This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

Background: The prevalence of both obesity & diabetes are increasing all over the world & more in women.  They have a negative impact not only on morbidity & mortality but also on quality of life.

Objectives: To assess the HRQoL with a specific comparison between obese & normal weight among wo

Background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women of reproductive age with primary manifestations of infertility, menstrual dysfunction and clinical or biochemical hyperandrogenism (hirsutism, acne and elevated androgen). Adiponectin is the most abundant adipokine. It has insulin-sensitizing, anti-atherogenic, and antiinflammatory actions.Objective: Low adiponectin levels in women with PCOS have been largely attributed to obesity which is common among these patients. Therefore, the aim of this study was to measure adiponectin levels in normal weight women with PCOS and its contribution to development of disease.Subjects and Methods: Fifty two (52) women were included in this study with age ra

In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

The gypseous soil may be one of the problems that face the engineers especially when it used as a foundation for hydraulic structures, roads, and other structures. Gypseous soil is strong soil and has good properties when it is dry, but the problem arises when building hydraulic installations or heavy buildings on this soil after wetting the water to the soil by raising the water table level from any source or from rainfall which leads to dissolve the gypsum content. Cement-stabilized soil has been successfully used as a facing or lining for earth channel, highway embankments and drainage ditches to reduce the risk of erosion and collapsibility of soil. This study is deliberate the treatment of gypseous soil by using a mixture

The gypseous soil may be one of the problems that face the engineers especially when it used as a foundation for hydraulic structures, roads, and other structures. Gypseous soil is strong soil and has good properties when it is dry, but the problem arises when building hydraulic installations or heavy buildings on this soil after wetting the water to the soil by raising the water table level from any source or from rainfall which leads to dissolve the gypsum content.

Cement-stabilized soil has been successfully used as a facing or lining for earth channel, highway embankments and drainage ditches to reduce the risk of erosion and collapsibility of soil. This study is deliberate the treatment of gypseous soil by u

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

The study aims to identify the effect of training with weight added to different parts of the body in improving the biomechanical variables of the last step and upgrading the high jump for young people, the research was applied to one of the elite high jumpers for young people, and video imaging and kinetic analysis were conducted to extract the variables under study, and then the jumper underwent For the proposed exercises by 3 training units per week for a period of (8) weeks, in which emphasis was placed on improving the rotational forces (moments) of these parts, and then the post-tests were conducted, and the researcher concluded that the exercises applied and the added weights for all parts of the body (leg, thigh, trunk, and arms) le