Purpose: The purpose of the study is to compare and evaluate Earnings Management in Tunisia and Iraq.   Theoretical framework: Earnings Management is an important topic that has been studied by a significant number of researchers, as well as those who are interested in the accounting profession. Earnings Management has gotten a lot of attention from academics, professionals, and other interested parties in recent years (e.g. Kliestik et al., 2020; Rahman et al., 2021; Gamra &Ellouze, 2021)   Design/methodology/approach: The sample includes ten banks listed on the Bourse of Tunisia and Iraq Stock Exchanges for the year 2017. We have used a model of Kothari et al., (2005) as a tool to measure Earnings Management in both mark

A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter  was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of  are derived from the relation between  and level density parameter . The formulae used to derive  are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on  from the Thomas-Fermi formula show a good agreement with the experimental data.

The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

A group of acceptance sampling to testing the products was designed when the life time of an item follows a log-logistics distribution. The minimum number of groups (k) required for a given group size and acceptance number is determined when various values of Consumer’s Risk and test termination time are specified. All the results about these sampling plan and probability of acceptance were explained with tables.

You Mohammed, you're prophet of God and I'm Gabriel)). With this heavenly call which Mohammed, the messenger of God (may God's mercies be on him), got and when he left Hiraa cave and after getting the aye ((read with your God's name)), a new period of mankind's history started. From that time, the greatest state was established. There was no public treasury and no public financial resources at that time. Abu Baker (God bless him) spent a lot of money to support the costs of the new mission. After Al-Hijra, the bases of establishing the Islamic state were available but it lacked administrative and financial organizing. Therefore the prophet was very keen to find Islamic system which ensures justice and availability of

يسعى البحث إلى الاهتمام بإحدى الوظائف المهمة في إدارة الموارد البشرية وهي تقويم الأداء التي تواجه مجموعة من الانتقادات والآراء السلبية، اذ ظهر في الأّونة الأخيرة أنموذج جديد يمكن إن يتجاوز تلك السلبيات وهو أنموذج التغذية العكسية المتعدد المصادر درجة .وقد حاول الباحثان توظيف هذا المفهوم في اثنتين من المنظمات العامة العراقية هما (دائرة كهرباء الوسط) التابعة لوزارة الكهرباء
و (دائرة الماء والمجاري) ال

Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

This researchpaper includes the incorporation of Alliin at various energy levels and angles 

With Metformin using Gaussian 09 and Gaussian view 06. Two computers were used in this work. Samples were generated to draw, integrate, simulate and measure the value of the potential energy surface by means of which the lowest energy value was (-1227.408au). The best correlation compound was achieved between Alliin and Metformin through the low energy values where the best place for metformin to b

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin