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:
Over recent years, the evolution of mobile wireless communication in the world has become more important after arrival 5G technology. This evolution journey consists of several generations start with 1G followed by 2G, 3G, 4G, and under research future generations 5G is still going on. The advancement of remote access innovations is going to achieve 5G mobile systems will focus on the improvement of the client stations anywhere the stations. The fifth era ought to be an increasingly astute innovation that interconnects the whole society by the massive number of objects over the Internet its internet of thing IOT technologies. In this paper present a review of advancement mobile generations by contrasting the type, data transmission rate, challenges, techniques, features and applications used to give by comparing and clarifying the enhancements have been produced till the upcoming 5G revulsion. Also, highlights on innovation 5G its idea, necessities, service, features advantages and applications
Detection of objects that are not common is an important issue in the field of classification of vehicles to come. In object detection, many objects have been classified, such as cars, motorbikes, bicycles, and others. But there are still many objects that are not common, especially in Indonesia. There are still many objects that only exist in Indonesia but not in other countries. Like illegal parking, carts street vendors, and many more. Therefore the writer takes the object detection theme. This proposal proposes detecting unusual objects. The object that the author will detect is illegal parking. With the tools the authors will make, there will be a new classification of illegal parking. In this way a new classification of object detection will be born, namely illegal parking objects. So foreign people will not be confused by the situation they will encounter in Indonesia. The output of this research is the label of illegal parking classification and the probability value of the results of the illegal parking classification. The object detection system uses a faster R-CNN algorithm that can work well when detecting object distances and get accurate results for distances of 6 meters by 70%, 12 meters at 90%, 18 meters at 70%
