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

      The problem of multi assembly line balancing appears as one of the most prominent and complex type of problem. The research problem of this dissertation is concerned with choosing the suitable method that includes the nature of the processes of the multi assembly type of the sewing line at factory no. (7). The State Company for Leather Manufacturing. The sewing line currently suffers from idle times at work stations which resulted in low production levels that do not meet the production plans. The authors have devised a flexible simulation model which uses the uniform distribution to generate task time for each shoe type produced by the factory. The simulation of the multi assembly line was based on assigni

The study was conducted over the period of Oct 2018 to Apr 2019 and is aimed for the detection and estimation of four hazardous Volatile Organic Compounds VOC (benzene, toluene, ethylbenzene, and xylene) so-called (BTEX) in samples collected from the produced water in the Al-Ahdab oil field in Iraq also to track their availability in the important natural water sources around the field. These compounds pose a risk to human health as well as environment. To avoid the laborious and tiresome conventional extraction methods, water samples were collected and concentrated using solid-phase extraction technique (SPE) which is a robust and cost-effective method of sample extraction with minimal exposure and handling of solvents and then to be analy

Four metal compounds mixed ligand of azo dye ligand (L) and metformin.(Met) were produced at aquatic ethanol for (1:1:1) (M:L:Met). The prepared compounds were identified by utilizing atomic absorption flame, FT.IR and UV–Vis spectrum manners as well as conductivity mensuration. These compounds was assayed of the gained datum the octahedral geometry was proposed into whole prepared complexes.Also in this research was studied represented examining the antibacterial and antifungal impact of the azo dye ligand (L), metformin.(Met) and (Co,Ni, Cu and Cd complexes) on four types of pathogenic, clinically isolated bacteria that are resistant to antibiotic, like Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, Klebsiella pneu

ABSTRACT— In primary teeth, root canal treatment is a time consuming and challenging procedure, particularly during the most important step in endodontic treatment which is the preparation of the canal. Pulpectomy is the treatment of choice in all the necrotic primary teeth. For better treatment protocol, advancing technology brought the rotary system to reduce the manual dexterity and improve the quality of treatment for pulpectomy. This study aimed to compare and assess the efficacy of cleaning and the time required for the instrumentation during the preparation of root canals of the primary molars using the rotary and the manual (conventional) systems. Thirty root canals of primary teeth were selected. These teeth submitted to a

Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti