Middle East Journal of Applied Science & Technology
Volume 9 Issue 2 April-June 2026
Current Issue
Research Article
Lived Experiences of Criminology Faculty Teaching in Industrial Security Management Program
Carolyn E. Fernandez, Bernaflor B. Canape & Jose F. Cuevas Jr.
Abstract: Background: This study explored the lived experiences of Criminology faculty members who teach BSISM courses. It focused on understanding how faculty navigate the demands of teaching Industrial Security Management (ISM) subjects within the province of Misamis Occidental, Philippines. The study highlights the importance of supportive relationships, institutional resources, and conducive learning environments in shaping teaching effectiveness and faculty adjustment. Aims: This study aims to explore how criminology faculty members cope with, adjust to, and experience teaching ISM subjects. Methods: The study employed a qualitative phenomenological research design. It was conducted among 15 criminology faculty members who are currently teaching or have previously taught ISM courses, selected based on the inclusion criterion of relevant teaching experience. Data collection continued until saturation was reached, meaning no new significant themes emerged. Data were analyzed using Moustakas’ method of data analysis. Tool: Data were collected using an interview guide questionnaire designed to elicit participants lived experiences and insights regarding teaching ISM courses. Results: The study revealed six major themes that describe the lived experiences of criminology faculty teaching ISM courses. Faculty members experienced physical and mental fatigue, highlighting the body as a site of strain due to the demands of teaching unfamiliar or specialized subjects. Despite these challenges, they demonstrated adaptability and strong emotional investment in their teaching roles. They also navigated present demands while finding personal fulfillment in their teaching journey. The classroom environment emerged as a significant factor influencing both teaching and learning experiences. Additionally, supportive relationships with colleagues and administrators played a crucial role in enhancing their teaching effectiveness. Technology was identified as an important enabler of effective instruction, while purpose-driven engagement and motivation helped sustain their commitment to teaching ISM. Overall, the findings emphasize the importance of institutional support, adequate resources, and positive learning environments in fostering faculty adjustment and effectiveness.
Research Article
Ibragimov Mirfayz Ikrom Ugli
Abstract: This article analyzes the issue of the relationship between the state and society in Western philosophical thought from a historical and philosophical perspective. It examines the views of ancient Greek thinkers such as Socrates, Plato, and Aristotle, as well as the socio-political ideas of modern philosophers including Hobbes, Rousseau, and Voltaire. In addition, the essence of the state, its role in society, and the interrelationship between the individual, society, and the state are explored. Furthermore, theoretical approaches formed in different historical periods are comparatively analyzed, and their common and distinctive features are identified.
Research Article
Nayyar Ahmed Khan, Mohammad Ahmad, Rim Hamdoui, Asif Rashid Khan, Sivaram Rajeyyagari, Md. Mobin Akhtar & Ahmad Masih Uddin Siddiqi
Abstract: Attendance tracking is a fundamental aspect of educational management systems. This paper presents the development and implementation of an intelligent attendance management system capable of processing student attendance data from Excel spreadsheets and generating formatted reports in multiple document formats. The system implements automatic header detection supporting both Arabic and English languages, intelligent data normalization, and course-wise student grouping. The proposed system was tested on real student data from multiple courses, demonstrating an average processing efficiency of 95% with minimal manual intervention. Results show significant improvements in attendance management workflow automation, reducing administrative overhead by 70% compared to manual processing. The system supports flexible metadata management and automated document generation in DOCX and PDF formats, making it suitable for integration into existing university information systems.
Research Article
Nayyar Ahmed Khan, Mohammad Ahmad, Rim Hamdoui, Asif Rashid Khan, Sivaram Rajeyyagari, Md. Mobin Akhtar & Ahmad Masih Uddin Siddiqi
Abstract: This article presents a comprehensive LaTeX manuscript detailing the design, implementation, and evaluation of an automated Optical Mark Recognition (OMR) system for efficient and accurate multiple-choice question (MCQ) assessment. The system integrates advanced computer vision techniques, a user-friendly web interface, cloud-ready deployment strategies, and robust evaluation pipelines to minimize manual grading efforts, enhance consistency, and enable scalable academic workflows. By leveraging image preprocessing, template matching, and contour analysis, the OMR system accurately detects marked bubbles on scanned answer sheets, supporting both single and multiple-choice formats while incorporating quality assurance mechanisms. The methodology outlines a modular architecture encompassing image acquisition, preprocessing, answer recognition, evaluation, and reporting, with emphasis on security, auditability, and modularity. Experimental validation includes architecture and deployment diagrams, demonstrating high recognition accuracy (98\%) and efficient processing (1.3 seconds per sheet). Results are presented with performance tables and scalability diagrams, showing reliable operation under varying loads. The literature review integrates 41 references from the author's bibliography, covering intelligent systems, cloud applications, AI optimization, and educational technologies. Conclusion and discussion highlight the system's benefits for academic institutions, while future work explores AI enhancements, federated learning, and blockchain integration. This work contributes to the field of automated educational assessment by providing a complete, referenced manuscript that bridges traditional paper-based exams with modern digital evaluation paradigms.
Research Article
Asoshi Paul Anule, Anagu Emmanuel John & Ogar Michael Oko
Abstract: Cardiovascular disease remains one of the leading causes of mortality worldwide, necessitating the development of accurate and interpretable predictive systems that support early diagnosis and clinical decision-making. While numerous machine learning models have demonstrated promising predictive capabilities, many operate as black-box systems that provide limited transparency regarding how predictions are generated. This lack of interpretability presents significant challenges in healthcare environments where trust, accountability, and regulatory compliance are essential. This study presents a comparative evaluation of six supervised machine learning classifiers for heart disease prediction using the Cleveland Heart Disease Dataset. The evaluated models include Decision Tree, Logistic Regression, Support Vector Machine, K-Nearest Neighbours, Random Forest, and Gradient Boosting. A comprehensive machine learning pipeline comprising data preprocessing, feature selection, hyperparameter optimization, repeated stratified cross-validation, and performance evaluation was implemented. Explainable Artificial Intelligence (XAI) techniques based on SHAP were integrated to provide both global and local interpretability of model predictions. Experimental results demonstrate that the Decision Tree classifier achieved the highest overall performance, attaining an accuracy of 98.54%, precision of 98.21%, recall of 98.34%, and F1-score of 98.27%. Furthermore, SHAP-based analysis revealed that chest pain type, number of major vessels, exercise-induced angina, maximum heart rate, and ST depression were the most influential predictors of cardiovascular disease risk. The findings indicate that interpretable machine learning models can achieve predictive performance comparable to or exceeding more complex algorithms while maintaining transparency and clinical usability. The study contributes a reproducible framework for explainable cardiovascular disease prediction and demonstrates the feasibility of integrating interpretable machine learning models into clinical decision support systems. The proposed approach offers a foundation for trustworthy healthcare artificial intelligence applications that balance predictive accuracy with explainability.
Research Article
Gbolahan Babatunde Ajayi, E.J. Garba, Y.M. Malgwi & Kehinde Agboola
Abstract: Phishing is perpetrated by using electronic devices to deceive users of internet in order to extract valuable information from such users using fake website which resembles the original website they clone. Clicking on the fake website redirects the users to the fake website and then valid information is extracted from the users. Phishing has made many to lose their financial credentials to criminals and within few seconds, their hard-earned income disappeared into thin air. The breach of privacy alone is a threat to internet users and it is a criminal offense. This study developed self-organizing map model that is capable of preventing real-time phishing of -financial data. The methodology adopted in this study is a rule-based approach which ensures that features relevant to the study are preprocessed for learning of the model in preventing real-time phishing. The rule-based approach classified the URL to phishing and legitimate/benign in which the phishing URLs is blocked and prevented from opening. SOM is a clustering algorithm; result showed that it is highly effective in detecting and preventing phishing. Validating the SOM model showed Openphish dataset have accuracy of 95.00% and UCI dataset has accuracy of 86.00% respectively. The SOM model from the Openphish outperformed the model from UCI dataset. Using machine learning, especially artificial neural network is a proactive defense mechanism that marks a paradigm shift in cybersecurity. Harnessing the power of advanced analytics and pattern recognition makes SOM a more intelligent, adaptive, and efficient defense technique. It was suggested that users of internet should be educated on regular basis on how to avoid being phished on the internet.
Research Article
Maung Maung Mya, Chit Thet Nwe, Than Myat Htay, Aye Win Oo, Zar Zar Aung, Thu Zar Nyein Mu, Yee Yee Myint, Kaung Thant & Sein Thaung
Abstract: Mosquito-borne diseases are mostly harmful to children being and it is a public health problem in Myanmar. Laboratory reared Dagon Myothit North strain of Aedes aegypti larvae were used to test larvicidal, ovicidal and repellency properties of Citrus aurantifolia (Lemon) peels essential oil from June 2021 to May 2022 according to WHO. Fresh peels 300 grams from Taikkyi was extracted by stream distillation at 100°C for 3hours and obtained 1.65g of essential oil. Different concentrations of Lemon peels essential oil were prepared freshly in 100ml each of distilled water in 150ml plastic cups. Fifty each Aedes larvae were exposed 24hrs for each replication in different concentrations in laboratory. Acute toxicity and allergenicity tests were done in laboratory according to OECD Guidelines. Repellency test was done by laboratory reared 5-7 days old adult female Aedes mosquitoes with Lemon peels essential oil. Results revealed that the highest dose 0.01g of Lemon peels essential oil produced 100% knockdown within 60minute and 98.8% mortality within 24hrs respectively and 100% ovicidal effect for 4days as well as persistency was observed 98.8 - 100% mortality of larvae for 4 days. The effective lethal concentrations LC50 and LC90 values were found to be 0.0017g and 0.0053g of peels essential oil (x=0.05236, P=0.05). There was not found any acute toxicity on mice and allergenicity on the rabbits. 100% protection of Aedes mosquito landing to probe the skin was found 0.04g/ml or 0.000128g/cm2 of essential oil. Repellency activity of complete protection time was observed over 80% protection for 210minutes, over 90% prevention for 150 minutes, and 100% prevention for 120mins. Semi field trial observed that in the day time, it can prevent 3 hours of Aedes mosquito bite on oil applied areas of insect collectors in household. The essential oil is not toxicity, no allergenicity and no irritation of skins of animal. Therefore, the cheap, effective, ecofriendly and degradable lemon Citrus aurantifolia peels essential oil can be used as insecticide and repellent of mosquitoes in public sector.
Research Article
Shalini V. & Shilpa Kulkarni
Abstract: Indoor air quality is an important factor in maintaining a healthy living environment. In this study, indoor particulate matter concentrations (PM₁, PM₂.₅ and PM₁₀) were monitored in a residential living room in Bengaluru, India which is naturally ventilated, using a low-cost SmileDrive air quality sensor. Measurements were taken at hourly intervals over three consecutive days from 18 to 20 March 2025, along with temperature and relative humidity. The results showed that particulate matter concentrations varied throughout the day, with PM₁₀ recording higher values than PM₂.₅ and PM₁. The daily mean concentrations ranged from 10.47–12.24 µg m⁻³ for PM₁, 14.26–16.76 µg m⁻³ for PM₂.₅, and 16.21–19.24 µg m⁻³ for PM₁₀. Overall, the measured concentrations indicated relatively good indoor air quality during the monitoring period. Temperature and relative humidity also showed normal daily fluctuations. An analysis of the relationship between relative humidity and particulate matter concentrations revealed that the strength of the correlation varied across the three days, with stronger associations observed on 19 and 20 March 2025. The study demonstrates that low-cost sensors can be effectively used for short-term indoor air quality monitoring and can give useful information on the behaviour of particulate matter in residential environments.
Research Article
The influence of organizational culture on Viettel Group's performance
Master Dinh Van Thuc
Abstract: The overall objective of this scientific research project is to analyze and evaluate the influence of organizational culture on the performance of Viettel Group. Based on this, the research project will propose several management implications to improve cultural factors, contributing to enhanced performance of Viettel Group in the context of global competition and strong digital transformation. The quantitative analysis results using the structural equation modeling (SEM) demonstrated that all four organizational culture characteristics have a positive and statistically significant relationship with Viettel Group's performance. In particular, Participation was identified as the most impactful factor, showing that empowering and encouraging employee contributions is a key to improving performance at Viettel.
Research Article
Social State Policy in New Uzbekistan
Sotvoldiev Jaxongir Sultanali oglu
Abstract: This article analyzes the essence, theoretical foundations, and practical outcomes of the social state policy being implemented in New Uzbekistan. It examines the stages of the formation of the social state concept, its fundamental principles, and its role in the development of a modern democratic society. The study also explores recent reforms in Uzbekistan aimed at strengthening social protection, reducing poverty, supporting youth and women, enhancing the effectiveness of public administration, and improving the quality of social services. In particular, the practical significance of the social state policy is revealed through the activities of the National Agency for Social Protection, the “Youth Register” (Yoshlar Daftari), the “Women’s Register” (Ayollar Daftari), the “From Poverty to Prosperity” program, and the experience of strengthening executive discipline in the regions. The findings demonstrate that effective governance and the prioritization of human interests constitute the key foundations of the social state-building process.
Research Article
Sotvoldiyev Jakhongir Sultonali o‘g‘li
Abstract: This article examines the role of ensuring human rights in New Uzbekistan as one of the key factors in promoting sustainable development and strengthening national security. The author analyzes how the protection of human rights and fundamental freedoms contributes to the establishment of justice, the rule of law, and the enhancement of citizens’ trust in state institutions. The study also highlights the significance of the constitutional and legal reforms implemented in recent years in safeguarding human interests and advancing human-centered governance. Particular attention is given to issues such as ensuring transparency and openness in the activities of public authorities, improving citizens’ legal awareness and legal culture, and assessing the impact of effective human rights protection on social stability. The article concludes that respect for and protection of human rights constitutes essential prerequisites for sustainable development, national security, and the overall well-being of the population in New Uzbekistan.
Research Article
On farm Evaluation of Jimma Model Engine Operated Double Disc Coffee Pulpier
Wabi Tafa, Abayineh Awgichew & Abe Tullo
Abstract: Coffee processing is the process of converting the coffee cherry into green coffee bean after the fruit or pulp has been removed. Farmers in West Guji zones lost out because of the lack of value-adding technologies, which resulted in low quality and profit. The on-farm evaluation of Jimma model engine operated double disc coffee pulpier was undertaken at Adola Redde Woreda, Guji Zone to evaluate its performance under different operational parameters. A 3x3 factorial experiment in Completely Randomized Design (CRD) was used to determine the effects of disc speed (100, 200, 300 rpm) and feeding rate (6, 9, 12 kg/min) on pulping capacity, efficiency and mechanical damage. The results showed that both factors have a significant effect on machine performance. The pulping capacity was increased with increase in disc speed and feeding rate and attained maximum of 531.38 kg/hr at 300 rpm and 12 kg/min. However, the highest pulping efficiency (96.24 %) and the least mechanical damage were obtained at 200 rpm and 6 kg/min feeding rate. The study concluded that the Jimma model double-disc pulpier performs best at a disc speed of 200 rpm and a feeding rate of 6-9 kg/min and can be a good alternative for smallholder farmers to improve the quality and efficiency of wet coffee processing and hence improve market competitiveness and income.
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