This research reviews the aesthetic variables that were founded according to (theatrical rehearsal) as one of the most important pillars on which the theatrical process is based, because of its necessity in developing theatrical art on several levels that helped the theatrical director in organizing his work, and this became clear through the research chapters represented in the first chapter (methodological framework) and the second chapter, which consisted of the first topic (the duality of watching / rehearsal) and the second topic (the applications of theatrical rehearsal in theatrical experiences), all the way to the third chapter (research procedures), which included the analysis of theatrical rehearsals (sharing on life), and the

The purpose of this study is to investigate the effect of credit risk indicators on the Arab Gulf countries' banks Profitability over the period of 2015 to 2017.  The banking credit risk was calculated using non-performing loans ratio affecting banks profitability indicators like net income and by using fixed effect and random effect model analyses, the study found that increasing in non-performing loans ratio will decrease the net income in gulf banks, the study also found that personal loans represent the largest share of loans granted in gulf banks. Also, the study recommends the importance of developing the capabilities of credit departments in commercial banks in dealing with bad loans, and studying the financial statem

Imam al - Karji replies to some Islamic groups
In his book the jokes of the Koran

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

Let  be a non-trivial simple graph. A dominating set in a graph is a set of vertices such that every vertex not in the set is adjacent to at least one vertex in the set. A subset  is a minimum neighborhood dominating set if  is a dominating set and if for every  holds. The minimum cardinality of the minimum neighborhood dominating set of a graph  is called as minimum neighborhood dominating number and it is denoted by  . A minimum neighborhood dominating set is a dominating set where the intersection of the neighborhoods of all vertices in the set is as small as possible, (i.e., ). The minimum neighborhood dominating number, denoted by , is the minimum cardinality of a minimum neighborhood dominating set. In other words, it is the

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

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

Influence of metal nanoparticles synthesized by microorganisms upon soil-borne microscopic fungus Aspergillus terreus K-8 was studied. It was established that the metal nanoparticles synthesized by microorganisms affect the enzymatic activity of the studied culture. Silver nanoparticles lead to a decrease in cellulase activity and completely suppress the amylase activity of the fungus, while copper nanoparticles completely inhibit the activity of both the cellulase complex and amylase. The obtained results imply that the large-scale use of silver and copper nanoparticles may disrupt biological processes in the soil and cause change in the physiological and biochemical state of soil-borne microorganisms as well.

اثر بديع الزمان سعيد النورسي على الفكر الاسلامي المعاصر في تركيا

Watermelon is known to be infested by multiple insect pests both simultaneously and in sequence. Interactions by pests have been shown to have positive or negative, additive or non additive, compensatory or over compensatory effects on yields. Hardly has this sort of relationship been defined for watermelon vis-à-vis insect herbivores. A 2-year, 2-season (4 trials) field experiments were laid in the Research Farm of Federal University Wukari, to investigate the interactive effects of key insect pests of watermelon on fruit yield of Watermelon in 2016 and 2017 using natural infestations. The relationship between the dominant insect pests and fruit yield were determined by correlation (r) and linear regression (simple and multiple) analys