Jia Ying University

Meizhou, China

Jia Ying University

Meizhou, China

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Qiu W.,Jia Ying University | Zhang L.-C.,Guangdong University of Technology
Journal of Software | Year: 2012

Model Driven Architecture (MDA) is a development method of which can generate useable software products directly by the model. It includes a series of standardized modeling, transformation rules and other relevant standards architecture. Real-Time systems have been applied in many areas widely, but they have many nonfunctional requirements, which always crosscut the whole system modules. That may cause the code tangle and scatter, make the systems hard to design, reuse and maintain, and affect performance of systems badly. AOP is a new software development paradigm, which could attain a higher level of separation of concerns in both functional and nonfunctional matters by introducing aspect, for the implementation of crosscutting concerns. Different aspects can be designed separately, and woven into systems. This article introduces the technology of MDA, aspect-oriented, real-time systems and UML. This article takes the Aspectoriented to the MDA modeling by the UML extension mechanisms, and presents a method, which is Aspect- Oriented MDA. In this article, UML profile is utilized to construct the meta-modal specifications respectively for common Aspect-Oriented and AspectJ. So the core business logic and the crosscutting aspects can be modeled as separate, modular Aspect-Oriented PIM's and PSM's. The authors analysis non-functional requirements of the realtime systems, and then apply aspect-oriented MDA modeling to develop an example of real-time systems, and propose how to model aspects of timer and real-time constraints. Finally, in order to more clearly understand how to complete the MDA in the aspect-oriented modeling, especially in real-time system. This paper through the example of a real-time system is discussed. The system simulates the operation of self-automatic washer process. © 2012 ACADEMY PUBLISHER.


Pan L.,Nanjing Southeast University | Pan L.,Jia Ying University | Cao J.,Nanjing Southeast University
Neurocomputing | Year: 2012

This paper devotes to the stochastic robust stability of uncertain neural networks with time-varying delay and impulses. By using Lyapunov function and stochastic analysis approaches, a sufficient condition is derived in terms of linear matrix inequality (LMI), which can guarantee the uncertain neural network to be robustly exponentially stable in the mean square for all admissible uncertainties. We also extend the delay fractioning approach to the uncertainty system by constructing a Lyapunov-Krasovskii functional and comparing to a linear discrete system. The estimation of decay rate of uncertain neural network can be obtained by estimation of the decay of the linear discrete system. Meanwhile, two examples with numerical simulations are given to illustrate the applicability of the results. © 2012 Elsevier B.V.


Pan L.,Nanjing Southeast University | Pan L.,Jia Ying University | Cao J.,Nanjing Southeast University
Nonlinear Analysis: Real World Applications | Year: 2011

In this paper, we discuss anti-periodic solution for delayed cellular neural networks with impulsive effects. By means of contraction mapping principle and Krasnoselski's fixed point theorem, we obtain the existence of anti-periodic solution for neural networks. By establishing a new impulsive differential inequality, using Lyapunov functions and inequality techniques, some new results for exponential stability of anti-periodic solution are obtained. Meanwhile, an example and numerical simulations are given to show that impulses may change the exponentially stable behavior of anti-periodic solution. © 2011 Elsevier Ltd. All rights reserved.


Pan L.,Jia Ying University | Cao J.,Nanjing Southeast University | Cao J.,King Abdulaziz University
Neurocomputing | Year: 2015

This paper devotes to stability analysis of continuous time and discrete time bidirectional associative memory (BAM) neural networks whose parameters are randomly varying in a finite state Markov chain sense. Based on the ergodic theory of continuous time Markov chain, the matrix measure approach and Lyapunov theory, almost sure stability and exponential stability in the mean square for continuous time BAM neural networks are derived. We also present some new stability results for discrete time BAM neural networks with the help of the law of large numbers. Meanwhile, some examples with numerical simulations are given to show that the Markov chain plays an important role in stability of neural networks. © 2015 Elsevier B.V.


Chen S.,Sun Yat Sen University | Chen S.,Jia Ying University | Liang J.,Sun Yat Sen University | Mo Y.,Sun Yat Sen University | And 2 more authors.
Applied Surface Science | Year: 2013

A three-dimensional (3D) kinetic Monte Carlo simulation was performed for the growth evolution of Ag films during glancing angle deposition (GLAD). Under the GLAD conditions, we demonstrate that without substrate rotation the nanorods are grown aslant due to shadowing anisotropy, while with the rapid substrate rotation the nanorods are grown vertically aligned due to shadowing isotropy. Good agreement of growth trends between simulations and experiments has been achieved. In the case of substrate rotation, the critical rotate rate of nanorods just vertical to the substrate has been found. The growth exponent evolutions of Ag films in normal and glancing angle depositions are found similar in the very early stages of growth. The diverging of growth exponents with film height increasing indicates that shadowing instabilities overpower the smoothing effects associated with surface diffusion. Furthermore, we demonstrate the transition from two-dimensional to 3D islanded growth under the condition of high glancing angle deposition. © 2012 Elsevier B.V. All rights reserved.


