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Background: Emergency contraceptive pills (ECPs) are significantly underutilized in many parts of the world, especially in South-Asia. Within Pakistan, despite the population surge, the utilization of ECPs remains alarmingly low. The purpose of this study was to investigate the knowledge and practices regarding ECPs amongst married women and men in Karachi, Pakistan and the possible barriers hindering access to and use of these contraceptives. Methodology: A multi-centric cross-sectional study was conducted in Karachi, Pakistan. Interviews were conducted with participants using validated questionnaire involving different sections on demographics, knowledge, practices, and barriers to ECP use. Categorical variables were summarized as frequencies and percentages while continuous variables were characterized using mean and standard deviation. A chi-square test of variance was used for association between knowledge scores and different categorical values. A p-value of < 0.05 at 95% CI was statistically significant. Results: Over half of the respondents (52.5%) were not using any method of contraception. 11.1% of respondents had used ECP at some point in their life. 337 (85.8%) participants had low knowledge, 55 (14%) had moderate while only 1 (0.25%) had high knowledge regarding ECPs. There was no significant association of knowledge scores with gender, age, employment status or parity. However, participants who had received counseling for family planning in the past or had previously used ECPs had significantly higher knowledge regarding ECPs. A majority 58% (221) of the participants expressed concerns about the potential side effects and 128 (33.9%) of them believed that ECPs were in contradiction to their religious and moral values. Conclusion: Our study in Karachi, Pakistan, highlights critical challenges in ECP awareness, utilization, and family planning. Although the results show improved ECP usage than studies previously done in Pakistan, there is a further need to increase the reach of ECPs through a variety of methods. Persistent myths and misconceptions and a severe lack of awareness further hinders their use. [ABSTRACT FROM AUTHOR]

Real-time monitoring of transient stability has gained significant importance in the power system. This paper proposes an advanced hybrid Transient Stability Assessment (TSA) monitoring system, composed of a Convolutional Neural Network (CNN) and Random Forest (RF) classifier which captures the PMU measurements in real-time. CNN utilizes heatmaps for detecting the transient stability status which is hereby used as a feature extractor for the RF classifier. The IEEE-14 and the IEEE-39 bus systems are used as case studies in MATLAB. A wind turbine with a doubly-fed induction generator is also installed to inspect its impact on the power system stability. The efficiency of the system is tested under different contingency scenarios by implementing various faults on distinct locations under dynamic loading conditions. The test results verified that the proposed hybrid CNN-RF (Convolutional Neural Network-Random Forest) model exhibited excellent results in terms of monitoring accuracy, higher precision, and performance in the presence of noise. [ABSTRACT FROM AUTHOR]