The makers of strife exist in every era and time. They differ in how these temptations are created and the methods used in doing so. In our modern era, they are more; This is due to the presence of information technology and its easy availability at their fingertips, as well as the spread of social networking sites, which are rapidly spreading among ignorant groups and groups that are deficient in their use. Which led the makers of sedition to exploit these matters and create various temptations and spread them among peoples and societies. Today, we cannot predict the future of humanity in light of this huge amount of temptation. What the Holy Qur’an mentioned about the types of temptations in its noble verses and their embodiment in seve

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

The present paper stresses the direct effect of the situational dimension termed as “reality” on the authors’ thoughts and attitudes. Every text is placed within a particular situation which has to be correctly identified by the translator as the first and the most important step for a good translation. Hence, the content of any word production reflects some part of reality. Comprehending any text includes comprehending the reality’s different dimensions as reflected in the text and, thus illuminating the connection of reality features.

Аннотация 

Исследование под названием  ((«Понимание реальности» средство полно

تعد الثقافة التنظيمية في المجال االداري وكذلك الرياضي من المفاهيم الحديثة لذا وجب التعرف عليها من عدة اتجاهات لمعرفة تكوينها واب عادها والنظريات التي تناولتها لتكوين رؤية تختلف عن االخرين لما لها من دور مهم ونافع في مختلف المؤسسات ومنها االتحادات الرياضية، ولعل لعلوم الرياضة واالختبار والقياس على وجه الخصوص الدور الرئيس في المساعدة بإيجاد وسيلة علمية وتطبيقها على االعضاء لمعرفة انماط الثقافة لديهم ومن

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The test considers from important methods and tools when we using the evaluation because it is a basic role in diagnosis & classification & motive & selection &guiding &prediction and the problem was formatted in some questions like ( what is physical variables that tall players needs n the game and effect on the game ? what is the tests that measures these variables also the defense rebound variable and is there a references standard specialized in that ?) , the aims of research represented by knowing to some physical abilities for tall players in basketball school and their tests and putting new tests to measure defense rebound to one player and tow tall players also limiting the standards degrees ( modified un following method ) to resul

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect