The study aims to identify the educational research obstacles as perceived by the faculty members at the universities of south in the west bank. As for study population, it included all (60) faculty-member in the colleges of education (bait lahem, alahliyah, al-khalil, and al-Quds almaftoha). To collect study data, the researcher used a questionnaire that consisted of (43) item; it has categorized into seven-domains: academic working conditions, academic management, resources and information, faculty members, publication, planning, and funding educational research. The findings revealed that Educational research obstacles were high with an average of (4, 39), no significant differences among sample averages and stander deviations on the

The study of surface hardness, wear resistance, adhesion strength, electrochemical corrosion resistance and thermal conductivity of coatings composed from sodium silicate was prepared using graphite micro-size particles and carbon nano particles as fillers respectively of concentration of (1-5%), for the purpose of covering and protecting the oil distillation towers. The results showed that the sodium silicate coating reinforced with carbon nano-powder has higher resistance to stitches, mechanical wear, adhesive and thermal conductivity than graphite/sodium silicate composite especially when the ratio 5% and 1%, the electrochemical corrosion test confirmed that the coating process of stainless steel 304 lead to increasin

         The Na-alginate bead is commonly used in biotechnology fields such as adsorption due to ion exchange between Ca and Na with elements. Scanning electron microscopy (SEM-EDX) has proven to be a comparative method in the detections of these adsorbed elements, but the un-flat forming area of beads that can introduce impossible of the detection of element adsorbed. In contrast, X-ray fluorescence (XRF) documents analysis of elements, direct examination, which may analysis the adsorbents of elements. Here, this Study evaluated the possibility by using XRF for the direct analysis for examples of Cd and Ag in a bench stand. This Study compared this to commonly use

In this study the effect of fiber volume fraction of the glass fiber on the thermal conductivity of the polymer composite material was studied. Different fiber volume fraction of glass fibers were used (3%, 6%, 9%, 12%, and 15%). Specimens were made from polyester which reinforced with glass fibers .The fibers had two arrangements according to the direction of the thermal flow. In the first arrangement the fibers were parallel to the direction of the thermal flow, while the second arrangement was perpendicular; Lee's disk method was used for testing the specimens. The experimental results proved that the values of the thermal conductivity of the specimens was higher when the fibers arranged in parallel direction than that when the fibers

Renewable energy sources - realities of the present and future options

    Many of the directories indicate that the global energy system begin with a period of transition from total dependence on fossil energy sources, particularly oil, Into a new era in which renewable energy sources play an important role in meeting the growing needs of energy demand. There are many factors that will contribute to the strengthening of this trend towards transformation, which also will decide how quickly this transformation of renewable energy systems effectively in the global system of energy demand.

   These factors, In brief: the size of environmental pollution and cl

The aim of this research is to study the factors affecting drag coefficient (C d ) in
non-Newtonian fluids which are the rheological properties ,concentrations of non-
Newtonian fluids, particle shape, size and the density difference between particle and
fluid .Also this study shows drag coefficient (C d ) and particle Reynolds' number (Re
P ) relationship and the effect of rheological properties on this relationship.
An experimental apparatus was designed and built, which consists of Perspex pipe
of length of 160 cm. and inside diameter of 7.8 cm. to calculate the settling velocity,
also electronic circuit was designed to calculate the falling time of particles through
fluid.
Two types of solid particles were

The research deals with metaphors as being one of the primary means used by Lyudmila Ulitskaya when writing the novel " Sincerely Yours Shurik ", to form diverse and multifaceted collective female images of representatives of the classic psychological patterns presented in the work. This research reflects the results of the study related to the work of Lyudmila Yevkinevna Ulitskaya, an actress of modern Russian prose. The novel "The Sincerely to You Shorek" is one of Ludmila Ulitskaya's creations (the year of writing - 2003), which, like her other works, is distinguished by a unique presentation style, rich vocabulary, lexical and semantic diversity, and a special style of writing. writer. The main objective of the research is to look at th

     The goal of this paper is to show the kinematic characteristics of gaseous stellar dynamics using scaling coefficient relationships (such as Tully-Fisher) in different spiral galaxies. We selected a sample of types of spiral morphology  (116 early, 150 intermediate, and 146 late) from previous literature work, and used statistical software (statistic-win-program) to find out the associations of multiple factors under investigation, such as the main kinematic properties of the gaseous-stellar (mass, luminosity, rotational speed, and baryons) in different types of spiral galaxies. We concluded that there is a robust positive connection between Log Vrot.max.) and Log Mstar(B-V), as well as between Log Vrot.max. and Log Mbar (

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