This paper presents the Taguchi approach for optimization of hardness for  shape memory alloy (Cu-Al-Ni) . The influence of  powder metallurgy parameters on hardness has been investigated. Taguchi technique and ANOVA were used for analysis. Nine experimental runs based on Taguchi’s L9 orthogonal array were performed (OA),for two parameters was study (Pressure and sintering temperature) for three different levels (300 ,500 and 700) MPa ,(700 ,800 and  900)^oC respectively . Main effect, signal-to-noise (S/N) ratio was study, and analysis of variance (ANOVA) using  to investigate the micro-hardness characteristics of the shape memory alloy .after application the result of study shown the hei

It is often needed to have circuits that can display the decimal representation of a binary number and specifically in this paper on a 7-segment display. In this paper a circuit that can display the decimal equivalent of an n-bit binary number is designed and it’s behavior is described using Verilog Hardware Descriptive Language (HDL).
This HDL program is then used to configure an FPGA to implement the designed circuit.

In this work, the synergistic effect of chlorinated rubber (additive I),with zeolite 3A (additive II), zeolite 4A (additive III), and zeolite 5A (additive IV) in (1:1) weight percentage, on the flammability for unsaturated polyester resin was studied in the weight ratios for (3,7,10,13&15%) by preparing films of (130×130×3) mm in diameters. Three standard test methods used to measure were the flame retardation which are; ASTM: D-2863, ASTM: D- 635& ASTM: D-3014. Results obtained from these tests indicated that all of the additives were effective additive IV has the highest efficiency as a flame retardant.

A simple, sensitive and rapid method was used for the estimate of: Propranolol with Bi (III) to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on a reaction between propranolol and Bi (III) in an aqueous medium to obtain a yellow precipitate. Optimum parameters were studied to increase the sensitivity for the developed method. A linear range for calibration graph was 0.1-25 mmol/L for cell A and 1-40 mmol/L for cell B, and LOD 51.8698 ng/200 µL and 363.0886 ng /200 µL , respectively to cell A and cell B with correlation coefficient (r) 0.9975 for cell A, 0.9966 for cell B, RSD% was lower than 1%, (n = 8) for the

Azo derivative ligand[H3L] have been synthesized by the reaction of diazonium salt of p-amino benzoic acid with orcinol in(1:1)mole ratio. The bidente ligand was reacted with the metal ions MnII,FeIIandCrIIIin(2:1)mole ratio via reflux in ethanol using Et3N as a base to give complexes of the general formula: [ M(H2L)2(H2O)x]Cly The synthesized compounds were characterized by spectroscopic methods[ I.R , UV-Vis, A.A and H1 NMR]along with melting point, chloride content and conductivity measurements. The complexes were screend for their in vitro antibacterial activity against one strain of staphylococcus as Gram(+) positive and one strain of pseudomonas as Gram(-) Negative, using the agar diffusion technique.

The urban Gentrification  is an inclusive global phenomenon to restructure the cities on the overall levels, the research to propose a specific study about the concept of urban Gentrification in the cities and showcasing its, specifications, and results, and how to deal with the variables that occur on cities through improvements as part of urban renewal projects, then the general axis of the research is shrinked, choosing the urban centers as the most important areas that deal with the urban Gentrification process due to its direct connection with indivisuals and social changes, and to process the specific axis of the research theses and studies will be showcased that discuss the topic in different research directions, and emerged

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog