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)
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Hospital is an organization that is highly dependent on the quality of human resources, this is related to the knowledge of medical personnel. It is therefore important that hospitals can concentrate on managing this knowledge. This study analyzes the process of knowledge management of medical personnel by looking at the SECI model owned by medical personnel, and it will also be analyzed with regard to the characteristics of information technology, social interaction skills and knowledge leadership through descriptive statistical analysis of 33 hospitals in Jakarta. The results of this study showed that hospitals need to increase the knowledge acquisition of medical personnel (tacitly explicitly), in particular using information technology to support this documentation process
In this paper, we seek to present or explain how an application that helps in the process of diagnosing the Corona virus (COVID-19) was designed through the use of X-rays of the respiratory system of the person to be examined where this application was built based on artificial intelligence techniques that are represented in the algorithms of learning machine and deep learning, and with the expectation of a rapid increase in the spread of infection and the emergence of new cases, due to the scarcity of health resources, which require a long time in conducting tests in the laboratories for diagnosing the virus, according to which these results diagnose the patient, as no quarantine is imposed on the person who is the furthest to obtain the result, and it is this period that is waiting The results will spread the virus more quickly due to crowding. We have focused on this situation where the application displays the results very quickly too. The application can move in more than one health center, even in poor areas. Where the main idea is to take an X-ray for a person, enter the image for application, and give immediate results in less than a second, which helps in speeding the diagnosis and reducing congestion
