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
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
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
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
A Study to Assess the Knowledge and Attitude Regarding Palliative Care among Oncology Nurses at Selected Hospitals in the City.
Palliative care improves the quality of life of patients and that of their families who are facing challenges associated with life-threatening illness, whether physical, psychological, social, or spiritual. The quality of life of caregivers improves as well. Each year, an estimated 56.8 million people, including 25.7 million in the last year of life, need palliative care.Worldwide, only about 14% of people who need palliative care currently receive it.Unnecessarily restrictive regulations for morphine and other essential controlled palliative medicines deny access to adequate palliative care. Adequate national policies, programmes, resources, and training on palliative care among health professionals are urgently needed to improve access .“A study to assess the knowledge and attitude regarding palliative care among oncology nurses at selected hospitals in the city”.Non-probability Convenient sampling technique was used and the sample size was 60 nurses, the majority of the samples, 9(15%) had having inadequate level of knowledge, where as 23(38%) had moderate knowledge and 28(46.6%) had having adequate knowledge level on PC. Attitude shows majority of the samples, 23(38%) Positive attitude, and 37(62%) have a Negative attitude. Association between Knowledge regarding PC With Selected Demographic Variables. In order to compute the association between the level of knowledge score and demographic variables, chi-square was applied, and the value was observed at 5% significance level. Variables are found statistically significant association with the knowledge score about PC selected demographic variables. association between levels of attitude score on PC with selected demographic variables. In order to compute the association between the level of attitude score and demographic variables, chi-square was applied, and the value was observed at a 0.05 significance level. The chi-square value of the demographic variables, such as education was χ = 13.296 with a 3 degree of freedom and year of experience χ = 7.118 with a 3 degree of freedom showed significant association with level of attitude at 0.05 level, and there were no other demographic variables found association with level of attitude on PC
Published by: Alishiba Bhosale, Anamika Satyaprem Bobade
Author: Alishiba Bhosale
Paper ID: V11I3-1402
Paper Status: published
Published: July 2, 2025
Time Series Forecasting through Hybrid ARIMA-ANN Modelling for Rice in Odisha
Rice, being the staple food grain of Odisha, holds a crucial place in the state’s economy and food security. Rice holds around 69% of the total cultivable area in Odisha, making it crucial to have an accurate forecast of its status for stakeholders in agriculture. Modelling and forecasting of time series dataset of yield and production of rice from 1970-71 to 2019-20 is carried out in this study, using Auto Regressive integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and Hybrid ARIMA-ANN methodologies. ARIMA is a linear modelling approach where whereas ANN is more of a non-linear modelling technique. The hybrid ARIMA-ANN methodology integrates the strengths of both models to effectively capture both linear and non-linear patterns within the dataset under study. It was found that ARIMA(1,1,1) with constant and under the developed ANN models, the Neural Network Autoregression(NNAR) of order NNAR(3,2) came out to be the best fitted model for both of the variables under study. ARIMA(1,1,1)-NNAR(1,1) is found to be suitable for both yield and production of rice in Odisha. All three models are compared using accuracy measures like RMSE and MAPE, and the hybrid methodology is found to be superior to others.
Published by: Madhu Chhanda Kishan
Author: Madhu Chhanda Kishan
Paper ID: V11I3-1404
Paper Status: published
Published: July 2, 2025
