The sintering behavior of Alumina was investigated by adding TiO2. The addition of TiO2 lowered the sintering temperature of the Alumina compared with those of pure Alumina. The result suggests that TiO2 acts as an activator for sintering of Alumina. Water absorption, apparent porosity and density were examined for both pure and TiO2 added to Alumina samples. The variations of sintering behavior were discussed in terms of shrinkage, porosity, water absorption and density. Thermal shock resistance was also examined. In term of this work, the way of improving the thermal shock resistance in oxide- based materials by adding reactive Titania powder to the Alumina samples. The laboratory results showed an improvement in thermal shock resistance

   In the oil industry, the processing of vacuum residue has an important economic and environmental benefit. This work aims to produce industrial petroleum coke with light fuel fractions (gasoline, kerosene , gas oil) as the main product and de asphalted oil (DAO) as a side production from treatment secondary product matter of vacuum residue. Vacuum residue was produced from the bottom of vacuum distillation unit of the crude oil. Experimentally, the study investigated the effect of the thermal conversion process on (vacuum residue) as a raw material at temperature reaches to 500 °C, pressure 20 atm. and residence time for about 3 hours. The first step of this treatment is constructing a carbon steel batch re

The structural behavior of Segmental Precast Post-tensioned Reinforced Concrete (SPPRC) beams largely depends on the behavior of the joints that connect between the segments. In this research, series of static tests were carried out to investigate the behavior of full-scale SPPRC beams with different types of epoxy-glued joint configurations; multi-key joint, single key, and plain key joint. The reference specimen was monolithically casted beam and the other specimens were segmental beams with five segments for each one. The general theme from the experimental results reflects an approximate similarity in the behavior of the four beams with slight differences. Due to the high tensile strength of the used epoxy in comparison to concr

Vacuum evaporation technique was used to prepare pure and doped ZnS:Pb thin films at10% atomic weight of Pb element onto glass substrates at room temperature for 200 nm thickness. Effect of doping on a.c electrical properties such as, a.c conductivity, real, and imaginary parts of dielectric constant within frequency range (10 KHz - 10 MHz) are measured. The frequency dependence of a.c conductivity is matched with correlated barrier hoping especially at higher frequency. Effect of doping on behavior of a.c mechanism within temperature range 298-473 K was studied.

In this study, an analysis of re-using the JPEG lossy algorithm on the quality of satellite imagery is presented. The standard JPEG compression algorithm is adopted and applied using Irfan view program, the rang of JPEG quality that used is 50-100.Depending on the calculated satellite image quality variation, the maximum number of the re-use of the JPEG lossy algorithm adopted in this study is 50 times. The image quality degradation to the JPEG quality factor and the number of re-use of the JPEG algorithm to store the satellite image is analyzed.

Copper Telluride Thin films of thickness 700nm and 900nm, prepared thin films using thermal evaporation on cleaned Si substrates kept at 300K under the vacuum about (4x10-5 ) mbar. The XRD analysis and (AFM) measurements use to study structure properties. The sensitivity (S) of the fabricated sensors to NO2 and H2 was measured at room temperature. The experimental relationship between S and thickness of the sensitive film was investigated, and higher S values were recorded for thicker sensors. Results showed that the best sensitivity was attributed to the Cu2Te film of 900 nm thickness at the H2 gas.

An experiment was conducted in pots under field conditions during fall seasons of 2017 and 2018. This study aimed to improve a weak growth of seedlings under salt stress in sorghum. Three factors were studied. 1st factor was three cultivars (Inqath, Rabeh, and Buhoth70). 2nd factor was seed priming (primed and unprimed seed). Seed were primed by soaking for 12 hours in a solution containing 300 + 70 mg L−1 of gibberellic (GA3) and salicylic (SA) acids, respectively. 3rd factor was irrigation with saline water (6, 9 and 12 dS m−1) resulting from dissolving sodium chloride in distilled water in addition to control treatment (distilled water). Randomized complete block design was used with four replications. In both seasons: the results sh

The residual limb within the prosthesis, is often subjected to tensile or fatigue stress with varying temperatures. The fatigue stress and temperatures difference which faced by amputee during his daily activities will produces an environmental media for growth of fungi and bacteria in addition to the damage that occurs in the prosthesis which minimizingthe life of the prosthetic limb and causing disconfirm feeling for the amputee.

In this paper, a mechanical and thermal properties of composite materials prosthetic socket made of different lamination for perlon/fiber glass/perlon, are calculated by using tesile test device under varying temperatures ( from 20oC to 60oC), also in this paper a device for measuring rotational bendin

FG Mohammed, HM Al-Dabbas, Science International, 2018 - Cited by 2

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye