تنفذ أجهزة اإلحصاء الدولية ومنها الجهاز المركزي لإلحصاء في العراقإحدى أجهزة وزارة التخطيط، تقوم بإجراء مسوح سنوية ودورية لإنتاج مؤشرات تقييم وتقويم أنشطة القطاعات الاقتصادية المختلفة. يتيح هذا الكم الهائل من البيانات بشكل سلسل زمني لهذه الأجهزة إنتاج مؤشرات جديدة، بما في ذلك القيم التنبؤية لمؤشرات رئيسية تستخدم في إعداد الخطط طويلة وقصيرة المدى. في عام 2015، قامت مديرية الإحصاء الزراعي في الجهاز المركزي للإ

من خلال ملاحظة الباحثتين الميدانية لمستوى الأداء الفني لمنتخب ناشئات القطر بالجمناستك لمهارة قفزة اليدين الأمامية على جهاز منصة القفز الحديثة لاحظن وجود مشكلة تكمن في ضعف هذا الأداء والذي يؤثر على بعض المتغيرات البيوكينماتيكية لهذه المهارة مما يؤدي إلى عدم أداء المهارة بالشكل الصحيح ، وتعزو الباحثتان ذلك الضعف إلى قلة الدفع بالرجلين والذراعين . لذا ارتأت الباحثتان إجراء هذا البحث الذي يهدف إلى تنمية القوة

       The implicit is the narrative technique used to give indirect hidden messages. To read between the lines means to understand the implicit meaning that is not directly indicated. This technique is expressed in two forms: the hypothesis and the implications of linguistic and non-linguistic rules. Nathalie Sarraute’s "Pour un oui ou pour un non" states this narrative method through her character’s verbal and non-verbal dialogue. The present paper discusses the implicit method and shows the reason behind which  the author uses it in her play "Pour un oui ou pour un non".

Résumé

The goal of this study was to investigate the protein peroxidation role by measuring serum levels of advanced oxidation protein products (AOPP) in type 2 diabetic patients with or without retinopathy and comparing them to controls to see if circulating AOPP levels can be used as a detection biomarker for DR. And see which of the two widely used antidiabetic treatment groups had the most impact on this oxidative stress marker. The groups were divided into two subgroups: 1) 70 type 2 diabetic patients (36 male, 34 female), 35 with diabetic retinopathy (DR) and 35 with no evidence of DR, and 2) non-diabetic controls (11 male, 9 female) were chosen from Ibn AL-Haitham Hospital for Ophthalmology and a Specialized Center for Endocrinology and Dia

With today's rapid and full of dangers the world banking sector is one of the most vital sectors at risk, and on the supervisory bodies responsible for monitoring the work of banks to take an active role in influencing the banks and put on the right track and is compatible with internationally approved curriculum. The lie of the research problem in the weak supervisory role of the Central Bank for banks in general and private banks in particular, limited the process of performance audit carried out by the Federal Office of Financial Supervision in auditing oversight role of the Central Bank control over the banks, according to the methods of performance audit followed by the upper bodies of financial control and accounting, And it was ba

The study aimed to examine the impact of audit committee characteristics on the practices of intellectual capital disclosure in the annual reports of Bank and Insurance companies listed on Palestine Exchange, through performing content analysis of the annual reports for the study sample which totaled thirteen companies, including six banks and seven insurance companies. To achieve the study objectives, the study employed a content analysis approach in order to analyze the content of the intellectual capital disclosure practice, in addition, the study used cross-sectional with longitudinal data for time series for a period of time between 2014-2019. The empirical results indicated that financial expertise and the number of meeting

In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

     A global pandemic has emerged as a result of the widespread coronavirus disease (COVID-19). Deep learning (DL) techniques are used to diagnose COVID-19 based on many chest X-ray. Due to the scarcity of available X-ray images, the performance of DL for COVID-19 detection is lagging, underdeveloped, and suffering from overfitting. Overfitting happens when a network trains a function with an  incredibly high variance to represent the training data perfectly. Consequently, medical images lack the availability of large labeled datasets, and the annotation of medical images is expensive and time-consuming for experts. As the COVID-19 virus is an infectious disease, these datasets are scarce, and it is difficult to get large datasets