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Evaluation of D-Dimer in the diagnosis of suspected deep vein thrombosis
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Background: Deep vein thrombosis is a multi causal disease and its one of most common venous disorder, but only one quarter of the patients who have signs and symptoms of a clot in the vein actually have thrombosis and need treatment .The disease can be difficult to diagnose. Venous ultrasound in combination with clinical finding is accurate for venous thromboembolism, its costly because a large number of patients with suspicious signs and symptoms. Venography still the gold standard for venous thromboembolism but it is invasive. The D-dimer increasingly is being seen as valuable tool rolling out venous thromboembolism and sparing low risk patients for further workup.Objectives: this study has designed the role of D-dimer to confirm diagnosis of deep vein thrombosis for patients with positive Doppler and those show no features of thrombosis in Doppler using more accurate and sensitive instrument measuring the concentration of D- dimer.Methods: Thirty patients with deep vein thrombosis diagnosed by Doppler and clinical signs and symptoms (for those with negative Doppler) assessed for D- dimer by automachine cormy accent 200 based on immunoassay which more sensitive than the ordinary methods.Results: Twenty-eight patients out of thirty shows a significant elevation of D-dimer compared to control group which show no elevation in D- dimer level. On other side higher level of D- dimer found in those with negative Doppler as same as level to the patients with positive Doppler.Conclusion: Patients with clinical sign and symptoms of deep vein thrombosis and negative Doppler should be assessed for D- dimer using more sensitive technique based on immunological assay.Key words: deep vein thrombosis (DVT) pulmonary embolism (PE), Doppler

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Evaluation the Emotional Intelligence of Administrative and Audit leaderships in the Federal Board of Supreme Audit to achieve audit Effectiveness
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The Psychologists have noticed, not long ago, that the man’s success and happiness in life do not only depend on his degree and education, which express on his mental intelligence but also they need another kind of intelligence called emotional intelligence. The research aims at identifying the emotional intelligence level of the top and administrative leaderships in the Federal Board of Supreme Audit by evaluating their emotional intelligence when the administrative and audit leaderships face emotional interactions by dealing with administrative and audit stuffs in the Board. The research problem is focused on the following question “Is the emotional intelligence of the top and administrative leaderships in the Fede

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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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 Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of the proposed strategy of Maysan Oil Company for the years 2020-2024
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ناقش البحث في طياته عدداً من القضايا الرئيسة المتعلقة بالتقييم الاستراتيجي والإطار العام للخطة الاستراتيجية المقترحة لشركة نفط ميسان للسنوات الخمس المقبلة (2020_2024)، وهدف هذا البحث يتمحور في تقييم عملية صياغة استراتيجية شركة نفط ميسان لتحديد نقاط القوة وتعضيدها ومواطن الضعف ومحاولة معالجتها لتجنب الوقوع بها عند وضع استراتيجية للسنوات القادمة، وعلى هذا الاساس فان مشكلة البحث تكمن في مدى نجاح الاستراتي

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of Educational And Psychological Researches
Evaluation Tasks of Performance Quality of the University Students According to the Developmental Environment
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 Education is a process of learning and education at the same time. As the conditions of modern life necessitate every person to keep learning, education has become a necessity to meet life needs. The society today is concerned with the educational process and aims to live up the expectations. Since education is an integral part of education and its means, it has become as a mean to achieve its purposes. The educational environment was a traditional environment limited to specific inputs, possibilities and stimulus of both teacher and student. Due to the latest advancement, the educational environment has been expanded to become a rich, with strong connections. It has expanded to encompass the entire global environment. The current

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Publication Date
Wed May 29 2019
Journal Name
Journal Of Planner And Development
Evaluation the individual's share of urban land use for the holy city of Karbala
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The research aims to analyze and evaluate the urban land use according to the needs of the current and future population by adopting the planning criteria for the holy city of Karbala. In the theoretical side, we discussed the most important concepts of urban land use planning. In the practical aspect of the study, field surveys were conducted to obtain the required information. Using the GIS program, the land uses were planned and executed, Analysis By comparing the per capita use of urban land with criteria and the production of maps.

The main findings of the study are that there is a large deficit in meeting some of the needs of the urban land uses and the basic services of the city. The research recommended that the needs of

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