A new nano-sized NiMo/TiO2-γ-Al2O3 was prepared as a Hydrodesulphurization catalyst for Iraqi gas oil with sulfur content of 8980 ppm, supplied from Al-Dura Refinery. Sol-gel method was used to prepare TiO2- γ-Al2O3 nano catalyst support with 64% TiO2, 32% Al2O3, Ni-Mo/TiO-γ-Al2O3 catalyst was prepared under vacuum impregnation conditions to loading metals with percentage 3.8 wt.% and 14 wt.% for nickel and molybdenum respectively while the percentage for alumina, and titanium became 21.7, and 58.61 respectively. The synthesized TiO2- γ-Al2O3 nanocomposites and Ni-Mo /TiO2- γ-Al2O3 Nano catalyst were then characterized by XRD, AFM, and BET surface area, SEM, XRF, and FTIR. The performance of the synthesized catalyst for removing sulfur compounds was conducted through the pilot HDS laboratory unit, various temperatures range 275oC to 375°C, LHSV 1 h-1 were studied; moreover, the effect of LHSV 1 to 4 h-1 on the percentage of sulfur removal was also studied at the temperature of the best removal with constant pressure 35 bar and H2/HC ratio 200cm3/200cm3. The sulfur content results generally revealed that there was a substantial decrease at all operating conditions used, while the maximum sulfur removal was 87.75% in gas oil on Ni-Mo/TiO2-γ-Al2O3 catalyst at temperature 375˚C and LHSV 1h-1.
Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach
Abstract
In this research we study the wavelet characteristics for the important time series known as Sunspot, on the aim of verifying the periodogram that other researchers had reached by the spectral transform, and noticing the variation in the period length on one side and the shifting on another.
A continuous wavelet analysis is done for this series and the periodogram in it is marked primarily. for more accuracy, the series is partitioned to its the approximate and the details components to five levels, filtering these components by using fixed threshold on one time and independent threshold on another, finding the noise series which represents the difference between
... Show MoreResearch was: 1- known as self-efficacy when students perceived the university. 2- know the significance of statistical differences in perceived self-efficacy according to gender and specialty. Formed the research sample of (300) students were chosen from the original research community by way of random (150) male specialization and scientific and humanitarian (150) females specialized scientific and humanitarian. The search tool to prepare the yard tool to measure perceived self-efficacy based on measurements and previous literature on the subject of perceived self-efficacy. The researcher using a number of means, statistical, including test Altaúa and analysis of variance of bilateral and results showed the enjoyment of the research s
... Show MoreThe use of deep learning.
Construction of photographed bullying scale of kindergarteners was the aim of this study. The study conducted to answer the raised question, could the bullying among kindergarteners be measured?. A total of (200) boy and girl were selected from city of Baghdad to be the sample of the study. The scale composed of (27) item with colored pictures. It takes about (15) minuets to answer the whole scale items. SPSS tools were used to process the collected data. The result showed that the bullying among kindergarteners could be measured.
Autonomous motion planning is important area of robotics research. This type of planning relieves human operator from tedious job of motion planning. This reduces the possibility of human error and increase efficiency of whole process.
This research presents a new algorithm to plan path for autonomous mobile robot based on image processing techniques by using wireless camera that provides the desired image for the unknown environment . The proposed algorithm is applied on this image to obtain a optimal path for the robot. It is based on the observation and analysis of the obstacles that lying in the straight path between the start and the goal point by detecting these obstacles, analyzing and studying their shapes, positions and
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