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:
Kongzhi yu Juece/Control and Decision
Azerbaijan Medical Journal
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)
Zhonghua yi shi za zhi (Beijing, China : 1980)
Changjiang Liuyu Ziyuan Yu Huanjing/Resources and Environment in the Yangtze Valley
Tobacco Science and Technology
Shenyang Jianzhu Daxue Xuebao (Ziran Kexue Ban)/Journal of Shenyang Jianzhu University (Natural Science)
General Medicine (ISSN:1311-1817)
Community users of digital technologies such as the Internet and various facilities such as social media, internet, games, and various other applications provide a variety of positive and negative effects. efficiency, safety, comfort, and effectiveness are positives of this technology but there are also negative impacts such as the decline of social behavior, crime, and moral vulnerability. Although there have been internet ethical guidelines such as Cyber Ethics but have not been able to play a maximum role to be able to control the negative impact. Cyber religious is a model of internet user control of amoral and criminal acts, which can be applied to various elements related to the internet world. One of the applications of cyber religious for user control internet with applications that can detect immoral behavior or crime on the internet through detection on the browser used. It's so easy for someone to access internet information resulting in Uncontrolled Internet users. This can lead to problems such as dangerous access to cysts, pornography, crime, cruelty, abnormal behavior, and committing criminal acts to others. Cyber religious processing is to check the internet access of a person, if found any indication of immorality or crime then the system will provide warning and or provide other information more useful. This research provides various models of cyber religious architecture with adaptation from some research about connection control with internet networks. Each model influences different communities to access from small office (LAN), large office (MAN), Access from any country, and access to the world
One of the main issues with k-means-type algorithms is their sensitivity to seeding selection. Typically, good seeding selection leads to good clustering results. This study provides supporting evidence that the recent k-approximate modal haplotype (AMH)-type algorithm is insensitive to seed selections for clustering categorical data, compared with its counterpart, the fuzzy k-modes-type algorithm. The k-AMH algorithm demonstrates its advantages using six real-world datasets, obtaining high minimum, maximum, and median scores compared with those obtained by the fuzzy k-modes algorithms as verified using analysis of variance and t-tests. Hence, the k-AMH-type algorithm provided statistically significantly different scores at a 5% significance level, compared with the fuzzy k-modes-type algorithm. However, the t-test showed that the k-AMH-type algorithm did not show a significant difference, compared with randomized or k-means++ seeding. Therefore, with insensitive seed selection, the k-AMH-type algorithm could be used to develop a categorical clustering tool