Skip to main content
main-content
Top

About this book

International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA) is one of the flagship conferences on Bio-Computing, bringing together the world’s leading scientists from different areas of Natural Computing. Since 2006, the conferences have taken place at Wuhan (2006), Zhengzhou (2007), Adelaide (2008), Beijing (2009), Liverpool & Changsha (2010), Malaysia (2011) and India (2012). Following the successes of previous events, the 8th conference is organized and hosted by Anhui University of Science and Technology in China. This conference aims to provide a high-level international forum that researchers with different backgrounds and who are working in the related areas can use to present their latest results and exchange ideas. Additionally, the growing trend in Emergent Systems has resulted in the inclusion of two other closely related fields in the BIC-TA 2013 event, namely Complex Systems and Computational Neuroscience.

These proceedings are intended for researchers in the fields of Membrane Computing, Evolutionary Computing and Genetic Algorithms, DNA and Molecular Computing, Biological Computing, Swarm Intelligence, Autonomy-Oriented Computing, Cellular and Molecular Automata, Complex Systems, etc.

Professor Zhixiang Yin is the Dean of the School of Science, Anhui University of Science & Technology, China. Professor Linqiang Pan is the head of the research group of Natural Computing at Huazhong University of Science and Technology, Wuhan, China. Professor Xianwen Fang also works at the Anhui University of Science & Technology.

Table of Contents

Frontmatter

Erratum to: A New Parallel Genetic Algorithm Based on TriBA Topological Structure

Kang Sun, Chang Wook Ahn

Retraction Note to: Using Inner-Outer Factorization to Solve the Spectral Factor of Discrete-Time Descriptor Systems

Luhua Liang, Wei Xing, Rongwu Xiang

Theories

Frontmatter

Remarks on Invariant Method of the Second-Order Linear Differential Equations with Variable Coefficients

Invariant method was used to solve the linear second-order equations with variable coefficients. We employ the invariant variable method to give the integrable condition of equations and to display the superiority of this method.

Linlong Zhao

Convergence Analysis on Immune Optimization Solving CCP Problems

This work concentrates on studying the property of convergence of a sample allocation-based immune optimization approach used in solving linear or nonlinear chance-constrained programming (CCP) with general random variables. First, we make some theoretical studies about existence of optimal reliable solutions and give an approximate relation between the true CCP and the sample average approximation problem, depending on some statistic and analysis theory. Second, a bio-inspired immune optimization approach is developed to assume solving CCP problems. Our theoretical analysis shows that such approach, which is capable of being formulated by a non-homogeneous Markov model, is convergent. Experimentally, performance searching curves reveal that the approach can obtain valuable performances including the optimized quality, noisy suppression and convergence.

Zhuhong Zhang, Fei Long

Robust Coordination with Transmission Delay and Measurement Noises

This paper is concerned with the problem of distributed stochastic approximation in single-integer multi-agent systems on general directed

unbalanced

networks with measurement noises and transmission delay. The time-varying control gains satisfying the stochastic approximation conditions are introduced to attenuate noises. Then based on Lyapunov technique, the convergence result of mean square consensus is established provided that the transmission delay is bounded.

Dequan Li, Xinyu Huang, Zhixiang Yin

Study on the Importance of Cultural Context Analysis in Machine Translation

Context of culture affects the specific meaning of the language. So the analysis of cultural context is essential for Machine Translation (MT). If the cultural context analysis of the source language is omitted in MT, ambiguity or mistranslation will be produced. The paper analyzes briefly the present situation of MT first and then, based on the theory of cultural context, it discusses with examples the importance of cultural context analysis in MT. The paper holds that if the cultural context analysis is paid enough attention in MT, the literal meaning and cultural connotation of source language can be exactly and completely translated into target language so as to improve the quality of MT. Therefore, the large-scale context corpus is very necessary for MT.

Zonghua Wang

The Evaluation Model of Construction Industry Financial Risk Based on SVM

The model of evaluating profession financial risk can be added with industry characteristic indicator, a general evaluation model is more suitable for a particular industry, and it can improve the accuracy. This paper has chosen 23 financial indexes aims at six respects such as solvency, profitability, cash flow, asset management ability, development ability and capital structure of construction industry, and has built the evaluation index system of building trades. Selected the construction enterprises in the Shanghai and Shenzhen listed as samples, applied cluster analysis on samples to preprocessing, then using the theory of support vector machine, respectively constructed polynomial Gauss radical, Sigmoid three kernel function SVM evaluation model of construction industry financial risk, and has verified them, The results shows that the SVM model that applied in the financial risk evaluation of construction industry has a high accuracy.

Xiaomei Chang

Replaceable Encoding for Basic Variable of Traffic Network Transportation Optimization Problem

A linear programming problem is solved for the first time based on DNA computing model, which has important significance for research on DNA computing. According to feature of the mathematical model of traffic network transportation optimization problem (TNTOP), three groups of replaceable encoding for each basic variable are designed in the algorithm as follows: basic variable group; variable value group and c value group, which stores the information of basic variable and its value and has many groups replaceable foreign DNA corresponding to the basic variable. In the algorithm of TNTOP based on replaceable encoding for basic variable, combination operation which is used can assign or re-assign values to variables, which is composed of group insert experiment, gel electrophoresis experiment and group deleting experiment. The combination operation can test the constraint conditions and extract all optimal solutions of TNTOP. Detection experiment designed based on electrophoresis experiment can detect mixture containing many kinds of closed circle DNA sequence, and can detect out all closed circle DNA sequences or one closed circle DNA sequence of the mixture according to requirement of the algorithm. The correctness and the complexity of the DNA algorithm are proved, and a simulation example is given to explain feasibility of the DNA algorithm.

Kang Zhou, Yule Zhu, Feng Jin, Xin Tao

Upper and Lower Solutions of Boundary Value Problems for Impulsive Fractional Differential

This paper studies the existence of solutions for boundary value problem of impulsive fractional differential equations, we obtain the method of upper and lower solutions by using Schauder’s fixed point theorem.

Chuan xia Hou, Yong Li

A Generalized Multi-Attribute Group Decision Making with Intuitionistic Fuzzy Set

The aim of this paper is to introduce a new decision making model called the generalized multi-attribute group decision making (GMAGDM), which provides a very general form that includes multi-attribute decision making (MADM) and multi-attribute group decision making (MAGDM) as two special cases. A GMAGDM under intuitionistic fuzzy environment is proposed. The relation between intuitionistic fuzzy set and hesitant fuzzy set is utilized. Then we propose a hesitant fuzzy TOPSIS method for the solution of the mentioned problem. Finally, a numerical example is given to illustrate the flexibility and validity of the proposed approach.

Zhifu Tao, Huayou Chen, Weiyuan Zou, Ligang Zhou, Jinpei Liu

Asymptotic Optimality of Balanced Routing in a Multiclass G/G/1 Queue

In this paper we consider a multiclass G/G/1 queueing system. When the server is idle, we use a balanced routing control policy to determine what kind of customer is served. Under such a balanced policy, we derive the diffusion limits of the queue length processes and the workload processes. The diffusion limits are the same for these processes regardless the choice of

c

as long as

c

≥ 2. We further show that the proposed balanced routing policy for any fixed

c

≥ 2 is asymptotically optimal in the sense that it minimizes the workload over all time in the diffusion limit.

Xiao Xiao, Lu Wu

The Optimization of DNA Encodings Based on GAFSA/GA Algorithm

The design of DNA sequence is important in improving the reliability of DNA computing. Some appropriate constrained terms that DNA sequence should satisfy are selected, and then the evaluation formulas of each DNA individual corresponding to the selected constrained terms are proposed. The paper analyzes the objective and several constraints of DNA encoding, it builds a combinational optimization model. A Global Artificial Fish Swarm algorithm/Genetic Algorithm (GAFSA/GA) is proposed to produce DNA encoding sequences. The result shows that the DNA sequences produced by GAFSA/GA have better quality than that produce by the genetic algorithm.

Juan Hu, Dong Li, Li-li Zhang, Zhixiang Yin

Kernel Optimal Unsupervised Discriminant Projection and Its Application to Face Recognition

Kernel Optimal Unsupervised Discriminant Projection (KOUDP) is presented in this paper. The proposed method first maps the input data into a potentially much higher dimensional feature space by virtue of nonlinear kernel trick, and in such a way, nonlinear features is extracted by running UDP on the kernel matrix. The singularity problem of the non-local scatter matrix due to small sample size problem occurred in UDP is avoided. Experimental results on YALE database indicate that the proposed KOUDP method achieves higher recognition rate than the UDP method and other kernel-based learning algorithms.

Xingzhu Liang, Yu’e Lin, Jingzhao Li

The Binary Anti-Collision Algorithm Based on Labeled Packet

An improved algorithm based on label packet (PABI) is put forward, which aimed at much times search and the large amount of communication data of current binary anti-collision algorithm. The new algorithm improve decoding accuracy by grouping labels within the field that reader identify by setting a counter on the label, extract conflicts bit then make up conflict block in the recognition process, and introduce the concept of matrix to express the possible decode of conflict block, thereby. The simulation results show that the algorithm have a significant advantage in the number of searches and the amount of communication data in the case of a large number of tags.

Jianbin Xue, Lijing Qin, Wenhua Wang

Research and Implementation on Event-Based Method for Automatic Summarization

By studying the technology of automatic summarization, this paper considers event as a basic semantic unit for narrative texts, and presents a new Event-based method for automatic summarization. This method utilizes events and the relationship between events to build Event-Network text representation model, which can retain the structure information and semantic information of the text to a greater extent. The experimental results show that the Event-based automatic summarization method has better performance.

Tao Liao, Zongtian Liu, Xianchuan Wang

Closed Circle DNA Algorithm of Maximum Weighted Independent Set Problem

Closed circle DNA algorithm of maximum weighted independent set problem is proposed upon closed circle DNA computing model and its biochemistry experiment. In the algorithm, first we get all independent sets though an appropriate encoding and delete experiments, and then we find the maximum weighted independent set using electrophoresis experiment and detect experiment. Only using delete experiment, the algorithm is simple and credible.

Qingyan Li, Zhixiang Yin, Min Chen

Bivariate Barycentric Rational Hermite Interpolaiton Based on the Lebesgue Constant Minimizing

Barycentric interpolation is considered to be the most stable formula for a rational Hermite interpolation. The core problem is to choose the optimal weights. In this paper, the optimal weights of the bivariate barycentric rational Hermite interpolation are obtained based on the Lebesgue constant minimizing. Then the solution of the optimization model can be obtained by the software LINGO. Further, the numerical examples are given to show the effectiveness of the new method.

Qianjin Zhao, Jie Qiao

Efficiency of Parallel Computing Based on .Net 4.5

In recent decades, with the continuous development of the CPU, the speed of single-core processors is increasingly close to the limit. Therefore, multi-core processors, through the internal integration of multi cores, solve the bottleneck in the development of the CPU. Over the past decade, the pace of development of multi-core technology is very fast, but the development of the software has not kept up with the pace of hardware. Most software and program failed to fully utilize the performance of multi-core processors. This paper introduces the parallel programming knowledge of Microsoft .Net 4.5 through the design of an experiment seeking the largest prime number demonstrates parallel the implementation process. Meanwhile, through the comparison of the time consumption between the parallel computation and traditional method, the author draw a conclusion that the computation efficiency is greatly improved by parallel computation then the traditional method in case of large amount of data.

Wei Hao, Rongrong Gu, Kelei Sun, Ping Ren

Boundary Value Problem for a Coupled System of Nonlinear Fractional Differential Equation

This paper is concentrated on the following coupled system of the nonlinear fractional differential equation

$$ \left\{ \begin{aligned} &D^{\alpha } u\left( t \right) = f\left( {t,v\left( t \right)} \right) + \int_{0}^{t} {K\left( {s,v\left( s \right)} \right)ds,\quad 5 < \alpha ,\beta \le 6,\;0 < t < 1} \hfill \\ &D^{\beta } v\left( t \right) = g\left( {t,u\left( t \right)} \right) + \int_{0}^{t} {H\left( {s,u\left( s \right)} \right)ds} \hfill \\ &u\left( 1 \right) = \mathop {\lim }\limits_{{t \to 0}} u\left( t \right) \cdot t^{{2 - \alpha }} = v\left( 1 \right) = \mathop {\lim }\limits_{{t \to 0}} v\left( t \right) \cdot t^{{2 - \beta }} = 0. \hfill \\ \end{aligned} \right. $$

{

D

α

u

(

t

)

=

f

(

t

,

v

(

t

)

)

+

0

t

K

(

s

,

v

(

s

)

)

ds

,

5

<

α

,

β

6

,

0

<

t

<

1

D

β

v

(

t

)

=

g

(

t

,

u

(

t

)

)

+

0

t

H

(

s

,

u

(

s

)

)

ds

u

(

1

)

=

lim

t

0

u

(

t

)

·

t

2

α

=

v

(

1

)

=

lim

t

0

v

(

t

)

·

t

2

β

=

0

.

where

$$ f,\;K,\;g,\;H:\;\left[ {0,\,1} \right]\, \times \,\Re \, \to \,\left[ {0,\, + \infty } \right) $$

f

,

K

,

g

,

H

:

[

0

,

1

]

×

[

0

,

+

)

are the positive continuous functions.

$$ D^{\alpha } $$

D

α

and

$$ D^{\beta } $$

D

β

are the standard Riemann–Liouville fractional derivatives with the order

$$ \alpha ,\, \beta, $$

α

,

β

,

respectively. We give the existence and the uniqueness of the solution by using the Schauder fixed point theorem and the generalized Gronwall inequality.

Ya-ling Li, Shi-you Lin

On the Existence of Extremal Positive Definite Solutions of a Class of Nonlinear Matrix Equation

The nonlinear matrix equation

$$ X^{r} + \sum\nolimits_{i = 1}^{m} {A_{i}^{*} } X^{{\delta_{i} }} A_{i} = Q $$

is studied. A necessary condition for the existence of positive definite solutions of this equation is derived. Based on the Banach fixed point theorem, a sufficient condition for the existence of a unique positive definite solution of this equation is also derived. Iterative methods for obtaining the extremal (maximal–minimal) positive definite solutions of this equation are proposed.

Bo Wang, Qingchun Li

An Iterative Algorithm for the Generalized Center Symmetric Solutions of a Class of Linear Matrix Equation and Its Optimal Approximation

For any symmetric orthogonal matrix

P

, i.e.,

$$ P^{\rm T} = P,\,P^{\rm T} P = I, $$

P

T

=

P

,

P

T

P

=

I

,

the matrix

X

is said to be a generalized centrosymmetric matrix if

$$ PXP = X $$

PXP

=

X

for any matrix

X

. The conjugate gradient iteration algorithm is presented to find the generalized centrosymmetric solution and its optimal approximation of the constraint matrix equation

$$ AXB + CXD = F. $$

AXB

+

CXD

=

F

.

By this method, the solvability of the equation can be determined automatically. If the matrix equation

$$ AXB + CXD = F $$

AXB

+

CXD

=

F

is consistent, then its generalized centrosymmetric solution can be obtained within finite iteration steps in the absence of round off errors for any initial symmetric matrix

$$ X_{1} , $$

X

1

,

and generalized centrosymmetric solution with the least norm can be derived by choosing a proper initial matrix. In addition, the optimal approximation solution for a given matrix of the matrix equation

$$ AXB + CXD = F $$

AXB

+

CXD

=

F

can be obtained by choosing the generalized centrosymmetric solution with the least norm of a new matrix equation

$$ A\tilde{X}B + C\tilde{X}D = \tilde{F}. $$

A

X

B

+

C

X

D

=

F

.

Jie Liu, Qingchun Li

Multi-Objective Genetic Algorithm with Complex Constraints Based on Colony Classify

The paper presents a constraint-handling approach for multi-objective optimization. The general idea is shown as follow: Firstly, the population was classified into two groups: feasible population and infeasible population. Secondly, feasible population was classified into Pareto population and un-Pareto population. Thirdly, the Pareto population was defied with k-average classify approach into colony Pareto population and in-colony Pareto population. Last, R-fitness was given to each population. Simulation results show that the algorithm not only improves the rate of convergence but also can find feasible Pareto solutions distribute abroad and even.

Li-li Zhang, Feng Xu, Juan Hu

Hypothesis Testing for Squared Radial Ornstein–Uhleneck Model: Moderate Deviations Method

We study the moderate deviations for the log-likelihood ratio of the squared radial Ornstein-Uhleneck (O–U) model, with the help of them we give negative regions in testing squared radial O–U model, and get the decay rates of the error probabilities.

Cai-Ping Chen, Shou-Jiang Zhao, Qiao-Jing Liu

A Nonconforming Characteristic Finite Element Method for Nonlinear Advection-Dominated Diffusion Equation with Memory Term

A nonconforming characteristic finite element method is considered for nonlinear convection-dominated diffusion equation with memory term. By the use of some special properties of the finite element interpolation operator, and without Rietz-Volterra projection operator which is an indispensable tool in the convergence analysis of finite element methods for integro-differential evolution equations in the previous literature, the optimal error estimate on

L

2

-norm and the superconvergence result on

H

1

-norm are obtained.

Jiaquan Zhou, Chao Xu, Jianlai Gao

Exact Solutions for the Compound KdV-Burgers Equation Using the Improved (G′/G)-Expansion Method

Exact solutions of nonlinear partial differential equation are major subject in the study of nonlinear science. In this paper, with the aid of computer algebraic system mathematica, the compound KdV-Burgers equation are investigated by using the improved (G′/G)-expansion method. As a result, many exact solutions are obtained which including hyperbolic function solutions, trigonometric function solutions and rational function solutions.

Rui Cao

The Design of Asynchronous Motor Performance Testing System Based on the MSP430f47187

This thesis uses MSP430F47187 as the control core, through collecting the data of asynchronous motor no-load test and short-circuit test, and calculating the asynchronous motor performance parameters based on the circle diagram. Finally, we can obtain the visual performance test report in the operation terminal. Therefore, we can acknowledge the performance of the motor parameters intuitively and control the operation of the asynchronous motor better.

Qing Wang, Weilong Li, Lihua Zhang, Sheng Lu

Two-Step Iterative Algorithms for Two Multivalued Quasi-Nonexpansive Mappings

In this paper, a new two-step iterative algorithms is introduced to approximate common Fixed point of two multivalued quasi-nonexpansive mappings in a real uniformly convex Banach Space. Furthermore, we also prove some strong and weak convergence theorems in uniformly convex Banach Space.

Yinying Zhou

Analyzing Real-Time Predictability of Business Processes Based on Petri Nets

The real-time property is an important indicator of trustworthy business processes. Guaranteeing the real-time predictability is pivotal to ensure the efficient execution of business processes. For the real-time requirements of business processes, a method of modeling and analyzing business processes called Timed Business Process Net (TBPN) is proposed. It is a combination of business process modeled by Petri nets and the time factor on places. A real-time predictability analysis method is proposed. Using the proposed methods, we can provide an effective way to guarantee the real-time predictability of business processes.

Wangyang Yu, Xianwen Fang

Automatic Text Classification Based on Hidden Markov Model and Support Vector Machine

This paper researches the technology of text classification, and proposes a two-layer structure automatic text classification based on HMM and SVM. The given text is classified with HMM classifiers first to select the most likely two classes. Then these classes as SVM input are processed. Finally the given text is classified into the corresponding category with SVM classifier. The experimental results show that this method is more efficient for text classification in recognition ratio.

Li Wang, Li Li

Existence of Periodic Solutions for n-Dimensional p-Laplacian Equation with Multiple Deviating Arguments

In this paper, we mainly discuss the existence of periodic solutions for n-Dimensional p-Laplacian differential equation with multiple deviating arguments. Under some broader sign conditions, new existence results are obtained by using the degree theory.

Jinbo Ni, Juan Gao

Approximate Completed Trace Equivalence of Linear Algebra Transition Systems

We proposed the approximate completed trace equivalence of Linear Algebra Transition Systems(LATS); it is inefficient to eliminate states. We use linear polynomial programs to describe system actions, and then the completed trace equivalence of inhomogeneous linear transition systems is established. Subsequently, it proposed the theory and algorithm of approximate completed trace equivalence of linear algebra transition systems.

Hao Yang, Anping He, Zhiwei Zhang, Shihan Yang, Yang liu

A Soft Subspace Clustering Algorithm Based on Multi-Objective Optimization and Reliability Measure

Subspace clustering finds clusters in subspaces of the data instead of the entire data space to deal with high-dimensional data. Most existing subspace clustering algorithms lean on just one single objective function. Single objective function is often biased. On the other hand, most existing subspace clustering algorithms are based on wrapper approach, which brings a negative effect on the quality of subspace clustering. This paper presents a soft subspace clustering algorithm based on multi-objective evolutionary algorithm and reliability measure, called R-MOSSC. Comparing with optimization of a scalar function combining multiple objectives, it does not need to determine weight hyperparameters, and offers a deep insight into the problem by obtaining a set of solutions. Further, reliability-based dimension weight matrix from filter approach is used to enhance the performance of subspace clustering. Simulation results show that R-MOSSC is better than existing algorithms.

Zhisheng Bi, Jiahai Wang, Jian Yin

A New Type of Wavelet Threshold Denoising Algorithm

According to spectrum subtraction, this paper puts forward a new type of threshold value determination algorithm. Firstly, through the artificial extraction or by the zero point detection method, extract background noise from no sound segment. Secondly, do wavelet decomposition with background noise, and determine the threshold value on the basis of each layer’s wavelet decomposition coefficient. Then, we can make a speech enhancement for the speech signal with noise. The simulation results show that this algorithm can effectively remove the noise component and keep the details of the useful signal characteristics very well. More over, the amount of calculation is far less than the traditional threshold algorithm’s.

Li Kun Xing, Sen Qi, Wen Jing Wang

The Application of DNA Nanoparticle Conjugates on the Graph’s Connectivity Problem

A DNA computing algorithm is proposed in this paper which uses the assembly process of DNA-AuNP (DNA Au nanoparticle) conjugates to solve an NP-complete problem in the Graph theory, the connectivity problem, and a 3D DNA self-assembly algorithm model are also established. According to the algorithm we need to design the special DNA-AuNP conjugates which will assemble based on a specific graph, then a series of experiments are performed to get the final answer. This biochemical algorithm could reduce the complexity of the connectivity problem. The biochemical experimental technologies are mature and available, which will provide a practical way to validate the practicability and effect of DNA self-assembly algorithm model.

Yafei Dong, Yanchai Wang, Jingjing Ma, Li Jia

Using Inner-Outer Factorization to Solve the Spectral Factor of Discrete-Time Descriptor Systems

In this paper, we use the state-space realization of discrete-time descriptor system to solve the inner-outer and spectral factorization problems. The algorithm is based on finding two orthogonal matrices to decompose the pole separated realization of transfer function matrix, to get a stabilizing solution by sloving a algebraic Riccati equation which order usually smaller than the McMillan degree of the transfer function. We give a theorem to discuss the relation of inner-outer and spectral factorization and get the inner-outer factor of the system. Thus, the inner-outer factor is the spectral factor of the system. Finally, a simple numerical example is also illustrated.

Luhua Liang, Wei Xing, Rongwu Xiang

Multi-Objective Evolutionary Algorithm Based on Arena Principle and Niche

This paper researches the principle of RM-MEDA & MOEA/D, proposes Regularity Model Based Multi-Objective Estimation of Distribution Algorithm and Decomposition Algorithm. In order to solve the problem of Pareto optimal solutions, a new method with Niche Genetic Algorithm, a policy of double elite and a Pareto local search strategy. And use numerical simulation to prove the algorithm is better than NSGA-II.

Jian-Qiu Zhang, Feng Xu

Solving the Set Cover Problem in the Tile Assembly Model

The tile assembly model is a novel biological computing model that is scalable and has highly parallel computing ability. In this paper, the tile assembly model can be applied to solve the set cover problem which is a well-known NP-complete problem. In order to achieve this, we design a MinSetCover system which is composed of three parts, the initial configuration subsystem, the nondeterministic choosing subsystem and the detecting subsystem. Then we analysis the system’s complexity and certify the system’s correctness by experiment simulation.

Zhou Xu, Zhou Yan Tao, Li Ken Li

Boundedness for Multilinear Commutators of Calderón-Zygmund Operator on Herz-Hardy Spaces

In this paper, the boundedness for the multilinear commutators generated by Calderón-Zygmund operator with Lipschitz function is discussed, and obtain that it is bounded on Herz-Hardy spaces.

Jiangfeng Hao, Hailian Wang, Rulong Xie

Algorithm of DNA Computing Model for Gate Assignment Problem

In the core of airport operation, aircraft stands assignment (ASA) is a typical kind of combinatorial optimization. In this paper, by analyzing the ASA problem, gate assignment problem is transferred to vertex coloring model. A DNA computing model for airport gate assignment is proposed. The simulation results show that the algorithm compared with other optimization is very easy and feasible.

Zhixiang Yin, Min Chen, Qingyan Li

The Advantages and Disadvantages of DNA Password in the Contrast to the Traditional Cryptography and Quantum Cryptography

In recent years, DNA Password is a new cryptography field which appears with DNA calculation. This paper briefly introduces the DNA cryptography, Traditional cryptography and Quantum cryptography. From the basic concepts, theoretical foundations, concrete operation processes, safety basis and the current development achievements and shortcomings of the three fields, this paper obtains DNA cryptography’s advantages and disadvantages compared with traditional DNA cryptography and quantum cryptography and analyzes its causes. Then, this paper shows the achievements of DNA cryptography in practical application and its future development direction. Finally, it will make an outlook that a new mixed cryptography system can be created on the advantages of the three kinds of cryptography.

Jun Jiang, Zhixiang Yin

The Principle and Algorithm for Generating Incidence Matrix for Any Arbitrary Network

In this paper, a new principle and algorithm for obtaining the incidence matrix for any arbitrary network which were represented by nodes and segments while we have already known the endpoints of each line segments in 2D space were introduced. In addition, a calculated procedure was compiled by C++ language and two extra examples were calculated. The results shown that the principal and algorithm we stated were right for auto-generating of the incidence matrix for any arbitrary network.

Wei Zhang, Chao-bo Lu, Hai-bo Li

An Efficient and Improved Particle Swarm Optimization Algorithm for Swarm Robots System

In recent years, the number of researches in which swarm intelligence shown by individual communication in swarm robots is increasing. As one of the representative algorithms in swarm intelligence, particle swarm optimization has been applied to many fields because of its simple concept, easy realizing and good optimization characteristics. However, it still has some disadvantages such as easy falling in the local best situation and solving the discrete optimization problems poor. In this paper, genetic algorithm has been integrated with particle swarm optimization to improve the performance of the algorithm; the simple particle swarm optimization algorithm has been simulated in the Player/Stage and compared with the particle swarm optimization. The simulation shows that the algorithm is faster and more efficient.

Zhiguo Shi, Xiaomeng Zhang, Jun Tu, Zhiyong Yang

Ratio Estimation and Regression Estimation Method in Three-Stage Sampling

This paper discusses the ratio estimator and regression estimator of population mean in the three-stage sampling, in which all level of unit sizes are equal, when some auxiliary information can be available.

Shu Lv, Bing Chen

Oscillation Criteria for Second Order Functional Differential Equation

In this paper, by introducing nonnegative kernel function H(t, s) and h(t, s), using the generalized Riccati technique and the integral averaging technique, second order functional differential equations with deviating arguments are discussed.

Nan Tang, Jie Zhang

An Outlier Detection Method for Robust Manifold Learning

Manifold learning algorithms have been widely used in data mining and pattern recognition. Despite their attractive properties, most manifold learning algorithms are not robust to outliers. In this paper, a novel outlier detection method for robust manifold learning is proposed. First, the contextual distance based reliability score is proposed to measure the likelihood of each sample to be a clean sample or an outlier. Second, we design an iterative scheme on the reliability score matrix to detect outliers. By considering both local and global manifold structure, the proposed method is more topologically stable than RPCA method. The proposed method can serve as a preprocessing procedure for manifold learning algorithms and make them more robust, as observed from our experimental results.

Chun Du, Jixiang Sun, Shilin Zhou, Jingjing Zhao

Motif Identification Based on Local Structure Clustering

Network motif identification is significant in that motifs generally reflect functionalities. However, the task is greatly challenging due to diverse patterns of motifs possibly existent in a network and high computation complexity for large scale networks. In this study, we propose a network motif identification method, FCMD, based on clustering subgraphs according to their local structures. By modeling local-topological feature of a network with a feature vector, the approach maps motif identification problem into a clustering problem of feature vectors in a feature space, which greatly reduces computation complexity hence facilitates very large scale networks. Experiments on 8 real networks, including biochemical network, neural network, electronics circuit network, et al., indicates that the proposed method is very effective in motif detection with computation complexity approximately independent to the scale of the network.

Junying Zhang, Yuling Xue

Computation of Synchronic Distance in Marked S-net

Synchronic distance is an important analyzing metric to describe the synchronic relationship between two events. Due to the difficulties to calculate the synchronic distance, which is determined by both the structure characteristics and the initial marking of the net system, no simple and feasible algorithms have been presented to get the synchronic distance of normal Petri nets. However, the computations of synchronic distance in some special subclass of Petri nets, such as marked T-graph, marked S-graph, and marked T-net, are relatively simple and feasible. The solution of the synchronic distance in another subclass of Petri net-marked S-net, is given in this paper. The synchronic distance of the marked S-net is directly obtained according to the structure of the net systems and the distribution situation of initial marking, which makes the solution of the synchronic distance become more feasible. The corresponding solution theorems are also given in the paper.

Li–li Wang, Xian-wen Fang, Dao-hao Liu

Petri Net Modeling and Analysis Based on Gene Logic Network

Petri net has recently emerged as a promising tool for the modeling and analysis of molecular networks. In this research, gene logic network constructed by approach-logic analysis of phylogenetic profiles method is described. In order to depict the logic interactions between genes, a new Petri net formalism with augmented inhibitor arc is proposed, which is called ALTPN. Two different types of places and different transitions are formulated in ALTPN, and then corresponding firing rule is given. Further, ALTPN of all 1-order and 2-order gene logic types are listed. Finally reachability graph method is used to accomplish asynchronous dynamic analysis of gene logic interactions in colon cancer and some conclusions are drawn.

Yulin Zhang, Shudong Wang, Hongyue Wu, Yan Yi

DOA Estimation for Nonuniform Linear Arrays Using Root-MUSIC with Sparse Recovery Method

Direction-of-arrival (DOA) estimation with nonuniform linear arrays (NLA) using the sparse data model is considered. Different with the usually used sparse data model, we introduce a linear interpolation operator which can transform the data of the NLA to the data of a virtual uniform linear array (VULA). We first reduce the dimension of the model using the singular value decomposition technique, next recover the solution of the reduced MMV using a compressed sensing (CS) algorithm, then get the data of the VULA using the recovery result and the linear interpolation operator, and lastly use root-MUSIC to estimating DOA. The method is called CS-RMUSIC. The experiments illustrate the good efficiency of the CS-RMUSIC algorithm.

Xinpeng Du, Xiang Xu, Lizhi Cheng

Research of ROM Based on Molecular Beacon DNA Computing

ROM is an indispensable part in the DNA computer system. It is used to store binary data. Based on DNA computing, the ROM developed by molecular beacon can realize the data storage in a high speed and on a large scale. And it has direct influence on the development process of DNA computer technology. This paper puts forward a new implementation method of logic gates, which based on the molecular beacon calculation mode, and realize a simple combinational logic circuit, the construction of the ROM. In this method, logic gates are represented by molecular beacons. Input signals are represented by single strands of DNA, which can realize the operations of logic gates in DNA type; the connection between two logic gates according to the circuit levers can be realized by the marks of tubes. The construction of the ROM, which use the molecular beacon and based on DNA computing, will play a huge role in advancing the development of DNA computer.

You-rui Huang, Jing Wang, Xiao-min Tian

Improved Genetic Algorithm for Solving Optimal Communication Spanning Tree Problem

Optimal Communication Spanning Tree (OCST) is a well-known NP-hard problem on the graph that seeks for the spanning tree with the lowest cost. The tree cost depends on the communication volume between each pair of nodes. This paper proposed an improved Genetic Algorithm combining with Ahujia and Murty’s Tree Improvement Procedure. The proposed algorithm was experimented on known benchmark tests which used in many papers related to OCST problem, and random instances from 200 to 500 vertexes. The experimental results show that the proposed algorithm is better than the heuristic and out-performance the most recent evolutionary algorithm approaches.

Nguyen Duy Hiep, Huynh Thi Thanh Binh

Algorithm for Generating Decision Tree Based on Adjoint Positive Region

In this paper, all of the three relationships of attribute selection standard based on positive region, based on rough bound and based on attribute dependency are firstly analyzed. At the same time, it is proved that the three kinds of selection attribute standards are equivalent to each other. Furthermore the advantages and disadvantages of algorithm for generating decision tree based on positive region are analyzed. Meanwhile, aiming at these disadvantages, a new selection attribute standard based on adjoint positive region is proposed. The decision tree generated with the new standard of attribute selection has the following characteristics: fewer leaf nodes, fewer levels of average depth, better generalization of leaf nodes. Finally an example is used to illustrate the advantages of this new selection attribute standard.

Jing Gao

A Historical Study About the Developing Process of the Classical Linear Time Series Models

Through investigating the original literatures of some statisticians who have made key contributions to the development of the ARMA model, the author not only analyzes the evolution process of AR, MA and ARMA model, but also emphasizes the inheritance relation between them. It will lay a foundation and provide a clear clue for the study of the discipline history of time series analysis.

Shu-yuan Nie, Xin-qian Wu

A Novel Attributes Partition Method for Decision Tree

In the decision tree’s making phase, it is frequent to find the optimal partition of elements with different values of a category attribute at a node. This needs to search over all the partitions for the one with the minimal impurity, which is exponential in

n

. We present a new heuristic search algorithm, SORT_DP, to find an effective partition, which is polynomial in

n

. The method uses the mapping from the class probability space to the sub-spaces and the technique of dynamic programming. By comparing the performance against other methods through experiments, we demonstrated the effectiveness of the new method.

Zhen Li, Aili Han, Feilin Han

Synthesized Algorithms of Concept Similarity Based on the Semantic Correlation Prerequisite

This paper offers a synthesized approach of solving the shortage of the traditional similarity in ontology mapping. First, it selects high correlation concepts by Hirst-St-Onge semantic relativity algorithms, in order to reduce the complexity of the account. Then according to the characteristic of the ontology concept, we designs a synthesized method through calculating the respective similarity in name, attribute and instance of concepts, and works out weight by Sigmoid function. Experiment data indicates that it makes the better accuracy than the traditional methods.

Hui-lin Liu, Qing Liu

A Framework for Density Weighted Kernel Fuzzy c-Means on Gene Expression Data

Clustering techniques have been widely used for gene expression data analysis. However, noise, high dimension and redundancies are serious issues, making the traditional clustering algorithms sensitive to the choice of parameters and initialization. Therefore, the results lack stability and reliability. In this paper, we propose a novel clustering method, which utilizes the density information in the feature space. A cluster center initialization method is also presented which can highly improve the clustering accuracy. Finally, we give an investigation to the parameters selection in Gaussian kernel. Experiments show that our proposed method has better performance than the traditional ones.

Yu Wang, Maia Angelova, Yang Zhang

Simulation of Extracting Phase from the Interferogram by the Phase Shifting Method

The phase information extraction from the interference fringe is a key step in optical interferometry. Phase shift extraction method is proposed. This method is introduced amount of phase shift in the reference light, changing the relative phase of two coherent wavefront, comparing with a different amount of phase shift value in the intensity light to solve the points phase. The four steps phase shifting extraction is simulated. The simulation results show that the method not only has a strong ability of the inhibition noise, but also can identify the arbitrarily shaped interference fringes.

