New vision of Mr. Abdul Mahdi Al-Muttafiqi in the light of unpublished documents

Burnishing improves fatigue strength, surface hardness and decrease surface roughness of metal because this process transforms tensile residual stresses into compressive residual stresses. Roller burnishing tool is used in the present work on low carbon steel (AISI 1008) specimens. In this work, different experiments were used to study the influence of feed parameter and speed parameter in burnishing process on fatigue strength, surface roughness and surface hardness of low carbon steel (AISI 1008) specimens. The first parameter used is feed values which were (0.6, 0.8, and 1) mm at constant speed (370) rpm, while the second parameter used is speed at values (540, 800 and 1200) rpm and at constant feed (1) mm. The results of the fatigue

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The basic analytical formula for particle-hole state densities is derived based on the non-Equidistant Spacing Model (non-ESM) for the single-particle level density (s.p.l.d.) dependence on particle excitation energy u. Two methods are illustrated in this work, the first depends on Taylor series expansion of the s.p.l.d. about u, while the second uses direct analytical derivation of the state density formula. This treatment is applied for a system composing from one kind of fermions and for uncorrected physical system. The important corrections due to Pauli blocking was added to the present formula. Analytical comparisons with the standard formulae for ESM are made and it is shown that the solution reduces to earlier formulae providing m

In this work, results of a mathematical analysis of the role of workpiece preheating in laser keyhole welding were presented. This analysis considered the steady-state welding as well as certain range of boundary conditions over which preheating effect would be indicated. This work is an attempt to interpret the role of preheating to increase welding depth and perform keyhole welding with high quality using physical and thermal properties of steel alloys.

The effectiveness inhibitory to extract alcohol for the leaf and flower to plant sage Salvia pratensis each of Staphylococcus aureus, streptococcus epidermidis, Salmonella typhi, Pseudomonas aeroginosa, Escherichia coli, Aspergillus niger and Candida albicans whom had any inhibition to aqueous extracts of the parts itself species bacterial and fungal. The study also demonstrated that the extract of plant containing compounds chemical such as tannins, Alkaloids, Flavonoieds, and saponins, which owns effectiveness of medical. The MIC, MBC and inhibition zones for crud extract were determinated for microbial agents.

Antimicrobial and antiyeast activity of ethanolic and aqueous extract of grape fruit seed (Citrus paradise ; Rutaceaa) was examined against 10 bacterial and 2 yeast strains. The level of the antimicrobial effects was established using an in vitro agar assay and minimum inhibitory concentration (MIC). In general ethanolic extract were more effective on gram positive bacteria than gram negative bacteria and strongest antimicrobial effect against Streptococcus pyogenes and Salmonella entritidis. Other tested bacteria and yeasts were sensitive to extract ranging from 4 to 16 mg/ml and more.

This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.

A microbial desalination cell (MDC) is a new approach to bioelectrochemical systems. It provides a more sustainable way to electrical power production, saltwater desalination, and wastewater treatment at the same time. This study examined three operation modes of the MDC: chemical cathode, air cathode, and biocathode MDC, to give clear sight of this system's performance. The experimental work results for these three modes were recorded as power densities generation, saltwater desalination rates, and COD removal percentages. For the chemical cathode MDC, the power density was 96.8 mW/m², the desalination rate was 84.08 ppm/hr, and the COD removal percentage was 95.94%. The air cathode MDC results were different