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)
This paper presents the methodology of surface roughness inspection in CNC Turning process. Adaptive Neural Fuzzy Inference System classifier utilizes to predict the high accuracy roughness value with insisting of surface roughness image. The vision system captures the image and determines the mean value by using ANFIS algorithm. Training sets variables speed, depth of cut, feed rate and mean value are feed as the input and manual stylus probe surface roughness value feed as the output. After the simulation process, the testing input performed and finally getting the vision measurement value. This higher accuracy (above 95%) and low error rate (below 4%) can be achieved by using the ANFIS classifier, which is predominantly helpful for the industry to measure the surface roughness. Assign the quality of the product by evaluating the manual stylus probe and vision measurement value.
Flesh and skin of red dragon fruits contain anthocyanins which are potential as a natural dye. This study aimed to improve the stability of anthocyanins using the copigmentation method. The stages on this study were maceration, extraction, evaporation, and copigmentation. The anthocyanins levels in the sample were determined by measuring the absorbance using UV-Vis spectroscopy. Copigmentation was carried out by adding anthocyanins with alum, Al2(SO4)3, in ratio of 1:1; 1:2; and 1: 3 by volume. Stability of the color was tested by storing of the solutions and the cotton fabrics at room temperature for 0, 3, and 6 days. The results analysis showed that the anthocyanin levels in flesh and skin of red dragon fruit were 13.20 mg/100 g and 5.37 mg/100 g. Stability of anthocyanin with copigment alum Al2(SO4)3 in a ratio of 1:1, 1:2, and 1:3 and a storage time of 0, 3, and 6 days of the cotton fabrics showed decreasing in color intensity due to the degradation and temperature. The color change in the copigmented extract to yellow compared to the pure anthocyanin