Journal of Research in Engineering and Computer Sciences

Enhancing Safety and Efficiency in Autonomous Vehicles through Integrated AI Technologies

Asadi Srinivasulu — 2024-06-08

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.

Soil Test Crop Response Based Phosphorus Calibration Study on Food Barley (Hordium Vulgare L.) in Degem District of North Shewa Zone, Oromia, Ethiopia

Abera Donis — 2024-06-10

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^1-) and five P rates (0, 10, 20 ,30 and 40) were applied to determine optimum N, the treatment laid out in randomized complete block design with three replications. Food barely (HB-1307 variety) was used. 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.

Conservation of Energy Applied to Moving Electrons in Materials at Constant Drift Velocity Under High Electric Fields

Ravi Kumar Chanana — 2024-06-29

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.