The Study aims to show the role of Flexible Budget in planning and control The Factory over head.

The study consists four reaserchs the First introduction for the role of Budget in planning and control The second definition Flexible Badget the Third Factory overhed cost variances Analysis The four conclusions and recommendations.

The factory overhead cost represents great ratio from product cost so the management must planning and control on cost Through the year by the Budget of factory over head in the beginning of the year and determind overhead rater.

In some cases, surgeons need to navigate through the computer system for reconfirmation patients’ details and unfortunately surgeons unable to manage both computer system and operation at the same time. In this paper we propose a solution for this problem especially designed for heart surgeon, by introducing voice activation system with 3D visualization of Angiographic images, 2D visualization of Echocardiography processed video and selected patient’s details. In this study, the processing, approximation of the 3D angiography and the visualization of the 2D echocardiography video with voice recognition control are the most challenging work. The work involve with predicting 3D coronary three from 2D angiography image and also image enhan

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

             Polycystic syndrome (PCOS) is a considerable infertility disorder in adolescents and adult women in reproductive age. Obesity is a vigorous risk factor related to POCS.  This study aims to evaluate the association of obesity and PCOS by investigating several parameters including:  anthropological, biochemical (lipid profile, fasting blood sugar, glucose tolerance test, and hormone levels (LH, FSH, LH/FSH ratio, Estradiol2 and Testosterone),and genetic parameters (Fat mass and Obesity associated gene (FTO) polymorphism at rs17817449) in 63 obese and non-obese PCOS women. The biochemical tests were investigated by colorimetric methods while FTO gene polymorphism was detected by PCR–RFLP.  Lipid profile, F

Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, with noise and reverberation present, MFCC performance is not reliable. To address this, we propose a new feature 'entrocy' for accurate and robu

The study deals with China's soft power and diplomacy in the Middle East, and it focuses specifically on the tools and foundations of China's soft diplomacy and how it achieves its goals in the region in addition to its challenges in the region. In this regard, the study also focuses on the Chinese Belt and Road Initiative and its soft foundations and how they serve China’s diplomacy and soft power in the region. The study ends with a set of conclusions, perhaps the most prominent of which is that diplomacy and soft power have become a fundamental pillar of China's foreign policy to achieve its foreign goals and to establish an international system compatible with China's principles. As for the Middle East, China has established a poli

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.