This research highlights the light on the general framework of accounting discloser in the Islamic banks, and show the types and the concepts of Cost Efficiency, In this present study, the sample included Fourteen Islamic banks, where the data was collected from the annual financial reports. Accordingly, the study in order to achieve the aims and access to the results based on the analytical method and the descriptive analysis, and conducted a Simple & Multiple Linear Regression analysis, in order to test hypotheses of the research by using of statistical analysis software (SPSS). The research has arrived to many results such as: the commitment of Islamic banks working in the Kingdome of Bahrain (Wholesale) to the requirements of the

Is the subject of the mind took a dimension in philosophy and psychology , and has cared psychologists this topic to a large extent , I started education institutions interest in the capabilities of intelligence since the early twentieth century , and the development of interest in them until he arrived to find Standards and Criteria to identify the degree IQ of any individual , and began to educational institutions interested in mental talent and talented .

The United States is the country chock first of these research projects , but they devoted all their attention on the wish talent mental and Gifted , until I got to the projects, the so-called time ( ( wars of the mind ) ) and projects Schools gifted

A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.

Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se