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FINITE ELEMENT ANALYSIS OF HUMAN AND ARTIFICIAL ARTICULAR CARTILAGE
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Joint diseases, such as osteoarthritis, induce pain and loss of mobility to millions of people around the world. Current clinical methods for the diagnosis of osteoarthritis include X-ray, magnetic resonance imaging, and arthroscopy. These methods may be insensitive to the earliest signs of osteoarthritis. This study investigates a new procedure that was developed and validated numerically for use in the evaluation of cartilage quality. This finite element model of the human articular cartilage could be helpful in providing insight into mechanisms of injury, effects of treatment, and the role of mechanical factors in degenerative
conditions, this three-dimensional finite element model is a useful tool for understanding of the stress distributions within articular cartilage in response to external loads and investigating both the prevention of injury and the pathological degeneration of the joints.
In this study, 21 models were analysed by using ANSYS workbench v12.1: four normal articular cartilage models (distal femur, patella, medial and lateral tibia). A redesign to the distal femur model was done to get osteoarthritis articular cartilage (simple and deep) seven models by making partial cut without affecting the subchondral bone, and full cut with part of the subchondral bone in different diameters. Finally a treatment done by replacing the defective parts with artificial articular cartilages with different types of treatment. The finite element analysis studied depending on a Von Mises criteria and total deformation in different activities. The results shows that Autologous Chondrocyte Implementation is the best treatment way and it is close by 87.50% to normal cartilage. This procedure can be used as a diagnostic procedure for osteoarthritic patients and to choose the best treatment options.

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Publication Date
Thu Mar 30 2006
Journal Name
College Of Islamic Sciences
The Islamic call for the unity of human society and the rejection of division
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الحمد الله أولا واخرا وبعد .. إن الواقع الذي عايشه الناس في ظل دولة المسلمين منذ إقامة دولة الإسلام بعد بعثة الرسول الكريم (صلى الله عليه وسلم ) في المدينة ولأكثر من أربعة عشر قرنا نرى إنه عاش في كنف هذه الدولة الكبيرة من بلاد الصين شرقا وإلى وسط أوربا وجنوب فرنسا غربا العشرات من الملل و الأديان والأجناس وممن لا يدينون بالإسلام وهم كما تحفظ لهم دولة الإسلام منهم وعيشهم الرغيد فهم يمارسون شعائرهم وطقوسهم الديني

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare between result of analysis of variance after and before use analysis covariance to Split-blocks design
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This research aims to study the important of the effect of analysis of covariance manner for one of important of design for multifactor experiments, which called split-blocks experiments design (SBED) to deal the problem of extended measurements for a covariate variable or independent variable (X) with data of response variable or dependent variable Y in agricultural experiments that contribute to mislead the result when analyze data of Y only. Although analysis of covariance with discussed in experiments with common deign, but it is not found information that it is discussed with split-Blocks experiments design (SBED) to get rid of the impact a covariance variable. As part application actual field experiment conducted, begun at

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Publication Date
Wed Jun 28 2023
Journal Name
Al–bahith Al–a'alami
The Future of Television Work in the Light of Artificial Intelligence Challenges an Exploratory Study
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This research examines the future of television work in light of the challenges posed by artificial intelligence (AI). The study aims to explore the impact of AI on the form and content of television messages and identify areas where AI can be employed in television production. This study adopts a future-oriented exploratory approach, utilizing survey methodology. As the research focuses on foresight, the researcher gathers the opinions of AI experts and media specialists through in-depth interviews to obtain data and insights. The researcher selected 30 experts, with 15 experts in AI and 15 experts in media. The study reveals several findings, including the potential use of machine learning, deep learning, and na

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Publication Date
Wed Apr 03 2024
Journal Name
International Journal Of Economics And Finance Studies
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON ACCOUNTING PERFORMANCE: SUSTAINABLE DEVELOPMENT AS A MEDIATING VARIABLE
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The UN plans to achieve several development objectives by 2030. These objectives address global warming, a major issue. This method aims to improve sustainable accounting performance (AP). In this circumstance, AI is being applied in various fields, notably in economic, social, and environmental (ESE) domains. This research investigates how sustainable development (SD) influences AI methodologies and AP improvement. The research examined a sample of Iraqi banks listed on the Iraq Stock Exchange from 2014 to 2022. AI was measured by ATM and POS prevalence. A three-dimensional approach examined economic, social, and environmental (ESE) sustainability. Meanwhile, the performance of sustainable accounting was measured through the return on asse

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Scopus
Publication Date
Sat May 09 2015
Journal Name
International Journal Of Innovations In Scientific Engineering
USING ARTIFICIAL NEURAL NETWORK TECHNIQUE FOR THE ESTIMATION OF CD CONCENTRATION IN CONTAMINATED SOILS
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The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

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Publication Date
Sun Jun 21 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluation the Incidence of Genotoxic Effects of Artificial Food Favoring Additives in Bone Marrow Cells and Spleen Cells in Mice
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Genetic material is the most important component of cells because it contains the genetic information; hence any disruption to the structure chromosome of cells could lead to very bad results. Genotoxicity use to evaluate the safety of any chemical compounds on genetic materials. Artificial food flavoring additive are chemical substances to produce specific placebo effects added to foods but impart specific flavor to it.

The present study evaluates the genotoxic effect of artificial food flavoring additive on structure of chromosomes at three different concentrations (50%, 100%and 150%) on both bone marrow cells and spleen cells in mice for fourteen successive days. It was found that artificial food flavoring addit

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Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Computer Model Application for Sorting and Grading Citrus Aurantium Using Image Processing and Artificial Neural Network
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Abstract<p>This study was conducted in College of Science \ Computer Science Department \ University of Baghdad to compare between automatic sorting and manual sorting, which is more efficient and accurate, as well as the use of artificial intelligence in automated sorting, which included artificial neural network, image processing, study of external characteristics, defects and impurities and physical characteristics; grading and sorting speed, and fruits weigh. the results shown value of impurities and defects. the highest value of the regression is 0.40 and the error-approximation algorithm has recorded the value 06-1 and weight fruits fruit recorded the highest value and was 138.20 g, Gradin</p> ... Show More
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