European Journal of Science, Innovation and Technology

Academic Background, Engagement, and Self-Efficacy: A Correlational Analysis to Academic Achievement of Pre-service Mathematics Teachers

Christopher R. Vergara — Mon, 27 Jan 2025 00:00:00 +0200

Pre-service mathematics teachers’ academic success is a crucial indicator of effective and competent mathematics educators. Identifying the factors influencing their academic achievement offers valuable insights for teacher preparation programs. This study investigates the interplay between academic background, academic engagement, mathematics self-efficacy, and academic achievement. The study employed a descriptive-correlational research design encompassed 71 pre-service mathematics teachers who participated voluntarily. Findings indicate pre-service teachers had diverse academic backgrounds and held moderate levels of academic achievement, academic engagement, and mathematics self-efficacy. Notably, disparities in mathematics achievement are evident, with male pre-service teachers and those aspiring to specialize in mathematics achieving higher levels. Furthermore, the study underscores a positive correlation between heightened academic engagement, self-efficacy, and enhanced mathematics achievement, underscoring the pivotal role of active engagement and confidence in fostering mathematical proficiency among pre-service teachers.

Feasibility of Radiation Schemes to Predict Extreme Temperature Conditions over Bangladesh

Gazi Mamunar Rashid, MM Touhid Hossain, Md. Abdullah Elias Akhter — Thu, 30 Jan 2025 00:00:00 +0200

An extreme temperature is a weather phenomenon that is distinguished by marked cooling or heating of the air, or with the invasion of very cold or hot air, over a large area. The present study is associated with the simulation of regional climate using the Weather Research and Forecasting (WRF) model that was experimented through 30 different combinations of radiation parameterization schemes over Bangladesh. The intention was to investigate the response to the radiation parameters schemes for dynamic down-scaling of climatic variables. The predicted temperature of 30 different WRF setups were analyzed and compared with the Bangladesh Meteorological Department (BMD) recorded data and were found sensitive to the radiation physics on the basis of Root Mean Square Error (RMSE) at 2-meter air temperature on 02-05 January 2019, 02-05 February 2019 and 28-31 December 2019 for Cold Wave (CW), and 24-27 April 2019, 09-12 May 2019 and 19-22 May 2019 for Heat Wave (HW) at 34 stations over Bangladesh. We conclude that the Rapid Radiative Transfer Model (RRTM) for long wave and Dudhia for short wave schemes are the most appropriate combinations to simulate in the extreme temperature. Using the selected combinations of WRF parameterizations to downscale the extreme weather events, which showed good agreement with the reference data. It was suggested WRF parameters from this study could be utilized for regional climate modeling of Bangladesh.

Quality Health Information for Health Annual Work Plans in Implementing Strategic Plans to Reduce Maternal Morbidity and Mortality, Migori County, Kenya

Wilfred Obwocha — Sat, 08 Feb 2025 00:00:00 +0200

It is important to determine quality of health information for supporting health annual work plans in implementing strategic plans to reduce/prevent maternal morbidity and mortality in the four study health facilities in Migori county; County referral, St Joseph mission, Rongo Sub County referral and Isebania county hospitals. The study used cross-section design. The sample frame population was 260 and the sample size was 155 determined by Cochran method. Data were collected using closed ended questionnaires and were analyzed using statistical package for social scientists (SPSS). The methods of analysis of data were descriptive. Results were presented in charts and percentage tables. In the four facilities data were collected from healthcare workers and analyzed to determine quality of health information to support annual plans in implementing strategic health plans. The study results revealed that the most used system was electronic; 86% at St Joseph mission hospital while Migori county referral hospital was 40%. Routine health information software (RHIS) was most used ranging between 54% and 92%. Then analytic software knowledge among healthcare workers was 28% and electronic health records (EHR) 19%. Achievements in midwifery training were 93%, health information systems 61%, data analytics 28% and data quality improvement training covered 68%, and financial support 17%. The use of electronic health records was highly limited and yet it is key to quality data, information and healthcare services. Therefore, there is high need for investment as county in electronic healthcare systems including healthcare data framework to improve information quality.

Framework for Improving Quality Health Information to Reduce Maternal Morbidity and Mortality in Migori County, Kenya

Wilfred Obwocha — Sat, 08 Feb 2025 00:00:00 +0200

Quality health framework is a reference guide to evaluate and improve healthcare. It provides guidance to health services, on what good quality care entails and how it can be evaluated and demonstrated. Healthcare and quality are complex and highly vary between low and high income countries. Using quality health information reduces maternal morbidity and mortality among healthcare facilities; County referral, St Joseph mission, Rongo Sub County referral and Isebania county hospitals. Therefore, a framework was developed to improve data/ information quality and in turn maternal healthcare. The study used cross-sectional design and the population sample size for the study was 155 healthcare workers. The sample size was determined by Cochran method and closed ended questionnaires were used to collect data. Data analysis used statistical package for social scientists (SPSS), and results were presented in percentages using tables and charts. These data were collected from healthcare workers and analyzed to determine quality of health information to reduce/ prevent maternal morbidity and mortality in Migori County. The study revealed that, the framework can improve quality of data, information and healthcare services. This resulted from data collected and analyzed using basic variables; Agree/ strongly agree achieving 95% for Migori county referral hospital, St Joseph 94%, Rongo subcounty referral hospital 96% and Isebania county hospital 95% and on average coverage was 95%. The frame is good for improving data/ information quality and its implementation is necessary due to its effectiveness.

Enhanced Crude Oil Pipeline Leakage Detection System Using Reinforcement Learning

Nkolika O. Nwazor, Lloyd E. Ogbondamati — Mon, 10 Feb 2025 00:00:00 +0200

This work used advanced reinforcement learning (RL) techniques to enhance crude oil pipeline leakage detection systems to address the frequent occurrence of undetected or misidentified leaks, which can lead to significant financial losses and safety risks. The existing pipeline monitoring system's performance was analysed, identifying the detection accuracy and response time limitations. Reinforcement learning algorithms were then integrated to optimize the system's ability to detect leaks and minimize false positives. The RL model was trained to enhance its performance through iterative learning and feedback, ultimately improving its accuracy to 100% and increasing precision to 100%. This was achieved by adjusting detection thresholds and refining control actions based on real-time data. When the system detected a pressure drop from 55 psi to 36 psi, reinforcement control measures were successfully implemented to restore pressure to 55 psi. Additionally, a leakage was accurately located at 600 meters along the pipeline, allowing for targeted intervention. The results also demonstrated the impact of flow rate and pressure variations on detection performance, emphasizing the importance of dynamic and responsive control strategies. The integration of RL techniques offers a significant advancement over traditional methods, providing a robust framework for managing pipeline integrity and ensuring environmental safety. This study sets a precedent for future developments in pipeline monitoring and management, advocating for the continuous incorporation of innovative technologies in maintaining infrastructure resilience.

Real-Time Monitoring and Control of Crude Oil Export Pumps

Nkolika O. Nwazor, Justus N. Dike, Ezekiel O. Ashaka — Mon, 10 Feb 2025 00:00:00 +0200

This paper is on the application of Model Reference Adaptive Control (MRAC) in optimizing the performance of crude oil export pumps with the goals of improving pump performance, enhancing system reliability, and increasing energy efficiency, by dynamically adjusting operational parameters in response to real-time changes in flow rates and crude oil properties. Manual control was compared to MRAC control, with a focus on error rate and accuracy rate evaluation. The MRAC method was implemented to reduce error rates and enhance control precision. The findings revealed significant improvements in both error and accuracy rates. The efficiency of the manual control is 84.5% while the efficiency of the MRAC is 90%. These results demonstrate the effectiveness of MRAC in optimizing pump operations, enhancing reliability, and reducing energy consumption. This work recommends the integration of MRAC in crude oil export pump systems to ensure sustained performance improvements, operational efficiency, efficient management of energy resources and the reduction of operational anomalies in oil export operations.

Control Process Stability Analysis of a Solid-Liquid Separation System

A. A Tamunobere, Z. Jaja, J. I. Sodiki — Thu, 13 Feb 2025 00:00:00 +0200

A key performance indicator in any control process is the sustainability of steady state operation for attainment of stability of the applicable control mechanism. In this work, analysis is carried out on the response of a pressure controller with set pressure of 3bar, 7bar and 12bar and the time stability is attained. Pressure is considered as the operating parameter of the control process using a Differential Pressure Cell (DPC) as the controller mechanism. Using a Proportional Integral Derivative (PID) process controller, the performance of a desander was monitored. At 12 bar set point, the result showed that, with PID values of 0.09518, 0.1438/s, 0s, the operation attained stability in 5.53s in the automatic mode, whereas in the manual mode operation, stability was achieved after 7.96s with PID values of 13, 8/s and 7s manually selected. At 7bar set point, stability was attained in 4.7s with PID values of 1.076, 0.87798/s, 0.19657s in automatic mode whereas in manual mode the system stabilized in 4.79s with PID values of 7, 9/s, 5s. At 3bar set point, the controller gain stability in 5.19s, with PID values of 1.3608, 1.0562, 0.41093s in automatic mode whereas in manual mode, stability was attained in 12.5s with PID values of 12, 8/s, 5s respectively.

Vote Buying and the Integrity of 2019 and 2023 General Elections in Nigeria

Ifeoma Ethel Ezeabasili — Fri, 14 Feb 2025 00:00:00 +0200

Vote buying is a persistent challenge that has undermined the integrity of elections in Nigeria. It is a practice where political actors offer material inducements, such as cash, food, or other gifts, in exchange for votes. This practice subverts the principles of free and fair elections by distorting the electorate's will and compromising the democratic process. This study examines the impact of vote buying on the Integrity of 2019 and 2023 in Nigerian General Elections. The study utilized the Principal-Agent Theory as the theoretical framework and secondary data were sourced from textbooks, journal articles, newspaper, government reports. The collected data were analyzed with content analysis and the findings revealed that the widespread vote buying in 2019 and 2023 distorted and compromised the election integrity. It was also revealed that the persistent vote buying in the 2019 and 2023 general elections has contributed to low voter turnout and further erosion of public trust in the electoral process. The study concluded that the widespread prevalence of vote buying has distorted the electoral process, eroded public trust, concentrated political power, and perpetuated the status quo, with long-term implications for democratic consolidation. The study therefore made the following recommendations: (1) enacting robust legislation that clearly defines and prohibits vote buying, with stringent penalties for offenders, (2) adopting biometric voter registration and identification systems to enhance the integrity of the voter roll and reduce the potential for vote buying, and (3) implementing comprehensive civic and voter education programs to raise awareness among citizens about the negative impacts of vote buying on the democratic process.