney flap is a fixed flap installed normal to the airfoil surface at its trailing edge. The length of the Gurney flap, its position and its orientation are important design parameters investigated in the present work. The effect of Gurney flap parameters on the lift and drag forces as well as the lift to drag ratio (glide ratio) are assessed for different angles of attack. The present study was performed using Computational Fluid Dynamics (CFD) technique. The computational model was validated and mesh sensitivity tests were carried out to ensure accurate model results. The SST k-ω model of turbulence was used to close the Reynolds averaged Navier Stokes equations. The results showed that locating the Gurney flap on the top orientation of the airfoil has bad effect on lift and drag, while locating it on the lower side improved lift to drag ratio. Based on the significance increase of the glide ratio of airfoil with Gurney flap compared to the baseline airfoil, the best length of Gurney flap is 2% of chord length and the best position of Gurney flap to be added is to the airfoil trailing edge while the best orientation of the Gurney flap is down aligned with the airfoil pressure side. The lift coefficient is increased significantly by an average of 30%, also the drag coefficient is slightly increased by an average of 15% compared to the lift and drag generated by the baseline airfoil.

Published by: Ahmed K. Etman, Ahmed M.R. Elbaz

Author: Ahmed K. Etman

Paper ID: V11I4-1143

Paper Status: published

Published: July 8, 2025

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Research Paper

Optimizing Jira-Based Support Operations With AI: A Lightweight Framework for Smart Ticket Routing and SLA Breach Prediction

This paper introduces a lightweight AI-powered framework designed to enhance technical support operations within JIRA-based environments. By integrating Python scripts and machine learning models, the system automates ticket classification based on urgency and predicts potential SLA breaches before they occur. The framework uses historical ticket data to train classification algorithms, enabling proactive routing and escalation through JIRA’s REST API and Automation Rules. In real-world testing, the solution demonstrated a 34% reduction in ticket resolution time and improved SLA adherence by 40%. This approach eliminates the need for expensive plugins or enterprise licenses, making it a scalable and cost-effective automation strategy for small to mid-sized IT support teams.

Published by: Arooj Javed

Author: Arooj Javed

Paper ID: V11I4-1144

Paper Status: published

Published: July 7, 2025

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Research Paper

AI-Powered Dashboard for SLA Monitoring and Team Performance in JIRA

This paper introduces a visual analytics dashboard powered by AI and Python that helps technical support teams monitor SLA compliance, ticket trends, and team performance in real time. Built for JIRA-based environments, the dashboard collects and processes ticket metadata to visualize SLA breaches, categorize ticket flows, and highlight areas of delay. Designed with open-source libraries and scalable for small to medium support teams, the solution empowers stakeholders with actionable insights, improving service delivery and operational transparency.

Published by: Arooj Javed

Author: Arooj Javed

Paper ID: V11I4-1145

Paper Status: published

Published: July 7, 2025

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Thesis

A Study to Assess the Effectiveness of a Structured Teaching Programme on Knowledge Regarding Laparoscopic Transabdominal Cervical Cerclage among Fourth Year Basic B.Sc Nursing Students at Selected Nursing Colleges in the City

A transabdominal cerclage is highly effective in reducing both fetal loss and premature birth. It can be placed before (interval) and during pregnancy and by laparoscopic (LC) or open laparotomy (AC) procedure. The Fourth-year BSc nursing students often come in close contact with patients and know the complete obstetrics history of the woman; hence assess the knowledge regarding laparoscopic transabdominal cervical cerclage (LCTAC) among fourth-year BSc Nursing students. The objectives of the study were: 1. To assess the knowledge regarding laparoscopic transabdominal cervical cerclage. 2. To assess the effectiveness of a structured teaching program regarding laparoscopic transabdominal cervical cerclage. 3. To compare the level of knowledge between the pre-test and post-test. Students with selected sociodemographic variables. The material and methods of study were developed in the form of three sections as demographic variables, general knowledge regarding laparoscopic transabdominal cervical cerclage. The non-probability purposive sampling technique was used for selecting 60 students from nursing colleges. Results of the study indicated that findings of demographic variable reveals that, there was no one variable found statistically significant association with knowledge score about Laparoscopic Transabdominal Cervical Cerclage with selected demographic variables. The finding of the study reveals that, in the pre-test majority of the samples, 35 (58.33%), had inadequate knowledge, 25(41.66%) had Moderate knowledge, and none of the samples had adequate knowledge regarding laparoscopic transabdominal cervical cerclage. With regard s the post-test knowledge majority of the samples, 30(50%), had Moderate knowledge, 20(33.33%) had adequate knowledge, and 10(16.66%) had inadequate knowledge regarding laparoscopic transabdominal cervical cerclage. The study concludes that students, after receiving knowledge on Laparoscopic Transabdominal Cervical Cerclages higher knowledge scores in the post-test than pre-test. The findings of the present study indicated that nursing students have adequate knowledge regarding Laparoscopic Transabdominal Cervical Cerclages.

