Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability. Trend test was performed to ensure that the developed model would follow the physical laws. Results show that the developed model outperforms the published correlations in term of absolute average percent relative error of 6.5%, and correlation coefficient of 96%.
The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in
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Human beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.
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The aim of this study was to establish the existence and interaction of TMPRSS2 – ERG gene fusion status with clinicopathological features of prostate cancer patients. This research consisted of 123 embedded formalin-fixed tissues obtained from the prostate tumor patients. The above gene fusion is detected through the technique of fluorescent in situ hybridization (FISH) by means of a triple color probe. Seven samples have not been scored due to technical difficulties and 46 patients have fusion (39.6%), while the remaining (70) have not been seen with fusion. Of the 46 fusion-positive, 17 (36%) were caused by ERG-translocation, of the other 29 (63%) were caused by the interstitial segment deletion between the two genes due to the
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Background: Coronary Artery Disease (CAD) is one of the largest causes of mortality worldwide. Clopidogrel, antiplatelet drug, has been widely used for management of CAD. The current study aimed to investigate the effect of clopidogrel on the oxidative stress in CAD patients. Methods: One hundred CAD patients, who were followed-up for 5 days after receiving clopidogrel, and 50 healthy volunteers were included in this study. Parameters include catalase (CAT), total antioxidant capacity (TAC), total oxidant capacity (TOC), total protein, albumin, and globulins were determined before and after treatment with clopidogrel. Results: CAT, TAC, and Tp were significantly decreased (P<0.0001) in CAD patients compared to healthy control and
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The synchronization of a complex network with optoelectronic feedback has been introduced theoretically, with use of 2×2 oscillators network; each oscillator considered is an optocoupler (LED coupled with photo-detector). Fixing the bias current (δ) and increasing the feedback strength (Ԑ) of each oscillator, the dynamical sequence like chaotic and periodic mixed mode oscillations has been observed. Synchronization of unidirectionally coupled of light emitting diodes network has been featured when coupling strength equal to 1.7×10-4. The transition between non-synchronization and synchronization states by means of the spatio-temporal distribution has been investigated.