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

The study aimed to identify the news framing on the Israeli Arabic-speaking i24 channel of the Israeli aggression on Gaza -2021 by analyzing the channel’s Program “this evening”. The study used the media survey method, and in its framework, it relied on the content analysis method for the program’s episodes from May 5, 2021 AD until June 4, 2021 AD, with 22 episodes. The study showed the program’s interest in launching the Palestinian resistance’s rockets significantly, followed by the Israeli military operations, and the program’s reliance on correspondents largely as a source of news material related to the aggression. It also proved that a news report and a reporter's report was the most important form of presenting news

A freshwater bivalve plays a crucial function in aquatic habitats as the filtered water and burrowing mussels mix the sediment, thus increasing oxygen content and making the ecosystem healthier. The aim of the study is to see how chlorpyrifos affects biochemical markers in freshwater mussel Unio tigridis. About 180 individuals per taxon and water samples were collected from the Qandil water resource on the Greater Zab River, Erbil Province, Iraq. Once arrived at the lab, the individuals were kept in aquaria with river water and an air-conditioned room Temperature: 25±2 and Light: 12h/12h and acclimatized to laboratory conditions for seven days in aged tap water. The mussel's identification molecularly and the DNA sequence of t

The present study was designed to show the potential role of Matricaria chamomilla flower extract against toxicity of Entamoeba histolytica  . The study used 20 adult albino male rats that divide randomly to four groups (each group consist 5 rats); control group received ad libidium, group of rats administrated with 1X10³ cyct/ml suspension for seven days, group of rats administrated with 1X10³ cyct/ml suspension and treated with 50mg/kg extract for month, group of rats administrated with 1X10³ cyct/ml suspension and treated with 100mg/kg extract for month. The results show high significant increased (P < 0.05) in levels of Alanine

The trade war, of course, leads to a sharp tension in international relations because the economy is the lifeblood of the states. In the world of trade and economy, countries began to lean towards cooperation. Economic relations after World War II were more liberal, trade barriers were removed and global trade became more flexible and smooth

This work is aimed to design a system which is able to diagnose two types of tumors in a human brain (benign and malignant), using curvelet transform and probabilistic neural network. Our proposed method follows an approach in which the stages are preprocessing using Gaussian filter, segmentation using fuzzy c-means and feature extraction using curvelet transform. These features are trained and tested the probabilistic neural network. Curvelet transform is to extract the feature of MRI images. The proposed screening technique has successfully detected the brain cancer from MRI images of an almost 100% recognition rate accuracy.

Due to the lack of vehicle-to-infrastructure (V2I) communication in the existing transportation systems, traffic light detection and recognition is essential for advanced driver assistant systems (ADAS) and road infrastructure surveys. Additionally, autonomous vehicles have the potential to change urban transportation by making it safe, economical, sustainable, congestion-free, and transportable in other ways. Because of their limitations, traditional traffic light detection and recognition algorithms are not able to recognize traffic lights as effectively as deep learning-based techniques, which take a lot of time and effort to develop. The main aim of this research is to propose a traffic light detection and recognition model based on

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Face recognition is a type of biometric software application that can identify a specific
individual in a digital image by analyzing and comparing patterns. It is the process of
identifying an individual using their facial features and expressions.
In this paper we proposed a face recognition system using Stationary Wavelet Transform
(SWT) with Neural Network, the SWT are applied into five levels for feature facial
extraction with probabilistic Neural Network (PNN) , the system produced good results
and then we improved the system by using two manner in Neural Network (PNN) and
Support Vector Machine(SVM) so we find that the system performance is more better
after using SVM where the result shows the performance o

Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa