The shortage of irrigation water requires specific measures. One of these measures is the application of the rationing system (a period of irrigation followed by a period of drought). This system could have an effect on the behavior and properties of irrigation canals. So, studying rationing system on the irrigation canals is important both in civil engineering and water resources engineering, especially if these channels constructed with gypsum soil. This study includes the calculation of seepage velocity and water content in each cycle (10 days wetting and 10 days of drying). The model is built for this research contains four samples, two samples for untreated soil one of them exposed to a rationing system while the other two samples mixed with 10% cement also one of them exposed to rationing system. The paper reveals that the seepage velocity decreases about 90% when using cement as a treatment material. The seepage velocity and water content value changes with cycles of rationing, where the seepage velocity relatively increases and stabilizes in the case of untreated soil. In the case of the treatment soil, the seepage velocity is very little and reduces with each cycle of rationing. In the absence of a rationing system, the results are completely reversed.
In this paper, we present multiple bit error correction coding scheme based on extended Hamming product code combined with type II HARQ using shared resources for on chip interconnect. The shared resources reduce the hardware complexity of the encoder and decoder compared to the existing three stages iterative decoding method for on chip interconnects. The proposed method of decoding achieves 20% and 28% reduction in area and power consumption respectively, with only small increase in decoder delay compared to the existing three stage iterative decoding scheme for multiple bit error correction. The proposed code also achieves excellent improvement in residual flit error rate and up to 58% of total power consumption compared to the other err
... Show MoreHuman detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty
... Show MoreObjective: The study aims to determine the effectiveness of the continuing nursing education
program on nursing staffs knowledge in kidney transplantation unit and to find out the relationship
between nursing staffs knowledge and demographic characteristics (age, gender, education level, and
years of experiences in kidney transplantation unit).
Methodology: A quasiexperemental design (One-group Pretest - Posttest design) was carried out in
kidney transplantation units at Baghdad Teaching Hospitals, from December 2011 to July 2012. A nonprobability
(purposive sample) of (16) nurses were selected from kidney transplant units at Baghdad
teaching hospitals, the choice was based on the study criteria. The data were collec
Objective: to identify the effect of the Instruction program on the knowledge of pregnant women who suffering anemia.
Methodology: A quasi-experimental design was carried out with the application of pre- post test for the study and the control group. Purposive sample, consists of (60) pregnant women diagnosed with anemia attending four health care centers in Baquba city.
Result: The findings indicate that the level of hemoglobin is increasing post instructional program among women in the study group, in which (46.7%) of women are reveal a level of (8.1-9) g/dl that is less than normal pre instructional program and the level is increased to normal level post instructional
... Show MoreThis work aimed to investigate the effect of Diode laser 805 nm on plasmid DNA and RNA
contents of some Gram negative bacteria represented by Escherichia coli and Proteus mirabilis isolates
.Plasmid extraction was done using two methods (Salting out and CTAB method).Different powers and
pulse repetition rates for 805 nm Diode Laser were used to study this effect. Results revealed that the
plasmid profile of the two species were highly affected using (2, 3) W at different frequencies including
5and 10 kHz as compared with 1 kHz while plasmids were gradually disappeared at 1W, 10 kHz. In the
same time the shining of RNA was also decreased gradually then disappeared with increasing powers
especially at 2W and 10 kHz cau
This study investigates the impact of nonsurgical periodontal treatment (NSPT) on oral health-related quality of life (OHRQoL) in patients with periodontitis stages (S)2 and S3, and the factors associated with the prediction of patient-reported outcomes. Periodontitis patients (n = 68) with moderately deep periodontal pockets were recruited. Responses to the Oral Health Impact Profile (OHIP)-14 questionnaire and clinical parameters including plaque index, bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment loss (CAL) were recorded. All patients received supra- and subgingival professional mechanical plaque removal. All clinical parameters and questionnaire responses were recorded again 3 months after NSPT.
... Show MoreThe objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.
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