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:
ABTRACT - There are real businesses in the community, especially small and middle business, experiencing paralysis in this pandemic era covid 19 where the economic and social sectors experience shocks. This problem is very interesting to examined. This research aims to know how to produce market oriented batik in the pandemic era covid 19 and be able to be sold in the market and still exist. This research can be used as a recommendation for batik entrepreneurs in producing batik based on the market demand in the pandemic era. The method used in collecting the data is conducted by interview, questionnaire, and literature. This research was conducted in batik industrial center in Masaran, Sragen, Indonesia with population 165 batik entrepreneurs and 200 consumers of Batik Masaran Indonesia. The research design used qualitative and quantitative mix method with sequential explanatory. The method of data analysis uses management of batik production through conjoint analysis in batik attributes, marketing model in increasing the sales in the pandemic covid 19. The result of the research shows that the management model can be carried out through consumer information, entrepreneur’s characteristics, entrepreneur’s environment, entrepreneurs interest, stake holder empowerment, entrepreneurs’ behavior and the entrepreneur learning process in increasing sales during the pandemic.
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
Concrete damage condition rating based on visual assessment is qualitative and subjective and depends on the investigator’s experience, knowledge, and skills, which results in varied assessments from each investigator. To resolve this problem, a condition rating scale of visual-based concrete damage assessment has been developed in order to show a measured condition and rate the concrete damage conditions of buildings. The scale can describe buildings that are in very good to very bad condition; a very bad rating means that the building cannot be used. This assessment also calculates the building structure element’s critical rating. The condition rating scale is determined based on the concrete’s damage condition and the concrete’s compressive strength requirements. Concrete damage-condition rating values are determined based on expert appraiser feedback that was obtained through a questionnaire, which was processed using the fuzzy logic approach. The condition rating scale usage of visual-based concrete damage assessment will show the building’s structural element damage condition rating and the building damage condition rating as a whole, as well as the actions that need to be taken. Assessment results can also show a priority scale to determine the next actions to be taken by the decision-maker.
Supply chain (SC) lays out the heart of every industry, including the automotive industry. Recently, several studies in SC has been conducted to look for the innovation that potentially adopted to gain the value-added for the industry. In this line, SC in the automotive industry is a very complex process and required the high standard for the product such as a car. In this context, the companies are collaborating to supply the component for the automotive industry. However, a single component defect might cause huge financial losses for the company or life. Technically, the new Blockchain technology with matching features is required by automotive. In this set, SC explores the possible adoption. This bibliography descriptive research is facilitated by Publish or Perish tools to gather the high-quality works of literature from Scopus index database. It also used VosViewer tools to process the thirty-seven papers found to visualize the development trend of SC Blockchain Technology based in the automotive industry. The study revealed essential Blockchain Technology research in the automotive industry started in 2017 and eight essential relevance terms or important factor for the automotive industry
