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:
Laser drilling is one of the earliest applications of lasers in materials processing. Less than 0.25mm in diameter are difficult to drilled mechanically. Laser drilling offers good choices for small hole drilling, especially for hard and brittle materials such as ceramics, but cracks appearance is one of the most difficulties that appears in this drilling. Therefore, this paper aims to study the effect of number of pulses on the drilling of soda lime glass (SLG) using under water laser drilling technique. A 1.15 mm thickness SLG sheets were immersed 1mm below the de-ionized water surface, then irradiated with CW CO2 laser. The laser parameters used were (19, 20.5 and 22) W power, (5, 7.5 and 10) sec exposure time and (2, 3 and 4) pulses. The drilled points were investigated under optical transmission microscope. Then the upper diameter, lower diameter, crack length and taper angle for these drilled holes were measured by analyzing the OM images using ImageJ software. Clearly appeared that hole diameter and the crack lengths could be controlled by the laser power and no. of pulses. When power or pulses were increased, the hole diameter increased. While the length of cracks is decreased with increasing no. of pulses and increased when the power increased. The good results found at laser power 24 W, five sec. and one pulse for hole diameter, while the minimum crack length was found at four pulses, five sec. and 19 W power
Machine learning (ML) and data mining have established several effective applications in gene selection analysis. This paper review of machine learning supervised algorithms of gene selection. The high dimension that mean select a gene technique before submitting data to classifier. Supervised learning is learning involves an expert well-versed in the environment. We present a number of methods using machine learning supervised algorithms of gene selection data set leukaemia, colon, lymphoma. Furthermore, compare which algorithms is the best for using gene selection. Finding the accuracy of data set selection. The classification accuracy with minimum number of genes is improved better than further filtering and combination
