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Aims and Scope

Middle East Journal of Applied Science & Technology (MEJAST) is the dominant journal for publishing innovative research ideas in arts, science, medicine, law, engineering and technology domains with relevant applications. MEJAST welcomes full papers, communications, technical notes, critical and tutorial review articles, editorials, and comments, in addition to the literature reviews that are prepared by an expert panel. This includes, but is not restricted to, the most recent progress, developments and achievements in all the below mentioned domains.

Submissions are welcome in the following areas, but note this list reflects the current scope and authors are strongly encouraged to contact the editorial team if they believe that their work offers potentially new and emerging research relevant to the journal scope and coverage & not strictly limited within: Aerodynamics, Automation Systems, Biology, Biomedical Engineering, Botany, Chemistry, Communication Systems, Computer Science, Conventional Energy, Data Communication, Dentistry, Economics, Education, Electromagnetics, Embedded Systems, Engineering Domains, Finance, Food & Nutrition, Geology, Green Computing, Grid Computing, High Speed Networks, Image Processing, Management, Mathematics, Mechanics, Meteorology, Microbiology, Mobile Computing, Nano Robotics, Nursing, Operating Systems, Optical Communication, Physics, Physiotheraphy, Political Science, Power Systems, Psychology, Red Taction, Sensor Networks, Sociology, Sensor Networks, Thermodynamics, Veterinary Medicine, Video Signal Processing, VLSI Design, Wireless Communication.


Vision and Mission

Mission: MEJAST is dedicated in making authentic knowledge contributions to research and technical communities worldwide. We are proud to be engines of these communities by contributing our painstaking efforts to their advancements in these fields. By delivering world-class trustworthy information and innovative discoveries to researchers, educators and practitioners around the globe, we help them to become more productive in their work and successful in their career.

When information is to be displayed worldwide, searching for quality information is a big challenge. That is why MEJAST partners (by making them Fellows) with leading experts, and publishes the most trustworthy and innovative information here, so that scientists and professionals can make critical decisions with advance scientific discoveries.

MEJAST uses various user-friendly modern technologies to broadcast and multi-cast world-class information with a view to ensure it reaches to each and every one of global community of scientists, doctors, researchers, educators and decision-makers without any barriers or boundaries for optimum utilization of valuable explorations in various research fields.

Vision: We strive to utilize our best available resources and efforts to improve quality of our authors constantly. We partner with professionals in research and technical communities to understand and ascertain how they work and what they need, so that we can develop techniques and produce research which help them to be more effective. We distribute information and contribute to a common goal of advancing research and share the benefits such as progress, prosperity and potential for incremental growth which that brings for entire research society, in a long-term manner.

 

Abstracting & Indexing

 

 

Crossref

 

Google Scholar

 

Dimensions

 

Middle East Journal of Applied Science & Technology publishes only cutting-edge articles and is  currently being indexed in Google, Google Scholar, Open Ukrainian Citation Index, Crossref, Slideshare, Academia, Researchgate, Semantic Scholar, Scribd, Issuu, Worldcat, etc.

 

 

Plagiarism

The primary step by our quality maintenance team before starting the review process.

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Open Access

Freely available on online upon publication without any Limitations.

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Peer Review

Maintaining the high standards of peer review while enhancing the quality of the review process.

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Submission

Submit your manuscript through our online submission portal.

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Volume 8 Issue 1 January-March 2025

Recent Articles

Research Article

Performance Evaluation of Hepatitis Disease Prediction in Early Stage Using Machine Learning Techniques

Mst. Sumaiya Akter Mim, Md. Julker Nayeem, Sohel Rana & Md. Rabiul Islam

Page No. 01-20

 Abstract: The application of classification approaches utilizing multi-variable with machine learning methods holds immense implications, particularly in the realm of healthcare and disease prediction. Accurate classification of medical conditions, such as hepatitis, is critical for early diagnosis and timely intervention. In order to identify people based on important hepatitis-related characteristics, this study applies advanced machine learning with statistical techniques. It also examines a real dataset in order to create a reliable early detection predictive model. Through this model, we aspire to raise awareness and guide affected individuals toward timely treatment. The paper focuses on comprehensive data preprocessing, including outlier removal, handling class imbalance problem, missing values and extract highly correlated features in order to improve model performance. In our research paper, we have applied mean/mode imputation technique to deal with missing values. Furthermore, we have used z score approach to detect and remove outliers from out dataset and handle class imbalance problem by using oversampling technique. To identify features that are highly correlated, we have used the embedded feature selection approach in our paper. Classic machine learning algorithms, notably K-Nearest Neighbors (KNN), Naive Bayes (NB) and Random Forest (RF) have employed to predict either a person is affected by hepatitis disease or not. To assess the efficacy of our model, we have utilized the 10-fold cross validation procedure. At 97.44%, we have the highest classification accuracy from RF, with Precession, Recall, F1 score and ROC values of, respectively, 0.99, 0.96, 0.97 and 1.00.

DOI: https://doi.org/10.46431/MEJAST.2025.8101

Review Article

Clinical Guidelines and Best Practices for Neuromuscular Blockade Monitoring: Ensuring Patient Safety and Optimal Outcomes

Ravi Yadav

Page No. 21-30

 Abstract: Background: The reliability of neuromuscular monitoring is essential in optimizing anesthesia outcomes. Quantitative Train-of-Four (TOF) monitoring has emerged as a tool for ensuring precise neuromuscular blockade management. Objectives: This study aims to compare the efficacy and safety of neuromuscular blockade reversal guided by quantitative TOF monitoring with reversal conducted without such monitoring. Methods: A literature-based analysis was conducted, evaluating existing data and trends regarding the use of quantitative TOF monitoring in clinical practice. Performance metrics, such as precision in blockade reversal, efficiency, and associated outcomes, were assessed to highlight the advantages and limitations of each approach. Results: Findings demonstrated that quantitative TOF monitoring facilitates a more consistent and reliable reversal of neuromuscular blockade. It reduces the risk of residual paralysis and enhances patient safety. In contrast, practices without TOF monitoring showed variability in outcomes, reflecting potential gaps in blockade management. Conclusions: Incorporating quantitative TOF monitoring into anesthesia practices improves the accuracy of neuromuscular blockade reversal, emphasizing its importance in modern anesthetic care. The study underscores the need for broader adoption of such technologies to standardize outcomes and enhance procedural safety.

DOI: https://doi.org/10.46431/MEJAST.2025.8102

Review Article

Review on renewable energy-based KY boost converter and seven level-inverter systems

Gopika B.S. & Rajeshwari

Page No. 31-39

 Abstract: Static VAR compensators (SVC), power rectifiers, and thyristor converters are examples of power electronics components that significantly contribute to harmonics in a range of applications. The use of power electronic converters, especially DC/AC PWM inverters, has been expanding in the industry due to the advantages they provide, including reduced energy consumption, improved system efficiency, higher-quality products, simplicity of maintenance, and more. One of the most basic and well-known topologies for multilevel inverters is cascaded H-Bridge (CHB) MLI. A KY boost converter with seven-level inverters is suggested in this study. A Matlab simulation is used to evaluate the suggested work. According to the simulation findings, the output voltage climbed from 121V to 155V, the motor speed increased from 940 rpm to 1050 rpm, the motor torque increased from 0.92 N/m to 1.80 N/m, and the output current THD decreased from 31.2% to 19.01% when a KY boost converter with a seven-level inverter was used. According to the simulation results, the conventional boost converter with a five-level inverter system performs worse than the suggested KY boost converter with seven-level inverters.

DOI: https://doi.org/10.46431/MEJAST.2025.8103

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Editorial Board