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jcopolicy-636
The Impact of Putinism on the Russian-Ukrainian Conflict: an analysis of the contents of the speeches of Russian President Vladimir Putin on the causes of the Russian war on Ukraine in 2022
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this research seeks to shed light on the study of the impact of Putinism on the Russian-Ukrainian war that broke out in early 2022, by studying the contents of the speeches of Russian President Vladimir Putin before the start of the war. This research uses the structural approach in analyzing the components of the Russian political regime. The research tools used in this research include case studies, content analysis of Russian speeches, and personal meetings of researchers and specialists in Russian affairs. It sums up a number of important conclusions, most notably are : 1) Putinism is a totalitarian regime that includes the political doctrine during the era of Russian President Vladimir Putin. 2) Duginism represents the totality of the beliefs of the Russian thinker Alexander Dugin, including the Fourth political theory and Eurasianism, was part of the Putinism and not vice versa. 3) Putinism plays a major role in the outbreak of the Russian war on Ukraine at the ideological level and political decision-making within the Russian elite. 4) Putinism is developed in three Main stages: the first stage includes arranging the Russian house from the inside, while the second stage is balance, and international partnership, whereas the third stage is the quest to end unipolarity and establish a multipolar world through the preemptive strike represented by the Russian war on Ukraine in February 2022. A stage is still in the process of formation

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Publication Date
Tue Jul 01 2014
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Serum Leptin levels in ovarian polycystic disease and its correlation to body weight
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Background: Poly cystic ovary syndrome is a common disorder in women of reproductive age, it is associated with disturbance of reproductive, endocrine and metabolic functions. The pathophysiology of PCOS appears to be multifactorial and polygenic. Leptin seems to play an important role in pathophysiology of PCOS especially in women with BMI ≥25kg/m2. Objectives: To assess leptin level in both PCOS and healthy women and explore the relation to their body weight and body mass index. Patient and Methods: A total of 120 women were enrolled in this study, 60 women (50%) had PCOS (study group) and the reminder 60 women (50%) were healthy women and considered as control group. BMI was calculated first. Both groups were further sub

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Publication Date
Tue Jul 01 2025
Journal Name
South African Journal Of Chemical Engineering
Expired azithromycin and cephalexin as corrosion inhibitors for aluminum in saline-acidic solution
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Publication Date
Wed Nov 28 2018
Journal Name
Iraqi Journal Of Science
pvl-carried methicillin resistant Staphylococcus aureus isolated from hospitalized patients in Baghdad, Iraq
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Out of 150 different specimens, 67 S. aureus isolate were isolated. However, 16sRNA gene was located only in 60 isolates. Moreover, mecA gene was located in 48 isolates; thereby MRSA covered 80% of all S. aureus isolates. Of considerable interest, pvl gene was detected in only six isolates (10%). Hence, the present work emphasizes the notion suggested that pvl is not an indicative of CA-MRSA.

Publication Date
Sun Jan 01 2017
Journal Name
Lecture Notes In Computer Science
Constrained Differential Evolution for Cost and Energy Efficiency Optimization in 5G Wireless Networks
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The majority of real-world problems involve not only finding the optimal solution, but also this solution must satisfy one or more constraints. Differential evolution (DE) algorithm with constraints handling has been proposed to solve one of the most fundamental problems in cellular network design. This proposed method has been applied to solve the radio network planning (RNP) in the forthcoming 5G Long Term Evolution (5G LTE) wireless cellular network, that satisfies both deployment cost and energy savings by reducing the number of deployed micro base stations (BSs) in an area of interest. Practically, this has been implemented using constrained strategy that must guarantee good coverage for the users as well. Three differential evolution

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Publication Date
Sun Jan 01 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Fabrication and Characterization CdO: In/Si Photovoltaic Solar Cell Prepard By Thermal Evaporation
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Publication Date
Tue Dec 20 2022
Journal Name
2022 4th International Conference On Current Research In Engineering And Science Applications (iccresa)
Noise Detection and Removing in Heart Sound Signals via Nuclear Norm Minimization Problems
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Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Thu Jan 20 2022
Journal Name
Webology
Information Sources and their Role in E-learning from Iraqi College Students’ Viewpoint
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The study aims at identifying the sources of information and explaining their role in e-learning from the viewpoint of the Iraqi college students. The researchers relied on the descriptive method of the survey method to collect data and know the point of view of undergraduate students from the Department of Information in the College of Arts / Tikrit University and the Department of Quranic Studies at the College of Arts / University of Baghdad. The questionnaire was used as an instrument of the study, the research sample is (120) students; each section has (60) male and female students. The study concluded that there are many types and forms of information sources that students receive through electronic educational platforms from text con

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Publication Date
Tue Dec 30 2008
Journal Name
Al-kindy College Medical Journal
Left Ventricular Hypertrophy in Diabetic Patients and Its Relation to Other Diabetic Complications
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Background: left ventricular hypertrophy is independent risk factor for cardiovascular morbidity and mortality. The presence of diabetic complications such as autonomic neuropathy and retinopathy may predict cardiac structural changes in diabetic patients. Objective: To explore the chance of occurrence of left ventricular hypertrophy in diabetic patients and whether it is related to the presence of other diabetic complications. Methods: ninty seven (97) normotensive diabetic patients (57) type II with mean duration of diabetes of (12±6 y) and forty (40) type I with mean duration of (8±6 y) were studied by echocardiography and compared with 41 patients as control. Results: The LVMI was significantly higher in type II diabetics compared

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Publication Date
Mon May 15 2017
Journal Name
Journal Of Theoretical And Applied Information Technology
Anomaly detection in text data that represented as a graph using dbscan algorithm
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Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

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