Zhanrong Zhou, Aijun Li, Hongxia Wang, Yunfang Zhao, Jin Ma

Research and Implementation of CAPTCHA Based on Ajax

Currently, most authentication system requires users to answer the CAPTCHA (Completely Automated Public Turing Test to Tell Computer and Human Apart) before gaining the system access. CAPTCHA is a standard security technology for distinguish between human and computer program automatically. This paper describes the Ajax technology and its advantages of web interactivity and efficiency of the user to enter the CAPTCHA may appear misjudgment the inconvenience. Designed Ajax-based CAPTCHA scheme which can prompt the user input of right or wrong. This scheme using the characteristics of Ajax technology asynchronous transmission, after the user input CAPTCHA, immediately the prompt of entry correct or not gave. Greatly increase the website interactivity, improve the user experience, not only ensure the user security, but also improve software friendly degree.

Xiaokui Chen, Xinqing Lin

Numerical Characteristics of Rotor Angle in Power System with Random Excitations

With the integration of renewable power and new load, much more random components are operating in the power system. In this paper, according to stochastic differential equation (SDE) theories, the SDE model of one machine and infinite bus (OMIB) system is constructed. The simulations show that nonlinear system can be replaced by linear system in the neighborhood of the initial point by means of Euler-Maruyama (EM) method. On the basis of the explicit solution of the linear stochastic differential equation, we have obtained the mathematical expectation, variance, and density function of rotor angle under nonlinear state. Moreover, the limit of the density function has been discussed as well.

Jianyong Zhang, Mingang Hua, Hongwei Wang

An Epidemic-Dynamics-Based Model for CXPST Spreading in Inter-Domain Routing System

We study the CXPST attack which aims at the destruction of inter-domain routing system and propose a spreading model to represent the threatening scale. By analyzing the process we illuminate the mechanism of how CXPST seizes the BGP deficiencies to paralyze the Internet control plane from the traffic attack of data plane, and then the spreading model named as EDM-CS is presented based by the epidemic dynamics theory. Parameters of the model are closely associated with the real network topology and BGP router overloading condition which reflect the features of the CXPST spreading. In virtue of the classical BA scale-free network, spreading density that derives from EDM-CS behaves great consistency with the simulation results based on the collected data from CAIDA. This model can help understanding CXPST attack and providing a basis for predicting the spreading trend, as well as investigating effective defense strategy.

Yu Wang, Zhenxing Wang, Liancheng Zhang

An Approach for Diversity and Convergence Improvement of Multi-Objective Particle Swarm Optimization

To improve the diversity and convergence of multi-objective optimization, a modified Multi-Objective Particle Swarm Optimization (MOPSO) algorithm using Step-by-step Rejection (SR) strategy is presented in this paper. Instead of using crowding distance based sorting technique, the SR strategy allows only the solution with the least crowding distance to be rejected at one iteration and repeat until the predefined number of solutions selected. With introduction of SR to the selection of particles for next iteration, the modified algorithm MOPSO-SR has shown remarkable performance against a set of well-known benchmark functions (ZDT series). Comparison with the representative multi-objective algorithms, it is indicated that, with SR technique, the proposed algorithm performs well on both convergence and diversity of Pareto solutions.

Shan Cheng, Min-You Chen, Gang Hu

IRSR: Recover Inter-Domain Routing System from a Higher View Beyond Internet

Nowadays security situation of Internet is getting surprisingly worse. Many studies show that under the intensive paralyzing attack, inter-domain routing system which acts as the critical infrastructure of Internet, will falls into large-scale and long-term failure both of the routing nodes and links, endangering the running performance of Internet. Based on the centralized control theory, IRSR model proposed here builds an independent Decision Center above the existing inter-domain routing system, it could provide global situation awareness by using the sensor networks and controller networks deployed in each AS, and implements fast recovery from failures based on methods including pre-computed failover topology and consistent view. IRSR guarantees the maximum compatibility with existing routing protocols and structure of inter-domain routing system, which will reduce the deployment cost and complexity. Moreover, it also overcomes the problems like concealed AS information and long BGP convergence, which improves the recovery velocity and coverage rate.

Yu Wang, Zhenxing Wang, Liancheng Zhang

A New Parallel Genetic Algorithm Based on TriBA Topological Structure

In order to advance the speed of solving a large combinatorial problem, this paper proposes a new master-slave parallel genetic algorithm (PGA) based on the triplet based architecture (TriBA) topological structure. With the special topological structure by which the problem can be mapped into this model, the TriBA is able to realize the parallel computing in child topological structures and the parallel real-time communication. The theoretical analysis proves that the proposed TriBA PGA can enhance the computation speed and decrease the communication costs, thereby resulting in a novel PGA model to handle the large combinatorial problems.

Kang Sun, Wook Ahn Chang

Based on Grey Linguistic Multi-Criteria Decision Making Method for Real Estate Websites’ Evaluation

The evaluation system of real estate website has been studied and it shows that there are still many drawbacks that lead to inaccurate evaluation information and affect the decision of house buyers. Therefore, the thesis employs the Grey Linguistic Multi-Criteria Decision-Making (GLMCDM) Model to improve the evaluation system of real estate website. By establishing the Grey Linguistic Multi-Criteria Decision-Making (GLMCDM) Model, customers’ evaluation information is analyzed, then the proper apartments can be recommended to house buyers on the basis of their information. Finally, the feasibility of the model is proved by calculation.

ZhiFeng Li, LiYi Zhang

Generated Fast of the Aircraft Carrier Dimensions in Preliminary Design

This paper studies the overall elements of aircraft carrier at the stage of demonstration and preliminary design. Firstly, the estimation formula of the attributes is developed, which should be considered in preliminary design of ship. Secondly, the basic multi-objects optimize model is built up according to weighted vector obtained by lowest deviation method. Finally, optimization based on the simulated annealing algorithm is achieved. The computing system will find the most reasonable scheme of overall elements through the model after the designer determines the constraints of the principal dimensions and the number of carrier-based aircraft and the importance of each objects.

Yu-juan Wang, Sheng Huang, Xin-yue Fang, Gang Wang

Vehicle Scheduling Problem on Trees

In this paper, we study a subproblem of vehicle scheduling problem, which is in general strongly NP-hard. In this problem, the road map is a tree, the release times and the handling times of all the tasks are zero, the deadlines of all the tasks are all the same, and the vehicle has to return to the root finally. We aim to find an optimal schedule such that the total value of the completed tasks are maximized. We show that this problem is NP-hard, and give a pseudo polynomial time algorithm for this problem.

Jie Zhou, Tianming Bu, Hong Zhu, Yixiang Chen

Reflections on the Enterprise to Change Management Concept: In Perspective of Concept Innovation

A successful enterprise must have a set of modern ideas. In the modern business system, the ideological concept is most important. With the rapid development of the world economy and science and technology, more and more people have increasingly recognized that the most needed of the outstanding enterprise is the continuous innovation of the ideas, not the profit index and not sophisticated computer systems. Based on the connotation of the concept and innovation, this paper analyzes more deeply the necessity to concept innovation of the enterprise, and puts forward several suggestions for an enterprise to change the management concept.

Nana Cao, Bin Lu

Relaxed Two-Stage Multisplitting Algorithm for Linear Complementarity Problem

In this paper, the authors first set up relaxed two-stage algorithm for solving the linear complementarity problem, which is based on the two-stage splitting algorithm, parallel computation and the multisplitting algorithm. This new algorithm provides a specific realization for the multisplitting algorithm and generalizes many existing matrix splitting algorithms for linear complementarity problems and linear systems. And then, they establish the global convergence theory of the algorithm when the system matrix of the linear complementarity problem is an H-matrix, M-matrix, strictly or irreducibly diagonally dominant.

Ban-xiang Duan, Dong-hai Zeng

The Analysis Methods About Business Process of E-Commerce Based on the Petri Net

With the development and popularity of the Internet, electronic commerce has become an important mean of business in the developing current-social and economic. Presented methods on business process management mainly analyzed the correctness of the workflow model. However, these methods can’t easily uncover the underlying risks existing in the model. In this paper, the analyzing method about the underlying risks of the business process is presented based on the Petri net, and we analyze the specific example by the proposed method. The theoretic analysis and the example effect show the method is effective.

Ouyang Hong, Xian-wen Fang, Min Yu

Associated Relaxation Time for an Optical Bistable System with Coupling Between Non-Gaussian and Gaussian Noise Terms

The relaxation time

$$ T $$

T

of an optical bistable system with multiplicative non-Gaussian and additive Gaussian noise terms is investigated. The results indicate that the decay rate of fluctuation changes from slowing down to speeding up with increasing of non-Gaussian noise correlation time

$$ \tau $$

τ

. But with increasing of the parameter

$$ q $$

q

, the decay rate changes from speeding up to slowing down. The additive noise intensity

$$ D $$

D

and correlation intensity

$$ \lambda $$

λ

slow down the fluctuation decay in the stationary state of the system.

Bing Wang, Xiuqing Wu

Bicyclic Graphs with Nullity n−5

Let

$$ G $$

G

be a simple undirected graph on n vertices,

$$ A(G) $$

A

(

G

)

be its adjacency matrix. The nullity

$$ \eta (G) $$

η

(

G

)

of the graph

$$ G $$

G

is the multiplicity of the eigenvalue zero in its spectrum. In this paper, we characterize the bicyclic graphs with nullity

$$ n - 5 $$

n

5

.

Tian-tian Zheng

Study on Security Supervising and Managing Methods of the Trusted Cloud Computing Based on Petri Net

With the constant popularization of cloud computing, the importance of security problem is gradually increasing and becomes the important factor which restricts cloud computing development. Currently, combination of cloud computing and trusted computing technology are the main topic on cloud security. In the paper, according to analyzing the research situation of the cloud computing security, a novel trusted cloud computing technology according to the related technology is proposed, and a secure supervising and managing methods by behavioral analysis and service composition is analyzed based on Petri net.

Lu Liu, Xian-wen Fang, Xiang-wei Liu, Jing Ji

A Method for Security Evaluation in Cloud Computing Based on Petri Behavioral Profiles

To solve the problem of security evaluation in cloud computing, the modeling and analyzing methods of security evaluation about cloud computing are very important. Firstly, extending behavioral profiles into comprehensive behavioral profiles. Then, studying the degree of keeping consistent behavior relation which looks as the objective evaluation function based on comprehensive behavioral profiles. Finally, using behavioral theory of Petri Net to solve the evaluation function, a new method for security evaluation in cloud computing is proposed. The theoretical analysis and specific example show that the method is very effective.

Xianwen Fang, Mimi Wang, Shenbing Wu

The Homomorphic Encryption Scheme of Security Obfuscation

The cloud storage service, according to the data on the cloud computing safety protection problem, the paper presents secure obfuscating homomorphism encryption scheme. Constructing a point function obfuscator that based on perfectly one way probability hash function in scheme, construction depends on hash function and the computational difficulty problems, then use the computational difficulty problems, to realize the encrypted homomorphism function, also guarantee the function of the point function obfuscator at the same time, the scheme raises the security of the encrypted data. This paper provides the security proof of the scheme, and shows that the scheme is feasible.

Gao-Xiang Gong, Zheng Yuan, Xiao Feng

Construction of Barycentric Blending Rational Interpolation Over the Triangular Grids

Laying down the foundation for the basic function of the barycentric rational interpolation, some rational interpolations over all kinds of triangle grids were constructed, and duality theorems and characterization theorems were given, some significative characters are obtained. Compared with the traditional rational interpolation based on continued fraction, the barycentric blending interpolation inherited the advantages of the simple expressions, has many advantages such as small calculation quantity, good numerical stability, no poles and unattainable points, etc. The barycentric blending interpolation can also be extended to both higher dimensions, vector-valued case and matrix-valued case.

Qiang Li, Feng Xu

Hopf Bifurcation Analysis in an Intracellular Calcium Oscillation Model

Besides the mechanism of the calcium-induced calcium release (CICR), the Kummer-Olsen Calcium oscillation model focuses on the effect of the feedback inhibition on the initial agonist receptor complex by calcium and activated phospholipase C, as well as receptor type-dependent self-enhanced behavior of the activated G

α

subunit. The nonlinear dynamics of this model are investigated based on the theory of center manifold, bifurcations and stability of the equilibrium. Computations show that both appearance and disappearance of calcium oscillations of this system are related to supercritical Hopf bifurcation of the equilibrium. Numerical simulations including bifurcation diagram, temporal evolution and phase portraits, are performed to confirm the theoretical analysis. These results may be instructive for understanding the mechanism of other similar calcium oscillation models.

Yuanhua Li, Zhou Yi, Hongkun Zuo

Study on Protein Structure Based on Reverse Hamilton Path Models

We present a new method for studying protein structure based on reverse Hamilton path models. A protein conformation with n sequences is changed to a weighted completely graph

K

n

. The reverse minimum Hamilton path in this graph matches the protein reverse sequence and n is positive proportion to length of reversed Hamilton path. The time of finding a reverse minimum Hamilton path grows quickly when n rise.

Xiaohong Shi

Applications

Frontmatter

Based on the Queuing Model of CAN Bus Simulation and Application

In this paper, a queuing model based on the CAN is established and its simulation and application are considered. The specific steps for, through the hypothesis model related parameters, make the whole model CAN achieve stable state. Through the calculation model of the probability of no data transmission, data in the model in the probability of transmission, data sending average queue goal number, average each data queue time, average each data in the model of the time and other related parameters modeling. By solving the queuing model, the data in the CAN bus to send on quantitative analysis, which CAN be used to CAN bus to transfer data distribution scheme optimization.

Jing Zhang, Tao Li

Hierarchical Modeling Fault-Error-Failure Dependencies for Cyber-Physical Systems

While cyber-physical system (CPS) has grown in size and complexity, the existing single node failure of system are confronting some serious challenges. The strong coupling of software and physical processes in the emerging field motivates the development of new methods to respond to failure in both the cyber and physical domains. This paper presents formalized definitions for CPS from the view of hierarchical level model. The relationships between faults, errors and failures in the resource, service and process level are introduced. The application of stochastic Petri nets (SPN) on fault-error-failure dependencies Model in CPS is presented. Based on the model analyzing, the Fault-Error-Failure dependency relationships between resource, service and process are presented. The simulation results show the chances of resource faults are larger than the service error; the effects of a non-detected error perceived from resource level are less than that for the service level.

Shixi Liu, Xiaojing Hu, Jingming Wang

A Comparative Study of State Transition Algorithm with Harmony Search and Artificial Bee Colony

We focus on a comparative study of three recently developed nature-inspired optimization algorithms, including state transition algorithm, harmony search and artificial bee colony. Their core mechanisms are introduced and their similarities and differences are described. Then, a suit of 27 well-known benchmark problems are used to investigate the performance of these algorithms and finally we discuss their general applicability with respect to the structure of optimization problems.

Xiaojun Zhou, David Yang Gao, Chunhua Yang

Data Acquisition and Signal Processing for Endless Rope Continuous Tractor Monitoring

Through datas acquisition, processing the data and signal, to achieve full, real-time monitoring of running state of endless rope continuous tractor. Research and analysis the software and hardware of the endless rope continuous tractor monitoring, it has the function of the winch position and speed of real-time display, leakage communication, language broadcaster, fault logging, winch driver identification, fault masking, two-speed winch speed selection. It can be comprehensive protected for emergency stop to lockout, overwinding protection in the head and tail in running, and remote monitoring through the host computer.

Wei Chen, Hai-shun Deng

A Subcarriers and Bits Allocation Scheme for Multi-User OFDMA System

In Multiple-In Multiple-Out (MIMO) Broadcast systems with limited feedback, when receivers are equipped with multiple antennas, the so-called quantization error of channel direction matrix were unavoidably introduced. This quantization error will result in the reduction of system capacity since it was referenced in the beam forming design. In this paper, we proposed a robust beam forming method based on MMSE, which considers the statistical characteristics of the quantization error for channel direction matrix. Simulation results show that the proposed method effectively enhanced system capacity, reduced bit error rate (BER), as well as mitigated the Plateau Effect.

Jingxue Ran, Bo Xiao

Study on the Prediction of Gas Content Based on Grey Relational Analysis and BP Neural Network

The paper mainly illustrated a kind of BP Neural Network model in MATLAB Neural Network Toolbox to predict gas content of the coal seam based on analyzing grey relational degree. This model constructed a method of gas content prediction by choosing four dominate effect factors (Coal seam buried depth, Geologic structure, Roof lithology, Coal seam thickness) as the input parameters. It has been established for training and testing, and forecasting the gas content of coal seam by using the learning samples which were collected from the instances of typical exploited borehole data of Panyi East coal mine in Huainan coal mining area. The results show that the model is an efficient prediction method for gas content, and its prediction accuracy and feasibility are better than the traditional predicting methods. It also can better meet the practical requirements of safety production in coal mine including provide some references for mine gas disaster prevention.

Jiajia Lu, Ping Chen, Jinshan Shen, Zepeng Liang, Huaze Yang

Optimization Analysis of Dynamic Sample Number and Hidden Layer Node Number Based on BP Neural Network

Taking use of BP neural network theory, a cyclic search method between dynamic training samples number and dynamic hidden nodes number is proposed to improve the prediction accuracy of network model. By increasing the training samples one by one to control the network training, searching dynamic sample error expectation matrix, and finally getting the best training sample number, with the goal of minimum error expectations. Thus, through the optimization model of hidden nodes number, searching the number of hidden layer nodes of network minimum output error. The results of the analysis of examples shows that, with the increasing number of training samples, the network output error expectation experienced three stages, namely recurrent big error stage, yield decline error stage and stable small error stage. But with the increasing number of hidden layer nodes, the result is on the contrary. This shows that proper number of training samples and hidden layer nodes is of great significance to improving the output precision of neural network.

Chunyun Xu, Chuanfang Xu

Measurement of Concentration and Size Distribution of Indoor PM10

Adopting the microscopic observation imaging and digital image processing technologies, this paper researches a measurement method to the concentration and size distribution of indoor PM10. A new image threshold segmentation method based on the genetic algorithm and Otsu method has been put forward, which can obtain the segmentation threshold by the global optimization, and researches a identification algorithm to the main morphological parameters of a single indoor suspended particulate matter such as size, shape coefficient and the fractal dimension, then calculates the concentration and size distribution of particulate matter using data fusion method. The experimental results show that the method has advantages with intuitive, high precision, fast processing speed, easily data statistics, clearly data analysis and stable measuring results.

Hongli Liu, Xiong Zhou, Lei Xiao

A Novel Iris Segmentation Method Based on Multi-Line

In the iris authentication system, the existence of eyelids and eyelashes noises might generate negative effect on pattern analysis. This paper proposes a novel and accurate iris segmentation method which adequately considers the edges and statistical feature to detect the eyelids and eyelashes noises in the captured iris images. First, multi-scale edge detection is used to get the iris coarse locations, and rank filter is employed to smooth images for determining a more accurate searching area of eyelids. Second, morphological operations as well as line Hough transform are presented to reserve the available edge points for multi-line eyelids fitting. Specially, the adaptive average intensity of individual iris image based on region of interest (ROI) is educed to get the statistical threshold for eyelashes detection. Experimental results indicate that the proposed method can effectively remove the occlusion caused by eyelids and eyelashes, and increase the amount of information (AOI) of segmented iris and improve the iris location accuracy.

Yuhong Jia, Wanjun Hu, Xiaoxi Yu, Miao Qi

Maxwell Demon and the Integration Algorithm of Clustering-Partitioning

Maxwell Demon Model was proposed in 1871 to challenge the second law of thermodynamics. While ignoring the energy problem, we can find that Maxwell has started the original clustering model, which implements the clustering of quick molecule and slow molecule naturally. In this paper, we proposed a new model called MCP model, which integrated Maxwell multi-Demon and the ants’ movements, and implemented the integration of sample clustering and the whole data set partitioning. We tested our algorithm on UCI examples, the results show it behaves well.

Jinbiao Wang, Famin Ma, Hongwei Huang

Image Retrieval Method Based on Hybrid Fractal-Wavelet Image Coding

This paper presents a hybrid image coding method combined with fractal image coding and wavelet transform. Exploite wavelet transform decomposed an image into some different frequency subbands. We introduced two different processing courses of fractal coding in high frequency subbands and low frequency subbands, obtained corresponding coefficients as index file of an image. Differently with image compression we pay more attention on the accuracy of image retrieval and time consuming. From experimental results we can obtained satisfied results of image matching exploited index file which produced by our proposed hybrid image coding method.

Haipeng Li, Xu Ji, Jianbo Lu

Investment Risk Evaluation of High-Tech Projects Based on Random Forests Model

The investment of high-tech projects is characterized with high risk and huge profit, so a scientific and accurate risk evaluation is of importance to make decision. Based on the analysis of the indicators influencing the investment risk, a typical sample set was chosen according to the quantitative score results from the experts. After training, a random forests regression model was established to comprehensively evaluate the investment risk. The assessment result from a case shows the model not only can give a correct rank to the unknown samples, but also give the contribution degree and importance of the indicators. Subsequently, aimed at the leading model parameters, many tests were done to illustration their impact on the output results of the model. Finally, the importance of variables was analyzed, and was compared with that of projection pursuit model. The above results show it has stronger adaptability and robustness.

Guangzhou Chen, Jiaquan Wang, Chuanjun Li

Design and Implementation of Flash Online Recorder

Online recorder software is used extensively because it can acquire data directly and conveniently. More and more online recorder software which base on Flash platform is invented, however, all of these need support of Flash Media Server, it increases expense of development. This paper is trying to achieve local coding and storage by Flash ActionScript3.0 and open source library, supplying a new solution for online recorder.

Minhui Wang

The Intelligent Campus Energy-Saving System Research Based on Power Line Carrier

This paper introduces a power line carrier technology based on MCU-51 of the campus power saving control system’s working principle and structure; At the same time, it introduces direct sequence spread spectrum and half duplex asynchronous modem PL2102 carrier chip, which are used in the power line carrier application system can realize the classroom management and control of the electric light; With PL2102 are given for the control of electric light’s basic principle and the method how to realize through software and hardware, along with its design schematic diagram.

Jinpeng Li, Guangbin Xu

Synthetic Decision Support of Broadcasting and Television System

To improve the traditional decision support system (DSS) with data driven or model driven only, a synthetic DSS for broadcasting and television system is proposed in this paper. It is consisted by three main bodies which are the combination of data base, model base and method base, the combination of data warehouse and on-line analysis processing (OLAP), and the combination of knowledge base and data mining. The use case of this synthetic DSS is also analyzed in this paper. And the result of typical model proves its validity.

Fulian Yin, Jianping Chai, Jiecong Lin

Research on Breast Cancer Metastasis Related miRNAs Network Based on a Boolean Network

Breast cancer (BC), which is one of the major malignant tumors, is a serious threat to women’s health with noticeably increased mortality. BC starts as a local disease, but it can metastasize to the other organs. Metastatic BC is the major difficult factor for treatment of advanced breast cancer. It suggests that early diagnosis for patients is of vital importance. Recent studies proved the involvement of microRNAs (miRNAs) in BC metastases. It was found that miRNAs contribute to oncogenesis by functioning as down-regulated tumor suppressors, and also can function as over-expressed oncogenes. The goal of this study is to construct a comprehensive BC metastasis related miRNAs regulatory network by collecting and integrating relevant information, the analysis results based on a Boolean network shows that it has great biological significances and provides new perspective for the later research.

Wenying Zhao, Yafei Dong

Design of Gas Monitoring System Based On Embedded ZigBee Module

In order to solve the problems of traditional mine gas monitoring system, a design proposal based on wireless sensor network technology is put forward, which takes ARM as control core. The gas concentration data is collected by underground wireless sensor node, and converge on a central node by ZigBee network. At last, the data is sent to the monitoring center. Then the monitoring center analyzes and processes data received and send corresponding instructions to sensor network according to the results of data processing. On the basis of the above steps, real-time monitoring of mine gas concentration is achieved in this system. This system overcomes the shortcomings of the traditional mine gas monitoring methods, which has some merits such as flexible networks, low cost and strong reliability etc.

