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jperc-1077
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
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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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Publication Date
Tue Apr 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Weak Pseudo – 2 – Absorbing Submodules And Related Concepts
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      Let  R  be a commutative ring  with identity  and  E  be a unitary left  R – module .We introduce  and study the concept Weak Pseudo – 2 – Absorbing submodules as  generalization of weakle – 2 – Absorbing submodules , where a proper submodule  A of  an  R – module  E is  called  Weak Pseudo – 2 – Absorbing  if   0 ≠ rsx   A   for  r, s  R , x  E , implies that  rx   A + soc ( E ) or  sx  A + soc (E)  or   rs  [ A + soc ( E ) E ]. Many basic  properties, char

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
DNA Encoding and STR Extraction for Anomaly Intrusion Detection Systems
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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Stamps extraction using local adaptive k- means and ISODATA algorithms
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<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected regi

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Publication Date
Tue Oct 01 2013
Journal Name
Sensors And Actuators A: Physical
Enhanced energy harvesting using multiple piezoelectric elements: Theory and experiments
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Publication Date
Mon May 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
An Improved Image Compression Technique Using EZW and SPHIT Algorithms
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 Uncompressed form of the digital images are needed a very large storage capacity amount, as a consequence requires large communication bandwidth for data transmission over the network. Image compression techniques not only minimize the image storage space but also preserve the quality of image. This paper reveal image compression technique which uses distinct image coding scheme based on wavelet transform that combined effective types of compression algorithms for further compression. EZW and SPIHT algorithms are types of significant compression techniques that obtainable for lossy image compression algorithms. The EZW coding is a worthwhile and simple efficient algorithm. SPIHT is an most powerful technique that utilize for image

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Publication Date
Wed Oct 01 2008
Journal Name
Journal
Acanthosis Nigricans in Iraqi Patients Clinical, Histopathological and Theraputic Study
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KE Sharquie, AA Noaimi, AH Muhammad Ali, 2008 - Cited by 3

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Publication Date
Tue Jan 17 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Private Backend Server Software-Based Telehealthcare Tracking and Monitoring System
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In these recent years, the world has witnessed a kind of social exclusion and the inability to communicate directly due to the Corona Virus Covid 19 (COVID-19) pandemic, and the consequent difficulty of communicating with patients with hospitals led to the need to use modern technology to solve and facilitate the problem of people communicating with each other. healthcare has made many remarkable developments through the Internet of things (IOT) and cloud computing to monitor real-time patients' data, which has enabled many patients' lives to be saved. this paper presents the design and implementation of a Private Backend Server Software based on an IoT health monitoring system concerned emergency medical services utilizing biosenso

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Publication Date
Sun Jan 01 2023
Journal Name
Reviews In Agricultural Science
Technological Advances in Soil Penetration Resistance Measurement and Prediction Algorithms
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Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use

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Publication Date
Fri Sep 01 2023
Journal Name
Civil Engineering Journal
Fundamental Challenges and Management Opportunities in Post Disaster Reconstruction Project
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The study examines the root causes of delays that the project manager is unable to resolve or how the decision-maker can identify the best opportunities to get over these obstacles by considering the project constraints defined as the project triangle (cost, time, and quality) in post-disaster reconstruction projects to review the real challenges to overcome these obstacles. The methodology relied on the exploratory description and qualitative data examined. 43 valid questionnaires were distributed to qualified experienced engineers. A list of 49 factors causes was collected from previous international and local studies. A Relative Important Index (RII) is adapted to determine the level of importance of each sub-criterion in the fou

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Publication Date
Wed Jan 01 2025
Journal Name
Fusion: Practice And Applications
Enhanced EEG Signal Classification Using Machine Learning and Optimization Algorithm
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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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