The study aims to indicate the role of the mechanisms and principles of corporate governance in the activation of social responsibility reports, and increase disclosure, to achieve sustainability, legitimacy, and integrity of the business. Through the presentation of the conceptual framework for corporate governance and social responsibility, identify the key dimensions of social responsibility and the statement of the relationship between the mechanisms of governance and social responsibility reports in accordance with these dimensions. To prove the hypothesis research has selected a sample of listed companies in the Iraqi market for securities,

This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

Background: Breast Cancer is the commonest type of malignancy in Iraq. The Iraqi Cancer Registry displays an obvious trend for the disease to affect younger women with advanced stages at the time of presentation. This report presents a review on the main demographic characteristics and clinicopathological parameters in Iraqi patients diagnosed with breast cancer.
Patients & Methods: The study was carried out on 721 out of a total of 5044 patients (14.3%) who complained of palpable breast lumps that were diagnosed as cancer. The procedure for tumor nuclear DNA Ploidy assessment was performed by means of Image Cytometry. Immuno-cytochemical and  histochemical assays were applied for the determination of

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

The performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to resul

Extracting moving object from video sequence is one of the most important steps
in the video-based analysis. Background subtraction is the most commonly used
moving object detection methods in video, in which the extracted object will be
feed to a higher-level process ( i.e. object localization, object tracking ).
The main requirement of background subtraction method is to construct a
stationary background model and then to compare every new coming frame with it
in order to detect the moving object.
Relied on the supposition that the background occurs with the higher appearance
frequency, a proposed background reconstruction algorithm has been presented
based on pixel intensity classification ( PIC ) approach.

Recently new concepts such as free data or Volunteered Geographic Information (VGI) emerged on Web 2.0 technologies. OpenStreetMap (OSM) is one of the most representative projects of this trend. Geospatial data from different source often has variable accuracy levels due to different data collection methods; therefore the most concerning problem with (OSM) is its unknown quality. This study aims to develop a specific tool which can analyze and assess the possibility matching of OSM road features with reference dataset using Matlab programming language. This tool applied on two different study areas in Iraq (Baghdad and Karbala), in order to verify if the OSM data has the same quality in both study areas. This program, in general, consists

     Marking content with descriptive terms that depict the image content is called “tagging,” which is a well-known method to organize content for future navigation, filtering, or searching. Manually tagging video or image content is a time-consuming and expensive process. Accordingly, the tags supplied by humans are often noisy, incomplete, subjective, and inadequate. Automatic Image Tagging can spontaneously assign semantic keywords according to the visual information of images, thereby allowing images to be retrieved, organized, and managed by tag. This paper presents a survey and analysis of the state-of-the-art approaches for the automatic tagging of video and image data. The analysis in this paper covered the publications