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Composition effects on formation energies, electronic and vibrational properties of ZnCdS wurtzoid molecules: A DFT study
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
The Effect of Speaking Strategies on Iraqi EFL College Students
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The present study deals with the effect of teaching speaking Strategies (SS) on
EFL Iraqi College students. The use of speaking strategies not only solves learners’
communication problems, but also enhances the learner’s interaction in target language,
and improves their oral proficiency .The aim of the study is to find out the effect of
teaching SS used by EFL College students .The learner of the first stage is population of
the study at the Department of English, College of Education /Ibn-Rushd .The sample
consists of (60) students distributed on experimental group(A) as well as control
group(B) each group contains (30) students . In order to achieve the aim of the study,
questionnaire has been constructed t

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Engineering
Development of Spatial Data Infrastructure based on Free Data Integration
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In recent years, the performance of Spatial Data Infrastructures for governments and companies is a task that has gained ample attention. Different categories of geospatial data such as digital maps, coordinates, web maps, aerial and satellite images, etc., are required to realize the geospatial data components of Spatial Data Infrastructures. In general, there are two distinct types of geospatial data sources exist over the Internet: formal and informal data sources. Despite the growth of informal geospatial data sources, the integration between different free sources is not being achieved effectively. The adoption of this task can be considered the main advantage of this research. This article addresses the research question of how the

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Publication Date
Sat Jan 01 2022
Journal Name
Annals Of Parasitology
The effect of toxoplasmosis on renal function in hemodialysis patients
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Toxoplasma gondii is an obligate intracellular protozoan parasite; it spreads via the circulatory system during infection and causes chronic infection in various organs. Toxoplasmosis affects nearly one third of people worldwide, especially immunocompromised people. This study aimed to determine the effect of toxoplasmosis on renal function in hemodialysis patients. Overall 300 patients referred to the Medical City, Al-Karama General Hospital, Baghdad, Iraq were enrolled from 2021 to 2022. All serum samples were tested for T. gondii immunoglobulins (IgG and IgM) antibodies, urea and creatinine levels. In patients undergoing hemodialysis, the results revealed a high positivity percentage for anti-Toxoplasma IgG. In hemodialysis patients infe

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Publication Date
Sun Jan 13 2019
Journal Name
Iraqi Journal Of Physics
Porous Silicon effect on the performance of CdS nanoparticles photodetector
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Cadmium sulfide photodetector was fabricated. The CdS nano
powder has been prepared by a chemical method and deposited as a
thin film on both silicon and porous p- type silicon substrates by spin
coating technique. Structural, morphological, optical and electrical
properties of the prepared CdS nano powder are studied. The X-ray
analysis shows that the obtained powder is CdS with predominantly
hexagonal phase. The Hall measurements show that the nano powder
is n-type with carrier concentration of about (-5.4×1010) cm-3. The
response time of fabricated detector was measured by illuminating
the sample with visible radiation and its value was 5.25 msec. The
specific detectivity of the fabricated det

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Publication Date
Mon Jan 01 2024
Journal Name
Communications In Computer And Information Science
Automatic Identification of Ear Patterns Based on Convolutional Neural Network
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Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

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Publication Date
Mon Aug 01 2022
Journal Name
Mathematics
Face Recognition Algorithm Based on Fast Computation of Orthogonal Moments
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Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Influence of Nanofluid Flooding on Oil Displacement in Porous Media
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Hydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO2 NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil at dif

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Publication Date
Tue Mar 12 2019
Journal Name
Al-khwarizmi Engineering Journal
Optimization Drilling Parameters of Aluminum Alloy Based on Taguchi Method
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This paper focuses on the optimization of drilling parameters by utilizing “Taguchi method” to obtain the minimum surface roughness. Nine drilling experiments were performed on Al 5050 alloy using high speed steel twist drills. Three drilling parameters (feed rates, cutting speeds, and cutting tools) were used as control factors, and L9 (33) “orthogonal array” was specified for the experimental trials. Signal to Noise (S/N) Ratio and “Analysis of Variance” (ANOVA) were utilized to set the optimum control factors which minimized the surface roughness. The results were tested with the aid of statistical software package MINITAB-17. After the experimental trails, the tool diameter was found as the most important facto

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Publication Date
Fri Jul 01 2022
Journal Name
Iraqi Journal Of Science
The Solar Attraction Effect on Orbital Elements of the Moon
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In this paper, the solar attraction effect on the Moon orbital elements had been studied. The solar attraction considered a third body perturbation. The initial values of the Moon orbital elements at 2015-1-21.5 which are used (semi major axis=380963.78 km, eccentricity =0.056o, Eular angles (Ω=30°, ω=40°, , i=18.4°). The Moon in a perigee of its orbit at the initial time. A program which designed, was used to calculate the Moon position ,velocity and orbital elements through the years (2015-2035). The position and velocity components of the Moon were calculated by solving the equation of Kepler for elliptical orbit using Newton Raphson's method for (1000) periods and hundred steps of time for each period. The results show a secular

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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