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jcopolicy-680
The Future of the Russian- Ukrainian War and the Extent of its Reflection on the Security of Eastern European Countries after 2022
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Wars represent one of the most serious threats to the world order; It is considered a violation of international laws and norms, and humanitarian principles. From this point comes the study of the importance of the topic entitled (The Future of the Russian-Ukrainian war and the extent of its Reflection on the security of Eastern European countries after the year 2022). This study is based on reviewing future possibilities (scenarios) of war. The Russian-Ukrainian war, which was launched by the Russian government led by Russian President Vladimir Putin in February 2022, is still ongoing at the time of writing this research. This chapter includes three possibilities (scenarios). The first possibility deals with the development of the war to dangerous levels, and this possibility is unlikely. Because both sides of the conflict (the West and Russia) possess nuclear deterrence. While the second possibility deals with the continuation of the war, this is also unlikely because history has proven that every war has an end, even if it is somewhat long, but it will inevitably end. The third possibility deals with a solution to end the war, which is likely and is expected to satisfy Russia because Russia will not accept withdrawal without compensation or keeping the areas controlled by Russia and to which they are annexed. These are the expected possibilities (scenarios) in the Russian-Ukrainian war.

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Publication Date
Wed Dec 11 2019
Journal Name
Journal Of The College Of Education For Women
Terrorism and Internal Displacement in Iraq: A Field Study in Baghdad
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    Terrorism is a serious problem for many societies today. This research aims to identify the impact of terrorism and displacement crisis on human security, which was a shock to the Iraqi society in terms of its impact on the psychological, social and economic conditions of the individual, family, and society. The variety of methods of carrying out the terrorist operations that resulted from the phenomenon of human displacement witnessed by Iraq since the middle of 2014. This phenomenon has its demographic, political and social dimensions.

    In order to achieve the goal of this study and the importance of the subject, the social survey method was used by selecting a sample of 200 IDPs in a compou

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Publication Date
Fri Oct 28 2022
Journal Name
Surgical Neurology International
Extracranial carotid localized fibromuscular dysplasia: A case report and literature review
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Background:

Fibromuscular dysplasia (FMD) is a noninflammatory and nonatherosclerotic arteriopathy that is characterized by irregular cellular proliferation and deformed construction of the arterial wall that causes segmentation, constriction, or aneurysm in the intermediate-sized arteries. The incidence of FMD is 0.42–3.4%, and the unilateral occurrence is even rarer. Herein, we report a rare case of a localized extracranial carotid unilateral FMD associated with recurrent transient ischemic attacks (TIAs) treated by extracranial-intracranial bypass for indirect revascularization. The specific localization of the disease rendered our case unique.

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Fri Oct 03 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced TEA Algorithm Performance using Affine Transformation and Chaotic Arnold Map
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In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

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Publication Date
Thu Jun 30 2011
Journal Name
Kufa Journal For Veterinary Medical Sciences
Bacterial isolation from burn wound infections and studying their antimicrobial susceptibility
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The present study was carried out to determine the bacterial isolates and study their antimicrobial susceptibility in case of burned wound infections. 70 burn wound swabs were taken from patients, who presented invasive burn wound infection from both sex and average age of 3-58 years, admitted to teaching medical Al- Kendi hospital from October 2007 to June 2008. Pseudomonas aeruginosa was found to be the most common isolate (48.9%) followed by Staphylococcus aureus (24.4%), Citrobacter braakii (13.3%), Enterobacter spp. (11.1%), Coagulase-negative Staphylococci (11.1%), Proteus vulgaris (6.66%), Corynebacterium spp. (6.66%), Micrococcus (6.66%), Proteus mirabilis (4.44%), Enterococcus faecalis (4.44%), E.coli (4.44%), Klebsiella spp. (2.22

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Publication Date
Wed Apr 10 2019
Journal Name
Engineering, Technology &amp; Applied Science Research
Content Based Image Clustering Technique Using Statistical Features and Genetic Algorithm
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Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

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Publication Date
Fri Aug 01 2014
Journal Name
International Journal Of Engineering And Innovative Technology (ijeit)
New Predictive Block Matching Searching Algorithms and Hybrid Predictive Search System
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In this paper, two new simple, fast and efficient block matching algorithms are introduced, both methods begins blocks matching process from the image center block and moves across the blocks toward image boundaries. With each block, its motion vector is initialized using linear prediction that depending on the motion vectors of its neighbor blocks that are already scanned and their motion vectors are assessed. Also, a hybrid mechanism is introduced, it depends on mixing the proposed two predictive mechanisms with Exhaustive Search (ES) mechanism in order to gain matching accuracy near or similar to ES but with Search Time ST less than 80% of the ES. Also, it offers more control capability to reduce the search errors. The experimental tests

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Publication Date
Mon Mar 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Hurst Exponent and Tsallis Entropy Markers for Epileptic Detection from Children
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The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Fatigue and Tensile Characteristics for Composite Materials Used in Prosthetic Socket
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In this research, the use of natural materials like wool and cannabis as intermediate reinforcement for prosthetic limbs due to their comfort, affordability, and local availability was discussed. As part of this study on below-the-knee (BK) prosthetic sockets, two sets of samples were made using a vacuum method. These sets were made of natural fiber-reinforced polymer composites with lamination 80:20: group (Y) had 4 perlon, 1 wool 4 perlon, and group (G) had 4 perlon, 1 cannabis 4 perlon. The two groups were compared with a socket made of polypropylene. Tensile testing was used to determine the mechanical characteristics of the socket materials. The Y group has a yield stress of 17 MPs, an ultimate strength of 18.75 MPa, and an elastic

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Regression shrinkage and selection variables via an adaptive elastic net model
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Abstract<p>In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in </p> ... Show More
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