In this research, the multi-period probabilistic inventory model will be applied to the stores of raw materials used in the leather industry at the General Company for Leather Industries. The raw materials are:Natural leather includes cowhide, whether imported or local, buffalo leather, lamb leather, goat skin, chamois (raw materials made from natural leather), polished leather (raw materials made from natural leather), artificial leather (skai), supplements which include: (cuffs - Clocks - hands - pockets), and threads.This model was built after testing and determining the distribution of demand during the supply period (waiting period) for each material and completely independently from the rest of the materials, as none of the above mate

The no parity problem causes determining is the most interesting case by doctors and researchers in this filed, because it helps them to pre-discovering of it, from this point the important of this paper is came, which tries to determine the priority causes and its fluency, thus it helps doctors and researchers to determine the problem and it’s fluency of increase or decrease the active sperm which fluencies of peregrinating. We use the censored regression (Tobit) model to analyze the data that contains 150 observations may by useful to whom it concern.         

<span lang="EN-GB">This paper highlights the barriers that have led to a delay in the implementation of E-Health services in Iraq. A new framework is proposed to improve the E-Health sector using a SECI model which describes how explicit and tacit knowledge is generated, transferred, and recreated in organizations through main stages (socialization, externalization, combination and internalization). Class association rules (CARs) is integrated to mine the SECI model by extracting related rules which correspond to the medical advice. The proposed framework (SECICAR) can be done through a web portal to assemble healthcare professionals, patients in one environment. SECICAR will be applied to the hypertension community to show th

Addition of bioactive materials such as Titanium oxide (TiO₂), and incorporation of bio inert ceramic such as alumina (Al₂O₃), into polyetheretherketone (PEEK) has been adopted as an effective approach to improve bone-implant interfaces. In this paper, hot pressing technique has been adopted as a production method. This technique gave a homogenous distribution of the additive materials in the proposed composite biomaterial. Different compositions and compounding temperatures have been applied to all samples. Mechanical properties and animal model have been studied in all different production conditions. The results of these new TiO₂/Al₂O₃/PEEK biocomposites with different

The unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I

The Khabour reservoir, Ordovician, Lower Paleozoic, Akkas gas field which is considered one of the main sandstone reservoirs in the west of Iraq. Researchers face difficulties in recognizing sandstone reservoirs since they are virtually always tight and heterogeneous. This paper is associated with the geological modeling of a gas-bearing reservoir that containing condensate appears while production when bottom hole pressure declines below the dew point. By defining the lithology and evaluating the petrophysical parameters of this complicated reservoir, a geological model for the reservoir is being built by using CMG BUILDER software (GEM tool) to create a static model. The petrophysical properties of a reservoir were computed using

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi