Fraud Includes acts involving the exercise of deception by multiple parties inside and outside companies in order to obtain economic benefits against the harm to those companies, as they are to commit fraud upon the availability of three factors which represented by the existence of opportunities, motivation, and rationalization. Fraud detecting require necessity of indications the possibility of its existence. Here, Benford’s law can play an important role in direct the light towards the possibility of the existence of financial fraud in the accounting records of the company, which provides the required effort and time for detect fraud and prevent it.
At different stages of the evolution of the modern Iraqi state ears last century did not receive the industrial sectors importance in great domestic production (GDP) and that the limited resources available in the initial stage and the dominance of public sector industry in the late stage , so the continued decline in the contribution of the private industrial sector in GDP , and this is why imbalance in the labor market and reduced demand for manpower in this sector despite the high rates of labor supply and the various skills and levels of investments, their human and the different geographical distribution , and direction of labor to other economic sectors most requested of the l
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp
... Show MoreThis work presents the modeling of the electrical response of monocrystalline photovoltaic module by using five parameters model based on manufacture data-sheet of a solar module that measured in stander test conditions (STC) at radiation 1000W/m² and cell temperature 25 . The model takes into account the series and parallel (shunt) resistance of the module. This paper considers the details of Matlab modeling of the solar module by a developed Simulink model using the basic equations, the first approach was to estimate the parameters: photocurrent Iph, saturation current Is, shunt resistance Rsh, series resistance Rs, ideality factor A at stander test condition (STC) by an ite
... Show MoreThe role of university in awareness of Social and Cultural Human Rights to Students
still at the beginnings . the irritable secure of Iraqi environment is the most challenges that
cease any work that may raise the human rights in university . in spite of obstacles the same
society of university like conferences and meetings that related to this subject . as well as the
luck of professional teachers.
This study raises a group of important questions, perhaps the most :
The contribution of university in educates their students of the social and cultural human
rights? What are the most challenges that facing these students? Does the university
responsible of this luck of understanding these human rights?
This Study
Companies compete greatly with each other today, so they need to focus on innovation to develop their products and make them competitive. Lean product development is the ideal way to develop product, foster innovation, maximize value, and reduce time. Set-Based Concurrent Engineering (SBCE) is an approved lean product improvement mechanism that builds on the creation of a number of alternative designs at the subsystem level. These designs are simultaneously improved and tested, and the weaker choices are removed gradually until the optimum solution is reached finally. SBCE implementations have been extensively performed in the automotive industry and there are a few case studies in the aerospace industry. This research describe the use o
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This study was conducted in the poultry field of the department of animal production, college of agricultural engineering sciences, university of Baghdad for the period from 10/15/2021 to 11/25/2021 with the aim of showing the effect of adding different levels of dill seeds to the diet on productive and carcass traits For broiler meat. In this study, 200 unsexed broiler chicks of breed (Ross 308) were used, one day age, with a starting weight of 41.46 g. The chicks were randomly distributed to 5 treatments, and each treatment included 4 replicates, 10 birds for each replicate. The birds were fed three diets: the starter diet, the growth diet and the final diet. The experiment treatments were T1,
... Show Moreمستخلص البحث كان الهدف من البحث هو إعداد تمرينات خاصة لتطوير مهارة التصويب بالقفز بكرة السلة للشباب، إذ لوحظ ضعفاً ملموساً ولاسيما عند فئة الشباب في إحراز النقاط في مهارة التصويب بالقفز المحسوب بنقطتين وذلك لصعوبة أداءه إذ ان المدافعين أصبحوا متمكنين من قدراتهم فضلاً عن عامل الوقت عند الأداء يكاد يكون قليل جداً عند اتخاذ القرار. وقد اعتمد الباحثان في إعداد التمرينات مبدأ التدرج من السهل إلى الصعب والتنوع في
... Show MoreQJ Rashid, IH Abdul-Abbas, MR Younus, PalArch's Journal of Archaeology of Egypt/Egyptology, 2021 - Cited by 4
Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and
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