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:
In the internet of things era, everything gets connected at anytime from anywhere. Big data results from increasing in transforming raw information from different sources. In this context, an efficient processing approach has used. Image registration techniques consider one of the widely used techniques for manipulating redundant images before storing them permanently. However, there is still one more issue to discuss with this technique, the optimization problem. Finding the best transformation which requires working with too many solutions is called optimization. The computational intelligence field of artificial intelligence includes many algorithms based on the natural inspired process. The evolutionary algorithm is the first choice for many researchers to overcome this problem for their easy and low-cost implementation. But the local optima problem is inherently in these algorithms. So the researcher tries to use different emerging techniques to overcome this obstacle. In this review, different optimization techniques reviewed and summarized in order to give an extent to the current development in this
Grinding is one of the most important finish processing methods for hard-to-machine metallic alloys. For precise grinding, dressing is required. In grinding processes, the dressing regime parameters are the most important enabling factors that need to be determined. This study refers to the influences of the dressing parameters when grinding sharpen convex surface by CBN wheel on CNC milling machine are investigated. Those parameters are the depth of dressing cut, the rate of dressing feed and the speed of grinding wheel. This study has applied Taguchi technique and analysis of variance (ANOVA) to identify the impact of dressing regime parameters on the surface roughness. The results show that the impact level of the feed rate (Fe), the wheel speed (Rpm), the cutting depth (aed) are 38,35%, 28.84%, 24.44% with an error on surface roughness (Ra) is 7.36%. For the desired result “smaller is better”, optimum dressing parameters with the cutting depth of 0.02 mm, the wheel speed of 1000 rpm and the infeed rate of 200 mm/min have been determined. With their optimum dressing parameters, the grinding processe convex shaped profile cylinder part by CBN wheel on CNC milling machine gets the best surface roughness
