This research deals with the case of the Iraqi joint-stock companies listed on the Iraq Stock Exchange study in terms of compliance with the requirements of IAS 33 "Earnings per share" and the research problem Alrtash concentrated in a statement the commitment of those companies the requirements of the International Standard 33, which may adversely affect the quality of financial reporting where and in particular the quality of accounting information and content of the primary and secondary characteristics make them be of interest to the decisions of its users, so the aim of this research to the statement of financial reporting earnings per share on the quality of financial reporting in listed shareholding in Iraq Stock Exchange

This research aims to find out the extent the reflection of tacit knowledge dimensions (experience, skill, intuition, the ability to think) on Organizational performance of the offices of inspectors general dimensions (internal processes, growth and learning the focus, the focus on the customer) and the measurement and analysis of the type of impact the tacit knowledge of auditors on performance Organizational in inspectors general offices, the research seeks to diagnose the extent of awareness of Office Management knowledge implicit and the attention span of the administration in determining levels and performance levels, and the resolution means the main information-gathering adopted by the researcher, which, as well as his exp

Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm³.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

Cloud computing is the new technological trend for future generations. It represents a new way to use IT resources more efficiently. Cloud computing is one of the most technological models for developing and exploiting infrastructure resources in the world. Under the cloud, the user no longer needs to look for major financing to purchase infrastructure equipment as companies, especially small and medium-sized ones, can get the equipment as a service, rather than buying it as a product. The idea of ​​cloud computing dates back to the sixties of the last century, but this idea did not come into actual application until the beginning of the third millennium, at the hands of technology companies such as Apple, Hp, IBM, which had

In this paper, SiO2 nanoparticles thin films were synthesised at different PH values of solution by sol gel method at fixed temperature (25oC) and molar ratio (R =H2O/precursor) of (Tetra Ethyl Ortho Silicate) TEOS as precursor at (R=1). The structure and optical properties of the thin films have been investigated. All thin films were tested by using X-RAY diffraction. All X-RAY spectrum can be indexed as monoclinic structure with strong crystalline (110) plane. The morphological properties of the prepared films were studied by SEM. The results indicate that all films are in nano scale and the particle size around (19-62) nm .The size of silica particles increases with increasing PH value of solution where both the rate of hydrolysis and

على الرغم من إن الابداع والمبدعين وخصائصهم العقلية والشخصية تعد من المفاهيم المهمة والشائعة في الحياة بمجالاتها كافة، ففي الوقت الذي نجد فيه العديد من الدراسات والمقالات العربية والاجنبية التي تناولته بشكل او باخر، لكنها جميعها اعتمدت على المقياس الخاص بالتفكير الابداعي لمؤسسه الاول تورانس منذ عام (1967)، متجاهلة التغيير والتطور المعلوماتي ولا سيما في الانترنيت والحاسوب وما افرزه هذا من مفردات شاعت وتداول

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

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

   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

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