The study of sex Structure and age characteristics of an important element of the
follow-up changes between different population groups, which are connected to a large degree
the demographic, social and economic characteristics, particularly since each population
group varying characteristics in terms of age, sex entail social, demographic, cultural and
economic implications, and from that the researcher has taken from Structure of sex and age
for population in the district of Tuz Khurmatu for (1997-2012 ) the subject of consideration
and maintain compared to see the contrast between them. Qualitative Research for installation
and the age of the urban and rural areas has touched the judiciary, as well as its respects

The research aimed to modeling a structural equation for tourist attraction factors in Asir Region. The research population is the people in the region, and a simple random sample of 332 individuals were selected. The factor analysis as a reliable statistical method in this phenomenon was used to modeling and testing the structural model of tourism, and analyzing the data by using SPSS and AMOS statistical computerized programs. The study reached a number of results, the most important of them are: the tourist attraction factors model consists of five factors which explain 69.3% of the total variance. These are: the provision of tourist services, social and historic factors, mountains, weather and natural parks. And the differenc

Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm³.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

Abstract

The current study aims to identify the predictability of burnout in perceived self-competence among mothers of students with disabilities in the Sultanate of Oman. The study sample consists of (484) respondents who were mothers of students with disabilities. The researcher developed a burnout Scale which consists of (19) items and a perceived self-competence Scale which consists of (20) items. A correlation descriptive design was used. The results showed that the level of burnout was low (Mean= 2.30), while the level of burnout was high (Mean= 3.87). Regarding the correlation coefficient, the results showed that there was a significant negative correlation between burnout and perceived self-competence. A

Abstract

The current research aims to reveal the extent to which all scoring rubrics data for the electronic work file conform to the partial estimation model according to the number of assumed dimensions. The study sample consisted of (356) female students. The study concluded that the list with the one-dimensional assumption is more appropriate than the multi-dimensional assumption, The current research recommends preparing unified correction rules for the different methods of performance evaluation in the basic courses. It also suggests the importance of conducting studies aimed at examining the appropriateness of different evaluation methods for models of response theory to the

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de