This study tested the impact of region and gender on adolescents 'stress perceptions and coping styles. A total sample of 650 adolescents (5 9.4% female) from 2 countries (Iraq - Algeria). Samples of n = 325 were drawn from each country completed questionnaires on stress and coping behaviors in four domains (school, parents, peer, and future). Results revealed that levels of perceived stressfulness of issues in different domains were universally similar among adolescents from the two countries. School-related stress received the highest rankings, Parent- , future-, peer-related stress, ranked (second, third, and fourth) respectively. Differences emerged with respect to coping style depending on region and gender. Coping sty

يعتبر الخزين من الامور الهامة في العديد من الشركات حيث يمثل نسبة 50 % من رأس مال المستثمر الكلي مع شدة الضغط المتمثل الى خفض التكاليف الكلية المتمثلة مع انواع اخرى من حالات عدم التأكد (الضبابية) لذا سوف نقدم في هذا البحث نظام اقتصادي للكميات الكلية ( الانتاج الاقتصادي للكميات) للوصول حجم الدفعة المثلى المضببة (FEOQ) عندما تكون كل المعالم في حالة عدم التأكد حيث يتم تحويلها الى فترة واحدة وبعد ذلك الحصول على حجم الد

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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البرنامج النووي الايراني واشكالية العلاقة مع الولايات المتحدة الامريكية

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

At the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat

Greenhouses are provide that produce of vegetable in non times seasons production by controlling the various environmental factors that appropriate atmosphere in temperature and humidity for the growth of plants in the plastic houses and owner plastic.
The objective of this research is to study of the most important natural and human factors affecting the Greenhouses in the province of Baghdad and study geographic distribution for the Greenhouses in the province.
Some properties on curriculum geographical descriptive analytical that used in describe and analysis of data and information that could be available from Directorate of agriculture in Baghdad to 2014. As it turns out that district of Mahmudiya acquired (45.3%) of the total

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l