The present research was conducted to investigate the effectiveness of a training program to improve some aspects of sensory integration disorder and its effect on self-direction among a sample of children with intellectual disabilities. The study sample consists of (10 subjects as an experimental group) were exposed to the training program، and the control group consists of (10 subjects as a control group) were not exposed to the training program. The study included the following tools: A scale of self-direction for intellectual disability (prepared by the researcher). Training program (prepared by the researcher). The Results of the study showed the following: There are no statistically significant differences between the means ranks of the experimental group and the means ranks of the control group (pre the training program) on the sensory integration Scale. There are statistically significant differences between the means ranks of the experimental group and the means ranks of the control group (after the training program) on the sensory integration scale in favor of the experimental group. There are statistically significant differences between the means ranks of the experimental group in the pre-test and the means ranks of the same group in the post-test on the sensory integration scale in favor of the post-test. There are no statistically significant differences between the means ranks of the experimental group in the post-test and the means ranks of the same group in the follow up-test on sensory integration scale. There are no statistically significant differences between the means ranks of the experimental group and the means ranks of the control group (pre the training program) on the self-direction scale. There are statistically significant differences between the means ranks of the experimental group and the means ranks of the control group (after the training program) on the self-direction scale in favor of the experimental group. There are statistically significant differences between the means ranks of the experimental group in the pre-test and the means ranks of the same group in the post-test on the self-direction scale in favor of the post-test. There are no statistically significant differences among the means ranks of the experimental group in the post-test and the means ranks of the same group in the follow up-test on the self-direction scale.
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Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.
Comparative studies are, in a sense, a study of cultural identity in a broader and deeper way, as self-knowledge is in part an awareness of the other. Therefore, every study that falls within the scope of comparative literature is a study of the authentic human identity that is open to the other without distorting the individual self or cancellation of social, environmental or national affiliation.
Modern comparative studies seek to go beyond the unilateral perspective of knowledge, which often leads its holders to condescend to all that may be the characteristics of the other. They strengthen the human ties between societies that differ in their culture, literature, and language, esp
... Show MoreThis work aimed to design and testing of a computer program – based eyeQ improvement, photographic memory enhancement, and speed reading to match the reading speed 150 – 250 word per minute (WPM) with the mind ability of processing and eye snap shooting 5000WPM . The package designed based on Visual Basic 6. The efficiency of the designed program was tested on a 10 persons with different levels of education and ages and the results show an increase in their reading speed of approximately 25% in the first month of training with noticeable enhancement in the memory as well as an increase in the ability to read for longer time without feeling nerves or boring, a nonlinear continuously increase in reading speed is assured after the first mo
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Moment invariants have wide applications in image recognition since they were proposed.
CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.
The rate of births delivered by cesarean section (CS) has gone up substantially all over the world. Post-cesarean surgical site infection (SSI) is a common cause of maternal morbidity and mortality that results in prolonged period of hospitalization with increased cost and direct health implications, especially in low socioeconomic population, resource- restricted settings, and war- related conditions with internal forced movement. This study was aimed to find incidence of post cesarean section surgical site infection withthe accompanying risk factors.Pregnant ladies admitted to department of obstetrics and gynecology at Medical City Hospital in Baghdad who had undergone CSs were followed up prospectively from first of January 2017 till end
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This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance
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This paper investigates an effective computational method (ECM) based on the standard polynomials used to solve some nonlinear initial and boundary value problems appeared in engineering and applied sciences. Moreover, the effective computational methods in this paper were improved by suitable orthogonal base functions, especially the Chebyshev, Bernoulli, and Laguerre polynomials, to obtain novel approximate solutions for some nonlinear problems. These base functions enable the nonlinear problem to be effectively converted into a nonlinear algebraic system of equations, which are then solved using Mathematica®12. The improved effective computational methods (I-ECMs) have been implemented to solve three applications involving nonli
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