Young people represent the power and cornerstone of societies and their superiority is linked to their well-being. Their empowerment is as essential as the heart to the body, if it is corrupt, then the whole body is corrupt, and vice versa. The exposure to extremism and pressure from their families leads to violent acts and crimes for obtaining money through unknown organized bodies. This will drive them to fail in their life in an attempt to fulfill their most basic needs, which they have been deprived of by their families, the government, and other institutions. Therefore, governments should provide job opportunities for young people and provide entertainment centers, sports clubs, and family education centers that raise awareness of s

The aimed of the research was recognize the Big five personality factors and Academic procrastination among Baghdad university students, recognized differences between the gender according to   Big five personality factors and Academic procrastination , to recognized differences between specialization (scientific, human), and to recognize the relationship Between the variables of the research, and the extend of contribution Big five personality factors in Academic procrastination , to achieve these aims , Adopt scale to measure the Big five personality factors for (John Danahue & Kentle) , As we as the preparation of scale Based on An amber of previous scales to measure Academic procrastination, After processing the data st

This study aimed to measure the innovative thinking and cognitive cessation among university students. The sample consisted of (400) male and female students at al Mustansiriya University for the academic year (2018/2019). The results of the study showed that there are differences in innovative thinking and cognitive inhibition according to the gender variable in favor of males. There is a positive relationship between innovative thinking and cognitive inhibition. In light of these findings, the researcher presented a set of conclusions and recommendations.

The matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single l

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

Facial expressions are a term that expresses a group of movements of the facial fore muscles that is related to one's own human emotions. Human–computer interaction (HCI) has been considered as one of the most attractive and fastest-growing fields. Adding emotional expression’s recognition to expect the users’ feelings and emotional state can drastically improves HCI. This paper aims to demonstrate the three most important facial expressions (happiness, sadness, and surprise). It contains three stages; first, the preprocessing stage was performed to enhance the facial images. Second, the feature extraction stage depended on Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) methods. Third, the recognition stage w

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

Abstract: The article aimed to formulate an MLX binary ethosome hydrogel for topical delivery to escalate MLX solubility, facilitate dermal permeation, avoid systemic adverse events, and compare the permeation flux and efficacy with the classical type. MLX ethosomes were prepared using the hot method according to the Box–Behnken experimental design. The formulation was implemented according to 16 design formulas with four center points. Independent variables were (soya lecithin, ethanol, and propylene glycol concentrations) and dependent variables (vesicle size, dispersity index, encapsulation efficiency, and zeta potential). The design suggested the optimized formula (MLX−Ethos−OF) with the highest desirability to perform the