This paper focuses on the optimization of drilling parameters by utilizing “Taguchi method” to obtain the minimum surface roughness. Nine drilling experiments were performed on Al 5050 alloy using high speed steel twist drills. Three drilling parameters (feed rates, cutting speeds, and cutting tools) were used as control factors, and L9 (3³) “orthogonal array” was specified for the experimental trials. Signal to Noise (S/N) Ratio and “Analysis of Variance” (ANOVA) were utilized to set the optimum control factors which minimized the surface roughness. The results were tested with the aid of statistical software package MINITAB-17. After the experimental trails, the tool diameter was found as the most important facto

Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

Forty eight isolates (41.02%) were obtained from 117 wound and burn samples. The isolates that showed high resistance for both antibiotic was two only that represent 4,1% from all isolates. The result of PCR product electrophoresis was referred that the gene is VIM gene. Lactose and raffinose showed double increasing in diameter of inhibition zone of imipenem with 1% that mean showed highest susceptibility that decreased with the concentration increasing, the same result were with meropenem. But no effect were detected on meropenem inhibition zone diameter. Mannose have no effect on the resistance in 1%, 3% and 7%. Results showed that only three case that increase the expression of gene, they were lactose at 1% concentration that increased

This research came with the aim of showing the impact of governance mechanisms on tax avoidance practices, and in light of this, the financial data of the joint stock companies (industrial, service, agricultural, and hotels) listed in the Iraq Stock Exchange amounting to (35) companies were collected during the period (2009-2020). Through the financial reports published on the market website, multiple linear regression analysis was used as a tool to study the relationship between variables, and (Eviews 12) program was used for analysis and hypothesis testing. To achieve the objectives of the research,(administrative ownership, board size, board independence, women's membership) was adopted as an indicator of the dimensions of governance, an

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima