Applied Mechanics and Materials Vols. 380-384

Abstract: The multi-response linear polynomial model is transformed into a single response polynomial model. In symmetric test area, for the polynomial models the A-D- and E-optimal experimental designs are obtained.

Abstract: The 3-Regular Subgraph Problem is: Given a graph G = (V, E), can we find a subgraph H = (V, E) in G such that for each vertex u in V, , where is the degree of u in H This problem is an NP-complete problem for general graphs. In this paper, we design an O(n) time algorithm to solve The 3-Regular Subgraph Problem for a Halin graph H, where n is the number of vertices of H. Given a Halin graph H, if there is a cubic subgraph G in H, then our algorithm will find G and give an answer Yes, otherwise our algorithm will give an answer No. We also prove the correctness of this algorithm.

Abstract: To resolve the nonlinear non-Gaussian tracking problem effectively, a novel filtering algorithm based on Cubature Kalman Filter (CKF) and Particle Filters (PF) is proposed, which is called Cubature Kalman Particle Filter (CPF). CKF is used to generate the importance density function for PF. It linearizes the nonlinear functions using statistical linear regression method through a set of Gaussian cubature points. It need not compute the Jacobian matrix. Moreover, it makes efficient use of the latest observation information into system state transition density, thus greatly improving the filter performance. The simulation results show that CPF has higher estimation accuracy and less computational load comparing against the widely used Unscented Particle Filter (UPF).

Abstract: Along with the development of the network information age, people on the dependence of the computer network is more and more high, the computer network itself the security and reliability of becomes very important, the network management put forward higher request. This paper analyzes two algorithms of the network layer topology discovery based on the SNMP and ICMP protocol, based on this, this paper puts forward a improved algorithm of the comprehensive two algorithm, and makes the discovery process that has a simple, efficient, and has a strong generalization, and solved in the discovery process met the subnet judge, multiple access routers identification.

Abstract: Modelling as a technique continually keeps important place in information system development (ISD) methodologies and is adopted for implementing systems effectively. Contrasting to modelling, agile methodology is a new concept. It aims to overcome shortcomings of early ISD methodologies. It welcomes changes and adapt to them. Meanwhile it is people-oriented. Used in the new methodologies, besides traditional roles, modelling has more critical roles in ISD methodologies.The report illustrates main roles of modelling, including traditional and new ones. Meanwhile, it also addresses idea of ISD is social with the roles of modelling.

Abstract: in order to improve the efficiency of maze optimal routing problem, a GPU acceleration programming model OpenACC is used in this paper. By analyzing an algorithm which solves the maze problem based on ant colony algorithm, we complete the task mapping on the model. Though GPU acceleration, ant colony searching process was changed into parallel matrix operations. To decrease the algorithm accessing overhead and increase operating speed, data were rationally organized and stored for GPU. Experiments of different scale maze matrix show that the parallel algorithm greatly reduces the operation time. Speedup will be increased with the expansion of the matrix size. In our experiments, the maximum speedup is about 6.1. The algorithm can solve larger matrices with a high level of processing performance by adding efficient OpenACC instruction to serial code and organizing the data structure for parallel accessing.

Abstract: A latest optimization algorithm, named Teaching-Learning-Based Optimization (simply TLBO) was proposed by R. V. Rao et al, at 2011. Afterwards, some improvements and practical applications have been conducted toward TLBO algorithm. However, as far as our knowledge, there are no such works which categorize the current works concerning TLBO from the algebraic and analytic points of view. Hence, in this paper we firstly introduce the concepts and algorithms of TLBO, then survey the running mechanism of TLBO for dealing with the real-parameter optimization problems, and finally group its real-world applications with a categorizing framework based on the clustering, multi-objective optimization, parameter optimization, and structure optimization. The main advantage of this work is to help the users employ TLBO without knowing details of this algorithm. Meanwhile, we also give an experimental comparison for demonstrating the effectiveness of TLBO on 5 benchmark evaluation functions and conclude this work by identifying trends and challenges of TLBO research and development.

Abstract: How to check if a given matrix is a nonsingular matrix is important. In the recent paper, several simple criteria, as well as a necessary condition for nonsingular matrices, have been obtained. Inspired by these results, we partition the row and column index set of square matrix, construct a positive diagonal matrix according to the elements and row sum, column sum of the matrix as well, then obtain a new criterion for the nonsingular matrices, and extend the criteria of nonsingular matrices. Finally, a numerical example for the effectiveness of the proposed criterion is presented.

Abstract: This paper presents an algorithm for estimating the parameters of polynomial-phase signals (PPSs). This algorithm combines the CPF-HAF method and Radon transform, and can be referred to as the Radon-CPF-HAF method. In the proposed algorithm, the HAF is first applied on the original PPS to produce a cubic phase signal, whose parameters are then estimated by the Radon transform of the cubic phase function for the derived cubic phase signal. As involving in lower order nonlinearity, the proposed algorithm outperforms the HAF in terms of the accuracy and signal-to-noise-ratio (SNR) threshold. When multicomponent PPSs are considered, the product version of the proposed algorithm removes the identifiability problem which the product version of the CPF-HAF (PCPF-HAF) suffers from. Computer simulations have been carried out to support the theoretical results.

Abstract: The complicated decision making problem is one of the important components for the study on the system of artificial intelligence area. This thesis, based on the Bayesian technology and decision-making theory, is going to optimize the traditional IDs model and improve the ability of expression of the model. and also by using the sum of individual utility function instead of the joint utility function to create the BP neural network to study the utility function structure of the IDs. The experimental result shows the method mentioned above is effective.