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Awadalla M.,SQU | Al Khazraji A.,CCE | Al Delimi K.,Nahrain University
International Journal of Control Theory and Applications | Year: 2015

This paper surveys the background literature relevant to the work presented on co-operating mobile robots which was examined from different perspectives. First, it was surveyed with a focus on the classification of co-operating mobile robots. Second, the focus shifted to the collective behaviour of social insects and the connection of the functioning principles of social insect colonies with the design principles of artificial systems. Third, the literature was reviewed related to the action selection problem (ASP) and behaviour coordination. Fourth, previous work on robot awareness and its effect on the performance of co-operating mobile robots was examined. © International Science Press.


Morvan M.,Rhodia | Degre G.,Rhodia | Beaumont J.,Rhodia | Dupuis G.,Poweltec | And 4 more authors.
SPE - DOE Improved Oil Recovery Symposium Proceedings | Year: 2012

Recent publications indicate injection of polymer solutions at concentration larger than conventional polymer flooding can result in higher recovery at field scale. Typically more than 20% OOIP compare to waterflooding have been reported (Wang et al; 2011). However injectivity issues have to be considered when injecting such concentrated polymer solutions. This work describes an alternative approach based on surfactant-based fluids. The technology we have developed matches the rheological properties of polymer solutions in a broad range of reservoir conditions (temperature & salinity) without any injectivity limitation even when considering very viscous surfactant solutions (ie up to 1000 cps) and low permeability cores. Average first normal stress difference measurements have been used to compare the elastic properties of surfactant and high molecular weight polymer solutions. The degree of non linearity in the mechanical properties for both fluids has been expressed by Weissenberg number. The surfactant solution has much larger Weissenberg number than the polymer solution at a shear rate corresponding to the fluid propagation in the reservoir. The potential of this surfactant-based technology is illustrated through a specific reservoir case involving heavy oil. A series of core-flood experiments has been performed in reservoir cores. The surfactant slug can be combined with a conventional low-concentration polymer flooding to further improve the process. Reduction in residual oil saturation in the range of ΔSw = 10-15%o has been obtained. Complementary simulation study giving rise to economic analysis have been performed.


Awadalla M.,SQU | Awadalla M.,Helwan University | Yousef H.,SQU
International Journal of Electrical and Computer Engineering | Year: 2016

Installation of down-hole gauges in oil wells to determine Flowing Bottom-Hole Pressure (FBHP) is a dominant process especially in wells lifted with electrical submersible pumps. However, intervening a well occasionally is an exhaustive task, associated with production risk, and interruption. The previous empirical correlations and mechanistic models failed to provide a satisfactory and reliable tool for estimating pressure drop in multiphase flowing wells. This paper aims to find the optimum parameters of Feed-Forward Neural Network (FFNN) with back-propagation algorithm to predict the flowing bottom-hole pressure in vertical oil wells. The developed neural network models rely on a large amount of available historical data measured from actual different oil fields. The unsurpassed number of neural network layers, the number of neurons per layer, and the number of trained samples required to get an outstanding performance have been obtained. Intensive experiments have been conducted and for the sake of qualitative comparison, Radial Basis neural and network and the empirical modes have been developed. The paper showed that the accuracy of FBHP estimation using FFNN with two hidden layer model is better than FFNN with single hidden layer model, Radial Basis neural network, and the empirical model in terms of data set used, mean square error, and the correlation coefficient error. With best results of 1.4 root mean square error (RMSE), 1.4 standard deviation of relative error (STD), correlation coefficient (R) 1.0 and 99.4% of the test data sets achieved less than 5% error. The minimum sufficient number of data sets used in training ANN model can be low as 12.5% of the total data sets to give 3.4 RMSE and 97% of the test data achieved 90% accuracy. Copyright © 2016 Institute of Advanced Engineering and Science. All rights reserved.


