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Unlocking Solar Potential: Advancements in Automated Solar Tracking Systems for Enhanced Energy Utilization Hussain, Abadal-Salam T.; Hakim, Baqer A; Ahmed, Saadaldeen Rashid; Abed, Tareq Hamad; Taha, Taha A.; Hasan, Taif. S.; Hasan, Raed Abdulkareem; Hashim, Abdulghafor Mohammed; Tawfeq, Jamal Fadhil
Journal of Robotics and Control (JRC) Vol 5, No 4 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i4.19931

Abstract

The use of solar tracking systems has become vital and has established itself as a vital element in the generation of solar energy by enhancing the collection efficiency. This paper seeks to understand the necessity of shifting from conventional energy sources and why issues like scarcity of fossil fuel, and pollution are some of the hurdles toward achieving sustainable energy. Solar power, in particular, is one of the lights at the end of this tunnel since it pioneers a shift towards the usage of clean energy in the world. The subject of interests of the study is on how tracking systems help in maximizing energy collection from solar systems by interchanging it with the movement of sun’s path. It discusses the method that was followed, which involves selecting component, designing circuit and developing software together with presenting empirical data that was obtained from a three-day, Twenty-four-hour experiment. Outcomes show that there is an improvement on voltage stability, the level of solar irradiation and temperature regulation when the system is applied as compared to static system and its applicability for the enhancement of the renewable energy harnessing methods by using the solar tracking technology. Finally, it outlines the future research directions to continue exploring the proposed methods and its wider impact on renewable energy generation.
A powerful heuristic method for generating efficient database systems Abbas, Haider Hadi; JosephNg, Poh Soon; Khalaf, Ahmed Lateef; Tawfeq, Jamal Fadhil; Radhi, Ahmed Dheyaa
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5070

Abstract

Heuristic functions are an integral part of MapReduce software, both in Apache Hadoop and Spark. If the heuristic function performs badly, the load in the reduce part will not be balanced and access times spike. To investigate this problem closer, we run an optimal database program with numerous different heuristic functions on database. We will leverage the Amazon elastic MapReduce framework. The paper investigates on general purpose, implementation, and evaluation of heuristic algorithm for generating optimal database system, checksum, and special heuristic functions. With the analysis, we present the corresponding runtime results. For the coding part, the records counting part is hasty and can only work for local Hadoop part, it can be debugged and optimized for general purpose implement on Hadoop and Spark and turn into an effective performance monitor tool. As mentioned before, there are strange issue, also the performance of BLAKE2s is unexpectedly slow in that it’s widely accepted the performance of BLAKE2s is much better than MD5 and SHA256, we would like to figure out why the common-sense performance of heuristics is deferent from what we got in distributed frameworks.