This work involves three parts , first part is manufacturing different types of laminated below knee prosthetic socket materials with different classical laminated materials used in Baghdad center for prosthetic and orthotic (4perlon layers+2carbon fiber layer+4 perlon layers) , two suggested laminated materials(3perlon layers+2carbon fiber layer+3 perlon layers) and (3perlon layers+1carbon fiber layer+3 perlon layers) ) in order to choose perfect laminated socket . The second part tests (Impact test) the laminated materials specimens used in socket manufacturing in order to get the impact properties for each socket materials groups using an experimental rig designed especially for this purpose. The interface pressure between the residual leg and prosthetic socket is also measured to cover all the surface area of the B-K prosthetic socket by using piezoelectric sensor in order to estimate the resulting stress according to loading conditions. A male with age, length, mass, and stump length of 42 years, 164 cm, 67 Kg and 13 cm respectively with a right transtibial amputation is chosen to achieve the above mentioned test procedures. The last part suggests a theoretical and analytical models for each group of specimen to find out the absorbed energy behavior and subjected maximum stress for each laminated B-K prosthetic socket materials .
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
... Show MoreLactobacillus Plantarum and Lactobacillus rhamnosus GG were encapsulated using 3% of alginate via extrusion technique. And the probiotics capsules produced were further coated used 1% chitosan to increase the survival of probiotics, and evaluation of The heat resistance of the slow pasteurization and fast pasteurization for Lb,pla and Lb.GG for control and bacteria coated one layer and bacteria coated two layer at 63°C/ 30 minutes and 72°C/ 15 seconds. The results indicate that the Probiotic coated two layer are more resistant to pasteurization temperatures at 63°C/ 30 minutes and 72°C/ 15 seconds than the Probiotic coated one layer. While the results of the control follow a significant reduction for viability of cell toward pasteuri
... Show MoreThe idea of ech fuzzy soft bi-closure space ( bicsp) is a new one, and its basic features are defined and studied in [1]. In this paper, separation axioms, namely pairwise, , pairwise semi-(respectively, pairwise pseudo and pairwise Uryshon) - fs bicsp's are introduced and studied in both ech fuzzy soft bi-closure space and their induced fuzzy soft bitopological spaces. It is shown that hereditary property is satisfied for , with respect to ech fuzzy soft bi-closure space but for other mentioned types of separations axioms, hereditary property satisfies for closed subspaces of ech fuzzy soft bi-closure space.
The aim of this study is to identify the effect of enabling the effectiveness of the work of the audit committees in private commercial banks and to identify the extent of awareness of the importance of empowerment in the work of these committees, especially as it is known that these committees, especially the inspection committees that go to private banks and from various sources including committees of the Central Bank of Iraq Committees of the Securities Commission and finally committees of the external audit offices, through an analysis of the determinants of empowerment in the performance of the most important work of the audit committees, namely: supervising the process of preparing reports, supervising the system of intern
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Statistical control charts are widely used in industry for process and measurement control . in this paper we study the use of markov chain approach in calculating the average run length (ARL) of cumulative sum (Cusum) control chart for defect the shifts in the mean of process , and exponentially weighted moving average (EWMA) control charts for defect the shifts for process mean and , the standard deviation . Also ,we used the EWMA charts based on the logarithm of the sample variance for monitoring a process standard deviation when the observations (products are selected from al_mamun factory ) are identically and independently distributed (iid) from normal distribution in continuous manufacturing .
Ground penetrating radar (GPR) is one of the geophysical methods that utilize electromagnetic waves in the detection of subjects below the surface to record relative position and shape of archaeological features in 2D and 3D. GPR method was applied in detecting buried archaeological structure in study area in a location within the University of Baghdad. GPR with 3D interpretation managed to locate buried objects at the depth of (1m) . GPR Survey has been carried (12) vertical lines and (5) horizontal lines using frequency antenna (500) MHZ .
This work presents a computer studying to simulate the charging process of a dust grain immersed in plasma with negative ions. The study based on the discrete charging model. The model was developed to take into account the effect of negative ions on charging process of dust grain.
The model was translated to a numerical calculation by using computer programs. The program of model has been written with FORTRAN programming language to calculate the charging process for a dust particle in plasma with negative ion, the time distribution of a dust charge, number charge equilibrium and charging time for different value of ηe (ratio of number density of electron to number density of positive ion).