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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
Sat Dec 26 2020
Journal Name
International Journal Of Pharmaceutical Research
Complexes of Co(II), Cu(II), Ni(II), Pt(II) And Pd(II) with N 3 O-Chelating Ligand Incorporating Azo and Schiff Base Moieties: Synthesis, Spectroscopic, Thermal Decomposition, Theoretical Studies, and thermodynamic parameters
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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis and Charact'erizatio.n of new Schiff base ligand [(2-{1-[(2 hydraxy­ benzylidene)-hydrazono]-ethyl} benzene-I, 3, 5--triol.] and it's CQmp.lexes. with Co en\ Ni . (U),, c·u(U)' and · zn(II).
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The eaction  of 2 4 .6-trihydroxyactophenonemonohydra1e  with

l hydr.azine monohydrate was realized ti·nder reflu.(( in methanol and i:l.

Jew drops of glacial acetic acid we.re added to give lhe'(int rmediate)

2-(1hydr pno-ctbyt)-benzcne-·1.3.5-r:Qql,       which      reacted     wittl

saEcy.laldehyde. jn methm)ql to gjy;e 'a new :tyRe CNzOi) Ligand  (H:flL]

f(2-{1-[(2-=bydroxy-bertzylide·ne)-bydrazqoo,J-e·thy.1}bcnze·neJ ;3·,5

of

 

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Publication Date
Thu Mar 25 2021
Journal Name
International Journal Of Drug Delivery Technology
Synthesis, Structural Study, and Biological Activity Evaluation of VO(II), Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), and Hg(II) Complexes with New Schiff Base Ligand Derived from Pyrazine
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New Schiff base [3-(3-acetylthioureido)pyrazine-2-carboxylic acid][L] has been prepared through 2 stages, the chloro acetyl chloride has been reacting with the ammonium thiocyanate in the initial phase for producing precursor [A], after that [A] has been reacting with the 3-amino pyrazine-2-carboxilic acid to provide a novel bidentate ligand [L], such ligand [L] has been reacting with certain metal ions in the Mn(II), VO(II), Ni(II), Co(II), Zn(II), Cu(II), Hg(II), and Cd(II) for providing series of new metal complexes regarding general molecular formula [M(L)2XY], in which; VO(II); X=SO4,Y=0, Co(II), Mn(II), Cu(II), Ni(II), Cd(II), Zn(II), and Hg(II); Y=Cl, X=Cl. Also, all the compounds were characterized through spectroscopic techniques [

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Synthesis, Theoretical Study, and Biological Evaluation of Some Metal Ions with Ligand "Methyl -6-[2-(4-Hydroxyphenyl) -2-((1-Phenylethylidene) Amino) Acetamido] -2,2-Dimethyl-5—Oxo-1-Thia-4-Azabicyclo [3.2.0] Heptane-3-Carboxyylate
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Schiff base (methyl 6-(2- (4-hydroxyphenyl) -2- (1-phenyl ethyl ideneamino) acetamido) -3, 3-dimethyl-7-oxo-4-thia-1-azabicyclo[3.2.0] heptane-2-carboxylate)Co(II), Ni(II), Cu (II), Zn (II), and Hg(II)] ions were employed to make certain complexes. Metal analysis M percent, elemental chemical analysis (C.H.N.S), and other standard physico-chemical methods were used. Magnetic susceptibility, conductometric measurements, FT-IR and UV-visible Spectra were used to identified. Theoretical treatment of the generated complexes in the gas phase was performed using the (hyperchem-8.07) program for molecular mechanics and semi-empirical computations. The (PM3) approach was used to determine the heat of formation (ΔH˚f), binding energy (ΔEb), an

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Publication Date
Mon Dec 10 2018
Journal Name
Aro-the Scientific Journal Of Koya University
Membrane Computing for Real Medical Image Segmentation
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In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Diagnosing Pilgrimage Common Diseases by Interactive Multimedia Courseware
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In this study, we attempt to provide healthcare service to the pilgrims. This study describes how a multimedia courseware can be used in making the pilgrims aware of the common diseases that are present in Saudi Arabia during the pilgrimage. The multimedia courseware will also be used in providing some information about the symptoms of these diseases, and how each of them can be treated. The multimedia courseware contains a virtual representation of a hospital, some videos of actual cases of patients, and authentic learning activities intended to enhance health competencies during the pilgrimage. An examination of the courseware was conducted so as to study the manner in which the elements of the courseware are applied in real-time learn

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
A Smishing Detection Method Based on SMS Contents Analysis and URL Inspection Using Google Engine and VirusTotal
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    Smishing is the delivery of phishing content to mobile users via a short message service (SMS). SMS allows cybercriminals to reach out to mobile end users in a new way, attempting to deliver phishing messages, mobile malware, and online scams that appear to be from a trusted brand. This paper proposes a new method for detecting smishing by combining two detection methods. The first method is uniform resource locators (URL) analysis, which employs a novel combination of the Google engine and VirusTotal. The second method involves examining SMS content to extract efficient features and classify messages as ham or smishing based on keywords contained within them using four well-known classifiers: support vector machine (SVM), random

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Intelligent System for Multi-Layer Lip Reading Based Microlearning
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     Intelligent systems can be used to build systems that simulate human behavior. One such system is lip reading. Hence, lip reading is considered one of the hardest problems in image analysis, and thus machine learning is used to solve this problem, which achieves remarkable results, especially when using a deep neural network, in which it dives deeply into the texture of any input. Microlearning is the new trend in E-learning. It is based on small pieces of information to make the learning process easier and more productive. In this paper, a proposed system for multi-layer lip reading is presented. The proposed system is based on micro content (letters) to achieve the lip reading process using deep learning and auto-correction mo

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid CNN-based Recommendation System
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Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
A Review on Face Detection Based on Convolution Neural Network Techniques
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     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

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