The problem of research was the lack of research that dealt with issue of the job design approach that is more suitable for knowledge work, therefore, the research aims to determine the impact of job enrichment, and knowledge capitalon strategic success, starting from the hypothesis that there significant impact of job enrichment and knowledge capital on strategic success, to achieve this goal the researchers from the theoretical literature and related studies conclude to the construction of the scheme shows the hypothetical relationship between the variables, which was adopted job enrichment as independent variable while knowledge capital plays two roles, the first as an independent variable and the second as an intermediate variable,while strategic success representing the dependent variables. The sample consisted of (227) Faculty Member in ten colleges in Baghdad. The research found that the adoption of job enrichment has a significant impact on knowledge capital and strategic success. The research also found that knowledge capital has a significant impact on strategic success. The research concluded that the effect of job enrichment on strategic success is increasing through knowledge capital. Accordingly, the research recommended the necessity of adopting job enrichment as an approach to design the functions of the knowledge capital owners, And to increase its knowledge capital to achieve its strategic success.
The use of blended cement in concrete provides economic, energy savings, and ecological benefits, and also provides. Improvement in the properties of materials incorporating blended cements. The major aim of this investigation is to develop blended cement technology using grinded local rocks . The research includes information on constituent materials, manufacturing processes and performance characteristics of blended cements made with replacement (10 and 20) % of grinded local rocks (limestone, quartzite and porcelinite) from cement. The main conclusion of this study was that all types of manufactured blended cement conformed to the specification according to ASTM C595-12 (chemical and physical requirements). The percentage of the compress
... Show MoreAbstract A description study was carried through out the present study aimed to assess health education provided by nurses to patient with gall stone "obstructive jaundice". The study was conducted at 4 teaching hospital, Baghdad teaching hospital, Al-Karama teaching hospital, Al-Yarmook teaching hospital, Al-Kendy teaching hospital where choloecystectomy was performed, in the period from first of June 2004 to end of July 2004. Data were collected through the use of questionnaire an interview from which was developed for the purpose of the present study. A non-probability (purposive) sample which was consist
This work deals with thermal cracking of three samples of extract lubricating oil produced as a by-product from furfural extraction process of lubricating oil base stock in AL-Dura refinery. The thermal cracking processes were carried out at a temperature range of 325-400 ºC and atmospheric pressure by batch laboratory reactor. The distillation of cracking liquid products was achieved by general ASTM distillation (ASTM D -86) for separation of gasoline fraction up to 220 ºC from light cycle oil fraction above 220 ºC. The comparison between the conversions at different operating conditions of thermal cracking processes indicates that a high conversion was obtained at 375°C, according to gasoline production. According to gasoline produ
... Show MoreMetasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat
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