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 explosive growth in the use of mobile and wireless devices demands an adequate level of security for such devices. The security level need to be strengthen not only in device, but also in mobile application installed in the devices. This paper presents design in developing secure files transfer mobile application using digital signature technology; Elliptic Curve Digital Signature Algorithm. The developed mobile application consist of 8 main modules, including two modules that apply ECDSA algorithm; sign and send module. The developed mobile application not only secure the transferred file using digital signature, it also provide signature pad for user to enable user to use electronic signature for document
Information and communication technology (ICT) development gives great impact on organization’s growth. Organization growth can cause change of structure in the organization, whether it is predictably happened or in a sudden. Education sector also can have impact on structural change, that’s why succession planning is important. Education Institution needs to prepare the successor in a systematic and continuous program. The way to improve the succession planning process is by implementing Machine Learning. This paper uses Systematic Literature Review to find the trends of implementation machine learning in education sector. The result shows three types of trends such as concept, research and thesis or dissertation product. These three trends also come with some factor to improve succession planning and the implementation of machine learning