The calibration of a low-speed wind tunnel (LSWT) test section had been made in the present work. The tunnel was designed and constructed at the Aerodynamics Lab. in the Mechanical Engineering Department/University of Baghdad. The test section design speed is 70 m/s. Frictional loses and uniformity of the flow inside the test section had been tested and calibrated based on the British standards for flow inside ducts and conduits. Pitot-static tube, boundary layer Pitot tube were the main instruments which were used in the present work to measure the flow characteristics with emphasize on the velocity uniformity and boundary layer growth along the walls of the test section. It is found that the maximum calibrated velocity for empty test section is 55 m/s. Three speeds are tested for uniformity and walls boundary layer at inlet and mid-section of test section. The results show that the flows are uniform at inlet and mid-section with turbulent flow from inlet to outlet.
In this study, the four tests employed for non-linear dependence which is Engle (1982), McLeod &Li (1983), Tsay (1986), and Hinich & Patterson (1995). To test the null hypothesis that the time series is a serially independent and identical distribution process .The linear structure is removed from the data which is represent the sales of State Company for Electrical Industries, through a pre-whitening model, AR (p) model .From The results for tests to the data is not so clear.
Hydrogen sulfide removal catalyst was prepared chemically by precipitation of zinc bicarbonate at a controlled pH. The physical and chemical catalyst characterization properties were investigated. The catalyst was tested for its activity in adsorption of H2S using a plant that generates the H2S from naphtha hydrodesulphurization and a unit for the adsorption of H2S. The results comparison between the prepared and commercial catalysts revealed that the chemical method can be used to prepare the catalyst with a very good activity.
It has observed that the hydrogen sulfide removal over zinc oxide catalyst follows first order reaction kinetics with activation energy of 19.26 kJ/mole and enthalpy and e
... Show MoreThis investigation was conducted to recognize the structure for (RHETI version 2.5 1999) by using exploratory and confirmatory factor analysis. Sample of (620) student of Al-Mustansrya University were administered the (RHETI).
The data of their responses was analyzed by using (PAF) and oblique rotating .
The findings explored (9) factors as one factor for each type and (184) items were loaded by the factors: (60) item for feeling center, (61) items for instinctive center and (63) items for thinking center.
Results of confirmatory factorial analysis supported a model designed by the researcher depended upon a theoretical views of Riso and Hudson
... Show MoreThe hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
... Show MoreAdipose tissue releases pro- and anti-inflammatory cytokines and hormones such as irisin, visfatin, and interleukin-6, which may be linked to periodontal diseases.
Our study aimed to determine salivary irisin, visfatin, and interleukin-6 levels in gingivitis and periodontitis patients, compare them with healthy periodontal patients, and evaluate the association between these biomarkers.
The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o
... Show MoreThe first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o
... Show More