ينقسم الاتجاه الأساسي الذي يجري مناقشته في هذه الورقة إلى مستويين: الأول يركز على تحديد مضمون العلاقة بين الشفافية والفساد، فضلا عن توضيح الدور الذي يمكن أن تؤديه أخلاقيات الأعمال، لتثار التساؤلات هي: هل أن الشفافية والفساد متغيرين مرتبطين معا؟ وهل تؤثر الشفافية في الفساد؟ وهل أن وجود الشفافية كفيل بإزاحة الفساد، أم نحتاج إلى شيء أخر يدعم عملية الشفافية؟ وإذا تم التحدث عن الشفافية كمصطلح بدون وجود مما

The Research aimed for identification the significant of health problems that occurrences through
misused of computer for those whom attaches with more than two hours daily and to identification the
nature of demographical characteristics variables and that related variables with using computer. Also to
know the level of user’s knowledge for some attaché’s equipment's and finally creating a new suggested
measurement scale for studying health problems that were occurred through misused of computer.
Creating questionnaire includes several domains (Social problems – family environment, Social problems –
external environment, some health problems attaches with related equipment's, psychological problems,
and hea

تحليل الأخطاء الصوتية في بعض كتب اللغة الروسية الدراسية

Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

The aim of this study is know the five leadership practices according to the theory of network of leadership by Black and Mouton for the presidents of the Taxation General Board from their prospective, that is through answering the questionnaire questions. To achieving the objectives of this study, the researcher organized a questionnaire form as a main instrument for data collection. It includes (30) items distributed into five leadership practices according to the theory of network of leadership. Each one is subdivided into (6) questions.

The questionnaire was distributed to the presidents of the Taxation General Board of (14). The researcher used the SPSS program to analyses the answers. Through the answers, h