هدفت الدراسة التعرف على الشفقة بالذات لدى الطلبة فضلا عن التعرف على الفروق في الشفقة بالذات وفق متغيرات : الجنس –التخصص الدراسي – المرحلة الدراسية، تالفت عينة الدراسة من (200) طالب وطالبة موزعين بالتساوي حسب الجنس (ذكور – اناث) والتخصص الدراسي (علمي - انساني) والمرحلة الدراسية ( الاولى - الرابعة )، وبعد تطبيق مقياس الدراسة وتحليل الاجابات احصائيا ، اظهرت النتائج ان الطلبة لديهم شفقة بالذات كما اظهرت النتائج عدم

هدفت الدراسة إلى التعرف على الحيوية الذاتية فضلاً عن التعرف على الفروق في الحيوية الذاتية بين الطلبة على وفق متغير الجنس (ذكر – انثى) والمرحلة الدراسية (أول-رابع) والتخصص الدراسي (علمي-انساني)، تألفت عينة الدراسة من (120) طالبا وطالبة من طلبة الجامعة، وتم تطبيق مقياس الدراسة -مقياس (الحيوية الذاتية) وهو (من إعداد الباحثة)، وقد اسفرت نتائج الدراسة عن: - إن طلبة الجامعة يتمتعون بدرجة عالية من الحيوية الذاتية. - وجود ف

ان الداسات القرانية تعد من الدراسات المتعلقة في اللغة العربية لانها تتعلق بدراسة جانب من جوانب اعجاز القرأن الكريم لذلك قمت بدراسة جانب من جوانب اعجاز القران الا وهي لفظة اكل

تحليل الأخطاء الصوتية في بعض كتب اللغة الروسية الدراسية

Neuroendocrine differentiation has been mentioned in many cancers of non-neuroendocrinal organs, involving the gastrointestinal tract. In contrast, the correlation of focally diffused neuroendocrine differentiation in colorectal adenocarcinoma with neuroendocrine cell hyperplasia has not been somewhat reported. The objective of this research is to study the relationship between neuroendocrine cell hyperplasia and neuroendocrine differentiation in colorectal adenocarcinoma and to find the correlation of neuroendocrine differentiation and VEGF expression with clinicopathological parameters of colorectal adenocarcinoma. Methods employed in the current study were including eighty-one patients with colorectal cancer. Formalin fixed paraffin e

The research aims to identify the factors affecting the customer and their impact desire for market share in a competitive market National Insurance Company, where he was after the tremendous developments that have taken place in the insurance sector, crowded markets, private companies and the intensified competition among those companies on one side and public sector companies, including national insurance company on the other hand, increased attention and study in a big way the customer and the factors influencing the desire. As the national insurance company ascertains its targets once the sale of insurance documents only, but by knowing the tendencies and aspirations of current and prospective customers a way that helps to strengthen

This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

In this study, an efficient compression system is introduced, it is based on using wavelet transform and two types of 3Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI)) and 1 st order polynomial approximation. Each one is applied on different scales of the image; CBI is applied on the wide area of the image in order to prune the image components that show large scale variation, while the 1 st order polynomial is applied on the small area of residue component (i.e., after subtracting the cubic Bezier from the image) in order to prune the local smoothing components and getting better compression gain. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, t

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an