Qiu W.,Jia Ying University
Advanced Materials Research | Year: 2010

This document explains and demonstrates on the Normalization for Internet computing and Modeling of Conceptual Model XML-based. The existing XML conceptual models have their limitation, largely because the semantic, such as "containment" and "multiple-scope", could not be sufficiently described. XUML is a XML conceptual model based on UML. It is independent of specific XML schema definition language, and puts emphasis on describing relationships between domain concepts and defining related semantic constrains. XML normalization theory is recently a research focus, but the existing research outcomes are very complex so they are hard to be understood by XML designers. The development of database design methodology reveals that it is more effective to apply normalization theory in conceptual design than that in logical design. By following the successful approach, the characteristics of XML normal form are represented in XUML. Several XUML forms are defined, and the normalization based on XUML is investigated. The research on XML normalization theory further enhances XUML methodology. So we show the process of XML normalization in XML conceptual model in the paper. And several normalization methods are introduced. Finally, an example is presented to explain the general application of XML normalization methods. © (2010) Trans Tech Publications, Switzerland.


Qiu W.,Jia Ying University
3rd International Conference on Knowledge Discovery and Data Mining, WKDD 2010 | Year: 2010

When carrying out knowledge representation, Ontology of information in an abstract manner similar to semantic networks, can be used with a labeled directed graph to sign, but the Ontology is more focused on specific areas that the overall content. Ontology development and application of this paper gave a brief overview of research: first introduced predicate logic-based ontology representation language and graph-based ontology representation language and to introduce the main body of the current development environment and tools; second describes the development of the relatively forming body methods and propose a ontology-based object-oriented development of a simple process; concluded the ontology development problems and development direction. © 2010 IEEE.


Chen S.,Jia Ying University | Luo J.,Jia Ying University | Bu S.,Jia Ying University
Applied Surface Science | Year: 2014

Kinetic Monte Carlo simulations are carried out to explore the growth of the Ag ultrathin film on Pt (1 1 1) in the early growth stage. With increasing temperature, the island shapes are demonstrated to transform from fractal to compact and resemble the surface crystal structure at high temperature. The transition temperature of the island evolution is demonstrated to increase with the deposition rate. The competing mechanism between nucleation and growth is pursued. The transition temperature of island evolution is deduced by the average island density distributions and demonstrated by the island morphology evolutions. In addition, the extent of a non-ideal substrate surface is explored. As the interaction energy between adatom and defect point increases, the island shape becomes small and irregular. The effect of surface defect on the nucleation and growth is demonstrated. © 2014 Elsevier B.V. All rights reserved.


Pan L.,Jia Ying University | Cao J.,King Abdulaziz University
Neurocomputing | Year: 2015

This paper devotes to stability analysis of continuous time and discrete time bidirectional associative memory (BAM) neural networks whose parameters are randomly varying in a finite state Markov chain sense. Based on the ergodic theory of continuous time Markov chain, the matrix measure approach and Lyapunov theory, almost sure stability and exponential stability in the mean square for continuous time BAM neural networks are derived. We also present some new stability results for discrete time BAM neural networks with the help of the law of large numbers. Meanwhile, some examples with numerical simulations are given to show that the Markov chain plays an important role in stability of neural networks. © 2015 Elsevier B.V.


Guo J.H.,Jia Ying University | Chen D.L.,Jia Ying University
Advanced Materials Research | Year: 2013

Data aggregation is an important method to reduce energy consumption in wireless sensor networks (WSN). Auth-ors proposed a cluster trisecting based data aggregation scheme for wireless sensor networks in which the cluster was trisected and some reporters were assigned to each region. The nodes have same reading and located in same region with reporter will keep silent in data aggregating, thus reducing the inner-cluster transmissions. Analysis and simulation show that the transmissions of inner-cluster aggregation in our scheme lower than that of related schemes and the decrease of trans- missions is obvious when redundancy of sensor readings is high. © (2013) Trans Tech Publications, Switzerland.

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