This research aims to find out the extent the reflection of tacit knowledge dimensions (experience, skill, intuition, the ability to think) on Organizational performance of the offices of inspectors general dimensions (internal processes, growth and learning the focus, the focus on the customer) and the measurement and analysis of the type of impact the tacit knowledge of auditors on performance Organizational in inspectors general offices, the research seeks to diagnose the extent of awareness of Office Management knowledge implicit and the attention span of the administration in determining levels and performance levels, and the resolution means the main information-gathering adopted by the researcher, which, as well as his exp

Experimental results for the density of states of hydrogenated amorphous silicon due to Jackson et al near the valence and conduction band edges were analyzed using Levenberg-Marquardt nonlinear fitting method. It is found that the density of states of the valence band and the conduction band can be fitted to a simple power law, with a power index 0.60 near the valence band edge, and 0.55 near the conduction band edge. These results indicate a modest but noticeable deviation from the square root law (power index=0.5) which is found in crystalline semiconductors. Analysis of Jackson et al density of states integral J(E) data over about (1.4 eV) of photon energy range, showed a significant fit to a simple power law with a power index of 2.11

The study was conducted at the fields of the Department of Horticulture and Landscape Gardening, College of Agriculture, University of Baghdad " Abu Ghraib" during the growing seasons 2013-2014 to Evaluate the Vegetative growth , yield traits and genetic parameter of some tomato mutants. Results showed significantly increased of plant height in M6-2 mutant 245cm in Comparison with M6- 3 130 cm . M6-4 mutant significantly increasing of floral clusters 13 . Mutant M6-3 showed significantly increasing the average of, fruit weight 125.9g and plant yield 7.17 kg.plant-1 as comparison with M6-2 which showed decreasing of average of fruit weight and plant yield 79.40g and 4.38 kg.plant-1 respectively. Also results showed the highest Genetic variat

The study was conducted at the fields of the Department of Horticulture and Landscape Gardening,College of Agriculture, University of Baghdad during the growing seasons of 2013- 2014 .forPerformance of Evaluation Vegetative growth and yield traits and estimate some important geneticparameter on seven selected breed of tomato which (S1-S7 ) Pure line. the results found significantdifferences between breeds in all study trails except clusters flowering number .S1 significantly plantlength which reached 227.3 .Also S1,S2 and S4 were significantly increased the number fruit for plant,Fruit weight Increased in S3 ,S6 and plant yield. Increased in S1, S4 ,S5. Genetic variation valueswere low in Floral clusters , TSS and fruit firmest and medium i

In light of the increasing interest in Child-rearing in nurseries and kindergartens and the most important experiences gained by the child at this stage that form the basis for the subsequent stages of her/his physical mental and social growth.

The significance of the research concentrates the need to asses the affecting variables on the child growth to create opportunities for her/him to have intact rearing.

The research also aims to classify these variables at each age level and highlight its moral role.

The problem of the research is the lack of clarity of different variables impact of the child growth in different age levels in nurseries and kindergart

    In this paper we introduce a brief review about Box-Jenkins models. The acronym ARIMA stands for “autoregressive integrated moving average”. It is a good method to forecast for stationary and non stationary time series. According to the data which obtained from Baghdad Water Authority, we are modelling two series, the first one about pure water consumption and the second about the number of participants. Then we determine an optimal model by depending on choosing minimum MSE as criterion.

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

Background: Cystoid Macular Edema (CME) in its various forms can be considered one of the leading causes of central vision loss in the developed world. It is not a disease itself, It represents a common pathologic sequel of the retina and occurs in a variety of pathological conditions such as, diabetic retinopathy, central or branch retinal vein occlusion(CRVO,BRVO), intraocular inflammation and following cataract extraction. Objective: This study was done to investigate the pattern of CME in patient attending Erbil Teaching Hospitals.Type of the study: Cross- sectional study.Methods and Materials: This is a hospital base cross- sectional study that included 61 patients (75 eyes) conducted at Erbil Teaching Hospitals for six months. All

Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa