دور مؤسسات التعليم العالي في تعزيز قيم المواطنة في المجتمع العراقي

    Sought Current search to know the concepts of modern literature theoretical educational, psychological and social are thinking double and tolerance and the definition of them in the theoretical frameworks of religious, social and psychological to clarify their role in life in general and in university life private and to understand their respective roles in the promotion of the other, and research has included a chapter first to identify the importance and the objectives and terms Search in detail, and a chapter of a second frameworks and theoretical literature of concepts ranging from religious heritage in Islam and other religions, especially the concept of tolerance, then look at social, psy

أصبحت التنشئة الاجتماعية السليمة من أكثر الأدوات في التصدي لأوبئـة العنف والتطرف ومظاهرها المتفشية بصورة أو بأخرى في مجتمعاتنـا المعاصـرة عامـة باختلاف أيديولوجياته الفكرية ومعتقداته الدينيـة ومسـتوى نموهـا الاقتصـادي، وأصبحت بأشكالها المتنوعة معنية بترسيخ التعاليم الدينيـة السـمحة وغـرس القـيم الديمقراطية السليمة ومبادئ وقيم حقوق الإنسان في شتى مجالات الحياة الإنسانية، وهي أيضا تعد حجر الأساس من اج

أصبحت التنشئة الاجتماعية السليمة من أكثر الأدوات في التصدي لأوبئـة العنف والتطرف ومظاهرها المتفشية بصورة أو بأخرى في مجتمعاتنـا المعاصـرة عامـة باختلاف أيديولوجياته الفكرية ومعتقداته الدينيـة ومسـتوى نموهـا الاقتصـادي، وأصبحت بأشكالها المتنوعة معنية بترسيخ التعاليم الدينيـة السـمحة وغـرس القـيم الديمقراطية السليمة ومبادئ وقيم حقوق الإنسان في شتى مجالات الحياة الإنسانية، وهي أيضا تعد حجر الأساس من اج

Static Synchronous Series Compensator (SSSC) is a well known device for effectively regulating the active power flow in a power system. In this paper, the SSSC linearized power flow equations are incorporated into Newton-Raphson algorithm in a MATLAB written program to investigate the control of active poweer flow and the transient stability of a five bus and a thirty bus IEEE test systems, during abnormal conduction (three phase fault near buses). A comparison of the results obtained for the base case without SSSC and with it to investigate the effectiveness of the device on both of the active power flow and the transient stability.

The research aims to know the concept of politic behavior as one of the important behaviours in the different fields and sectors. It is considered to be part of the organizatial work to face the expected  risks. It includes two group of factors personal (self –monitors, locus of control ,expectation s of success, perceived job alternatives)and organizational(promotion ,division resources,role  ambiguity ,democratic decision)studied by the researcher  in the frame of the relationship with the variable  of display  continuous trust matain which includes two variable (build trust mantain, display  trust continuouness)through applied frame by random sample consists of (90)employee  at Farouq State

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti