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
Interventional Pulmonology (middletown, de.)
File carving is a technique to extract data from digital evidence and the signature-based approach searches data for patterns of file signature. As a response to demands of employing a high-performance string searching algorithm, the baseline algorithm, namely Boyer-Moore algorithm, is being widely used since proposed. However, there are more algorithms which are better than it, being continually proposed. Therefore, this paper aims to identify the best string searching algorithm that can be used for optimizing the signature-based file carving in term of time and memory usage. Therefore, a performance analysis against the baseline algorithm and its variations are performed. The findings indicate that the Shift-Or (SO) algorithm can be used as string searching algorithm in signature-based file carving due to its faster completion time and lower memory consumption. For future work, SO algorithm will be integrated with the file carving tools to test the capability of reducing the carving duration and memory usage while maintaining the similar carving accuracy.
Multi-objective optimization of EDM machining process of hardened 90CrSi steel will be presented in this study. The input parameters including Concentration of powder, Pulse on time, Pulse off time, Current, and Voltage are chosen to minimize the electrode wear rate and maximize material removal rate. Grey Relational Analysis (GRA) is combined with Taguchi method to find the optimal set of machining parameters which can satisfy the responses. It is found that Current has the strongest influence (24.89%), but Volgage has the smallest effects (1.63%) on the responses. The proposed model corfirmed by experiment and ANOVA exhibits the reability approch to predict electrode wear rate and material removal rate.