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:
Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
Local structures within an image generally represents a challenge task to discriminate an accurate image texture specifically for some degree of uncertainty due to contrast and other noises on iris images. Feature encoding is a crucial stage so that robust feature descriptors can be produced for representing personal statistical information as failing to tackle it may degrade the performance. In achieving promising result, an evaluation on observing the capability of the fuzzy logic local binary pattern (FLLBP) to encode the iris texture is studied in this paper. An experimental setup based on the degree of fuzziness and the number of samples in the training data is performed and evaluated using iris images from CASIA V3 and IITD database. The results demonstrate a good accuracy score and show that the encoded descriptors from the FLLBP method are able to achieve a significant performance
This study aims to determine the reliability level and the root cause of downtime and propose a preventive action to reduce heavy equipment downtime. The study method used in this study is a mixed-method. Using Minitab 17 software for reliability calculation and using Fishbone Diagram, 5-Whys Analysis, and Pareto Diagram for Root Cause Analysis. The result showed that heavy equipment is not in reliable condition. The output from Root Cause Analysis led that the system is the most influential factor with the highest percentage. Therefore, the company should do a corrective action and the planned preventive action based on the 5-Whys Analysis to reduce downtime