Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati

The integration of gender in urban studies is considered a goal and objective to build a society characterized by justice and equality. It further allows all its residents to enjoy the opportunities to live in a safe urban life. Based on the that, the limitations of the research and its field of interest related to the relationship between gender and urban studies have become clear. The insufficient knowledge in this regard considers gender as a concept that does not exist in itself, but rather overlaps and intersects with several concepts and studies, including urban studies. Thus, it has become necessary to adopt a descriptive methodology that helps reach a theoretical framework to explain the beginnings of such an interaction and inte

Signal denoising is directly related to sample estimation of received signals, either by estimating the equation parameters for the target reflections or the surrounding noise and clutter accompanying the data of interest. Radar signals recorded using analogue or digital devices are not immune to noise. Random or white noise with no coherency is mainly produced in the form of random electrons, and caused by heat, environment, and stray circuitry loses. These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. This paper looks

Algorithms using the second order of B -splines [B (x)] and the third order of B -splines [B,3(x)] are derived to solve 1' , 2nd and 3rd linear Fredholm integro-differential equations (F1DEs). These new procedures have all the useful properties of B -spline function and can be used comparatively greater computational ease and efficiency.The results of these algorithms are compared with the cubic spline function.Two numerical examples are given for conciliated the results of this method.

تولي المجتمعات المتقدمة اجتماعياً واقتصاديا وثقافيا وعلميا اهتماما بارزا للعنصر البشري واستثماره على أفضل صورة ممكنة لتحقيق التقدم والرفاهية لتلك المجتمعات وللأفراد على حد سواء , وتحتل تنمية الثروة العقلية واستثمارها محل الصدارة حيث يبذل اهتمام خاص للكشف عن المواهب والكفاءات المبدعة وتنميتها وتوجيهها ورعايتها علميا وتربويا ومهنيا وذلك لان العنصر البشري يعد جزءا لا يتجزأ من الثروة القومية للأمة حيث

       In this work, the fractional damped Burger's equation (FDBE) formula    = 0,