In this work, nanostructure aluminum oxide thin films were deposited on glass substrates using a direct current (DC) magnetic reactive sputtering (MRS) technique. A gaseous mixture of argon and oxygen at different mixing ratios was used to synthesize Al2O3 nanoparticles. After extracting Al2O3 powder from the glass substrate, X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), and energy-dispersive spectroscopy (EDS) were used to analyze the structural and morphological properties of the synthesized thin films. The effect of deposition time on the spectral properties, as well as on the size of the nanoparticles, was determined.

Semiconductor-based metal oxide gas detector of five mixed from zinc chloride Z and tin chloride S salts Z:S ratio 0, 25, 50, 75 and 100% were fabricated on glass substrate by a spray pyrolysis technique. With thickness were about 0.2 ±0.05 μm using water soluble as precursors at a glass substrate temperature 500 ºC±5, 0.05 M, and their gas sensing properties toward CH4, LPG and H2S gas at different concentration (10, 100, 1000 ppm) in air were investigated at room temperature which related with the petroleum refining industry.
Furthermore structural and morphology properties were scrutinize. Results shows that the mixing ratio affect the composition of formative oxides were (ZnO, Zn2SnO4, Zn2SnO4+ZnSnO3, ZnSnO3, SnO2) ratios ment

It has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlight

Non-prismatic reinforced concrete (RC) beams are widely used for various practical purposes, including enhancing architectural aesthetics and increasing the overall thickness in the support area above the column, which gives high assurance to services that this will not result in the distortion of construction features and can reduce heights. The hollow sections (recess) can also be used for the maintenance of large structural sections and the safe passage of utility lines of water, gas, telecommunications, electricity, etc. They are generally used in large and complex civil engineering works like bridges. This study conducted a numerical study using the commercial finite element software ANSYS version 15 for analysing RC beams, hol

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         Allopurinol derivative were prepared by reacting the (1-chloroacetyl)-2-Hydropyrazolo{3,4-d}pyrimidine-4-oneiwith 5- methoxy- 2-aminoibenzothiazoleiunder certain conditions to obtain new compound  ( N- (2-aminoacetyl (5-methoxy) benzothiazole -2yl) (A₄), Reaction of 5-(P-dimethyl amine benzene)-2-amino-1,3,4- oxadiazole in the presence of potassium carbonate anhydrous to yield new  compound (N-(2- aminoacetyl-5-(P-dimethyl amine benzene )-1,3,4-oxadiazoles-2-yl)(A₃₀) and Azo compound (N-(5-(Azo-2-hydroxy-5-amino benzene)-1,3-Diazol-2yl)Allopurinol(A₄₆). The structure of prepared compounds were confirmed by (FT-IR)

Abstract Additive manufacturing has been recently emerged as an adaptable production process that can fundamentally affect traditional manufacturing in the future. Due to its manufacturing strategy, selective laser melting (SLM) is suitable for complicated configurations. Investigating the potential effects of scanning speed and laser power on the porosity, corrosion resistance and hardness of AISI 316L stainless steel produced by SLM is the goal of this work. When compared to rolled stainless steel, the improvement is noticeable. To examine the microstructure of the samples, the optical microscopy (OM), scanning electron microscopy (SEM), and EDX have been utilized. Hardness and tensile strength were us

Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.

In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe