Current Issue
Volume 10 - Issue 05 (September - October 2026)
| Title: | Development of an Intelligent Fault Detection and Calassification System for Power Grids using Artificial Neural Network |
| Authors: | Alaa Abdulwahhab Azeez Baker |
| Source: | International Journal of Latest Research in Engineering and Management, pp 01 - 07, Vol 10 - No. 05, 2026 |
| Abstract: | This research addresses the problem of faults in modern electrical grids, which cause power outages, reduced system stability, and financial losses. With the increasing sophistication of power systems due to their integration with artificial intelligence technologies, fault detection methods have become more efficient and effective. This paper proposes intelligent fault detection methods based on supervised deep learning techniques. These methods involve collecting existing electrical gauges from the power system, preprocessing the data, and applying a classification model to differentiate between normal and fault states. The model is trained using classified voltage and current datasets to enhance detection accuracy. Experimental results demonstrate that the proposed method achieves higher accuracy and faster fault detection compared to traditional methods. Its adoption enables efficient handling of large datasets, providing a scalable solution that can be integrated with other technologies to make real-time fault monitoring in smart grids more effective. Overall, this study highlights the importance of using intelligent technologies to improve the performance and safety of modern power systems. |
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| Title: | Research on University Lecturers' Intention to Mentor Students in Academic Competition: A literature Review |
| Authors: | Tang Ying, Wu Zhaohui, Zhang Yuhan, Sun Jian |
| Source: | International Journal of Latest Research in Engineering and Management, pp 08 - 12, Vol 10 - No. 05, 2026 |
| Abstract: | Academic competitions benefit university students by improving professional skills, innovative thinking and autonomous learning, with lecturers’ mentoring which serves as a critical guarantee for these outcomes. However, few studies explore factors affecting lecturers’ intention to mentor students in competitions. This paper develops a conceptual framework based on the Theory of Reasoned Action (TRA), identifying attitude toward mentoring and subjective norms as two core predictors. Positive attitudes and favorable subjective norms jointly promote their mentoring willingness. This study is limited to theoretical derivation without empirical tests. Future research can empirically verify the model and explore more influencing factors in higher education contexts. |
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| Title: | Development of a Standardized Time System in an Aerospace Manufacturing Company |
| Authors: | Ernesto Ramírez Cárdenas, Gabriela Espinoza Erunes, Martha E. Flores Rivera, María del Pilar Lizardi Duarte and Sergio Raúl Ruiz Ruiz |
| Source: | International Journal of Latest Research in Engineering and Management, pp 13 - 17, Vol 10 - No. 05, 2026 |
| Abstract: | This study was conducted in the production area of a manufacturing company where, due to the lack of updated standard times, there is no system for calculating production capacity, resulting in uncertainty in planning, resource allocation, and demand fulfillment. Therefore, the objective was to develop a standardized time study system that would allow for the calculation of production capacity, timely resource allocation, and improved demand fulfillment. The methodology employed consisted of identifying the area under study, classifying product families, conducting time studies using stopwatches, and finally calculating production capacity based on required and available hours. The results allowed for the identification and standardization of process operations. With the acquisition of reliable standard times for each product family, a capacity calculation model based on hours was established, providing objective information for production planning and personnel allocation. It is concluded that the implementation of the system improves the reliability of decision-making, reduces dependence on empirical estimates, strengthens the management of productive capacity, and contributes to meeting demand, optimizing resources, and increasing operational efficiency in the area of connectors. |
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