Medication safety and effectiveness can be improved through interprofessional collaboration. The goals of this study were to measure the degree of physician–pharmacist collaboration within Iraqi governmental healthcare settings and to investigate factors influencing this collaboration.

The study seeks to clarify the role of International Auditing Standard No. (320) of the relative importance in determining responsibility for planning and implementing the process of auditing financial statements and expressing neutral technical opinion through the analytical procedures of the auditor, whose responsibility is to obtain appropriate and reliable audit evidence that helps the auditor to form a general conclusion about whether The financial statements were consistent with the auditor's understanding of the entity. The relative importance contributes to defining the important accounts that help to set priorities for the auditor to set the necessary analytical procedures for these accounts. One of the most important co

This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

Some auditors may think that the audit process ends with discovering misstatements and informing management about them, while the discovery of misstatements may be classified by some as the first step in the phase of separating these distortions, as the auditor should collect these misstatements, evaluate them and detail them into misstatements involving errors or misstatements involving fraud Then evaluating it to material or immaterial according to what was stated in the international auditing standards and directing management to amend the essential ones.  The importance of this research lies in identifying the concept of distortions and their types, identifying the method of evaluating distortions into substantial and non-essent

There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. As more and more information is transacted over wireless media, there has been increasing criminal activity directed against such systems. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. We have studied the performance of differential chaos shift keying (DCSK) with 2×2 Alamouti scheme and 2×1 Alamouti scheme for different chaotic maps over additive white Gaussian noise (

ABSTRACT This paper has a three-pronged objective: offering a unitary set of semantic distinctive features to the analysis of nominal “hatred synonyms” in the lexicon of both English and Standard Arabic (SA), applying it procedurally to test its scope of functionality crosslinguistically, and singling out the closest noun synonymous equivalents among the membership of the two sets in this particular lexical semantic field in both languages. The componential analysis and the matching procedures carried have been functional in identifying ten totally matching equivalents (i.e. at 55.6%), and eight partially matching ones (i.e. at %44.4%). This result shows that while total matching equivalences do exist in the translation of certain Eng

Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach