The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

BACKGROUND: Acute coronary syndrome (ACS) is the clinical manifestation of acutely diminished coronary arterial blood supply. The rate of increase of intraventricular pressure during isovolumetric contraction (left ventricular dP/dt) represents the rate of change of pressure during ejection. OBJECTIVE: The aim of this study is to evaluate the usefulness of the rate of increase of intraventricular pressure during isovolumetric contraction (dP/dt) in assessment of left ventricular function in patients with acute coronary syndrome and its relation to certain clinical and echocardiographic features. PATIENTS AND METHODS: The study is a cross sectional study including 50 patients with an established diagnosis of acute coronary syndrome. The

In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better

Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

Rheumatoid arthritis is a chronic inflammatory autoimmune disease its etiology is  unknown . The classical autoimmune diseases, have adaptive immune genetic associations with autoantibodies and major histocompatibility complex(MHC) class II such as rheumatoid arthritis (RA), diabetes mellitus type two (DM II). Serum of99 males suffering from RA without DMII as group (G1), 45 males suffering from RA with DM II as group (G2) and 40 healthy males as group (G3) were enrolled in this study to estimation of alkaline phosphates (ALP),C-reactive protein(CRP) and Pentraxin-3(PTX). Results showed a highly significant increase in PTX3 levels in G1 and G2 compared to G3 and a significant decrease in G1comparing to G2. Results also revealed a si

A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

The study aims to use the European Excellence Model (EFQM) in assessing the institutional performance of the National Center for Administrative Development and Information Technology in order to determine the gap between the actual reality of the performance of the Center and the standards adopted in the model, in order to know the extent to which the Center seeks to achieve excellence in performance to improve the level of services provided and the adoption of methods Modern and contemporary management in the evaluation of its institutional performance.

The problem of the study was the absence of an institutional performance evaluation system at the centre whereby weaknesses (areas of improvement) and st