International Journal of Education and Management Engineering (IJEME)

ISSN: 2305-3623 (Print)

ISSN: 2305-8463 (Online)

DOI: https://doi.org/10.5815/ijeme

Website: https://www.mecs-press.org/ijeme

Published By: MECS Press

Frequency: 6 issues per year

Number(s) Available: 92

(IJEME) in Google Scholar Citations / h5-index

IJEME is committed to bridge the theory and practice of education and management engineering. From innovative ideas to specific algorithms and full system implementations, IJEME publishes original, peer-reviewed, and high quality articles in the areas of education and management engineering. IJEME is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of education and management engineering applications.

 

IJEME has been abstracted or indexed by several world class databases: Google Scholar, CrossRef, CNKI, Scilit, Baidu Scholar,  JournalTOCs, etc..

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IJEME Vol. 16, No. 5, Oct. 2026

REGULAR PAPERS

Urban Landscapes as Living Classrooms: A Bibliometric Analysis and Conceptual Framework for Inquiry-Based Learning

By Carlos Mario Fernandez Hoyos Elvira Patricia Florez Nisperuza

DOI: https://doi.org/10.5815/ijeme.2026.05.01, Pub. Date: 8 Oct. 2026

This article presents a reflective analysis concerning the evolution of the “Living Classroom” concept, traditionally associated with rural settings, and its re-conceptualization within urban socio-ecological systems. By synthesizing global scientific trends and contemporary research, the study explores how metropolitan green infrastructures—such as urban forests, biocultural canals, and school gardens—function as high-complexity laboratories for Inquiry-Based Learning (IBL). The methodological approach combines a PRISMA-inspired systematic qualitative synthesis with a bibliometric analysis of 2,732 open-access articles indexed in the Scopus database (2015–2026), applying the Authors–Journals–Contributions (ARA) methodology and VOSviewer for scientific mapping. The findings reveal the scientific leadership of China and several European countries, a predominance of publications in Q1 journals, and four major thematic clusters related to sustainable development, human health and education, interdisciplinary knowledge integration, and socio-ecological learning environments. The reflection argues that the urban landscape is not a substitute for nature but a primary pedagogical mediator that enhances cognitive development, health, and environmental citizenship. Furthermore, the discussion integrates findings from international research to propose a necessary shift in natural science education: the city can be understood as a living laboratory where scientific inquiry bridges the gap between urban development and ecological literacy. Building on this synthesis, the study develops a conceptual framework that addresses the phenomenon of environmental blindness by reconceptualizing urban living classrooms as pedagogical mediators that connect scientific inquiry with everyday socio-ecological experiences. The proposed framework supports the pedagogical reinterpretation of riverside territories and urban ecosystems as authentic contexts for scientific inquiry. It also provides a theoretical reference for future educational research on inquiry-based science education in urban contexts.

[...] Read more.
Evolutionary Neural Network for Obstructive Sleep Apnea Diagnosis Using GA, PSO, and CSA

By Alaa F. Sheta Salim Surani

DOI: https://doi.org/10.5815/ijeme.2026.05.02, Pub. Date: 8 Oct. 2026

Obstructive Sleep Apnea (OSA) is a well-known sleep disorder that can lead to major health consequences if
left untreated. The traditional diagnostic method, polysomnography, is precise but costly and labor-intensive. This research presents an Evolutionary Feedforward Neural Network (FFNN) optimized using a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and the Crow Search Algorithm (CSA) to diagnose OSA. We utilized a dataset comprising demographic and physical measurements. The adopted features include age, sex, weight (lb), height (in), neck circumference, body mass index (BMI > 30), (Neck > 17), airway evaluation via the modified Friedman grade (MF > 2), the Berlin apnea-hypopnea questionnaire (BAN), and the identification of apnea as indicated by the apnea hypopnea index (AHI ≥ 15). We used this methodology to optimize the FFNN’s weights and biases, improving generalization and avoiding local minima that traditional backpropagation can trap the model in. The results indicate that GA, PSO, and CSA achieved competitive, comparable performance, with PSO showing a marginally better performance across most evaluation metrics, rather than a significant superiority of any single optimization method.

[...] Read more.
Dynamic Multi-Criteria Task Assignment in Field Service Management: A Proximity-Skill-Priority Optimization Framework

By Erike Azubuike Izuchukwu John David Eno Nwandu Ikenna Caeser Orban Aondowase James Elei Florence Obiageli

DOI: https://doi.org/10.5815/ijeme.2026.05.03, Pub. Date: 8 Oct. 2026

Field service management (FSM) has been faced with the need to efficiently assign tasks to technicians in field service operations (FSOs). The problem of inefficient task allocation has led to either an over utilization or an under utilization of the organization’s workforce and resources across cities and states. This study focuses on developing a resource-efficient multi-criteria algorithm (Proximity-Skill-Priority, PSP algorithm) for optimized field service task management. A mathematical modelling approach was used to design a unified score that takes into consideration the proximity of the technician to the task location, the skillset of each technician and the priority level of the task at hand while ensuring effective workload balance to ensure unbiased task assignment. The study used adaptive weighting coefficients to ensure that real-time adjustments are made when there are varying time conditions. The model was evaluated through a simulation experiment and benchmarked against three single-rule baselines: Proximity-First, Skill-First, and Priority-First assignment. The performance of the algorithms was measured in a 100-run simulation conducted on a synthetic dataset that is parameterized with the attributes of technicians, task priorities, and geospatial information.  The lowest average response time and travel distance were achieved by Proximity-First and Priority-First rules, whereas Skill-First produced the highest first-time-fix-rate surrogate at the cost of substantially higher travel and response values. PSP produced a more balanced trade-off: it improved first-time-fix performance when compared to the proximity-first and priority-first heuristics. At the same time, it balances the severe travel penalty observed under Skill-First assignment. Statistical analysis using Friedman and Wilcoxon signed-rank tests shows that there are significant differences in operation across the different algorithms for the evaluation metrics. These findings show that PSP is best interpreted as a compromise strategy that balances service quality and operational efficiency rather than maximizing any single metric in isolation.

[...] Read more.
Latency Bias in Face Recognition Systems: Measurement, Statistical Evidence, and Mitigation Challenges for Eyeglass Wearers

By Shakibul Islam Akash Md. Omar Faruk Faisal Md. Rafiqul Islam

DOI: https://doi.org/10.5815/ijeme.2026.05.04, Pub. Date: 8 Oct. 2026

The face recognition systems (FRS) can have latency bias, with some of their inputs or subsets having disproportionate inference delays, which result in unfair quality-of-service despite apparently similar predictive performance. Although much research on fairness in face recognition research has been done on accuracy-based disparities, there has been little work on runtime behavior. This study seeks to understand whether there are differences in performance in real-time face recognition systems based on visually complex sub-groups, and whether these differences can be considered as operational fairness concerns. In this work, we investigate the latency problem of real-time FRS, with especially great attention to tail inference as the first-class fairness measure. We utilize a label-free auditing framework for conducting runtime fairness assessment, and propose the tail inference latency metric for evaluating the fairness level of the deployment. Instead of focusing on prediction scores as in prior work, our work focuses on the fairness level of our deployment. The MeGlass dataset (noted as a publicly available Kaggle release) is used as the base of experiments, which is an image-only face dataset to test the strength against eyeglasses, and the MeGlass dataset is a base to assess the reality of deployment through the Kaggle publicly available release. Using eyeglass wearers as a sample visually complex group, we conduct a label-free Responsible AI audit in the conditions when we do not have labels of the sensitive attributes. We observed that average performance difference in mean is not statistically significant (p = 0.36) by the permutation test, while mean difference in p99 is 16.85 ms between cohorts, bringing up fairness differences not captured by averages. Doing systems-level regression, we attribute such variances to pipeline-level attributes (e.g. detection confidence, input complexity) as opposed to the use of these attributes directly as causal factors. We also evaluate mitigation policies and determine trade-offs among the latency, fairness and recognition fidelity. The findings here show that fairness inequities can arise at worst-case runtime behavior, not in average latency, suggesting that the use of metrics focused on the tail of a run-time fairness distribution should be considered in fairness assessments of run-time deployed face recognition systems.

[...] Read more.
An ILM-Grounded Adaptive Framework for Gifted Learners: Integrating LLM Orchestration and Multi-Agent Tutoring

By Mohamed Badawi Mustafa Elkhalifa

DOI: https://doi.org/10.5815/ijeme.2026.05.05, Pub. Date: 8 Oct. 2026

Gifted learners require instructional environments that transcend conventional pedagogical boundaries, offering adaptive challenge, metacognitive scaffolding, and high degrees of learner autonomy. This study presents the design, implementation, and empirical evaluation of the AI-Enhanced Self-Directed Learning (AESDL) framework an integrated adaptive system grounded in Treffinger's Independent Learner Model (ILM) and operationalized through an ensemble of five artificial intelligence (AI) technologies: the Google Gemini API (as central orchestration controller), cognitive computing, multi-agent systems (MAS), expert systems, and automatic speech recognition. The model is built upon four core ILM components Guidance, Self-Development, Enrichment, and Seminars/In-Depth Study each computationally instantiated through dedicated AI subsystems. A quasi-experimental pre-test/post-test control group design was employed with 50 gifted secondary school learners (25 experimental, 25 control) drawn from model gifted-education classrooms in Khartoum State, Sudan. The experimental group received eight weeks of instruction via the AESDL system; the control group received equivalent instruction through conventional electronic resources. Outcome measures self-directed learning skills, problem-solving capacity, and academic enrichment achievement (each scored on a 50-point scale) were analyzed using independent-samples t-tests with Cohen's d effect sizes. Results indicated statistically significant and practically large superiority of the AESDL condition: self-directed learning (t(48) = 7.91, p < .001, d = 2.24), problem-solving (t(48) = 5.52, p < .001, d = 1.56), and academic achievement (t(48) = 6.50, p < .001, d = 1.84). These findings advance the empirical evidence base for AI-mediated gifted education and provide actionable design principles for intelligent adaptive learning systems. The control condition comprised conventional electronic learning resources (digital textbooks, instructional videos, and static online exercises). Ninety-five-percent confidence intervals for the between-group mean differences were [9.13, 15.35], [5.62, 12.06], and [7.02, 13.30] for self-directed learning, problem-solving, and academic achievement, respectively. Given the modest sample (n = 50) and the near-ceiling experimental-group scores, these findings should be interpreted with caution regarding potential ceiling effects and limited external validity, and warrant independent replication with larger, more diverse samples.

[...] Read more.
A Review on Quantum Computing for Business Applications

By Sneha Nej Subhasree Bhattacharjee Sudakshina Mandal Rupa Saha Jaya Kumari Sreya Dey

DOI: https://doi.org/10.5815/ijeme.2026.05.06, Pub. Date: 8 Oct. 2026

Quantum Computing is gradually gaining importance as a transformative technology with the potential to revolutionize business applications by solving complicated problems beyond the capabilities of classical computers. Using basic principles such as superposition and entanglement, quantum systems can concurrently handle a wide range of combinations of possibilities. It offers several benefits in optimization, financial modeling, supply chain management, risk analysis, and machine learning. Despite the limitations of existing hardware in the NISQ era, rapid developments are enhancing scalability and reliability. This study analyses the practical implications, opportunities, and challenges of integrating quantum computing into business environments, spotlighting its capacity to drive innovation, competitive advantage, and long-term strategic growth throughout industries. By situating quantum computing within a transdisciplinary engineering and business ecosystem, this review demonstrates that quantum technologies are not merely enablers of computational speed but catalysts for systemic innovation.

[...] Read more.
A Quantum-Optimized Decentralized Ledger for Real-Time TVET Skill Assessment via Wearable IoT Sensors: A Framework for the Kenyan Technical and Vocational Education and Training Sector

By David Shiala Ongoma

DOI: https://doi.org/10.5815/ijeme.2026.05.07, Pub. Date: 8 Oct. 2026

There exists an ongoing problem among technical and vocational education and training institutions in Kenya regarding validation of demonstrated practical competencies, since the verification method depends on periodic observation which is paper-based and hence prone to subjectivity and potential corruption. In this article, we propose a quantum-optimized decentralized ledger system in which trainees wear wearable Internet of Things sensors and a consensus algorithm referred to as Quantum-Optimized Decentralized Proof-of-Skill is used to record and validate skill demonstration. The sensors detect motion, physiological, and environmental signals that are converted into skill proficiency ratings using an edge-based feature-processing pipeline; validator nodes are then chosen by solving a quadratic unconstrained binary optimization problem with a quantum-inspired algorithm. Assessment records are written to a permissioned ledger accessible only to training institutions, national qualification authorities, and prospective employers. According to a discrete-event simulation of the proposed consensus algorithm relative to proof-of-work, proof-of-stake, and practical Byzantine fault tolerance, the proposed algorithm has a reduced mean confirmation time of 148 ms and an increased sustained throughput of 386 tx/s under the modeled conditions of the Kenyan network environment, alongside skill-scoring consensus (F1 overall = 0.88) with the assessor ground truth obtained through simulations based on the accuracy of the wearable-assessments in published reports.

[...] Read more.
Haralick Feature-Based Mammographic Breast Cancer Classification Using Cuckoo Search Optimization

By Jeevitha V. Laurence Aroquiaraj I.

DOI: https://doi.org/10.5815/ijeme.2026.05.08, Pub. Date: 8 Oct. 2026

Medical image analysis plays an important role in early breast cancer detection through mammographic image analysis. But, some information in the GLCM based Haralick texture features is redundant and irrelevant, which can impact performance in classification. In this study, a feature selection framework based on Cuckoo Search Optimization (CSO) is presented to select the optimum Haralick features for the breast cancer classification. The proposed approach consists of the preprocessing of mammograms, extraction of features from the GLCM, optimization of the GLCM features using the CSO technique, and classification using machine learning algorithms. Fourteen extracted GLCM attributes were used in the experiments performed on MIAS. The CSO-KNN model obtained the best classification rate of 90.00% with 6 selected features, which means that 8 attributes have been removed. The proposed framework significantly reduces feature dimensionality and improves the classification efficiency in computer-aided breast cancer diagnosis.

[...] Read more.
Stressors and Stress-Coping Mechanisms of Academic Scholars in HEIs: A Basis for Stress Management Plan Formulation

By Ruth G. Luciano Mickel John Salvatierra

DOI: https://doi.org/10.5815/ijeme.2022.03.01, Pub. Date: 8 Jun. 2022

This study aims to describe the stress coping mechanism of the academic scholars from the College of Education (COEd) in one of the private higher education institutions in Cabanatuan City, Philippines. This is an action research that focuses on the assessment of the academic scholars’ stressors and their correlates. It involves systematic observations and data collection that enables the researchers to reflect, decide and develop a training plan for stress management. The findings show that monthly family income and economic-related stressors were highly correlated. This further explains that students with high family income are less likely to experience frequent stress. In contrary, students who belong to low-income families are more prone to experience frequent stress. In other words, students who belong to poor families are more vulnerable to stress. Likewise, monthly family income and physiological responses to stress had high interdependence, which means that students with higher socio-economic status are less likely to experience severe anxiety, while students belonging to low-income families tend to experience severe anxiety. The results of this quantitative analysis served as basis in designing or preparing the stress management plan for these students. 