Rongrong Gu, Kelei Sun, Wei Hao, Ping Ren

Berth-Crane Allocation Model and Algorithm of Container Berths in the Uncertain Environment

According to the randomness of the vessel’s arrival time and handling time, the establishment of a randomly-oriented environment container berths—crane allocation model, the optimizing goal is to minimize the average ship-waiting time. Taking into account the complexity of the model solution, this paper offers the design of an improved genetic algorithm to reduce the searching space, and according to the characteristics of the optimal solution. With testing example to verify that the model can simulate decision-making environment of berths—crane allocation problem and reflect the decision-maker’s attitude toward risks and preferences. The algorithm can gain a stable and satisfactory solution within the operating time.

Jian-xin Liu, Yu-yue Du, Yong-fa Hong, Lin-lin Sun

Numerical Research on Coal Mine Ground Stress Field Based on Multi-Objective Optimization Method

With the depth and intensity of coal mining increasing, in situ stress plays more and more important roles in the surrounding rock control. This paper establishes a theoretical model for the in situ stress inversion problem, making use of multi-objective optimization method, and proposes an integrated stress analysis method, in which geo-mechanical method, finite element method, computer technology are adopted. This study method can acquire the magnitudes and directions of coalmine ground stresses via some discrete measured data, considering the basic influencing factors such as the folds and faults. One coalfield as the example of Huainan coalmine has been studied, and the results indicate that the relative errors are less than 10 %, which can mostly meet the requirement of the mining application. Then, the distribution of horizontal stresses has been predicted, which can provide an important reference for the stability design of mine openings, as well as the type and amount of ground support needed to maintain a safe working environment for coal miners.

Qinjie Liu, Xinzhu Hua, Ke Yang

Mapping Loops onto Coarse-Grained Reconfigurable Array Using Genetic Algorithm

Coarse-grained reconfigurable array (CGRA) is a competitive hardware platform for computation intensive tasks in many application domains. The performance of CGRA heavily depends on the mapping algorithm which exploits different level of parallelisms. Unfortunately, the mapping problem on CGRA is proved to be NP-complete. In this paper, we propose a genetic based modulo scheduling algorithm to map application kernels onto CGRA. An efficient routing heuristic is also presented to reduce the mapping time. Experiment result shows our algorithm outperforms other heuristic algorithms both in solution’s quality and mapping time.

Li Zhou, Dongpei Liu, Min Tang, Hengzhu Liu

The Investigation and Realization of IPSec Strategy Based on Linux for IPv6

IPSec is IP security protocol made by IETF which is designed for the next generation network, and is the mandatory part of IPv6 protocol stack. In this paper, the IPSec protocol and the Netfilter mechanism of Linux are introduced briefly. Then a new design idea and system design scheme is presented in detail, the final realization of IPSec protocol which is based on the Netfilter mechanism shows this scheme properly, efficiently and stability, which sets up the basis for the development of security route, VPN, next generation network.

Rui Su, Wei Su

An Improved Search Strategy for 8-Digits Puzzle

The search strategy for the 8-digits puzzle is discussed. The state space of the 3-digits puzzle consists of one odd-state-loop and one even-state-loop. For any instance of the 8-digits puzzle, we reduce each state-loop of 3-digits sub-problem to one class-node. If there is a common state between two state-loops, an edge is added between the two class-nodes, and the common state is attached to the edge as its weight. Based on this, we designed an improved method to make the movement in state-loop be compressed from different layers to one layer so that the value of

g

(

n

) decreased and the proportion of heuristic function

h

(

n

) in evaluation function

f

(

n

) increased. The running results show that the efficiency of algorithm has been improved.

Aili Han, Zhen Li, Feilin Han

DNA Sequence Motif Discovery Based on Kd-Trees and Genetic Algorithm

In the post-genomics era, recognition of transcription factor binding sites (DNA motifs) to help with understanding the regulation of gene is one of the major challenges. An improved algorithm for motif discovery in DNA sequence based on Kd-Trees and Genetic Algorithm (KTGA) is proposed in this paper. Firstly, we use Kd-Trees to stratify the input DNA sequences, and pick out subsequences with the highest scoring of the hamming distance from each layer which constitute the initial population. Then, genetic algorithm is used to find the true DNA sequence motif. The experiment performing on synthetic data and biological data shows that the algorithm not only can be applied to each sequence containing one motif or multiple motifs, but also improve the performance of genetic algorithm at finding DNA motif.

Qiang Zhang, Shouhang Wu, Changjun Zhou, Xuedong Zheng

Footplant Detection Based on Adjusting the Foot Height Threshold Automatically

In this paper, we present a footplant detection method by adaptive determining foot height threshold. In our method, we firstly divide one step into a number of stages, each stage has different types of constraints. Then adaptively electing foot height threshold according to motion type and the length

$$ l $$

l

of the minimum constraint frame that designed by the user and the maximum error

$$ \varphi $$

φ

of

$$ l $$

l

to determine which foot should be planted. Finally, we verify the effectiveness of our approach from the path offset error.

Qiang Zhang, Jingchao Zhang, Dongsheng Zhou, Xiaopeng Wei

Algorithmic Tile Self-Assembly for Solving the Maximal Matching Problem

The maximal matching problem is a classic combinatorial optimization problem. Recently, computation by algorithmic tile self-assembly is proved to be a promising technique in nanotechnology, and this computational model is also demonstrated to be Turing universal. In this paper, the process of tile self-assembly model which is used to solve the maximal matching problem is shown including three operations: nondeterministic guess operation, AND operation and comparing operation. Our method can be performed this problem in

Θ

(

mn

) steps, here

m

and

n

is the number of edges and vertices of the given graph respectively.

Zhen Cheng, Yufang Huang, Jianhua Xiao

Application of FDTD and Harmony Search Algorithm for Inverse Scattering Problem

Electromagnetic inverse scattering of two-dimensional (2-D) perfectly conducting objects with transverse magnetic (TM) wave incidence by the harmony search algorithm (HS) is presented. The idea is to perform the image reconstruction by utilisation of HS to minimise the discrepancy between the measured and calculated scattered field data. Finite difference time domain method (FDTD) is used to solve the scattering electromagnetic wave of the objects. The efficiency of applying the above methods for microwave imaging of a two-dimensional perfectly conducting cylinder are examined. Numerical results show that good reconstruction can be obtained by the optimisation method.

Jing Lu, Junhua Gu, Yang Lu

Simulation of Space Information Network SCPS-TP Based on OPNET

In order to prove the performance of SCPS-TP which is proposed by CCSDS in researching space information network, this paper designs a SCPS-TP model including SNACK module, congestion control module and header compression module based on the three key techniques of SCPS-TP using OPNET. A space information network simulation platform is built, and the performance of SCPS-TP is simulated and compared to TCP. The simulation results show that SCPS-TP performs better in high Bit Error Rate and long round-trip delay environment than TCP.

Yufei Zhang, Jinhai Su, Chuanfu Zhang

A Local Elitism Based Membrane Evolutionary Algorithm for Point Pattern Matching

Point pattern matching is a fundamental problem in computer vision and pattern recognition. Membrane computing is an emergent branch of bio-inspired computing, which provides a novel idea to solve computationally hard problems. In this paper, a new point pattern matching algorithm with local elitism strategy is proposed based on membrane computing models. Local elitism strategy is used to keep good correspondences of point pattern matching found during the search, so the matching rate and the convergence speed are improved. Five heuristic mutation rules are introduced to avoid the local optimum. Experiment results on both synthetic data and real world data illustrate that the proposed algorithm is of higher matching rate and better stability.

Zhuanlian Ding, Jin Tang, Xingyi Zhang, Bin Luo

Prediction of Coal Calorific Value Based on a Hybrid Linear Regression and Support Vector Machine Model

The gross calorific value (GCV) is an important property defining the efficiency of coal. There exist a number of correlations for estimating the GCV of a coal sample based upon its proximate and ultimate analyses. These correlations are mainly linear in character although there are indications that the relationship between the GCV and a few constituents of the proximate and ultimate analyses could be nonlinear, which has made artificial intelligence models as a useful tool for a more accurate GCV prediction. This paper focuses on an innovative method of GCV prediction using combination of Multivariate Linear Regression (MLR) as predictor and Support Vector Machine (SVM) as an error correction tool based on proximate and ultimate analyses. The GCV have been predicted using the MLR, ANN and the hybrid MLR–SVM models. In the analysis root mean squared error have been employed to compare performances of the models. Results demonstrated that both models have good prediction ability; however the hybrid MLR–SVM has better accuracy.

Kelei Sun, Rongrong Gu, Huaping Zhou

A New Attempt for Satisfiability Problem: 3D DNA Self-Assembly to Solve SAT Problem

The computational speed of an algorithm is very important to NP-hard problems. The 3D DNA self-assembly algorithm is faster than 2D, while 2D is faster than traditional algorithms because DNA molecule owns high parallelism and density. In this paper we mainly introduced how the 3D DNA self-assembly solves the SAT problems. Firstly, we introduced a non-deterministic algorithm. Secondly, we designed seed configuration and different types of DNA tiles which are needed in the computation. Lastly, we demonstrated how the 3D DNA self-assembly solves the SAT problem. In this paper, 3D DNA self-assembly algorithm has a constant tile types, and whose computation time is linear.

Xuncai Zhang, Ruili Fan, Yanfeng Wang, Guangzhao Cui

Study of Bookkeeping in the Small and Medium-Sized Enterprise

With the development of small and medium enterprises, there are some new accounting services, one of which is bookkeeping. But the bookkeeping has also its disadvantages. To solve the problem of many ignored questions of bookkeeping, the method of searching for countermeasures is given in this paper. The theoretical analysis and specific example show that the method is very effective.

Qingping Li

Towards the Development of a Framework of Organizational Performance Integrating Information Resource Allocation and Organizational Change in China

The paper focused on the relationship between information resources allocation, organizational change and organizational performance. Data were gathered from large and medium enterprises in Shan Dong, China. Method of snowball was used to issue and retrieve questionnaires. Mean score was used to present the current status of large and medium enterprises of information resources allocation, organizational change and organizational performance. Correlation analysis, regression analysis were used to identify the correlation between the three variables.

Fagang Hu, Yuandong Cheng

New Ideas for FN/RFN Queries Based Nearest Voronoi Diagram

While most research focuses on nearest neighbor (NN) and reverse nearest neighbor (RNN) queries, the furthest neighbor (FN) and reverse furthest neighbor (RFN) query are attracting more and more attention. In this paper, we give new ideas on the FN/RFN query issue. The nearest Voronoi diagram-based (VD-based) algorithms to process FN and RFN queries on 2-dimensional location data on the fly is proposed. These algorithms are especially useful for applications which have VD as their fundamental structure. Instead of constructing a new furthest neighbor diagram (FD), we aim to fully utilize the properties of VD. Besides, we implemented our new methods as well as the most promising competing methods which have been previously proposed. The results consistently indicate that our new algorithms outperform competitors.

Wencai Liu, Yuan Yuan

Video Summarization by Robust Low-Rank Subspace Segmentation

Video summarization provides condensed and succinct representations of the content of a video stream. A static storyboard summarization approach based on robust low-rank subspace segmentation is proposed in this paper. Firstly, video frames are represented as multi-dimensional vectors, and then embedded into a group of affine subspaces using low-rank representation according to the content similarity of the frames in the same subspace. Secondly, a series of subspaces are segmented based on the Normalized Cuts algorithm. The video summary is finally generated by choosing key frames from the significant subspaces and ranking these key frames in temporal order. The experimental results demonstrate that the proposed summarization algorithm can produce crucial key frames and effectively reduce the visual content redundancy in summary comparing with the conventional approaches.