Published by: Bidyarani Yumnam, Anamika Satyaprem Bobade

Author: Bidyarani Yumnam

Paper ID: V11I4-1141

Paper Status: published

Published: July 5, 2025

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Thesis

A Study to Assess the Knowledge and Attitude Regarding Integration of Artificial Intelligence in B.Sc Nursing Curriculum among 4th Year Students of B.Sc Nursing in Selected Colleges of Nursing in the City

To assess the knowledge regarding the integration of artificial intelligence in the nursing curriculum.To assess the attitude regarding the integration of artificial intelligence in the nursing curriculum.To correlate the level of knowledge and attitude regarding the integration of artificial intelligence in the nursing curriculum. Result: the level of Knowledge among 4th year B.Sc. Nursingstudents’’ majority of the samples 50(50%) moderate knowledge, 44(44%) hava Inadequate knowledge, and 6(6%) have Adequate knowledge. the level of attitude among 4th year B.Sc. The majority of the nursing students ' samples, 86(86%) Positive attitudes, and 14(14%) have negative attitudes. There were 100 compressions between Comparisons between the Level of Knowledge and Attitude Regarding the Integration of AI in Nursing Curriculum. Each of them had answered 30 questions and an attitude scale. They assessed the knowledge and attitude regarding the integration of AI in the nursing curriculum among 4th year B.Sc students of B.Sc nursing, and correct answers were recorded as mean and standard deviation of the level of Knowledge and attitude. The paired t-test was applied to compare the difference between the Level of Knowledge and Attitude Regarding the Integration of AI Into Nursing Curriculum. It was found that the Level of Knowledge and Attitude Regarding the Integration of AI in the Nursing Curriculum, the paired’ test value was 23.350* at the level of P 0.05. Since the P value is less than 0.05 (P value = 0.0001) difference in scores is statistically significant. The researcher concludes at a 5% level of significance and 198 degrees of freedom that the above data gives sufficient evidence to conclude that Comparison between Knowledge and Attitude Regarding Integration of AI In Nursing Curriculum, hence rejects the null hypothesis the research hypothesis.

Published by: Anamika Satyaprem Bobade, Bidyarani Yumnam

Author: Anamika Satyaprem Bobade

Paper ID: V11I4-1140

Paper Status: published

Published: July 5, 2025

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Review Paper

Myocardial Infarction with Non-Obstructive Coronary Artery (Minoca): A Systematic Review

Myocardial infarction with nonobstructive coronary arteries (MINOCA), which is characterized by clinical evidence of myocardial infarction (MI) with normal or near-normal coronary arteries on angiography (stenosis 50%), continues to be a perplexing clinical entity. Recent years have seen significant progress in our understanding of this illness. It is being researched and further analyzed because the precise pathophysiology is unclear. Recommendations state that MINOCA is a group of different illnesses with a range of pathological underlying causes. Given the variety of possible pathogenic reasons, it is unclear if the conventional secondary prevention and treatment strategy for MI with obstructive coronary artery disease (MI-CAD) is the best choice for those with MINOCA. There are currently no recognized predictors or prognoses for MINOCA patients. There are currently no documented vaticinations or predictors for MINOCA cases. According to guidelines, MINOCA is a collection of many illnesses with distinct pathogenic processes. Since there are multiple possible pathological mechanisms, it isn't certain that the classical secondary forestallment and treatment strategy for MI with obstructive coronary artery complaint (MI-CAD) is optimal for MINOCA cases. Uncertainty surrounds the prognosis and predictors for the MINOCA case. Although the prognosis is slightly better for MINOCA cases than for MI-CAD cases, MINOCA is not always benign.

Published by: Richa Sinha, Manroop Kaur Bajwa

Author: Richa Sinha

Paper ID: V11I4-1138

Paper Status: published

Published: July 5, 2025

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