The main objective of this research is to identify the role of job satisfaction in influencing strategic agility through knowledge sharing. The researcher used the descriptive as well as the analytical approach in the completion of this research by collecting data by means of the questionnaire as the main tool on a sample of the General Company for Food Industries' employees, whose number reached (76) individuals. Moreover, some statistical methods were employed to process the data; including the arithmetic mean, Standard deviation, simple linear correlation coefficient (Pearson), simple linear regression, and the median variable test. It was represented that there is a significant and essential impact of job satisfaction in influen

الغرض من البحث دراسة تأثير ادارة المعرفة (استراتيجية الشخصنة والترميز) في تحقيق التفوق الاستراتيجي في بيئة المصارف الاهلية العراقية ، وتم اعتماد منهج البحث الوصفي والتحليلي ، لذا اعتمد الباحث الفلسفة الوضعية وفق المنهج الاستنباطي لغرض اشتقاق فرضية البحث الاولى من الجانب النظري وتوصل البحث الى مجموعة من النتائج اهمها ان استراتيجية الشخصنة حققت تقدماً كبيراً في قدرتها على التأثير في التفوق الاستراتيجي بوصف

     The current environment is witnessing several developments as a result of the changes  taking place in all areas of economic, social , political and legal that led to the transformation of the industrial economy , which depends based on quantitative production to a knowledge economy which relies based on information and knowledge , as the central pillar of this economy during the trading  of  these information and knowledge between all individuals in general and decision makers , in particular, through information and communication technology of computers and the Internet to achieve sustainable human development in the social dimension.         &

Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

A novel series of chitosan derivatives were synthesized via reaction of chitosan with carbonyl compounds and grafted it’s by with different amine compounds substituted hydrogen. The produced polymers were characterized by different analyses FTIR, 1HCNMR, XRD, DSC and TGA. Solubility in water as well as many solvent was investigated, antibacterial activity of chitosan and its derivatives against two types of bacteria E. coli and S. aureus was also investigated. The results showed that derivatives sort of have antibacterial activities against Esherichia coli (Gram negative) better than chitosan whilst compound IX has better antibacterial against Staphylococcus aureus (Gram positive). SEM analysis showed that increase of surface roughness wi

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature