Abstract

The aim of this research is to formulate a proposed strategy for developing graduate studies at King Khalid University to support the achievement of the Kingdom's vision (2030). The research used the descriptive survey approach. The research community consisted of all graduate students at King Khalid University. The research was conducted on a random sample included (623) Male and female students, this research relied on the questionnaire as the main tool for collecting its data. The results revealed that the research sample believes that all the proposals included in this research are very important for the development of postgraduate studies at King Khalid University to support the achievement of the K

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

  In this study light elements 10B , 10Be for 10B(n,p)10Be reaction as well as proton energy from 0.987 MeV to 2.028 MeV with threshold energy (1.04MeV) are used according to the available data of reaction cross sections. The more recent cross sections data of 10Be(p,n)10B reaction is reproduced in fin steps in the specified energy range , as well as cross section (p,n) values were derived from the published data of (n,p) as a function of energy in the same fine energy steps by using the reciprocity theory of principle inverse reaction . This calculation involves only the first excited state of  10B , 10Be in the reactions 10Be(p,n)10B and  10B(n,p)10Be. 

In addition to the primary treatment, biological treatment is used to reduce inorganic and organic components in the wastewater. The separation of biomass from treated wastewater is usually important to meet the effluent disposal requirements, so the MBBR system has been one of the most important modern technologies that use plastic tankers to transport biomass with wastewater, which works in pure biofilm, at low concentrations of suspended solids. However, biological treatment has been developed using the active sludge mixing process with MBBR. Turbo4bio was established as a sustainable and cost-effective solution for wastewater treatment plants in the early 1990s and ran on minimal sludge, and is easy to maintain. This

In this paper Alx Ga1-x As:H films have been prepared by using new deposition method based on combination of flash- thermal evaporation technique. The thickness of our samples was about 300nm. The Al concentration was altered within the 0 x 40.
The results of X- ray diffraction analysis (XRD) confirmed the amorphous structure of all AlXGa1-x As:H films with x  40 and annealing temperature (Ta)<200°C. the temperature dependence of the DC conductivity GDC with various Al content has been measured for AlXGa1-x As:H films.
We have found that the thermal activation energy Ea depends of Al content and Ta, thus the value of Ea were approximately equal to half the value of optical gap.

Background: The skull base and the hard palate contain many anatomical features that make them rich in information which are useful in sex differentiation; in addition to that they have the ability to resist the hardest environmental conditions that support them in making sex differentiation. Three dimensional computed tomographic techniques has important role in differentiation between sex since it offers images with very accurate data and details of all anatomical structures with high resolution. This study was made to study sex variations among Iraqi sample by craniometric linear measurements of the hard palate and the skull base using 3D reconstructed Computed Tomographic scan. Materials and methods: This study composed of 100 Iraqi su

The research aims to derive the efficient industrial plans for Al – shaheed public company under risk by using Target MOTAD as a linear alternative  model for the quadratic programming models.

The results showed that there had been a sort of (trade- off) between risk and the expected gross margins. And if the studied company strives to get high gross margin, it should tolerate risk and vice versa. So the management  of Al- Shaheed Company to be invited to apply the suitable procedures in the production process, in order to get efficient plans that improves it's  performance .

The two-neutron halo-nuclei (¹⁷B, ¹¹Li, ⁸He) was investigated using a two-body nucleon density distribution (2BNDD) with two frequency shell model (TFSM). The structure of valence two-neutron of ¹⁷B  nucleus in a pure (1d_5/2) state and in a pure (1p_1/2) state for  ¹¹L and ⁸He nuclei. For our tested nucleus, an efficient (2BNDD's) operator for point nucleon system folded with two-body correlation operator's functions was used to investigate nuclear matter density distributions, root-mean square (rms) radii, and elastic electron scattering form factors. In the nucleon-nucleon forces the correlation took account of

Newly 4-amino-1,2,4-triazole-3-thione ring 2 was formed at position six of 2-methylphenol from the reaction of 6-(5-thio1,3,4-oxadiazol-2-yl)-2-methylphenol 1 with hydrazine hydrochloride in the presence of anhydrase sodium acetate. Seven newly fused heterocyclic compounds were synthesized from compound 2. First fused heterocyclic was 6-(6-(3,5-di-tertbutyl-4-hydroxyphenyl)-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazol-3-yl)-2-methylphenol 3 synthesized from reaction compound 2 with 3,5-di-tert-butyl-4-hydroxybenzoic acid in POCl3. Reaction compound 2 with bromophencylbromide afford 6-(6-(4-bromophenyl)-5H-[1,2,4]triazolo[3,4-b][1,3,4]-thiadiazin-3-yl)-2-methylphenol 4. 6-(6-thio-1,7a-dihydro-[1,2,4] triazolo[3,4-b][1,3,4]-thiadiazol-3-yl)-2