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
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