American Scientific Research Journal for Engineering, Technology, and Sciences <div style="float: left; width: 315; text-align: center; margin-left: 5px;"> <p style="text-align: justify;">The <a title="home page for American Scientific Research Journal for Engineering, Technology, and Sciences" href="">American Scientific Research Journal for Engineering, Technology, and Sciences</a> is <strong>multidisciplinary <strong>peer reviewed </strong>Journal </strong><strong>intended to publish original research papers, review articles, short communications and technical reports in all main branches of science (All scientific disciplines) such as Social Sciences , Natural Sciences , Formal Sciences, and Applied science. (but not limited to):</strong> anthropology, archaeology, communication, criminology, education, government, linguistics, international relations, political science, sociology, Earth science, Ecology, Oceanography, Meteorology, Life science, Human biology, Decision theory, Logic, Mathematics, Statistics, Systems theory, Theoretical computer science, Applied physics, Computer science, all Fields of engineering, Accounting, , Education, Economics, Medical Technology, Biology, Medicine, Management, History, Mineralogy, Civil Engineering, Marine Technology, Commerce, Chemical Engineering, Animal Sciences, Petroleum &amp; Gas, Energy Resources, Agriculture, Medical Sciences, Machine Learning, Machinery, computer Science, Chemistry, Neural Networks, Physics, Social Science, Geology, Transportation, Waste Management, Control Engineering, Applied Mathematics, Oceanography, Biomedical Materials, Construction, Metallurgy, Neural Computing, Industrial Arts, IT, Astronology, Fire &amp; Fire Prevention, Robotics Marine Sciences, Solid State Technology, Business Administration, Food &amp;Food Industry, Atmospheric Sciences, Artificial Intelligence, Textile Industry &amp; Fabrics, Education science, Physiology, Nano Science, Microbiology, Psychology, Statistics, Pharmaceutical Sciences, Genetics, Botany, Veterinary Sciences, Biotechnology, Biochemistry, Zoology, Oncology, Accounting, Entomology, Parasitology, Evolution, human behavior, Biophysics, Fisheries, Pharmacology, Geography, Cell Biology, Genomics, Plant Biology, Law, Religious Studies, Endocrinology, Dentistry, Infectious Diseases, Toxicology, Immunology, Teacher education, and Neuroscience. </p> <p style="text-align: justify;">This International journal usually will provide the Editor's decision based on the peer review results <strong>within 4 weeks (28 days)</strong> from the paper submission date.</p> <p style="text-align: justify;">The journal accepts scientific papers for publication after passing the journal's double peer review process. For detailed information about the journal kindly check <a title="About the Journal" href="">About the Journal</a> page. </p> <p> </p> </div> Mohammad Nassar for Researches (MNFR) en-US American Scientific Research Journal for Engineering, Technology, and Sciences 2313-4410 <p>Authors who submit papers with this journal agree to the <a title="Copyright_Notice" href="" target="_blank" rel="noopener">following terms.</a></p> Reliability Optimization in Healthcare Warehouses Through Advanced Quality Assurance Techniques <p>“Big data” refers to extremely useful and extensive datasets. A lot of people have been paying attention to it over the last 20 years because of the promising future it holds. The goal of many public and private organizations is to improve customer service by the collection, storage, and analysis of massive volumes of data. The healthcare business extensively uses big data from a wide variety of sources, including patient medical records, test results, hospital records, and Internet of Things devices. Additionally, biomedical research generates a substantial quantity of big data that is relevant to public healthcare. Proper management and analysis of this data are prerequisites for extracting actionable insights from it. This is crucial because without it, using big data analysis to solve problems is like trying to find a needle in a haystack. The only way to overcome the many challenges of processing massive data at each phase is to use state-of-the-art computer tools for big data analysis. For this reason, healthcare professionals who wish to propose solutions that can enhance public health must possess the appropriate infrastructure to methodically generate and evaluate large data. When big data is properly managed, analyzed, and understood, it can open up new possibilities for modern healthcare. That is why numerous industries, healthcare included, are putting in a lot of effort to make the most of this chance and transform it into better services and more money. Medical therapy and personalized treatment stand to benefit greatly from the current healthcare industry's increased emphasis on biomedical data integration.</p> Phani Chandra Barla Copyright (c) 2024 American Scientific Research Journal for Engineering, Technology, and Sciences 2024-05-26 2024-05-26 98 1 12 23 Use of Solar Photovoltaic Systems for Meeting the Power Demand in the Island of Crete, Greece Avoiding the Land Use Conflicts <p>Solar photovoltaic systems are increasingly used for power generation worldwide replacing the use of fossil fuels and reducing the energy-related carbon emissions. The abundant solar energy resources in Crete can generate green electricity increasing the island’s energy security and self-sufficiency. Apart from installing them on the ground new configurations for siting solar photovoltaics have been developed avoiding the conflicts related with land use. Several unconventional configurations regarding the installation of solar photovoltaic modules in Crete meeting the annual power demand have been investigated. These configurations include their installation on rooftops of buildings, on the surface of water bodies, on cultivated and uncultivated land allowing the dual production of energy and food and on the fields vertically sited. Evaluation of power generation from solar photovoltaics sited on rooftops of buildings in Crete indicated that they could generate a significant amount of the annual electricity demand of the island while the floating solar photovoltaics could only generate a small amount of its annual power demand. The use of agrivoltaics and of vertical photovoltaics in Crete could generate significant amounts of electricity although quantitative estimations have not been implemented. In conclusion, solar electricity generation in Crete can meet the annual power demand in the island allowing the dual use of valuable and fertile land for electricity generation and food production.</p> John Vourdoubas Copyright (c) 2024 American Scientific Research Journal for Engineering, Technology, and Sciences 2024-05-26 2024-05-26 98 1 37 52 Enhancing Quality Control in Medical Devices Supply Chain Using Artificial Intelligence and Machine Learning <p>Due to its significance, it plays in the management of public health, the healthcare industry is among the most important sectors. The rapid spread of several diseases, most notably the COVID-19 pandemic, has put this sector of the economy in the spotlight. The healthcare supply chain (HSC) has had its weaknesses exposed by the pandemic. The healthcare supply chain is undergoing a period of revolutionary change due to new inventions such as the advent of various cutting-edge technologies such as Industry 4.0 and artificial intelligence. Within the context of a growing economy, this research aims to identify the most critical success factors for using AI in HRM. Using an approximation of SWARA, the HSC ranks CSFs of AI adoption. According to the findings, technological (TEC) factors have the greatest impact on the adoption of AI in HCI within the setting of developing nations. The following dimensions pertain to human beings, groups, and institutions: INT, HUM, and ORG.</p> Phani Chandra Barla Copyright (c) 2024 American Scientific Research Journal for Engineering, Technology, and Sciences 2024-05-26 2024-05-26 98 1 1 11 Study to Improve Engineering Properties of the Mixtures of Cinder, Natural Pozzolana and Lateritic Soils for Construction of Surfacing Layers of Low Volume Roads in Mbeya Region Tanzania <p>The availability of suitable gravel materials for road construction that meet specified standards are becoming scarce and the use of available marginal materials shows challenges of not meeting engineering properties for construction of surfacing layers of Low Volume Roads (LVRs). This study aims at investigating the engineering properties of the mixtures of marginal materials which are natural cinder gravel, natural pozzolana and lateritic soils. Natural cinder and natural pozzolana were sourced from Ituha area in Mbeya Region and lateritic soils were sourced from Busale area in Tukuyu District Mbeya Region. In order to improve engineering properties of these marginal materials blending process of the three source materials was conducted. Characterization of source materials and four different blends which are 19La22Po59Ci, 21La20Po59Ci, 23La18Po59Ci and 25La16Po59Ci used for this study were conducted. The tests performed includes particle size distribution, Atterberg limit, compaction test and California bearing ratio.Laboratory test results indicates that all three source materials did not meet criteria to be used for construction of surfacing layer materials of LVRs in Tanzania. The results indicate that all four blends used for this study meet the specification as gravel materials for the construction of surfacing layers of LVRs in Tanzania. This is because the GC and SP values are within the recommended ranges and CBR values are above the minimum of 15%. From the results of this study, it is recommended to improve the engineering properties of marginal materials through blending techniques which could reduce the cost of construction and solve the challenge of scarce suitable materials in many areas in Tanzania.</p> Ally Seleman Mwita Dr. Duwa Hamisi Chengula Prof. Joseph John Msambichaka Copyright (c) 2024 American Scientific Research Journal for Engineering, Technology, and Sciences 2024-05-26 2024-05-26 98 1 24 36 Utilize Dense Optical Flow for Small Flying Targets Detection and Tracking <p>The detection of small targets remains a critical challenge within the field of image processing. Traditional techniques, such as image subtraction with frame-to-frame registration, suffer from high false alarm rates. Even state-of-the-art deep learning architectures, like YOLO and Masked R-CNN, exhibit limitations in this domain. In overextended distances, the inherent feature quality of small targets degrades significantly, leading to a scarcity of informative data for conventional detection algorithms. Consequently, accurate visual recognition becomes a particularly hard task.This work presents a novel detection approach that draws inspiration from the human visual attention mechanism. By leveraging dense optical flow, the model prioritizes moving objects within the scene, facilitating effective target detection. Furthermore, the proposed method employs K-Means clustering to achieve robust foreground-background separation based on color intensity characteristics. To address the limitations of dense optical flow with stationary targets, a dedicated tracking algorithm is also introduced. Our approach demonstrated a high level of accuracy (98%) when evaluated on unseen test data. Additionally, the algorithm functioned in real-time, enabling immediate processing.</p> Saad Alkentar Abdulkareem Assalem Copyright (c) 2024 American Scientific Research Journal for Engineering, Technology, and Sciences 2024-05-26 2024-05-26 98 1 53 70