Nosocomial infections are one of the most important causes of mortality and morbidity in hospitals. These are major public health problems worldwide, but particularly in developing countries. The purpose of this research was to analyze the frequency of the microorganisms in the specimens taken from the surgical wounds, and to examine antimicrobial susceptibility for some isolates . Wound swabs were examined from June 2010 to January 2011. The isolates were identified by conventional methods, antimicrobial susceptibility testing was performed by Kirby-Bauer disc diffusion method as per NCCLS guidelines.A total of 102 wound swabs were examined 22(21.56%) swabs were sterile and 80(78.43%) were positive for microorganisms. The results showed

Rock type identification is very important task in Reservoir characterization in order to constrict robust reservoir models. There are several approaches have been introduced to define the rock type in reservoirs and each approach should relate the geological and petrophysical properties, such that each rock type is proportional to a unique hydraulic flow unit. A hydraulic flow unit is a reservoir zone that is laterally and vertically has similar flow and bedding characteristics. According to effect of rock type in reservoir performance, many empirical and statistical approaches introduced.  In this paper Cluster Analysis technique is used to identify the rock groups in tertiary reservoir for Khabaz oil field by analyses variation o

This research paper studies the alienation of the intellectuals in the modern novel through the study of two alienated characters, John Marcher in Henry James's The Beast in the Jungle, and Mr. Duffy in James's Joyce's "A Painful Case." As a result of the complexity of life in the industrial societies, the individuals, especially the intellectual ones, feel themselves unable to integrate into social life; they fear society and feel that it endangers their individuality and independence. Thus, these characters live on the fringe of the societ

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

This research introduce a study with application on Principal Component Regression obtained from some of the explainatory variables to limitate Multicollinearity problem among these variables and gain staibilty in their estimations more than those which yield from Ordinary Least Squares. But the cost that we pay in the other hand losing a little power of the estimation of the predictive regression function in explaining the essential variations. A suggested numerical formula has been proposed and applied by the researchers as optimal solution, and vererifing the its efficiency by a program written by the researchers themselves for this porpuse through some creterions: Cumulative Percentage Variance, Coefficient of Determination, Variance