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Evaluating the Students Perception of Academic Learning Environments in AL-Kindy Collage of Medicine
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Background: Educational environment is one of the most important determinants of an effective curriculum. Students' perceptions of their educational environment have a significant impact on their behavior and academic progress. Objective: 1. To identify students’ perception to the educational environment.2. To identify any gender or class level differences in the students’ perception.Type of the study: This is a descriptive cross-sectional studyMethodology: The study was carried out on convenient sample of 150 students of 2nd and 5th grade. This study was done in Al Kindy Medical College, Baghdad, Iraq and conducted during the period from the 1st of October 2013 till the end of March 2014, by using DREEM questionnaire a validated universal diagnostic inventory for assessing the quality of educational environment through direct interview. Inclusion criteria include any student from the 2nd and 5th class who agree to participate in the study. The data was entered into a Microsoft Excel spreadsheet and were analyzed using SPSS version 16. Student t test was done to find out the difference between the mean scores, P<0.05 was considered as statistically significant.Results: For all students (n= 150) the total DREEM score of a maximum possible of 200 was 110.18 , it was more positive than negative overall domain score, which means that the students had positive perception and more positive scores than negative. Total DREEM scores were significantly higher for females (M = 138.8; SD = 17.2) than males (M = 132.3; SD = 20.7), although all domains mean scores were higher for female than male, there was statistical significant difference regarding Students’ perception of learning, Students’ perception of atmosphere and Students’ social self-perception.Regarding the class level, 5th year students gave significantly higher total DREEM ratings (M = 139.1; SD = 17.4) than 2nd year students (M = 135; SD = 18.8). Second year students also gave significantly higher Students’ perception of learning (SPL) ratings than 5th year students and significantly higher Students’ perception of atmosphere ( SPA ) ratings higher than 5th year students. Conclusions: Students assessed the educational environment as more positive than negative;. The greatest difficulty was with ‘students’ perception of learning’.

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Publication Date
Tue Oct 02 2018
Journal Name
Iraqi Journal Of Physics
Measurement of indoor radon levels and assessment of radiological hazards at Al-Tuwaitha nuclear site and the surrounding area
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In the present study the radon concentration was measured in indoor places by the RAD7 (radon detector) was in some locations at Al-Tuwaitha nuclear site and some surrounding areas for the duration from 13/10/2016 to 2/1/2017 and the measurement of the indoor radon concentration ranged from (4.96±4.4 to 102±25) Bq/m3. The high value of radon has been found at decommissioning directorate /emergency room, which is lower than the action value recommended by the Environmental Protection Agency (EPA) which is (148 Bq/m3) while the lowest value has been founded in central laboratories directorate \ models room. These values were used to calculate the annual effective dose and the health risks for cells bronchial which caused by the inhalatio

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Publication Date
Mon Apr 01 2024
Journal Name
Iraqi Journal Of Oil And Gas Research (ijogr)
Comparative study of electrochemical oxidation system hybrid with photocatalytic system for the treatment of Al-Najaf petroleum refinery wastewater
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Publication Date
Wed Oct 21 2015
Journal Name
Integrated Journal Of Engineering Research And Technology
A HYBRID CUCKOO SEARCH AND BACK-PROPAGATION ALGORITHMS WITH DYNAMIC LEARNING RATE TO SPEED UP THE CONVERGENCE (SUBPL) ALGORITHM
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Publication Date
Tue Feb 14 2023
Journal Name
Journal Of Educational And Psychological Researches
Partnership between Secondary Schools and Community Agencies to Improve the Outcomes of Students with Intellectual Disabilities (Reality and Development)
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Abstract

The current research aims to identify the level of partnership between school and community agencies to improve secondary school outcomes for students with intellectual disabilities and develop strategies that help enhance community partnerships between schools and agencies. The researcher used the qualitative research approach; he utilized the interviews as a tool for data collection. The sample of research included (12) participants: three female school leaders, three male-school leaders, three female-school supervisors, and three male-school supervisors in schools that have programs for students with intellectual disabilities in Riyadh. The results of the study showed that the level of partnership bet

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Statistical quality control charts for measuring educational service quality at Albaha University, Saudi Arabia, from the viewpoint of students
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تم استخدام خرائط ضبط الجودة الإحصائية لتقييم جودة الخدمة التعليمية في جامعة الباحة،  ويهدف هذا البحث إلى استخدام خرائط ضبط الجودة الإحصائية لقياس مستوى الجودة وفجوة الجودة بين توقعات الطلبة وإدراكاتهم لمستوى الخدمة الذي تقدمه جامعة الباحة. حيث تم اختيار عينة من 200 طالب وطالبة عشوائيا باستخدام العشوائية العنقودية من 4 كليات خلال الفترة 01 – 30/2015م، وجمعت البيانات من خلال استبيان جودة الخدمة الذي يقيس ت

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Constructing a Software Tool for Detecting Face Mask-wearing by Machine Learning
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       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
A Survey on Arabic Text Classification Using Deep and Machine Learning Algorithms
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    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

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Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
Unsupervised Learning: Discovering Patterns without Labels: Health Care, E-Commerce, and Cybersecurity
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