Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
ACS712 is a sensor to detect current. ACS712 current sensor can detect noise current or additional current. ACS712 current sensor is one of the sensors commonly used in current measurement circuits. In calibration there is an uncertainty that comes from calibration standards and calibrated devices. Analysis of uncertainty calibration ACS712 current sensor has been done with a purpose for acquired correction value, standard deviation, and uncertainty source estimation, and then the biggest source uncertainty from current measurement can be identified. The result of the analysis can be used to minimalize the possibility of appearance uncertainty source on measurement using the ACS712 current sensor. The analysis was conduct by comparing between ACS712 current sensor and clamp meter standard with a calibration certificate. ACS712 sensor test results have a significant correction when the current higher than 5A, and the temperature will increase. The biggest sources of uncertainty result from type uncertainty and expanded uncertainty
Essential oils from two species of mint leaves namely Mentha spicata (spearmint) and Mentha piperita (peppermint) were extracted using ethanol as the solvent. The leaves were mechanically cut into three particle sizes of BSS 200, BSS 80 and BSS 40. 200 ml of ethanol was used to extract oil from 40 grams of each particle size sample with a soxhlet extractor. The extraction was carried out at the boiling point of ethanol (78.37oc) for six hours and oil was recovered by boiling off the ethanol. The results obtained showed the yield of oil from Mentha spicata ranged from 12.44% to 38.50%, while Mentha piperita yielded oil ranging from 8.20% to 38.00%. The physio-chemical properties such as specific gravity, acid value, saponification value, peroxide value and iodine value were determined in other to characterise the two oils. The results obtained are as follows; the specific gravities of the oils are 0.935 and 0.862 for Mentha spicata and Mentha piperita respectively, acid values are 0.4769 and 0.4488 mg KOH/g Mentha spicata and Mentha piperita respectively. The saponification values are 93.126 and 86.394 mg KOH/g for Mentha spicata and Mentha piperita respectively, while the peroxide values are 8.50 and 7.0 mEqO2/kg for Mentha spicata and Mentha piperita respectively. The iodine values are 55.20 and 53.93 g I2/100g for Mentha spicata and Mentha piperita respectively. From the results obtained it is observed that the oil extracted from Mentha spicata is denser, and has a higher tendency to be rancid, has lower oxidation stability and higher proportion of unsaturated fatty acids
photovoltaic standalone buildings are suffering from energy volatility which mainly caused by weather conditions, for that, it is important to adopt a smart energy management system that able to manage the loads according to the available energy. Add for that the inverter overcurrent fault, which is mainly caused by the loads’ reactive power in a well-designed system. Power factor degrades leads to a decrease in the system’s efficiency and depriving it of the use of all available energy. The proposed system in this article offers a complete solution to manage the consumed energy according to the loads' priorities, available energy, user requirements, and the weather conditions for the day and two days ahead, as well as correct the power factor automatically by reducing the apparent power as well as the total current of the invertor. The presented system adopts an ESP32 microcontroller to monitor and control the loads remotely besides correcting the power factor by adding a capacitive load from capacitors bank and as required. AC power sensors PZEM-004T v3 had been used to monitoring the load's properties include voltage, current, active power, and power factor in the load branches and on the mainline. Results show a promising system that not only managed the consumed energy wisely but also improve the building power factor by 0.9
In order for an enterprise to get the best out of its employees and gain a high return of its investment, the Human Resources (HR) should be well managed. To have a good relationship at Small and Medium Enterprises (SMEs) and to have better practices, using Human Resource Management (HRM) is the option to have them thereby enhancing individual/organizational effectiveness. However, enterprise data are increasing enormously, therefore flexibility, scalability, cost of money, and efficiency are crucial challenges faced by SMEs. Another problem is the separated locations of HRs that result in a communication gap thus slow decision-making, inefficiency in data processing, and inability in reacting to the environmental challenges instantly. To fulfill the above-stated issues, it is a good idea to utilize cloud computing services to handle the massive data in order to improve HRM where the data stored at a central location (i.e. cloud). Therefore, this paper focuses on some cloud-based HRM within SMEs and explores the advantages and challenges of adopting such emerged technology. As a result of this aggregated study, it is clear that cloud adoption improves the HRM, allows the SMEs to expand, manage HRs in a flexible way, provides easy decision-making for the managers, and increases the productivity of the enterprise. The study also showed that one of the most important advantages of cloud adoption for SMEs is reduced cost while the most crucial barrier is security
The focus of the paper is toward designing an efficient approach to retrieve processing information from the performed parallel processing via cloud computations technology. Novel Remote Parallel Processing Code-Breaker System via Cloud Computing (NRPPCBSCC) proposed system depends three main sides (Client, Cloud and Server). Hence, the paper covers execution of complex problems, heavy load processing, benefiting from parallel processing approaches via cloud computing principles. The user can send a heavy load from single/multiple client(s) through the cloud-side to single/multiple server(s) for processing single/multiple hash-code(s) with single/multiple thread(s) organizations. The results return back from server-side through cloud-side to the client-side with full-details about the significant required parameters and metric to asses and evaluate the code cracking process. However, all these details will be remaining in the database system of cloud-side that has the role of communicating between client-side with server-side. The system is useful for lay users to understand and enhance intuitive perceptions of the parallel processing via cloud computing