Zhengzheng Tu, Dengdi Sun, Bin Luo

Nanostructure Thin-Film Removal via a Cylinders Tool for Computer Touch Sensing Material

This study describes a precise method for the electro-chemical removal of defective tin-doped indium oxide (ITO) thin film from the surface of polyethylene terephthalate (PET) touch screen material using a newly designed multi-cylinder electrode tool. In the current experiment, a small gap-width between the cylindrical cathodes and anodes and the workpiece reduces the time taken to remove a particular amount of ITO by dissolution. A large diameter cathode rotational circle also reduces the time taken for effective ITO film removal because the dissolution effect is facilitated by the provision of sufficient electrochemical power. High rotational speed of the multi-cylinder tool and a high electrolyte flow rate also corresponds with an increase in the dissolution rate of the defective ITO layer. A small diameter of either the anode or cathode combined with enough electric power also results in faster dissolution. The removal rate of the ITO layer is also improved by a reduction in the number of cylinders used. This tool design was found to be most effective for the electrochemical removal of defective ITO thin film nanostructures and can remove the material easily and cleanly in a very short time. This newly designed tool and ultra-precise reclamation process can be used very effectively in the optoelectronics semiconductor industry for the removal of defective ITO layers from PET touch screen substrate to allow the material to be returned to the production line. This recycling will reduce both production costs and pollution.

P. S. Pa

Research on Cow Epidemic Monitor System Based on ArcGIS Engine

In order to improve the work environment for cows epidemic monitor and raise working efficiency, this paper propose a general design scheme for this system and develops partial function using the methods of function analysis. Information system analysis design,with the VS.NET,ComGIS development platform(ArcGIS Engine),and database technology, Using various method of spatial analysis, realized the comprehensive analysis of the historical cows disease and Space–time distribution having certain effect for improving the level of controlling cows disease, providing some reference for cows disease geographic information system construction of relevant departments.

Wenbo Wang, Hongli Zhou, Jinghong Li

Application of Dual Bilinear Interpolation Fuzzy Algorithm in Fan Speed Control

This paper focused on ordinary fuzzy controller for operation of control rule by approximate processing for a particular discrete points, resulting in steady-state performance results information loss; made binary optimized fuzzy control algorithm of bilinear interpolation. On the basis of basic fuzzy controller, it was to avoid error due to an approximate calculation of the loss of information, used by dual bilinear interpolation algorithm to improve continuity of control rules, so as to achieve the goal of improving stability precision.

Kai-feng Huang, Ze-gong Liu, Jing Yang, Feng Xu, Kui Gao, Ya Kang

Research on Credibility of Web Service Composition Based on Stochastic Petri Net

The service-oriented architecture (SOA) has become inevitable in the development and wide application of computers and networks. SOA is characteristic of service composition so that it can provide more services to companies. While there is a promising future for the application of web service composition, some issues such as safety and reliability hinder its further development. To increase the trustworthiness of web service composition, the paper puts forth some indexes and a Petri net based approach. The credibility of web service composition can be evaluated with this approach.

Juan Guo, Xianwen Fang, Dawei Zheng, Xiuyun Zhang

Based on DNA Self-Assembled Computing to Solve MH Knapsack Public Key Cryptosystems of the Knapsack Problem

DNA self-assembly is a hierarchical build-up of complex assembly body; it is also a very important model in molecular computing. Cryptography problem not only has theoretical significance, but also has a very wide range of applications in national economy and other fields. We will use the way of self-assembly of DNA computing to solve the knapsack problem in the MH knapsack public key cryptosystem.

Jing Liu, Zhixiang Yin

Image Representation and Recognition Based on Directed Complex Network Model

Image structure representation is a vital technique in the image recognition. A novel image representation and recognition method based on directed complex network is proposed in this paper. Firstly, the key points are extracted from an image as the nodes to construct an initial complete undirected complex network. Then, the k-nearest neighbor evolution method is designed to form a series of directed networks. At last, the feature descriptor of the image is constructed by concatenating the structure features of each directed network to finally achieve image recognition. Experimental results demonstrate that the proposed method outperforms the traditional methods in image recognition and can describe the structure of images more effectively.

Ying Chen, Jin Tang, Bin Luo

Finite Element Analysis and Computation of the Reinforcement Effect and Mechanism of the Ventilation Roadway U-Type Arch

Though the U-type arch support is used widely in the environment of high earth pressure, damage rate still can not be controlled in some complicated condition. On the basis of U-type arch, the reinforcement structure established can improve the support intensity and control the deformation. The essay makes an adequate finite element analysis and computation on the U-type reinforcement structure by using numerical simulation software to test the validity of the reinforcement structure.

Ning Zhang, Mingzhong Gao, Laiwang Jing

Fast Distributed BFS Solution for Edge-Disjoint Paths

We propose an improved synchronous distributed message-based breadth-first search (BFS) solution, to identify maximum cardinality sets of edge-disjoint paths, between a source node and a target node in a digraph. Previously, we presented a BFS based algorithm, NW-BFS-Edge (Nicolescu R, Wu H (2011) BFS solution for disjoint paths in P systems. In: Calude C, Kari J, Petre I, Rozenberg G (eds.) Unconventional computation, lecture notes in computer science, vol. 6714. Springer Berlin, pp 164–176), Nicolescu R, Wu H (2012) New solutions for disjoint paths in P systems. Nat Comput 11:637–651, which is a distributed version of the Edmonds-Karp algorithm Edmonds J, Karp RM (1972) Theoretical improvements in algorithmic efficiency for network flow problems. J ACM 19(2):248–264. Here, we propose a faster solution, Fast-NW-BFS-Edge, which improves NW-BFS-Edge by detecting and discarding “dead” cells in the first search round. On a set of randomly generated single-source directed acyclic graphs (dags), Fast-NW-BFS-Edge is 8.2 % faster than NW-BFS-Edge. This improvement has been inspired and guided by a P system modelling exercise, but is suitable for any distributed implementation.

Huiling Wu

Stock Price Forecast Using Tree Augmented Naïve (TAN) Bayes

The Tree Augmented Naïve (TAN) Bayes is one of Bayesian network algorithm and it can create a simple Bayesian network model efficiently. This paper describes a method using TAN to create a Bayesian network which can help to forecast the change rate of Chinese Company’s stock price change per day. Firstly, we collect Wanke Company’s stock price data and discrete these data with discrete algorithm. Secondly, we use the discrete data to construct the TAN network. Thirdly, we use TAN network to forecast the Wanke Company’s stock price data with variable correlation coefficient and the root mean square error as estimators.

Yuanlu Liao, Xiangxiang Zeng, Tao Song, Lianfeng Zhang

A Hybrid Membrane Computing and Honey Bee Mating Algorithm as an Intelligent Algorithm for Channel Assignment Problem

Membrane computing is a model of computation inspired by the structure and functioning of cells as living organisms. Membrane computing naturally has parallel structure. Also, it uses communication rules to exchange information between membranes. This paper first proposes Hybrid Honey Bee Mating (HHBM) then uses parallelism advantage of membrane to parallelize and divide the HHBM algorithm as an evolutionary algorithm to different membranes (parts). These membranes can be executed in parallel way on different cores or CPUs. Simulation shows that when number of membrane increases performance of this algorithm increases.

Maroosi Ali, Ravie Chandren Muniyandi

A Salt and Pepper Noise Image Filtering Method Using PCNN

Based on Pulse Coupled Neural networks, an effective salt and pepper noise image filtering method is proposed. Similar groups of neurons burst synchronous pulses in a PCNN, thereby the noise pixels are detected. Considering a noise pixel has the most similarity with neighbor non-noise pixels, a filtering method called extended median filtering is put forward to filter the noises in an image. Simulation results show that the method proposed has excellent filtering performance for the noise images with different noise intensity, and has the obvious advantage compared with the median filter.

Rencan Nie, Shaowen Yao, Dongming Zhou, Xiang Li

Study of the Predictor Index System of Death Rate per Million-Ton Coal Based on Gray Relation

The thesis adopts gray correlation analysis methods, counting the country’s coal mine safety data, taking the provinces (cities) as the basic unit, to identify the key impacting factors of death rate per million-ton coal by comparing and analyzing the samples of death rate per million-ton coal in different years. And it establishes the streamlined and reasonable predictor index system of death rate per million-ton coal.

Huaping Zhou, Kelei Sun, Bojie Xiong

Multi-Objective Optimization of Post-Disaster Emergency Resources Scheduling Using Multiple Ant Colony Systems Optimization Algorithm

The multi-objective optimization mathematical model for post-disaster emergency resources scheduling was built. This model took into account multiple demand centers, multiple supply centers, multiple kinds of resources, and supply centers cooperating with each other in providing resources. The reliability of scheduling routes was taken into account to enhance the practicability. A new approach using multiple ant colony systems optimization algorithm was proposed to solve the model. The elitist strategy was imported into the global pheromone update strategy to guide exchanging and sharing information among multiple ant colony systems, and it improved the efficiency in searching global no-inferior solutions. It provided a practical approach to integrate resources location-allocation problem and scheduling routes planning problem together. The case was presented to verify the validity of the model and algorithm.

Renqiang Wen, Shaobo Zhong, Bin Zhang

Research on Modeling and Simulation of Virtual Miner Agent in Coalmine Virtual Environment

For the underground coal mines safety behavior analysis, the behavior modeling and motion control technology of virtual miner agent is studied under the virtual environment. Based on the theory modeling method of agent, the system structure and its formal description of virtual miner with decision ability is built and is used in the virtual environment, which is integrated with the perception, information processing, learning, behavior, planning, decision-making, and knowledge base and so on, and it can effectively realize the behavior control of virtual miner, as well as typical operation of the behavior simulation of underground, and it can generate lifelike personification behavior. The control of the complex behavior of the virtual miners’ agent and interactive simulation of virtual miner in the coalmine virtual environment are both realized in the PC using the object-oriented technology in this paper. So we build a behavior with realistic of underground of virtual miner in order to provide technical reference

Jingjing Tang, Zhixiang Yin, Liguo Qu, Chaoli Tang

Research of Detection Method of Mine Motor Vehicle Pedestrian Based on Image Processing

This paper use infrared camera to collect the front image of motor cars, and to pretreat image based on genetic algorithm and normalized incomplete Beta function. Using pulse coupled neural network for image two value segmentation; and using improved fuzzy edge detection algorithm based on genetic algorithm for recognition the rail and using heuristic method for fitting the rails; once pedestrian recognition algorithm identified pedestrian, the alarm is immediately triggered. This system can efficiently identify the pedestrian near the track, judge and early warn the position of pedestrian; it is a new technology which can eliminate the potential safety hazard of motor vehicles in the transportational process.

Chaoli Tang, Lina Wang, Liguo Qu, Yourui Huang

Analysis of TBM Monitoring Data Based on Grey Theory and Neural Network

This paper represented the main state parameters of Tunnel Boring Machine (TBM) system, analyzed the variation tendency of time series which were TBM characteristic parameters, predicted the development tendency for characteristic parameters of TBM equipment status combing the grey and neural network prediction, and then built the prediction model for characteristic parameters of TBM based on the grey theory and neural network. Through calculating the projects, the improvement measure of prediction model was given. The modified prediction model could ensure the running condition for 10 h when prediction accuracy reaches first class. Finally, this paper introduced the part of parameters prediction for the TBM fault diagnosis system developed by the author, so prediction results would be presented before the workers more directly.

Tianrui Zhang, Yuanxing Dai, Caixiu Lu, Haifeng Zhao, Tianbiao Yu

Kernel P Systems: Applications and Implementations

This paper explores the modelling capacities of a new class of P systems, called kernel P systems (kP systems). A specific language for describing kP systems and its translation into Promela, the specification language of Spin, are described. This Promela specification has been further used for simulation and property verification with the Spin model checker. Also, a parallel implementation on GPU parallel architectures, realized using CUDA, is presented and the results are compared with the ones obtained using Promela and Spin. A case study, namely the Subset sum problem, which has been modelled with kernel P systems and further implemented in Promela is presented.

Florentin Ipate, Raluca Lefticaru, Laurenţiu Mierlă, Luis Valencia Cabrera, Huang Han, Gexiang Zhang, Ciprian Dragomir, Mario J. Pérez Jiménez, Marian Gheorghe

Improved Weak Classifier Optimization Algorithm

In view of the slow speed and time-consuming training problem of the human face detection in complex conditions, we put forward an improved algorithm. To counter the time-consuming training defect of the Adaboot algorithm, we improve the about error rate calculation formula while training the weak classifier, thus accelerating the training speed of the latter and reducing the overall training time. The experimental results show that the improved system has greatly improved the training speed.

Shaowen Liao, Yong Chen

Improvement of the Sustainable Growth Model and Its Application in the Listed Power Companies of China

In order to achieve the goal of sustainable growth of finance, the enterprise should always, according to financial sustainable growth rate and its difference from the real growth rates, find out the reason for the difference between them. And then put forward the corresponding management strategy, to realize the sustainable development of the enterprises. Based on the traditional sustainable growth model, this paper made an improvement and reconstruction of it, by constructing the financial sustainable growth model under the condition of the easing of all conditions. And in the paper, we analyzed the reason of the deviation of the present situation of our listed power company’s sustainable development from the goal condition, leading to the reasonable suggestions for their sustainable development.

Li Liu, Zehong Li

Nuts Positioning System Based on Machine Vision

Aiming at the problems of high error ration, high labor intensity and low efficient manual static adjustment of screws and nuts, the system for intelligent nut positioning system on the overload detection part of low-voltage circuit breaker production line was designed. Machine vision technology was taken into the detection unit of the production line. The images of hexagon nut were real-time captured by the CCD camera and processed with image processing technologies such as binarization processing, Gaussian filter, canny edge extraction, Hough transform etc., then the center point position of the Hexagon nut was found, and was used to screws and nuts assembly. Now the system has already been qualified and accepted by factory’s customer, and running very well.

Rui Li

Information Fusion Estimation Based Optimal Control for Ship Course Control Problem

In this paper, a ship model with wave disturbances is used to simulate the ship autopilot system. An information fusion estimation based optimal tracking controller is designed for the ship course tracking system. Due to the effect of wave disturbances, the passive observer is adopted to estimate the system state and extern disturbance. Finally, two simulation tests in calm water and in waves respectively are carried out to demonstrate the effectiveness of the proposed control scheme.

Guoqing Xia, Huiyong Wu

Image Feature Extraction Based on Support Vector Machine and Multi-DSP Combined Structure

An image feature extraction method based on support vector machine (SVM) is presented in this paper, which first seeks the optimal separating hyperplane in small samples and then projects image data in the corresponding normal direction. In multiclass cases, the method has an optimal choose for selecting projecting axis by some sub-SVMs with simplified structure. A multi-DSP combined structure system has been designed to implement this method by TMS320DM648 and TMS320DM6446. The results show the proposed method is effective, and also meets the real-time requirement.

Hui Chen, Jiao Hu

Study on the Use of IDAs in Cloud Storage

Cloud storage is a model of networked online storage based on cloud computing, and provides users with immediate access to a broad range of resources and applications. Although a lot of cloud storage providers adopt encryption to protect costumer data, but users still suspect the security and privacy of their data. The paper analyzed Information dispersal algorithms (IDAs), and proved that it can better address the issues of confidentiality, integrity and availability of data. On this basis, the paper presented a cloud storage system adopting IDAs, and illustrated its key component and the process of writing file in cloud storage.

Honglei Wang, Xuesong Zhang

Influence of Potential Parameters on the Melting Temperature of MgSiO3 Perovskite

The melting temperatures MgSiO

3

perovskite have been calculated in previous studies by using MD simulation, but considerable discrepancy of melting temperature exists between these simulations. In this contribution, comparisons of potential energy curves are performed to explain the discrepancy. To further investigate the influence of the interaction potential parameters on the MD simulation result, a new set of potential parameters is developed based on combining two fitting potential parameters of previous studies, and is applied in the present study. The melting temperatures are calculated, and also compare with those derived from previous studies.

Qiong Chen

Research on Attack Graph Generation for Network Security Situation

Attack graph generation method based on network security situation is presented. Attack graph technique bases attack graph on the target network and the attack model. Generally, attack path is shown that the attacker uses vulnerability of target network to carry out network attack by graph structure. Attribute attack graph generation method based on breadth-first is put forward, which during the process of the attack graph generation solve the problem of circle path and combination explosion, the different scale of simulation experiment shows that the research results can found in time and make up for security problems existing in the network system, effectively improve the survivability of the network system, so as to improve the ability that network system deals with all kinds of sudden attack.

Yanbo Wang, Huiqiang Wang, Chao Zhao, Yushu Zhang, Ming Yu

Design of the Framework for Reverse Model Based on TTCN-3 Test Systems

Aimed at the comprehensibility, reusability and maintainability, the thesis presents the reverse model recovery for the legacy code developed by TTCN-3. It can also help tester and maintainers to verify the test implement, etc. First, the thesis introduces reverse model and its features based on TTCN-3 test systems. Then, the thesis builds the framework on Eclipse platform using the plug-in mechanism. Here the thesis reuses and expands the core parser in TRex project for the reverse engineering analyzer.

Yongpo Liu, Ji Wu, Chuangye Chang, Shuangmei Liu

The Information Acquisition System of Subsidence Mining-Induced Based on Mobile GIS

In order to solve the low efficiency, low inefficiency and low informationization problem of current mining subsidence acquisition technology backwardness, this paper provides a reliable and practical data acquisition terminal for mining subsidence monitoring and prediction work under CORS space information framework. This paper also adopts application of network RTK on the PDA communication between terminal and data center communication, Mobile GIS data organization, terminal and data center data fusion and other contents. The practice shows that this System greatly improves the speed and accuracy of the monitoring points’ information.

Meiwei Zhang, Weicai Lv, Guanghu Yao

Edge Collapse Considering Triangular Mesh for Model Simplification

Because of re-triangularization during the process of traditional edge collapse, this paper introduces a new edge collapsing method improved with the use of triangular mesh. We deal with a series of feature points, and directly establish the triangular mesh which meet the need of simplification, and avoid triangulating secondly. The experiment shows that this method can improve the convergence rate, and simplified effect, under condition of assurance of the triangle mesh approximation precision and the decrease of the amount of the triangular facets.

Ruifang Zhu, Wei Shen

Research on Real-Time Security Risk Management of Rural Power Based on Monte Carlo Simulation Method

With the development of science and technology, reliability of power grids in rural areas in the algorithm have made new progress, in a variety of simulation methods, Monte Carlo simulation method because the sampling frequency has nothing to do with the grid size and the required accuracy only the features, so network security risk management in rural areas has been widely used. This article describes the sequential simulation, non-sequential Monte Carlo simulation of the basic principles of probabilistic simulation methods and characteristics.

Xiaoqiang Song, Xia Lv, Xubo Guo, Zuhai Zheng

Canonical Duality for Radial Basis Neural Networks

Radial Basis Function Neural Networks (RBF NN) are a tool largely used for regression problems. The principal drawback of this kind of predictive tool is that the optimization problem solved to train the network can be non-convex. On the other hand Canonical Duality Theory offers a powerful procedure to reformulate general non-convex problems in dual forms so that it is possible to find optimal solutions and to get deep insights into the nature of the challenging problems. By combining the canonical duality theory with the RBF NN, this paper presents a potentially useful method for solving challenging problems in real-world applications.

Vittorio Latorre, David Yang Gao

Support Vector Machines for Real Consumer Circuits

Circuit analysis is an important phase of the circuit production process. This phase should be performed as fast as possible because of the strict temporal constraints in the industrial sector. On the other hand, there is the need of a certain precision and reliability of the analysis. For this reasons there is more and more interest toward surrogate models that are able to perform a reliable analysis in less time. In this work we analyze how a popular surrogate model, the Support Vector Machines (SVM), performs when it is used to approximate the behavior of industrial circuits, provided by ST-Microelectronics, that will be employed in consumer electronics. The SVM are also compared with the surrogate models created with the commercial software currently used by ST-Microelectronics for this kind of applications.

Ciccazzo Angelo, Di Pillo Gianni, Vittorio Latorre

A Triangulation Method for Unorganized Points Cloud Based on Ball Expanding

As an important research subject of the CAD, computer geometry, reverse engineering and other areas. The triangulation of the unorganized data has great significance in theory and the practical. In this paper, we introduce the current mainstream methods of triangulation that based on 3D points cloud data as well as the hash tables and put forward a direct triangulations method which based on a ball expanding.

Qiang Zhang, Nan Wang, Dongsheng Zhou, Xiaopeng Wei

The Analysis of Change Region About Networked Control System Based on the Behavior Profile

In the analysis of Networked Control System, sometimes there may appear a problem of change, it is a problem that how to find the change regions. Previously mostly on the basis of determined change activities, to analyze direct behavior, to study change region. On the basis of analysis of direct and indirect constraints between behaviors, extending behavioral profiles into comprehensive behavioral profiles, a new method to locate dynamic change transitions is proposed, and on the basis of which analytical methods to determine the smaller change region is given in the paper. The theoretical analysis and specific example show that the method is very effective.

Xiangwei Liu, Mimi Wang, Lu Liu

The Application of Ant Colony Optimization in CBR

In the Case-Based Reasoning (CBR) System, the retrieval efficiency and system performance are reduced because of the unlimited increasing case base with the incremental learning. This paper proposes the method of ant colony optimization (ACO) in the CBR system. This method combines the increased efficiency of case retrieval, the effective case base indexing, and the validity of maintenances by adding or reducing cases. Through the all processes we have used the clustering and classification algorithm based ACO. The implementation of the ACO algorithm into the CBR system is successful and the experimental results verify its effectiveness.

Jianhua Shu

Genetic Algorithm for Solving Survivable Network Design with Simultaneous Unicast and Anycast Flows

We consider the survivable network design problem for simultaneous unicast and anycast flow requests. In this problem, a network is modeled by a connected, weighted and undirected graph with link cost follows All Capacities Modular Cost (ACMC) model. Given a set of flow demand, this problem aims at finding a set of connection with minimized network cost to protect the network against any single failure. This problem is proved to be NP-hard. In this paper, we propose a new Genetic Algorithm for solving the ACMC Survivable Network Design Problem (A-SNDP). Extensive simulation results on Polska, Germany and Atlanta network instances show that the proposed algorithm is much more efficient than the Tabu Search and other baseline algorithms such as FBB1 and FBB2 in terms of minimizing the network cost.

Huynh Thi Thanh Binh, Son Hong Ngo, Dat Ngoc Nguyen

Based on the M-GIS System Structure of the Intelligent Mobile Phone Positioning and Tracking System

Based on the Android platform of mobile phone location tracking system will combined phone safety protection with positioning technologies, and use Google map seamlessly combine this advantage, to provide users with precise positioning service, changing the card lock machine to pre-set the phone number to send a warning message, remote control, data backup, the positioning of the machine, Friends positioning and electronic fencing. This system can be used for mobile phone anti-theft tracking, monitoring and care of the parents of children with specific financial and personnel monitoring, to provide users with a convenient and reliable service, with good commercial value and social value.

YueChun Feng, HaiRong Wang

A Comparison of Actual and Artifactual Features Based on Fractal Analyses: Resting-State MEG Data

Future standardized system for distinguishing actual and artifactual magnetoencephalogram (MEG) data is an essential tool. In this paper, we proposed the quantitative parameters based on fractal dimension (FD) analyses in which the FD may convey different features before and after artifact removal. The six FD algorithms based on time-series computation, namely, box-counting method (BCM), variance fractal dimension (VFD), Higuchi’s method (HM), Kazt’s method (KM), detrended fluctuation analysis (DFA), and modified zero-crossing rate (MZCR) were compared. These approaches measure nonlinear-behavioral responses in the resting-state MEG data. Experimental results showed that the FD value of actual MEG was increased statistically in comparison with the artifactual MEG. The DFA and the HM present a best performance for analyzing simulated data and resting-state MEG data, respectively.

Montri Phothisonothai, Hiroyuki Tsubomi, Aki Kondo, Yuko Yoshimura, Mitsuru Kikuchi, Yoshio Minabe, Katsumi Watanabe
Additional information

Premium Partner

    Image Credits