Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

The present work aims to study the removal of dyes from wastewater by reverse osmosis process. Two dyes were used direct blue 6, and direct yellow. Experiments were performed with feed concentration (75 – 450 ppm), operation temperature (30 – 50 oC) and time (0.2 – 2.0 hr). The membrane used is thin film composite membrane (TFC). It was found that modal permeate concentration decreases with increasing feed concentration and time operating, while permeate concentration increases with increasing feed temperature. Also it was found that product rate increase with increasing temperature, but it decrease with increasing feed concentration and time. The concentration of reject solution showed an increase with increasing feed concentratio

Background: The skin functions as a barrier to the external environment, damage to this barrier following a burn disrupts the innate immune system and increases susceptibility to bacterial infection. Objective: This study was carried out to determine the bacterial isolates and study their antimicrobial susceptibility in burned wound infections at one burn's hospital in Baghdad.Type of study:Cross-sectional study.Methods: The bacteria were identified at species level by using Analytic Profile Index (API) system and The antimicrobial susceptibility test was performed according to Kirby-Bauer (disk diffusion) technique.Results: Over a period of one year (from October 2014 to October 2015). Out of 848 patients with different degrees of burns

Abstract

 The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .

The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation