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:
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
In recent years research in the field of Artificial Intelligence (AI) has shown a fairly rapid and extensive development. The application of AI in the form of artificial neural networks in the field of Civil Engineering has also shown significant developments. In line with scientific advances in the field of numerical computing, artificial intelligence, also known as AI, has gained popularity in recent years (AI). One of the branches of AI is Machine Learning (ML). Machine Learning is a smart system that can learn and predict output based on learning done on the system. One form of ML is an artificial neural network (artificial neural network, ANN). ANN is a numerical computation model created by mimicking the workings of the human brain. ANN then developed extensively, with a greater number of neurons or by increasing the number of hidden layers. This development leads to a learning model known as Deep Learning (DL). This paper has an objective to describes how deep learning method, one of AI branch, can be used to predict the compressive strength of concrete, especially geopolymer concrete
