46139740
Automatic Path-Oriented Test Data Generation Using a Multi-population Genetic Algorithm
Automatic path-oriented test data generation is an undecidable problem and genetic algorithm (GA) has been used to test data generation since 1992. In favor of MATLAB, a multi-population genetic algorithm (MPGA) was implemented, which selects individuals for free migration based on their fitness values. Applying MPGA to generating path-oriented test data generation is a new and meaningful attempt. After depicting how to transform path-oriented test data generation into an optimization problem, basic process flow of path-oriented test data generation using GA was presented. Using a triangle classifier as program under test, experimental results show that MPGA based approach can generate path-oriented test data more effectively and efficiently than simple GA based approach does.
27063773
Aspect-Oriented Middleware-Based Real-Time and Embedded Systems Software Process
Middleware facilitates the development of real-time and embedded systems. However, middleware itself is becoming increasingly complex. Using the methodology of aspect-oriented software development to analyze and reconstruct the architecture of middleware can make the architecture more modularized and more customizable. In addition, since middleware plays a significant role in the realtime and embedded systems development, its characteristics must be considered in the entire real-time and embedded systems software process from requirements analyze phase to testing phase. This paper provides two contributions to the study of real-time and embedded systems development. First, presents the problems of current middleware architecture and analyzes functional requirements and non-functional requirements of aspect-oriented middleware. Second, proposes an aspect-oriented middleware based real-time and embedded systems software process. Both functional and non-functional characteristics of middleware are considered in all phases of the software process.
45747323
Generalized algebraic method and new exact traveling wave solutions for (2+1)-dimensional dispersive long wave equation
Abstract With the help of the symbolic computation system Maple , a new generalized algebraic method to uniformly construct solutions in terms of special function of nonlinear partial differential equations is presented by means of a more general ansatz. As an application of the method, we choose a (2 + 1)-dimensional dispersive long wave equation to illustrate the method. As a result, we can successfully obtain the solutions found by the method proposed by Fan [E.G. Fan, Phys. Lett. A 300 (2002) 243] and find other new and more general solutions at the same time, which include polynomial solutions, exponential solutions, rational solutions, triangular periodic wave solutions, hyperbolic, and soliton solutions, Jacobi, and Weierstrass doubly periodic wave solutions.
20327796
An effective algorithm of motif finding problem
Identification of the short DNA sequence motif, which serves as binding targets for transcription factors, is a fundamental problem in both computer science and molecular biology. Especially, finding the subtle motifs with variable gaps is more challenging. In this paper, a new algorithm is presented, which explores some new strategies. Based on a neighbourhood set concept, a new probability matrix is defined, which can capture the target motifs effectively. An iterative restart strategy is used, by which we can use several similar motifs' information to detect the real motif to demonstrate the effectiveness of our algorithm. We test it on several kinds of data and compare it with some other current representation algorithms. Simulation shows that the algorithm can effectively detect the subtle motifs.
28145787
Homotopy perturbation method for a type of nonlinear coupled equations with parameters derivative
Abstract In this paper, homotopy perturbation method is directly extended to investigate nonlinear coupled equations with parameters derivative and to derive their numerical solutions. These nonlinear coupled equations with parameters derivative contain many important mathematical physics equations and reaction–diffusion equations. By choosing different values of the parameters in general formal numerical solutions, as a result, a very rapidly convergent series solution is obtained. The efficiency and accuracy of the method are verified by using two famous examples: coupled Burgers and mKdV equations. Numerical solutions show that good results have been achieved.
15834568
An Artificial Neural Network Based on CIEA
Chaotic Immune evolutionary algorithm (CIEA) is proposed on the shortage of current algorithms training artificial neural network, biological immune mechanism and the characteristics of evolution. A novel artificial neural network based on chaotic immune evolutionary algorithm (CIEANN) is presented in this paper. The algorithm has the merits of chaos, immunity and evolutionary algorithm. It can ensure the ability of global search and local search and enhance the performances of the algorithm. At last, we analyzed the performance of CIEANN with a typical XOR problem and compared it with several common ANNs. The analysis results show that CIEANN converges quickly and avoids immature convergence and is an effective way to solve optimization problem.
28565174
Trust Evolution Policies for Security in Collaborative Ad Hoc Applications
The vision of pervasive computing has introduced the notion of a vast, networked infrastructure of heterogeneous entities interact through collaborative applications, e.g., playing a multi-player online game on the way to work. This will require interactions between users who may be marginally known or completely unknown to each other, or in situations where complete information is unavailable. This introduces the problem of assigning access rights to such marginally known or unknown entities. Explicit trust management has emerged as a solution to the problem of dealing with partial information about other users and the context in which the interaction takes place. We have implemented an access control mechanism based on the human notion of trust, where recommendations or initial participation in low risk interactions will allow entities to slowly build trust in each other. As the trust between two entities grows, interactions that entail a higher degree of risk may be allowed to proceed. We have used this mechanism in a simple role-based access control mechanism that uses trust to assign roles to users in a distributed blackjack card game application. This application allows us to experiment with different policies for trust-based admission control and trust evolution. In this paper we present an evaluation of policies specifying trust dynamics, which shows that our prototype reacts appropriately to the behaviour of other users and that the system updates trust values and implements admission policies in a manner similar to what would be expected from human trust assessment. This indicates that trust evolution policies can replace explicit human intervention in application scenarios that are similar to the evaluated prototype.