The study aimed to identify the awareness level of hidden curriculum among field education students, College of Education, Hail University. To identify the different awareness level of hidden curriculum among field education students depending on specialization variable, and grade variable in curriculum and instruction course, a descriptive survey method was used. The study sample consisted of (182) students: 78 students in Islamic Culture major, 46 primary major and 58 in physical education. To achieve the study objectives, a hidden curriculum awareness scale was designed included (36) items. The study results showed: the awareness level of hidden curriculum among students of field education, Education College, Hail University, achieved

Objective: The study aimed to 1) measure the prevalence of depression and anxiety among Iraqi pharmacy and medical students at a number of universities in Baghdad using Hospital Anxiety and Depression Scale (HADS) and 2) investigate the association between various sociodemographic factors and students’ HADS scores. Methods: This study was based on a cross-sectional descriptive design in four universities in Baghdad, Iraq. Depression and anxiety were screened using an Arabic version of the HADS. An online survey was administered via Qualtrics to convenience samples of students at four colleges of pharmacy and a college of medicine between March and June 2018. Multiple linear regression was used to identify factors associated

The study aims at knowing students’ academic assistance at the Department of Kindergarten. It further aims to know the difference of academic assistance among these students with respects to variables like (college of education for women, Baghdad, Thi-Qar). It also aims to know about the difference according to the academic level variable, in addition to its relation to some other variables. To achieve the objectives of the study, a number of university female students were selected from both Baghdad an Thi-Qar Universities in the academic year 2019-2020. The sample of the participants consisted of (400) students from the (second, third, and fourth) levels. To measure the study variable represented by the concept of academic assistance

     A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network

Single-input Multiple-output Signals Third-order Active-R Filter for different Circuit Merit Factor Q Configuration is proposed. This paper discusses a new configuration to realize third-order low pass, band pass and high pass. The presented circuit uses Single-input Multiple-output signals, OP-AMP and passive components. This filter is useful for high frequency operation, monolithic IC implementation and it is easy to design .This circuit gives three filter functions low-pass, high-pass and band-pass. This filter circuit can be used for different merit factor (Q) with high pass band gain. This gives better stop-band attenuation and sharper cut-off at the edge of the pass-band. Thus the response shows wider pass-band. The Ideal value of thi

This paper addresses the use of adaptive sliding mode control for the servo actuator system with friction. The adaptive sliding mode control has several advantages over traditional sliding mode control method. Firstly, the magnitude of control effort is reduced to the minimal admissible level defined by the conditions for the sliding mode to exist. Secondly, the upper bounds of uncertainties are not required to be known in advance. Therefore, adaptive sliding mode control method can be effectively implemented. The numerical simulation via MATLAB 2014a for servo actuator system with friction is investigated to confirm the effectiveness of the proposed robust adaptive sliding mode control scheme. The results clarify, after

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte