The basis of the personality of each individual lies in the early years of his or her life. If the personality of the child has been well organized and if the motives have been fully expressed and effectively directed, the child will have a strong will, happy self-confidence and a strong personality. If there is a failure In the early years, the individual will be unable to meet his responsibilities in life and may be the victim of many psychological disorders. The family is a learning process through which children acquire the customs, traditions, attitudes and values ​​prevailing in their social environment. (Pre-and-after) play and its relationship to parenting methods of (democratic-bullying-overprotection- and neglect), which wi

Abstract

The research problem Focused about extent adoption of the financial reporting obligations and assets of the deferred income tax attributable to the concepts of accounting theory and whether the tax laws or accounting principles as well as local accounting rules to recognize the obligations and assets of deferred income tax in the financial statements, and what is the impact of the financial reporting of liabilities and assets Deferred tax in the quality of accounting information, and research aims to the statement of the accounting concepts of the theory of financial reporting obligations and assets of deferred income tax, view and analyze the differences in reporting, resulting from a discrepanc

Factory is trotting home favorite of of Aeidid of Iraqi families since he Amta imparted to the taste of the housewife on the method of processing and preparation and the possibility of using some of the ingredients to raise the nutritional value of meat, sesame and other, but how keep Bz'zajh this product Atne storage

The aim of the study is to assess the risk factors which lead to myocardial infarction and relation to some variables. The filed study was carried out from the 1st of April to the end of Sept. 2005. The Sample of the study consisted of (100) patients in lbn-Albeetar and Baghdad Teaching Hospital. The result of the study indicated the following; 45% of patients with age group (41-50) were more exposed to the disease and there is no significant difference was seen in the level of education, Martial status, weight and height. The result shows that there are significant difference in risk factors like hypertension, cholesterol level in blood and diabetes. When analyzed by T.test at level of P < 0.01 and there are significant difference in smoki

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

In this research, the effect of reinforcing epoxy resin composites with a filler derived from chopped agriculture waste from oil palm (OP). Epoxy/OP composites were formed by dispersing (1, 3, 5, and 10 wt%) OP filler using a high-speed mechanical stirrer utilizing a hand lay-up method. The effect of adding zinc oxide (ZnO) nanoparticles, with an average size of 10-30 nm, with different wt% (1,2,3, and 5wt%) to the epoxy/oil palm composite,  on the behavior of an epoxy/oil palm composite was studied with different ratios (1,2,3, and 5wt%) and an average size of  10-30 nm.  Fourier Transform Infrared (FTIR) spectrometry and mechanical properties (tensile, impact, hardness, and wear rate) were used to examine the composites. The FTIR

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class