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:
The study aimed to establish chess influence on learner’s performance in mathematics. It adopted a quantitative approach and followed a descriptive research design. 70 Grade 9 learners from seven secondary schools participated in the study. Cluster sampling technique was employed with 70 learners being surveyed using a questionnaire. A close-ended questionnaire was used to gather data. The study found that the largest group of learners in school that did not offer chess could not understand or explain En Passant. It also emerged that in schools that offered chess, all learners agreed that they could explain En Passant. Slightly less than 50% of the participants strongly disagreed that they can algebraically notate the game whereas 17.1% disagreed. In non-chess schools, only 4% (N=2) indicated that they can algebraically notate whereas all 20 learners (100%) in chess schools confirmed that they can notate the game. The study concludes that the learners in those schools that offered chess had ideas/could explain the chess terms and vice versa. The study recommends that since the influence of chess training may have positive impact, chess training can be introduced to schools to enhance the mathematics performance of learners.
In recent times, the term ‘Big Data’ has been under the limelight due to its exponential increase in relevance and importance in small, medium, large and very large companies. Industries of divergent sectors such as education, health, agriculture and telecommunication are all leveraging on the power of Big Data to enhance business prospects along with improved customer experience. Testing such highly volatile data, which is unstructured data and generated from myriad sources such as web logs, radio frequency Id (RFID), sensors embedded in devices, which are quite challenging in order to derive maximum benefit in information processing and decision making from the use of big data, such data must be of acceptable quality and must be fairly usable in terms of interloper- ability, relevance, and accuracy. However, such data quality can only be guaranteed if systems from which these data are harvested are adequately tested to ensure that output data from such systems exhibits minimum big data quality standards and characteristics. The methods adopted include Test criterion and cases which consider the volatility of big data and its underlying characteristics which is not limited to, but include Volume, Velocity, Veracity and Variety. Testing such highly volatile data, which is unstructured. Hadoop and Map Reduce which are also tools for testing big data. One of the most challenging endeavour for a tester is how to keep pace with changing dynamics of the industry. This work discusses inherent challenges faced in big data testing and the respective best practices that can be adopted in big data testing to enhance big data quality and accuracy.
Wind energy is one of the promising alternative energy resources after solar and hydropower. Most of wind turbine technologies are designed at high speed, whereas, not effectively operated in low wind speed areas. An effective technology is required to enhance the possible use of wind energy at low wind speeds. Diffuser Augmented Wind Turbine (DAWT) has been used recently to improve the use of wind turbine in a low wind speed area by manipulating the wind speed. The main concept of this technology is the pressure difference between inside and outside of DAWT which is occurred, hence, it might enhance the wind velocity and the power is increased as well. In this paper, simulation using ANSYS was conducted to investigate the performance of Horizontal Axis Wind Turbine (HAWT) in low wind speed area applying DAWT by modifying the angle and the length of diffuser. The variation of the diffuser angle was in the range 4-16o at L=1.25D. The simulation results showed a good agreement with the reference literature which obtained the increased power around 1.4-2.9 times higher than the non-diffuser wind turbine. The parameter of diffuser length was also investigated at L=0.25D-2.5D, with the significant impacts are obtained until L=1.25D
To explore the sensitive characteristics of tiny hazardous gas molecules (SO, SO2, NO, NO2) on a BN monolayer and C-doped BN monolayer, the B3PLYP functional and 6-311G (d, p) basis set computations were utilized. These gases contribute significantly to environmental deterioration. Adsorption energy, adsorption distance, and charge transfer factors all helped us choose the optimal adsorption location from three options: Center, N, and Bridge. The adsorption energy and electron localization function results indicate that various gas molecules (SO, SO2, NO, and NO2) are chemically adsorbed on a BN monolayer and C-doped BN. Our findings further show that following adsorption, there is a large amount of charge transfer between gas molecules and a BN monolayer and a C-doped BN monolayer, with the exception of one location where the adsorption energy is weak and the charge transfer is weak (NO/pristine BN). This means that an a BN monolayer and a C-doped BN monolayer are more vulnerable to SO, SO2, NO, and NO2 adsorption than pristine and doped graphene, and that gas adsorption on the C-doped BN monolayers is stronger to other gases. Furthermore, small gas molecule adsorption clearly modifies the band - gap and work function of a BN and C-doped BN monolayer to variable degrees. Our study will give theoretical guidance for practical implementations
Communicative-based Japanese learning has been applied since the outbreak of the COVID-19 pandemic through Zoom and Aizuchi skill-based multimedia. This study aims to investigate the learners’ initial attitude of learning communicative-based Japanese using Zoom and multimedia-based methods, the impact of online learning using Zoom and multimedia to learn Japanese, the participants’ attitude towards multimedia that has characteristics, autonomous material and media effectiveness, as well as the advantages and disadvantages of learning communicative-based Japanese using Zoom and Aizuchi skill-based multimedia. The descriptive analysis is used as the method in this study. The data collected were processed using the scale of Likert and Guttman. This research was conducted for 6 months in the Japanese Literature Study Program of the University of Hasanuddin Makassar. The research subjects were 30 middle students who have been learning Japanese for more than 2 years. The results of the study proved that communicative-based Japanese learning using Zoom and multimedia for students is very positive ever since it began. The use of Zoom and multimedia provides motivation, comforts, and learners’ creativity, interaction with lecturers and colleagues and good access to learning despite the COVID-19 pandemic. Nonetheless, the amount of cost required concerning large internet quota needed particularly during bad weather is considered the biggest obstacle for learners
