Journal of Research in Engineering and Computer Sciences <p><em><strong>Journal of Research in Engineering and Computer Sciences (JRECS)</strong></em> is a peer-reviewed academic journal published on bi-monthly bases that publishes high-quality research in the fields of engineering and computer sciences. The journal provides a platform for researchers, engineers, and scientists from around the world to share their latest research findings, ideas, and innovations.</p> <p>Engineering and computer sciences are two fields that are constantly evolving and pushing the boundaries of what is possible. They are integral to the development of new technologies and innovations that have transformed the way we live and work. Research in these fields seeks to understand the underlying principles that govern complex systems, as well as to develop new tools and techniques for solving complex problems. From artificial intelligence and machine learning to robotics and biotechnology, engineering and computer science research are at the forefront of many cutting-edge fields. As the demand for new technologies and innovative solutions continues to grow, the importance of research in these fields cannot be overstated.</p> Headstart Publishing - United Kingdom en-US Journal of Research in Engineering and Computer Sciences Enhancing Safety and Efficiency in Autonomous Vehicles through Integrated AI Technologies <p style="text-align: justify; line-height: 150%; background: white;"><a name="_Hlk108175993"></a>Autonomous vehicles (AVs) stand as a groundbreaking innovation set to transform global transportation systems. Outfitted with sensors, artificial intelligence (AI), and control systems, AVs hold the promise of revolutionizing transportation by ensuring safer and more efficient travel, effectively eliminating human error and enabling seamless navigation. Nonetheless, current research on AVs reveals significant shortcomings across various domains, impeding the realization of their full potential. A notable deficiency identified in the literature is the scant attention given to specific implementations. While numerous studies provide comprehensive overviews or assessments of AV technology, they frequently lack in-depth discussions on practical applications or validation in real-world scenarios, resulting in a disconnect between theory and practice. Furthermore, papers concentrating on policy analysis or offering guidance for policymakers often lack the necessary technical depth, neglecting critical technical aspects and viable solutions. Additionally, many papers fail to sufficiently address associated challenges or constraints, offering superficial discussions on progress and opportunities without thoroughly exploring potential obstacles. This lack of comprehensive solutions exacerbates the issue, leaving significant challenges unaddressed. To address these limitations, a proposed approach could harness advanced AI methodologies, such as deep learning algorithms trained on extensive real-world driving data. Through the integration of these technologies, researchers can develop robust and verified solutions to tackle specific challenges within AV technology, ultimately enhancing safety and efficiency. Comparative evaluations between existing and proposed technologies, incorporating metrics like accuracy, precision, loss, iterations, epochs, and time complexity, will further clarify the effectiveness of integrated AI technologies in advancing AV systems<span style="color: #0d0d0d; background: white;">.</span></p> Clement Varaprasad Karu Asadi Srinivasulu Copyright (c) 2024 Journal of Research in Engineering and Computer Sciences 2024-06-08 2024-06-08 2 3 1 25 Soil Test Crop Response Based Phosphorus Calibration Study on Food Barley (Hordium Vulgare L.) in Degem District of North Shewa Zone, Oromia, Ethiopia <p>Soil productivity decline due to different factors. Blanket recommendation of fertilizer application without considering soil types and agro-ecological of the area are among the problem to obtain sustainable production. This force to site specific nutrients managements and soil test-based crop response fertilizer recommendations. The objective of the experiment was to determine economically optimum Nitrogen, Phosphorus critical (Pc) and Phosphorus requirement factor (Prf) for food barely production in Degam district. In the first year, a field experiment were conducted using, factorial combination of four N rates (0, 46, 92 , and 138 kg ha<sup>1-) </sup>&nbsp;and five P rates (0, 10, 20 ,30 and 40) were applied&nbsp; to determine optimum N, the treatment laid out in randomized complete block design with three replications. Food barely (HB-1307 variety) was used.&nbsp; Soil sample before plating and intensive soil samples after 21 days of sowing were taken from each plot and analyzed for selected physicochemical properties. Phosphorus critical level (Pc) determination was done using C'ate-Nelson diagram method. Agronomic data such as plant height, Spike length, biomass and grain yield were collected and subjected to two-way factorial analysis of variance (ANOVA) using R software while the partial budget analysis was done using CIMMYT (1998). The results indicate that combined NP fertilizer rates significantly influenced the agronomic parameters of food barely. Optimum nitrogen rate (92 N kg/ha), P critical (5.8 ppm) and P requirement factor (14.72) for food barely production in Degam District. Therefore, areas having similar soil conditions and agro-ecology is advisable to uses these finding. Farther verification of the result on farm land could be a pre-request before publicizes the technology to the user.</p> Abera Donis Dereje Girma Dejene Getahun Tadele Geremew Meron Tolosa Copyright (c) 2024 Journal of Research in Engineering and Computer Sciences 2024-06-10 2024-06-10 2 3 26 36 Conservation of Energy Applied to Moving Electrons in Materials at Constant Drift Velocity Under High Electric Fields <p>In this research article, the electron effective mass of drifting electrons in intrinsic Silicon and amorphous thermal silicon dioxide has been calculated by equating the total mechanical energies of electrons at the cathode and anode of the metal-semiconductor-metal, metal-insulator-metal, and metal-insulator-semiconductor structures under high electric fields using the principle of conservation of energy. &nbsp;&nbsp;</p> Ravi Kumar Chanana Copyright (c) 2024 Journal of Research in Engineering and Computer Sciences 2024-06-29 2024-06-29 2 3 37 38 Brain-Computer Interfaces, Generative Artificial Intelligence (ChatGPT and Deepfakes) and Criminal Procedure Law: What´s at Stake? <p>The rapidly increasing use of Artificial Intelligence is shaping up to fray the fabric of Rule of Law. In backsliding regimes, a boundless/ubiquitous Artificial Intelligence might usher in, and pave the way to, a steeper/sharper deterioration of Rule of Law. Which should merit nothing but our undeterred/unbridled preoccupation. Whilst there is a burgeoning consensus according to which the use of Generative Artificial Intelligence (<em>GenAI</em>, for short, which encompasses both Large Language Models and Deepfakes) is bound to put the fundamental tenets of Rule of Law at odds, there is perceived dearth/paucity of legal research regarding the impact of <em>GenAI</em> in the remit of criminal procedure law. &nbsp;Tellingly, and perhaps disturbingly, scant light has been cast upon the clout of Brain-Computer Interfaces in the purview of Criminal Procedure Law, which is swiftly/briskly gathering pace to besmirch/derail a pair of linchpins of the latter: the unwavering principle of presumption of innocence and the unassailable right to mental privacy. Against this stark background, this paper seeks to plug the foregoing gaps while charting the path ahead for a brawny/sturdy criminal procedure law in the age of a Generative Artificial Intelligence, thereby offering a useful template to shrewdly tackle the multifarious issues arising out the interplay between Brain-Computer Interfaces and Criminal Procedure Law.</p> Hugo Luz dos Santos Copyright (c) 2024 Journal of Research in Engineering and Computer Sciences 2024-06-30 2024-06-30 2 3 39 78 The Effects of Copper and Manganese Additives on the Mechanical and Structural Properties of Aluminium Alloy (Al-5wt.%Mg) <p>In this research work, the effects of copper and manganese addition of varying weight percentages, 0.2, 0.4, 0.6, 0.8 and 1.0 were investigated on mechanical and structure of Al-5wt%Mg. The alloys were produced using permanent mold, After the production of the alloy, samples for tensile, toughness, hardness tests and microstructural analysis were produced from various alloys maintaining specific ASTM standards. Characterization was done using Charpy Impact Testing Machine 3000N Joules, model MT 3050, Rockwell Hardness Tester Model HRS-150 and universal Materials Tester 20KN MODEL MT 2021, EDLABQUIP. The results showed that as the content of copper and manganese increased, the ultimate tensile strength, toughness strength and hardness value increased. The optimal tensile strength of 695.33 N/mm2 and 464.181 N/mm2 were obtained from Al-5wt.%Mg +1.0wt.%Cu and Al-5wt.%Mg +1.0wt.%Mn alloys respectively. Moreso, optimal toughness strength value of 19.50 Joules was obtained from Al-5wt.%Mg +1.0wt.%Cu. The microstructure morphologies of the alloy showed the as the additives content increased, refinement of the grains increased. Comparatively, the experimental results showed that copper as an additive in Al-5wt.%Mg alloy played greater role on improvement of its mechanical properties for engineering applications.</p> T. M Onyia Copyright (c) 2024 Journal of Research in Engineering and Computer Sciences 2024-06-30 2024-06-30 2 3 79 93