[...] Read more.
Push Management Platform Based on Wechat Small Program and Cloud Development

By Yan Wu Fang Wang Yanying Zou Huaijin Zhang Bingsheng Chen Mengshan Li

DOI: https://doi.org/10.5815/ijeme.2020.01.03, Pub. Date: 8 Feb. 2020

On the Wechat platform, the current article push is mainly completed by the Wechat Public Account, but it is not perfect in the aspects of user information collection, user service, data storage and management. With economic development and progress of the times, people seek development in spiritual and cultural aspects. This program "One Thing One Story" uses Wechat Web Developer Tools as the medium and Wechat Small Program and Cloud Development as the platform. The purpose of push management platform is "use at any time". Small program cloud development has a relatively complete cloud background. It does not need to rebuild the server in the development cycle. Through the relevant interface, small program development can be started and time cost can be reduced. Using JavaScript, CSS style, JSON database and other technologies, we can realize user data collection, article push, push classification management, push data storage, user praise collection and other functions. This program is applied to article pushing, cultural dissemination and other aspects. Through the platform of Wechat applet, the dream of "accessible" can be realized. 

[...] Read more.
A Study on Malware and Malware Detection Techniques

By Rabia Tahir

DOI: https://doi.org/10.5815/ijeme.2018.02.03, Pub. Date: 8 Mar. 2018

The impact of malicious software are getting worse day by day. Malicious software or malwares are programs that are created to harm, interrupt or damage computers, networks and other resources associated with it. Malwares are transferred in computers without the knowledge of its owner. Mostly the medium used to spread malwares are networks and portable devices. Malwares are always been a threat to digital world but with a rapid increase in the use of internet, the impacts of the malwares become severe and cannot be ignored. A lot of malware detectors have been created, the effectiveness of these detectors depend upon the techniques being used. Although researchers are developing latest technologies for the timely detection of malwares but still malware creators always stay one step ahead. In this paper, a detailed review of malwares types are provided, malware analysis and detection techniques are studied and compared. Furthermore, malware obfuscation techniques have also been presented.

[...] Read more.
Classroom Management Strategies and Academic Performance of Junior High School Students

By Maxwell Kontor Owusu Bakari Yusuf Dramanu Mark Owusu Amponsah

DOI: https://doi.org/10.5815/ijeme.2021.06.04, Pub. Date: 8 Dec. 2021

The study examined the influence of classroom management strategies of Junior High School teachers on the academic performance of students in the Ashanti Akim North District. The descriptive survey design was used for the study. One hypothesis and two research questions were developed to guide the study. Multistage sampling technique was used to select 48 teachers and 297 year two students to respond to the Behaviour and Instructional Management Scale (BIMS). Test scores in English Language, Integrated Science, Mathematics and Social Studies were used to measure students’ academic performance. The statistical tools used to analyse the data collected were means, standard deviation, Pearson’s Product Moment Correlation Coefficient (PPMCC) and Multiple Regression. The findings revealed that both students and teachers identified good relationship and reinforcement as the mostly used classroom management strategies. It was found that a significant positive relationship existed between reinforcement and antecedent as classroom management schemes and students’ academic performance. However, good relationship and punishment as classroom management strategies did not have a positive relationship with the academic performance of students. It is recommended that teachers should use reinforcement and antecedent strategies frequently in their classrooms since they play a dual role of managing behaviour and predicting the academic performance of students. Good relationship as a classroom management strategy should be cautiously used because it could potentially be misinterpreted or abused and can lead to low academic performance. Using punishment as a classroom management strategy should be avoided as its use hinders academic performance of students.

[...] Read more.
Medicine Management System: Its Design and Development

By Ruth G. Luciano Rhoel Anthony G. Torres Edward B. Gomez Hardly Joy D. Nacino Rodmark D. Ramirez

DOI: https://doi.org/10.5815/ijeme.2023.03.02, Pub. Date: 8 Jun. 2023

The researchers conducted this study with the main purpose of helping the residents of the municipality to expedite the process of obtaining free medicine. In the current setup, an individual who needs to avail of free medicine from the barangay or municipal health center personally visits the place to request maintenance medicine. This motivated the researchers to make a research study focusing on converting the manual requisition system to something that people can access quickly and comfortably without necessarily going out of their households, especially during these challenging times – the pandemic. The researchers called it a “Medicine Management System”. The researchers aimed to speed up the requisition of medicine using this online system. The patients or qualified recipients need not consume time lining up to request medicine from the municipal health center. This system can be accessed over the internet anytime and anywhere. Users must register and upload a legit doctor’s prescription. Researchers have created this system using HTML for the system interface, XAMPP for maintaining database records, and PHP for other system functionalities.

[...] Read more.
The Effectiveness of the TaRL Approach on Moroccan Pupils’ Mathematics, Arabic, and French Reading Competencies

By Abdessamad Binaoui Mohammed Moubtassime Latifa Belfakir

DOI: https://doi.org/10.5815/ijeme.2023.03.01, Pub. Date: 8 Jun. 2023

Teaching at the Right Level (henceforth, TaRL) is a new trending remedial educational approach being piloted in many countries. It basically matches pedagogical content to pupils’ educational needs through various adapted activities after segmentation of pupils’ depending on their actual difficulties and needs. In this respect, Morocco has been piloting this relatively new approach during the beginning of the school year 2022-23. Therefore, this study aimed at measuring the effectiveness of the TaRL approach on Moroccan pupils’ mathematics, Arabic, and French reading competencies. An experimental study took place involving 106 pupils from 4th grade to 6th grade during a one-month remedial course (half an hour per day, one subject per day) based on TaRL guidelines. After carefully examining the data through the Wilcoxon Signed Ranks Test by comparing the baseline and endline results in all three subjects. The results showed statistically high improvements with large effect sizes in the levels of the three subjects suggesting that TaRL was effective in raising the levels of numeracy and literacy and may be, safely, further adopted throughout Moroccan primary schools.

[...] Read more.
Machine Learning Applications in Algorithmic Trading: A Comprehensive Systematic Review

By Arash Salehpour Karim Samadzamini

DOI: https://doi.org/10.5815/ijeme.2023.06.05, Pub. Date: 8 Dec. 2023

This paper reviews recent advancements in machine learning (ML) driven automated trading systems (ATS). ATS has progressed from simple rule-based systems to sophisticated ML models like deep reinforcement learning, deep learning, and Q-learning that can adapt to evolving markets. These techniques have been successfully applied across various financial instruments to optimize trading strategies, forecast prices, and enhance profits. The literature indicates that ML improves ATS performance over conventional methods by identifying intricate patterns and relationships in data. However, risks like overfitting, instability, and low interpretability exist. Techniques to mitigate these limitations include cross-validation, careful model management, and utilizing more transparent algorithms. Although challenges remain, ML creates valuable opportunities for ATS via alternative data sources, advanced feature engineering, optimized adaptive strategies, and holistic market modelling. While research shows ML improves market quality through increased liquidity and efficiency, heightened volatility needs further analysis. Promising future research directions include leveraging innovations in deep learning, reinforcement learning, sentiment analysis, and hybrid systems. More work is also needed on evaluating different techniques systematically. Overall, the progress in ML-driven ATS contributes significantly to the field, but judicious application and balanced regulations are required to address risks. Further advancements in ML will enable more capable, nuanced, and profitable algorithmic trading.

[...] Read more.
The Application of Computer Softwares in Chemistry Teaching

By Wei Yu Lifei Chen

DOI: https://doi.org/10.5815/ijeme.2012.12.12, Pub. Date: 29 Dec. 2012

Chemistry is very interesting, but it is often regarded as a difficult subject. Computer software can make chemistry teaching easier, and keeps the students active. This paper seeks to introduce some implications of computer softwares in chemistry classroom teaching. These softwares include Powerpoint, Chemoffice, computer simulation softwares, LabVIEW software, some computational chemistry softwares, and other chemistry softwares, such as ACD/ChemSketch, ChemDB software, Chemical Reagent Calculator, Atom Builder and Atoms, Symbols and Equations. We gave the simple directions of these softwares and presented some applicable examples.

[...] Read more.
The Digital Literacy in Teachers of the Schools of Rajouri (J&K)-India: Teachers Perspective

By M Mubasher Hassan Tabasum Mirza

DOI: https://doi.org/10.5815/ijeme.2021.01.04, Pub. Date: 8 Feb. 2021

The present age is the age of information. The globalization has affected every sphere of the life including education. In spite of availability of ICT infrastructure in schools, their potential is underutilized because of digital incompetence of the teachers.  New digital technologies are acting as a catalyst towards improvement of learning outcome and enhancing quality of education, but only introduction of such technologies in schools for producing change and innovation is not enough, it requires digitally competent teachers to facilitate the use of ICT in education. These teachers will act as facilitators and mentors to students to lead them towards problem solving and innovation to meet the new challenges of globalization. Teachers must be able to create learning environments which are student centric and foster creativity, Meta cognition, meta-literacy, collaboration and communication in learners. Mere superficial use of ICT in teaching will not yield the required learning outcome, but the integration of ICT in pedagogy is important to enhance teaching, learning process. This can be done only when teachers are competent enough to use ICT tools and facilitate ICT integrated education. In this paper, we tried to assess the teacher’s perspective about the ICT and investigate the factors responsible for resistance of teachers in using ICT in schools and suggestive measures for successful integration of ICT in the teaching process by the teachers of Rajouri district (J&K, India). The ICT skills are very important for teachers to support alternative modes of teaching, learning, i.e. e-learning, mobile learning in the present outbreak of pandemic disease caused by Coronavirus-COVID19. 