Awadalla M.,SQU | Awadalla M.,Helwan University | Al-Abri A.,SQU | Al-Busaidi S.,SQU
International Journal of Control Theory and Applications | Year: 2015

This paper surveys real-time scheduling algorithms for multiprocessor systems. The survey outlines fundamental results about multiprocessor real-time scheduling that hold independent of the scheduling algorithms employed. It provides a taxonomy of the different scheduling methods, and considers the various performance metrics that can be used for comparison purposes. A detailed review is provided covering partitioned, global, hybrid scheduling algorithms, and heuristic approaches. The survey addresses the Dynamic Voltage and Frequency Scaling (DVFS) technique that is acommonly-used for power-management wherethe clock frequency of a processor is decreased to allowa corresponding reduction in the supply voltage. This reducespower consumption, which can lead to significantreduction in the energy required for a computation, particularlyfor memory-bound workloads. It found that while DVFS is effective on the older platforms,it actually increases energy usage on the mostrecent platform, even for highly memory-bound workloads. © International Science Press.


Awadalla M.,SQU | Al-Abri D.,SQU | Al-Lawati A.,SQU | Al-Busaidi S.,SQU
International Journal of Control Theory and Applications | Year: 2015

This paper presents an investigation of the development of system identification using intelligent algorithms. A simulation platform of a flexible beam vibration using finite difference (FD) method is accomplished to demonstrate the capabilities of the identification algorithms. Three heuristic approaches for system identification are explored and evaluated. These identification approaches are, Adaptive Neuro Fuzzy Inference System (ANFIS) model, Bees Algorithm (BA) and Particle Swarm Optimization, PSO. The above approaches are used to estimate a linear discrete second order model for the flexible beam vibration. The model is implemented, tested and validated to demonstrate the merits of the algorithms for system identification. Finally, a qualitative comparison have been accomplished to address the system performance in terms of error convergence of the proposed approaches. The achieved results of intensive simulated experiments show that PSO outperforms the other approaches. © International Science Press.


Awadalla M.,SQU | Abdien A.K.,ECC | Rashad S.M.,ECC | Ahmed A.,SQU | Al Abri D.,SQU
WSEAS Transactions on Systems | Year: 2014

In this paper, the performance of traditional Support Vector Machine (SVM) is improved using Genetic Algorithm (GA). GA is used to determine the optimal values of SVM parameters that assure highest predictive accuracy and generalization ability simultaneously. The proposed scheme, called Support Vector Machine Genetic Algorithm (SVM-GA) Scheme, is applied on a beforehand data of a Nuclear Power Plant (NPP) to classify its associated faults. Compared to the standard SVM model, simulation of SVM-GA indicates its superiority when applied on the dataset with unbalanced classes. SVM-GA scheme can gain higher classification with accurate and faster learning speed.


News Article | January 1, 2016
Site: www.nanotech-now.com

Abstract: Activities of the Second Gulf Forum on Nanotechnology Awareness has concluded at Sultan Qaboos University (SQU) under the patronage of Shaikh Mohammed bin Hamdan al-Toobi, Advisor of the Ministry of Education. Oman National Commission for Education, Culture and Science (ONCECS) organized the forum in collaboration with the International Organization for Leisure Investment in Technology and Science (Milest), according to Oman News Agency (ONA). The forum was attended by a number of experts and specialists in the field of nanotechnology from inside and outside the Sultanate. The forum came out with a number of recommendations, including the importance of including science and nanotechnology in the curriculum taking into account the various stages of study, work with the Arab Bureau of Education for the Gulf States in the adoption of programs and initiatives that support nanotechnology in the educational framework, as well as localization and standardization of concepts and terms that deal with the Nano science and technology at the level of GCC countries. The forum also recommended the importance of preparation of training packages for teachers and supervisors to enhance their competence in Nano science and technology and the development of pre-service teacher preparation programs to ensure having the necessary competencies and skills in the field of Nano science and technology. Dr. Dawood al- Ahmad, Milest's Asia Manager gave a speech in which he said that the forum included a group of experts in this scientific field and pointed out that the papers presented, with their depth and diversity sought to raise awareness of nanotechnology and to find ways to take advantage of the development in this area . The sponsor of the activity honored at the end of the concluding ceremony the participants in the forum, ONA reported. For more information, please click If you have a comment, please us. Issuers of news releases, not 7th Wave, Inc. or Nanotechnology Now, are solely responsible for the accuracy of the content.

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