This study  focused on a fundamental issue which was represented by ability of Iraqi central bank in facing the difficulty of determining  the optimal ratio of liquidity in the Iraqi banks in terms of the balancing between its obligations to the depositors and borrowers, and liquidate their funds on one hand and the risks on the other hand.the search aimed  for achieving the goals which represented by identifying the possibility of Iraqi banks to apply the regulations rules and  instructions  issued by central bank  of  Iraq in determining  ratio  of  liquidity and  its  appropriate with Iraqi  banks  action to implement  a  reasonable  profit to&

In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th

This study examines the impact of Digital Transformation (DT) on the Financial Reporting Quality (FRQ), taking into account the moderating role of the Trust Services Framework (TSF), in the context of rapid developments in the digital business environment and the resulting challenges and opportunities for accounting and financial systems. To achieve the study objectives, a descriptive–analytical approach was adopted, and a questionnaire was used as the primary data collection instrument. The study sample comprised 87 professionals working in accounting and financial functions. DT was measured through four dimensions: cloud computing, automation, data analytics, and systems integration. FRQ was assessed using the dimensions of accuracy and

The international humanitarian law found the special rules to protect women meanwhile the armed conflicts whether international or non-international. These rules are adopted for woman because of two reasons : that she is from civilians and on the other hand that her special constitution demands a special protection. The international community's attention of women is increased as a result of the tragic situation that faced women around the world especially in the Middle East and particularly in Iraq during the American-British war and ISIS period, these two periods sort many negative effects that reach women such as captivity, slavery, sexual enslavement and rape women especially Yazidis and Christians....

     This paper discusses estimating the two scale parameters of Exponential-Rayleigh distribution for singly type one censored data which is one of the most important Rights censored data, using the maximum likelihood estimation method (MLEM) which is one of the most popular and widely used classic methods, based on an iterative procedure such as the Newton-Raphson to find estimated values for these two scale parameters by using real data for COVID-19 was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. The duration of the study was in the interval 4/5/2020 until 31/8/2020 equivalent to 120 days, where the number of patients who entered the (study) hospital with sample size is (n=785). The number o

The Normalized Difference Vegetation Index (NDVI) is commonly used as a measure of land surface greenness based on the assumption that NDVI value is positively proportional to the amount of green vegetation in an image pixel area. The Normalized Difference Vegetation Index data set of Landsat based on the remote sensing information is used to estimate the area of plant cover in region west of Baghdad during 1990-2001. The results show that in the period of 1990 and 2001 the plant area in region of Baghdad increased from (44760.25) hectare to (75410.67) hectare. The vegetation area increased during the period 1990-2001, and decreases the exposed area.

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

The purpose of the current investigation is to distinguish between working memory ( ) in five patients with vascular dementia ( ), fifteen post-stroke patients with mild cognitive impairment ( ), and fifteen healthy control individuals ( ) based on background electroencephalography (EEG) activity. The elimination of EEG artifacts using wavelet (WT) pre-processing denoising is demonstrated in this study. In the current study, spectral entropy ( ), permutation entropy ( ), and approximation entropy ( ) were all explored. To improve the  classification using the k-nearest neighbors ( NN) classifier scheme, a comparative study of using fuzzy neighbourhood preserving analysis with -decomposition ( ) as a dimensionality reduction technique an

Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st