أيديولوجيا العنف في الفكر الاسلامي : داعش أنموذجاً

يتفق معظم العلماء على اهمية الرأي العام في کل الازمنه والامکنة کلها، لکل ناس حکام ومحکومون افراد وجماعات فهو يشکل قوة ضغط على تلک الانظمة والحکومات وان کانت تلک القضايا لها مساس بمصالح الناس ومدى تاثيرها على الانظمة في اتخاذ القرارات من خلال الاحکام التي تصدرها الناس. والبحث هنا يتناول الرأي العام بمفهوم الحرية الممنوحة لهم وان کانت مدة الدراسة لا تتناول المفهوم بذاته ولکن يعبر عنه بمفاهيم مثل ارادة ال

In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot

يعد موضوع الثورات العربية من الموضوعات التي تحظى بأهمية كبيرة على المستويين الاقليمي والدولي، لذا فقد طورت مؤسسات الابحاث الدولية ومراكز صنع القرار السياسي والاستراتيجي الاطر والمفاهيم الجديدة في مجال السياسة الدولية، نظرا للتطورات التي شهدتها المنطقة العربية والتي استدعت التطرق الى مجموعة من المفاهيم النظرية ذات العلاقة الوثيقة بما هو حاصل في المنطقة العربية من تغييرات مما تطلب الامر البحث والتدقيق ومن

يعد موضوع الثورات العربية من الموضوعات التي تحظى بأهمية كبيرة على المستويين الاقليمي والدولي، لذا فقد طورت مؤسسات الابحاث الدولية ومراكز صنع القرار السياسي والاستراتيجي الاطر والمفاهيم الجديدة في مجال السياسة الدولية، نظرا للتطورات التي شهدتها المنطقة العربية والتي استدعت التطرق الى مجموعة من المفاهيم النظرية ذات العلاقة الوثيقة بما هو حاصل في المنطقة العربية من تغييرات مما تطلب الامر البحث والتدقيق ومن

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar