The research seeks to identify the comprehensive electronic banking system and the role of the auditor in light of the customer's application of electronic systems that depend on the Internet in providing its services, as a proposed audit program has been prepared in accordance with international auditing controls and standards based on the study of the customer's environment and the analysis of external and internal risks in the light of financial and non-financial indicators, the research reached a set of conclusions, most notably, increasing the dependence of banks on the comprehensive banking system for its ability to provide new and diverse banking services, The researcher suggested several recommendations, the most important of which is the need for management to increase investment in information technology and monitor the financial allocations required to implement the comprehensive system according to a specific plan and schedule and monitor deviations in the application, their causes and ways to address them, with the need for the auditor to adopt an audit program in line with the size of the client's internal and external risks and analyze them to determine the risks that threaten the continuity of the client's activity and the size of the material misrepresentations. The remaining ones that extend to the financial statements.
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Any software application can be divided into four distinct interconnected domains namely, problem domain, usage domain, development domain and system domain. A methodology for assistive technology software development is presented here that seeks to provide a framework for requirements elicitation studies together with their subsequent mapping implementing use-case driven object-oriented analysis for component based software architectures. Early feedback on user interface components effectiveness is adopted through process usability evaluation. A model is suggested that consists of the three environments; problem, conceptual, and representational environments or worlds. This model aims to emphasize on the relationship between the objects
... Show MoreBiometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in
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tock markets changed up and down during time. Some companies’ affect others due to dependency on each other . In this work, the network model of the stock market is discribed as a complete weighted graph. This paper aims to investigate the Iraqi stock markets using graph theory tools. The vertices of this graph correspond to the Iraqi markets companies, and the weights of the edges are set ulrametric distance of minimum spanning tree.
Far infrared photoconductive detectors based on multi-wall carbon nanotubes (MWCNTs) were fabricated and their characteristics were tested. MWCNTs films deposited on porous silicon (PSi) nanosurface by dip and drop coating techniques. Two types of deposited methods were used; dip coating sand drop –by-drop methods. As well as two types of detector were fabricated one with aluminum mask and the other without, and their figures of merits were studied. The detectors were illuminated by 2.2 and 2.5 Watt from CO2 of 10.6 m and tested. The surface morphology for the films is studied using AFM and SEM micrographs. The films show homogeneous distributed for CNTs on the PSi layer. The root mean square (r.m.s.) of the films surface roughness in
... Show MoreFacial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f
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Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit
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