[...] Read more.
A Critical Review by Teachers on the Online Teaching-Learning during the COVID-19

By Malik Mubasher Hassan Tabasum Mirza Mirza Waseem Hussain

DOI: https://doi.org/10.5815/ijeme.2020.05.03, Pub. Date: 8 Oct. 2020

The world has witnessed a sudden change in the teaching-learning processes due to the ongoing pandemic of COVID-19. The worldwide compulsive lockdown for ensuring the preventive measures to stop the spread of this infection has equally affected education sector as other business sectors. As all of us know that quality education is the only long-term rescue for all the challenges and therefore, the need to find out the alternative solution to the traditional classroom teaching-learning is the concern of all stakeholders and the only option found is online mode of teaching-learning, which was somehow already available and had attracted an intense attention during this period. The aim of the paper is to study the teacher’s perspective in India about this mode of learning, challenges and issues faced by them in migration to online platform, experience about online tools/platforms used for instructional delivery and their suggestions to improve the process for effective teaching. This study will help in gaining insight towards the possible improvements in the ongoing mode of online teaching and in future situations also. The results obtained based on sample collection through web based questionnaire clearly gives some information, which could be an eye opener for enhancing the implementation of the online teaching-learning among the learners especially teachers, who can further help in implementation of the large. Although, the online mode was already in place and was utilized in blended form to a substantial level in the developed countries, but in developing countries like India, where teachers are not familiar with online platforms/tools, lack of knowledge and skills to handle the online ICT infrastructure in a challenging situation. The results also give an impression about the need of professional development with special focus on digital literacy skills and awareness among the teacher community about the merits of online platforms for the teaching-learning process.

[...] Read more.
Push Management Platform Based on Wechat Small Program and Cloud Development

By Yan Wu Fang Wang Yanying Zou Huaijin Zhang Bingsheng Chen Mengshan Li

DOI: https://doi.org/10.5815/ijeme.2020.01.03, Pub. Date: 8 Feb. 2020

On the Wechat platform, the current article push is mainly completed by the Wechat Public Account, but it is not perfect in the aspects of user information collection, user service, data storage and management. With economic development and progress of the times, people seek development in spiritual and cultural aspects. This program "One Thing One Story" uses Wechat Web Developer Tools as the medium and Wechat Small Program and Cloud Development as the platform. The purpose of push management platform is "use at any time". Small program cloud development has a relatively complete cloud background. It does not need to rebuild the server in the development cycle. Through the relevant interface, small program development can be started and time cost can be reduced. Using JavaScript, CSS style, JSON database and other technologies, we can realize user data collection, article push, push classification management, push data storage, user praise collection and other functions. This program is applied to article pushing, cultural dissemination and other aspects. Through the platform of Wechat applet, the dream of "accessible" can be realized. 

[...] Read more.
Stressors and Stress-Coping Mechanisms of Academic Scholars in HEIs: A Basis for Stress Management Plan Formulation

By Ruth G. Luciano Mickel John Salvatierra

DOI: https://doi.org/10.5815/ijeme.2022.03.01, Pub. Date: 8 Jun. 2022

This study aims to describe the stress coping mechanism of the academic scholars from the College of Education (COEd) in one of the private higher education institutions in Cabanatuan City, Philippines. This is an action research that focuses on the assessment of the academic scholars’ stressors and their correlates. It involves systematic observations and data collection that enables the researchers to reflect, decide and develop a training plan for stress management. The findings show that monthly family income and economic-related stressors were highly correlated. This further explains that students with high family income are less likely to experience frequent stress. In contrary, students who belong to low-income families are more prone to experience frequent stress. In other words, students who belong to poor families are more vulnerable to stress. Likewise, monthly family income and physiological responses to stress had high interdependence, which means that students with higher socio-economic status are less likely to experience severe anxiety, while students belonging to low-income families tend to experience severe anxiety. The results of this quantitative analysis served as basis in designing or preparing the stress management plan for these students. 

[...] Read more.
Medicine Management System: Its Design and Development

By Ruth G. Luciano Rhoel Anthony G. Torres Edward B. Gomez Hardly Joy D. Nacino Rodmark D. Ramirez

DOI: https://doi.org/10.5815/ijeme.2023.03.02, Pub. Date: 8 Jun. 2023

The researchers conducted this study with the main purpose of helping the residents of the municipality to expedite the process of obtaining free medicine. In the current setup, an individual who needs to avail of free medicine from the barangay or municipal health center personally visits the place to request maintenance medicine. This motivated the researchers to make a research study focusing on converting the manual requisition system to something that people can access quickly and comfortably without necessarily going out of their households, especially during these challenging times – the pandemic. The researchers called it a “Medicine Management System”. The researchers aimed to speed up the requisition of medicine using this online system. The patients or qualified recipients need not consume time lining up to request medicine from the municipal health center. This system can be accessed over the internet anytime and anywhere. Users must register and upload a legit doctor’s prescription. Researchers have created this system using HTML for the system interface, XAMPP for maintaining database records, and PHP for other system functionalities.

[...] Read more.
A Study on Malware and Malware Detection Techniques

By Rabia Tahir

DOI: https://doi.org/10.5815/ijeme.2018.02.03, Pub. Date: 8 Mar. 2018

The impact of malicious software are getting worse day by day. Malicious software or malwares are programs that are created to harm, interrupt or damage computers, networks and other resources associated with it. Malwares are transferred in computers without the knowledge of its owner. Mostly the medium used to spread malwares are networks and portable devices. Malwares are always been a threat to digital world but with a rapid increase in the use of internet, the impacts of the malwares become severe and cannot be ignored. A lot of malware detectors have been created, the effectiveness of these detectors depend upon the techniques being used. Although researchers are developing latest technologies for the timely detection of malwares but still malware creators always stay one step ahead. In this paper, a detailed review of malwares types are provided, malware analysis and detection techniques are studied and compared. Furthermore, malware obfuscation techniques have also been presented.

[...] Read more.
Machine Learning Applications in Algorithmic Trading: A Comprehensive Systematic Review

By Arash Salehpour Karim Samadzamini

DOI: https://doi.org/10.5815/ijeme.2023.06.05, Pub. Date: 8 Dec. 2023

This paper reviews recent advancements in machine learning (ML) driven automated trading systems (ATS). ATS has progressed from simple rule-based systems to sophisticated ML models like deep reinforcement learning, deep learning, and Q-learning that can adapt to evolving markets. These techniques have been successfully applied across various financial instruments to optimize trading strategies, forecast prices, and enhance profits. The literature indicates that ML improves ATS performance over conventional methods by identifying intricate patterns and relationships in data. However, risks like overfitting, instability, and low interpretability exist. Techniques to mitigate these limitations include cross-validation, careful model management, and utilizing more transparent algorithms. Although challenges remain, ML creates valuable opportunities for ATS via alternative data sources, advanced feature engineering, optimized adaptive strategies, and holistic market modelling. While research shows ML improves market quality through increased liquidity and efficiency, heightened volatility needs further analysis. Promising future research directions include leveraging innovations in deep learning, reinforcement learning, sentiment analysis, and hybrid systems. More work is also needed on evaluating different techniques systematically. Overall, the progress in ML-driven ATS contributes significantly to the field, but judicious application and balanced regulations are required to address risks. Further advancements in ML will enable more capable, nuanced, and profitable algorithmic trading.

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Classroom Management Strategies and Academic Performance of Junior High School Students

By Maxwell Kontor Owusu Bakari Yusuf Dramanu Mark Owusu Amponsah

DOI: https://doi.org/10.5815/ijeme.2021.06.04, Pub. Date: 8 Dec. 2021

The study examined the influence of classroom management strategies of Junior High School teachers on the academic performance of students in the Ashanti Akim North District. The descriptive survey design was used for the study. One hypothesis and two research questions were developed to guide the study. Multistage sampling technique was used to select 48 teachers and 297 year two students to respond to the Behaviour and Instructional Management Scale (BIMS). Test scores in English Language, Integrated Science, Mathematics and Social Studies were used to measure students’ academic performance. The statistical tools used to analyse the data collected were means, standard deviation, Pearson’s Product Moment Correlation Coefficient (PPMCC) and Multiple Regression. The findings revealed that both students and teachers identified good relationship and reinforcement as the mostly used classroom management strategies. It was found that a significant positive relationship existed between reinforcement and antecedent as classroom management schemes and students’ academic performance. However, good relationship and punishment as classroom management strategies did not have a positive relationship with the academic performance of students. It is recommended that teachers should use reinforcement and antecedent strategies frequently in their classrooms since they play a dual role of managing behaviour and predicting the academic performance of students. Good relationship as a classroom management strategy should be cautiously used because it could potentially be misinterpreted or abused and can lead to low academic performance. Using punishment as a classroom management strategy should be avoided as its use hinders academic performance of students.

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The Effectiveness of the TaRL Approach on Moroccan Pupils’ Mathematics, Arabic, and French Reading Competencies

By Abdessamad Binaoui Mohammed Moubtassime Latifa Belfakir

DOI: https://doi.org/10.5815/ijeme.2023.03.01, Pub. Date: 8 Jun. 2023

Teaching at the Right Level (henceforth, TaRL) is a new trending remedial educational approach being piloted in many countries. It basically matches pedagogical content to pupils’ educational needs through various adapted activities after segmentation of pupils’ depending on their actual difficulties and needs. In this respect, Morocco has been piloting this relatively new approach during the beginning of the school year 2022-23. Therefore, this study aimed at measuring the effectiveness of the TaRL approach on Moroccan pupils’ mathematics, Arabic, and French reading competencies. An experimental study took place involving 106 pupils from 4th grade to 6th grade during a one-month remedial course (half an hour per day, one subject per day) based on TaRL guidelines. After carefully examining the data through the Wilcoxon Signed Ranks Test by comparing the baseline and endline results in all three subjects. The results showed statistically high improvements with large effect sizes in the levels of the three subjects suggesting that TaRL was effective in raising the levels of numeracy and literacy and may be, safely, further adopted throughout Moroccan primary schools.

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An Empirical Study on Make-or-buy Decision Making

By Monika Arora Anand Kumar

DOI: https://doi.org/10.5815/ijeme.2022.01.03, Pub. Date: 8 Feb. 2022

Every enterprise will be based on the other enterprise to manufacture, product items/parts, for make or buy. The make-buy decision is based on the assessment whether it should be manufactured or buy it from an outside supplier to produce a component internally or to buy it from the outside. It depends on cost and profitability. The cost for both the alternatives may be calculated and the alternative with less cost is to be chosen. The aim of any enterprise is to improve its performance that is measured in terms of profitability. There is some research that has been carried out to make the decision based on profitability of the enterprise for make or buy decision.  The strategy is based on cost, flexibility and responsiveness of work to be carried out. However, some of the research is required to maintain the relationship between profitability and make or buy decision.

The reports of this paper attempt made on how buying decision influences the performances of an enterprise. The different sectors were chosen for the study such as Manufacturing, Automobile, Food, Textile and Hospitality. The focus of the study was based on three theories such as operational control, performance management and decision. The paper reveals the current trends and make or buy decision of the components and its relationship in taking decisions. It also discusses the two techniques break even analysis and economic analysis for decision making in make or buy decision. The study discusses the advantage of outsourcing and discusses the four theories in the study for make and buys decision

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An Internet of Thing based Agribot (IOT- Agribot) for Precision Agriculture and Farm Monitoring

By Kakelli Anil Kumar Aju. D.

DOI: https://doi.org/10.5815/ijeme.2020.04.04, Pub. Date: 8 Aug. 2020

Developing nations like India have a huge potential for agricultural business and better cultivation. Because of the large size of cultivation land, improper water supply systems and lack of technology-based agricultural practices, there is a huge gap among expected and actual quantity and quality of agricultural products. Hence there is a need for significant revival in agribusiness using emerging technologies. The article proposes an intelligent water framework device called Agribot designed for the agricultural industry to minimize the water wastage and a better supply of cultivating materials using the Internet of Things (IoT). Our proposed IOT- Agribot will energize the water framework, improve the cost-effective water usage and reduce the labor force to achieve precision agriculture. The proposed IOT- Agribot has performed well for variable weather conditions, soli type, moisture content and crops.

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Essential and New Maintenance KPIs Explained

By Fatima Zohra Berrabah Chahira Belkacemi Leila Zemmouchi-Ghomari

DOI: https://doi.org/10.5815/ijeme.2022.06.02, Pub. Date: 8 Dec. 2022

Maintenance in any manufacturing organization is critical, given its significant role in ensuring business continuity. Maintenance plays a crucial role and has a significant impact on the results of industrial companies. Therefore, it is essential to manage maintenance, observe, understand, and improve actions by adopting well-chosen performance indicators according to the company's needs. These indicators are known as Maintenance KPIs or Key Performance Indicators, which allow for gathering knowledge and exploring the best means to achieve the organization's goals. Maintenance KPIs are critical to keeping track of the function, monitoring performance, and ensuring fulfillment of business expectations. In addition, KPIs drive reliability growth while guiding decisions to improve maintenance efficiency and performance. A helpful maintenance KPIs help to identify the problems causing the maintenance effect and help to select the right strategy to support or correct the actions that produced the results. They also allow to identify the causes of equipment failures (measure the influence of life cycle factors), direct what maintenance does with its time and resources (measure the efficiency and effectiveness of the maintenance group) and identify if maintenance removes failure causes ( measure the improved reliability and operational risk reduction results of maintenance effort) and help drive the business benefits provided by maintenance (measure the contribution to the business value of maintenance).

Essential maintenance KPIs are the most commonly used for maintenance management and are adopted by most industries; among these primary KPIs which are essential for maintenance management, we cite Mean Time Between Failure (MTBF), Mean Time To Repair (MTTR), and Overall Equipment (OEE). Nevertheless, it is crucial to continuously redefine and update KPIs to ensure they are appropriate for the organization's current environment, significantly when the constant market or research methodologies change. Hence, researchers and the industry propose several other maintenance KPIs outside the essential ones used in the industry according to the needs and within the performance improvement framework. These proposed KPIs aim to compensate for the lack of maintenance data, the absence of decision support, and the problems related to specific equipment, also in the context of improving the management strategy, the application of predictive maintenance, and the quality control of a maintenance process or the monitoring of systems reviews. Unfortunately, these indicators are not sufficiently known and are, therefore, not used by the industry. However, we believe that some of them should gain maturity and reach the status of widely used traditional indicators, such as the KPI of obsolescence management in maintenance operations and schedule compliance KPIs that aim to link maintenance planning with production. In addition, although not all proposed KPIs in the literature are generalizable, it has been identified that they can sometimes be specific to problematic situations, equipment categories, and even sectors of industry activity. Therefore, this work aims to inventory the most widely used maintenance KPIs and some of the KPIs proposed by researchers and the industry. In addition, we study the trends and challenges of selecting these KPIs and for what purposes they are used to help their understanding and usability. Indeed, Maintenance managers need to select relevant KPIs aligned with the maintenance strategy and the company objectives. 

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