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The Role of Quality of Work Life in Reinforcing Core Competencies: A Descriptive and analytical research in the Ministry of Health
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يهدف البحث إلى تشخيص أوجه القصور ونقاط الضعف في تطبيق أبعاد جودة الحياة الوظيفية ومدى تأثيرها على اتجاهات وسلوكيات الموظفين، وبالتالي علاقتها بتعزيز مقدراتهم الجوهرية. وتنبع القيمة العلمية للبحث من إبراز أهمية أبعاد جودة حياة العمل في تحسين الكفاءة الإنتاجية للعاملين في القطاع العام ورفع مستوى الأداء التنظيمي. ولأن جودة الحياة العملية تلعب دوراً مهماً في تعزيز المقدرات الأساسية للموظفين في القطاع العام، فإنها يمكن أيضاً أن تكون حافزاً أو مثبطاً لأي موظف من خلال التكيف مع الظروف الاقتصادية والاجتماعية التي يعيش فيها الفرد والجهود المبذولة في عملهم. استخدم الباحثون المنهج الوصفي التحليلي من خلال اعتماد الاستبيان كأداة أساسية. تم اختيار وزارة الصحة كمجتمع للبحث من خلال مسح عينة شملت المدير العام ومساعديهم، ورؤساء الأقسام ومساعديهم، من مدراء الاقسام والشعب والوحدات. وبلغ حجم العينة 155 من قيادات وزارة الصحة، وتم استخدام البرنامج الإحصائي SPSS لتحليل البيانات. وأظهرت نتائج البحث أن هناك علاقة ارتباط وتأثير مباشر لابعاد جودة حياة العمل ومساهمتها في تعزيز المقدرات الجوهرية في الوزارة المبحوثة مما ينعكس على تحسين ادائها الوظيفي بشكل عام.   نوع البحث: ورقة بحثية

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Publication Date
Wed Dec 13 2023
Journal Name
2023 3rd International Conference On Intelligent Cybernetics Technology & Applications (icicyta)
GPT-4 versus Bard and Bing: LLMs for Fake Image Detection
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The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

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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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Publication Date
Mon Apr 03 2023
Journal Name
Karbala International Journal Of Modern Science
Performance Estimation and System Modeling for Refractive Index Structure Constant Cn2
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Publication Date
Sat Dec 01 2018
Journal Name
Fuel
Biodiesel from batch and continuous oleic acid esterification using zeolite catalysts
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Publication Date
Fri Sep 15 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Determine, Predict and Map Soil pH Level by Fiber Optic Sensor
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Abstract<p>Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal.</p> ... Show More
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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Speech Enhancement Algorithm Based on Super-Gaussian Modeling and Orthogonal Polynomials
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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Physics: Conference Series
Fusion Power Density and Radiation Losses Characteristics for Tritium Fusion Reactions
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A new data for Fusion power density has been obtained for T-3He and T-T fusion reactions, power density is a substantial term in the researches related to the fusion energy generation and ignition calculations of magnetic confined systems. In the current work, thermal nuclear reactivities, power densities of a fusion reactors and the ignition condition inquiry are achieved by using a new and accurate formula of cross section, the maximum values of fusion power density for T-3He and TT reaction are 1.1×107 W/m3 at T=700 KeV and 4.7×106 W/m3 at T=500 KeV respectively, While Zeff suggested to be 1.44 for the two reactions. Bremsstrahlung radiation has also been determined to reaching self- sustaining reactors, Bremsstrahlung values are 4.5×

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Publication Date
Tue Jun 01 2021
Journal Name
Ieee Systems Journal
Intelligent Traffic Management and Load Balance Based on Spike ISDN-IoT
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An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

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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
Tue Feb 27 2024
Journal Name
Tem Journal
Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
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Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

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