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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

 

SSRN - Elsevier

 

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

 

 

PLAGIARISM POLICY

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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SUBMIT MANUSCRIPT

Submit your manuscript through our online submission portal.

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Recent Articles


Research Article

Advanced Patient Monitoring System with Diseases Prediction System using Machine Learning

Udhayakumar C, Ashik S, Bala Subramaniyan S, Dharanishan K & Ganeshraja A

Page No. 01-08

 Abstract: IoT and machine learning (ML) are becoming increasingly efficient in the medical and telemedicine areas all around the world. This article describes a system that employs latest technology to give a more accurate method of forecasting disease. This technology uses sensors to collect data from the body of the patient. The obtained sensor information is collected with NodeMcU before being transferred to the Cloud Platform "ThinkSpeak" through an ESP8266 Wi-Fi module. ThinkSpeak is a cloud server that provides real-time data streams in the cloud. For the best results, data currently saved in the cloud is evaluated by one of the machine learning algorithms, the KNN algorithm. Based on the findings of the analysis and compared with the data sets, the disease is predicted and a prescription for the relevant disease is issued.

DOI: http://doi.org/10.46431/MEJAST.2022.5201


Research Article

A Novel Undistorted Image Fusion and DWT Based Compression Model with FPGA Implementation for Medical Applications

M. Mohankumar, S. Akilan, B. Hariprasath, R. Ariprasath & S. Dhanu Dharsan

Page No. 09-16

 Abstract: The usage of a fused image and compressed model in a VLSI implementation is demonstrated. In this study, distortion correction is also considered. In distortion correction models, least-squares estimate is utilized. The technique of picture fusion is widely employed in medical imaging. Many pictures are obtained from various sensors (or) multiple images are captured at different times by one sensor in the image fusion approach. CT scans give useful information on denser tissue with the least amount of distortion. The information obtained from a magnetic resonance imaging (MRI) of soft tissue with significant distortion is useful. The DWT-based image fusion approach employs discrete wavelet transforms, a novel multi-resolution analytic tool. Back mapping expansion polynomial is used to reduce computer complexity. Using 0.18um technology, the suggested VLSI design achieves 218MHz with 1480 logical components.

DOI: http://doi.org/10.46431/MEJAST.2022.5202


Research Article

Psoralen Promotes Myogenic Differentiation of Muscle Cells to Repair Fracture

Zhenhai Cui, Tingrui Huang, Chen Huang, Wenhai Zhao, Jianming Chen & Dezhi Tang

Page No. 17-26

 Abstract: Myogenic differentiation requires to be exactly explored for the effective treatment of fracture. The speed of healing is affected by skeletal muscle, linked to activation of specific myogenic transcription factors during the repair process. In previous study, we discovered that psoralen enhanced differentiation of osteoblast in primary mouse. In the current study, we show that psoralen stimulates myogenic differentiation through the secretion of factors to hone the quality of repair in fractured mice. 3-month old mice were treated with corn oil or psoralen followed by a tibial fracture surgery. Fractures were tested 7, 14, and 21 days respectively later by histology and images observation. Skeletal muscles including soleus muscle and posterior tibial muscle around the damaged bone were collected for quantitative real-time PCR, HE staining, as well as western blot. Daily treatment with psoralen at seven, fourteen days or twenty-one days improves protein or mRNA levels responsible for the whole myogenic differentiation process, makes the muscle fibers more tightly aligned, and promotes callus formation and development. This data shows that high levels of myogenic transcription factors in the process of fracture healing in mice foster the repair of damaged muscles, and indicates a pharmacological approach that targets myogenic differentiation to improve fracture repair. This also reflects the academic thought of "paying equal attention to both muscles and bones" in the prevention and treatment of fracture healing.

DOI: http://doi.org/10.46431/MEJAST.2022.5203

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Editorial Board