Lag projective synchronization of fractional-order delayed chaotic systems

This paper considers the lag projective synchronization of fractional-order delayed chaotic systems. The lag projective synchronization is achieved through the use of comparison principle of linear fractional equation at the presence of time delay. Some sufficient conditions are obtained via a suitable controller. The results show that the slave system can synchronize the past state of the driver up to a scaling factor. Finally, two different structural fractional order delayed chaotic systems are considered in order to examine the effectiveness of the lag projective synchronization. Feasibility of the proposed method is validated through numerical simulations.     

Stabilization of artificial gas-lift process using nonlinear predictive generalized minimum variance control

Artificial gas-lift (AGL) is one of the most widely used methods in oil production to maintain acceptable oil flow to the processing equipment and sales when the reservoir pressure is not high enough. In spite of its popularity, the AGL process is prone to casing-heading instability, which is revealed as significant flow oscillation. This is undesirable as it results in production losses and unstable behavior that has negative impact on the downstream equipment. Controller design for such a process is very challenging as it exhibits highly nonlinear dynamics. In this work, the predictive generalized minimum variance control (NPGMV) is employed to derive a robust controller based on the state estimation to stabilize AGL process when casing-heading phenomenon occurs. A closed-form optimal control law is obtained based on the Taylor series approximation. Further, a nonlinear state observer is produced and combined with the controller to ensure closed-loop control through variables that are most beneficial to the system performance, which are unmeasurable and can be obtained only via estimation. Through simulation studies, the effectiveness of the proposed controller is demonstrated.     

Dynamics of a stochastic multigroup SIQR epidemic model with standard incidence rates

In this paper, we consider a stochastic multigroup SIQR epidemic model with standard incidence rates. By using the stochastic Lyapunov function method, we establish sufficient conditions for the existence of a stationary distribution of the positive solutions to the model. Then we establish sufficient conditions for extinction of the diseases. A stationary distribution means that all the individuals can be coexistent and persistent in the long term. Finally, some examples and numerical simulations are introduced to illustrate our theoretical results.     

Integrating design science research and design based research frameworks for developing education support systems

Education and Information Technologies - This paper proposes an integrated research framework that takes advantage of the similarities of design science research (DSR) and Design-based research...     

The challenge of basic education for all

UNICEF Representative in China. Author of several books and articles ou non-formal education, rural development and educational planning.     

Views of Omani post-basic education students about religious and cultural tolerance

The study aims to investigate the views of Omani post-basic education students (Grades 10–12) about religious and cultural tolerance. The sample consisted of 1390 male and female students in grades 10, 11 and 12, from four of Oman’s seven regions. A questionnaire was used to gather data, which consisted of 27 items divided into five domains. The results showed that students place a strong emphasis on the importance of religious and cultural tolerance, both within Oman society and worldwide. They are also not in favour of any type of aggression, religious and cultural symbols or the fuelling of disagreements between religions or cultures. The results also indicated that female students are more strongly concerned with tolerance than males, grade 12 students more concerned than those in grades 10 and 11, and students from Muscat more concerned than those in other less urban areas.     

Writer identification approach based on bag of words with OBI features

Handwriter identification aims to simplify the task of forensic experts by providing them with semi-automated tools in order to enable them to narrow down the search to determine the final identification of an unknown handwritten sample. An identification algorithm aims to produce a list of predicted writers of the unknown handwritten sample ranked in terms of confidence measure metrics for use by the forensic expert will make the final decision.Most existing handwriter identification systems use either statistical or model-based approaches. To further improve the performances this paper proposes to deploy a combination of both approaches using Oriented Basic Image features and the concept of graphemes codebook. To reduce the resulting high dimensionality of the feature vector a Kernel Principal Component Analysis has been used. To gauge the effectiveness of the proposed method a performance analysis, using IAM dataset for English handwriting and ICFHR 2012 dataset for Arabic handwriting, has been carried out. The results obtained achieved an accuracy of 96% thus demonstrating its superiority when compared against similar techniques.