The research aims to identify Determination talent management dimensions of (attracting talent, developing talent, directing talent, performance management talent, retain talent) in the entrepreneurial performance of the organization dimensions of (advance planning, efficiency, effectiveness), so search occupies the extreme importance of being treated important and recent issue of the performance Entrepreneuria, management talent, aware of the importance of the subject and expected results of the company surveyed, was an analysis of data obtained through field visits in addition to the questionnaire and interviews, highlights were the results that have been reached to take the sample into account all the management requirements knack of att

Management is considered as most important resource of the society ones in modern era and an exchange
point in societies’ lives in order to achieve its goals and wishes. So far, management behinds the new
electronic society has become different in shape and nature due to the force of the nature of information
technology that shapes the relationships between the world’s individuals at the national level but it goes
beyond the international ones. The study aims at identifying the impact of the electronic management’s
components upon the improvement of the quality of nursing care in Baghdad’s hospitals. The descriptive
design, with a sample-survey approach, is used as appropriate ones for the field study of social

  Computer software is frequently used for medical decision support systems in different areas. Magnetic Resonance Images (MRI) are widely used images for brain classification issue. This paper presents an improved method for brain classification of MRI images. The proposed method contains three phases, which are, feature extraction, dimensionality reduction, and an improved classification technique. In the first phase, the features of MRI images are obtained by discrete wavelet transform (DWT). In the second phase, the features of MRI images have been reduced, using principal component analysis (PCA). In the last (third) stage, an improved classifier is developed. In the proposed classifier, Dragonfly algorithm is used instead

The principal goal guiding any designed encryption algorithm must be security against unauthorized attackers. Within the last decade, there has been a vast increase in the communication of digital computer data in both the private and public sectors. Much of this information has a significant value; therefore it does require the protection by design strength algorithm to cipher it. This algorithm defines the mathematical steps required to transform data into a cryptographic cipher and also to transform the cipher back to the original form. The Performance and security level is the main characteristics that differentiate one encryption algorithm from another. In this paper suggested a new technique to enhance the performance of the Data E

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J

        The adsorption of Congo red (CR) dye on modified synthetic zeolite 5A  , the general name of which is Linde Type A (LTA)which is modified by amino mercepto thiadiazole (AMT)  and have been characterized  by using fourier transform infrared (FT-IR) , x-ray diffraction (XRD) spectroscopies, atomic force microscopy (AFM) and scanning electron microscope (SEM) analysis.In this work Modified zeolite was utilized as adsorbent to remove (CR) dye from aqueous solution by adsorption. Batch experiments were conducted to study the effects contact time , initial concentration of adsorbate and temperature on dye adsorption. The equilibrium adsorption data were analyzed by using several isotherm models ( Freu

In this study, a genetic algorithm (GA) is used to detect damage in curved beam model, stiffness as well as mass matrices of the curved beam elements is formulated using Hamilton's principle. Each node of the curved beam element possesses seven degrees of freedom including the warping degree of freedom. The curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory. The identification of damage is formulated as an optimization problem, binary and continuous genetic algorithms
(BGA, CGA) are used to detect and locate the damage using two objective functions (change in natural frequencies, Modal Assurance Criterion MAC). The results show the objective function based on change in natural frequency i

This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio

The present study was conducted to evaluate the effect of variation of influent raw water turbidity, bed composition, and filtration rate on the performance of mono (sand) and dual media (sand and anthracite) rapid gravity filters in response to the effluent filtered water turbidity and headloss development. In order to evaluate each filter pe1formance, sieve analysis was made to characterize both media and to determine the effective size and uniformity coefficient. Effluent filtered water turbidity and the headloss development was recorded with time during each experiment.