A Priority-Based Negotiations Approach for Handling Inconsistencies in Multi-Perspective Software Requirements

Inconsistency of multi-perspective requirements specifications is a pervasive issue during the requirements process. However, managing inconsistency is not just a pure technical problem. It is always associated with a process of interactions and competitions among corresponding stakeholders. The main contribution of this paper is to present a negotiations approach to handling inconsistencies in multi-perspective software requirements. In particular, the priority of requirements relative to each perspective plays an important role in proceeding negotiation over resolving inconsistencies among different stakeholders. An algorithm of generating negotiation proposals and an approach to evaluating proposals are also presented in this paper, respectively.     

Web Services Composing by Multiagent Negotiation

Composing web services is gained daily attention in Service Oriented Computing. It includes the dynamic discovery, interaction and coordination of agent-based semantic web services. The authors first follow Function Ontology and Automated Mechanism Design for service agents aggregating. Then the problem is formulated but it is ineffective to solve it from the traditional global view. Because the complexity is NP-complete and it is dii~cult or even impossible to get some personal information. This paper provides a multi-agent negotiation idea in which each participant negotiates under the condition of its reservation payoff being satisfied. Numerical experiment is given and well evaluates the negotiation.     

Asymptotic Solution of Activator Inhibitor Systems for Nonlinear Reaction Diffusion Equations

A nonlinear reaction diffusion equations for activator inhibitor systems is considered. Under suitable conditions, firstly, the outer solution of the original problem is obtained, secondly, using the variables of multiple scales and the expanding theory of power series the formal asymptotic expansions of the solution are constructed, and finally, using the theory of differential inequalities the uniform validity and asymptotic behavior of the solution are studied.     

Optimal Investment with Noise Trading Risk

This paper investigates the optimal dynamic investment for an investor who maximizes constant absolute risk aversion （CARA） utility in a discrete-time market with a riskfree bond and a risky stock. The risky stock is assumed to present both the dividend risk and the price risk. With our assumptions, the dividend risk is equivalent to fundamental risk, and the price risk is equivalent to the noise trading risk. The analytical expression for the optimal investment strategy is obtained by dynamic programming. The main result in this paper highlights the importance of differentiating between noise trading risk and fundamental risk for the optimal dynamic investment.     

Testing serial correlation in semiparametric varying coefficient partially linear errors-in-variables model

The authors propose a V _{N, p} test statistic for testing finite-order serial correlation in a semiparametric varying coefficient partially linear errors-in-variables model. The test statistic is shown to have asymptotic normal distribution under the null hypothesis of no serial correlation. Some Monte Carlo experiments are conducted to examine the finite sample performance of the proposed V _{N, p} test statistic. Simulation results confirm that the proposed test performs satisfactorily in estimated size and power. This research is supported by the National Natural Science Foundation of China under Grant Nos. 10871217 and 40574003; the Science and Technology Project of Chongqing Education Committee under Grant No. KJ080609; the Doctor's Start-up Research Fund under Grant No. 08-52204; and the Youth Science Research Fund of Chongqing Technology and Business University under Grant No. 0852008.     

Designing a Hybrid Intelligent Mining System for Credit Risk Evaluation

In this study, a novel hybrid intelligent mining system integrating rough sets theory and support vector machines is developed to extract efficiently association rules from original information table for credit risk evaluation and analysis. In the proposed hybrid intelligent system, support vector machines are used as a tool to extract typical features and filter its noise, which are different from the previous studies where rough sets were only used as a preprocessor for support vector machines. Such an approach could reduce the information table and generate the final knowledge from the reduced information table by rough sets. Therefore, the proposed hybrid intelligent system overcomes the difficulty of extracting rules from a trained support vector machine classifier and possesses the robustness which is lacking for rough-set-based approaches. In addition, the effectiveness of the proposed hybrid intelligent system is illustrated with two real-world credit datasets.     

Robust Consensus and Soft Control of Multi-Agent Systems with Noises*

This paper considers the problem of robust consensus for a basic class of multi-agent systems with bounded disturbances and with directed information flow. A necessary and sufficient condition on the robust consensus is first presented, which is then applied to the analysis, control and decision making problems in the noise environments. In particular, the authors show how a soft control technique will synchronize a group of autonomous mobile agents without changing the existing local rule of interactions, and without assuming any kind of connectivity conditions on the system trajectories.     

STABILITY ANALYSIS OF TWO-SECTORS STOCHASTIC ECONOMIC GROWTH MODEL

In the paper, we investigate the stability of a two-sector economic growth model under stochastic case. A two-dimensional stochastic differential system is deduced by Ito＇s formula, by using Lyapunov function methods, whether the growth rates of physical capital and human capital are exponentially stable or unstable depends on the values for parameters. Finally, we also illustrate the results with two examples.     

Symmetry in world trade network

Symmetry of the world trade network provides a novel perspective to understand the world-wide trading system. However, symmetry in the world trade network (WTN) has been rarely studied so far. In this paper, the authors systematically explore the symmetry in WTN. The authors construct WTN in 2005 and explore the size and structure of its automorphism group, through which the authors find that WTN is symmetric, particularly, locally symmetric to a certain degree. Furthermore, the authors work out the symmetric motifs of WTN and investigate the structure and function of the symmetric motifs, coming to the conclusion that local symmetry will have great effect on the stability of the WTN and that continuous symmetry-breakings will generate complexity and diversity of the trade network. Finally, utilizing the local symmetry of the network, the authors work out the quotient of WTN, which is the structural skeleton dominating stability and evolution of WTN. This research was supported by the National Natural Science Foundation of China under Grant No. 70371070; Shanghai Leading Academic Discipline Project under Grant No. S30504; and Key Project for Fundamental Research of STCSM under Grant No. 06JC14057.     

Recognition of Structure Similarities in Proteins

Protein fold structure is more conserved than its amino acid sequence and closely associated with biological function, so calculating the similarity of protein structures is a fundamental problem in structural biology and plays a key role in protein fold classification, fold function inference, and protein structure prediction. Large progress has been made in recent years in this field and many methods for considering structural similarity have been proposed, including methods for protein structure comparison, retrieval of protein structures from databases, and ligand binding site comparison. Most of those methods can be available on the World Wide Web, but evaluation of all the methods is still a hard problem. This paper summarizes some popular methods and latest methods for structure similarities, including structure alignment, protein structure retrieval, and ligand binding site alignment.     

DESIGN METHODOLOGY OF NETWORKED SOFTWARE EVOLUTION GROWTH BASED ON SOFTWARE PATTERNS

Recently,some new characteristics of complex networks attract the attentions of scientistsin different fields,and lead to many kinds of emerging research directions.So far,most of the researchwork has been limited in discovery of complex network characteristics by structure analysis in large-scalesoftware systems.This paper presents the theoretical basis,design method,algorithms and experiment results ofthe research.It firstly emphasizes the significance of design method of evolution growth for networktopology of Object Oriented(OO)software systems,and argues that.the selection and modulationof network models with various topology characteristics will bring un-ignorable effect on the processof design and implementation of OO software systems.Then we analyze the similar discipline of“negation of negation and compromise”between the evolution of network models with different topologycharacteristics and the development of software modelling methods.According to the analysis of thegrowth features of software patterns,we propose an object-oriented software network evolution growthmethod and its algorithms in succession.In addition,we also propose the parameter systems for OOsoftware system metrics based on complex network theory.Based on these parameter systems,it cananalyze the features of various nodes,links and local-world,modulate the network topology and guidethe software metrics.All these can be helpful to the detailed design,implementation and performanceanalysis.Finally.we focus on the application of the evolution algorithms and demonstrate it by a casestudy.Comparing the results from our early experiments with methodologies in empirical software engi-neering,we believe that the proposed software engineering design method is a computational softwareengineering approach based on complex network theory.We argue that this method should be greatlybeneficial for the design,implementation,modulation and metrics of functionality,structure and per-formance in large-scale OO software complex system.     

Transient Queue Size Distribution Solution of Geom / G / 1 Queue with Feedback-A Recursive Method

This paper considers the Geom / G / 1 queueing model with feedback according to a late arrival system with delayed access (LASDA). Using recursive method, this paper studies the transient property of the queue size from the initial state N(0⁺) = i. Some new results about the recursive expression of the transient queue size distribution at any epoch n ⁺ and the recursive formulae of the equilibrium distribution are obtained. Furthermore, the recursive formulae of the equilibrium queue size distribution at epoch n ⁻, and n are obtained, too. The important relations between stationary queue size distributions at different epochs are discovered (being different from the relations given in M / G / 1 queueing system). The model discussed in this paper can be widely applied in all kinds of communications and computer network. This research is supported by the National Natural Science Foundation of China under Grant No. 70871084, the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No. 200806360001, and the Scientific Research Fund of Southwestern University of Finance and Economics.     

TWO-STAGE ESTIMATION FOR SEEMINGLY UNRELATED NONPARAMETRIC REGRESSION MODELS

This paper is concerned with the estimating problem of seemingly unrelated （SU） non- parametric regression models. The authors propose a new method to estimate the unknown functions, which is an extension of the two-stage procedure in the longitudinal data framework. The authors show the resulted estimators are asymptotically normal and more efficient than those based on only the individual regression equation. Some simulation studies are given in support of the asymptotic results. A real data from an ongoing environmental epidemiologie study are used to illustrate the proposed procedure.     

Stochastic differential equations and stochastic linear quadratic optimal control problem with Lévy processes

In this paper, the authors first study two kinds of stochastic differential equations (SDEs) with Lévy processes as noise source. Based on the existence and uniqueness of the solutions of these SDEs and multi-dimensional backward stochastic differential equations (BSDEs) driven by Lévy processes, the authors proceed to study a stochastic linear quadratic (LQ) optimal control problem with a Lévy process, where the cost weighting matrices of the state and control are allowed to be indefinite. One kind of new stochastic Riccati equation that involves equality and inequality constraints is derived from the idea of square completion and its solvability is proved to be sufficient for the well-posedness and the existence of optimal control which can be of either state feedback or open-loop form of the LQ problems. Moreover, the authors obtain the existence and uniqueness of the solution to the Riccati equation for some special cases. Finally, two examples are presented to illustrate these theoretical results. This work was supported by the National Basic Research Program of China (973 Program) under Grant No. 2007CB814904, the Natural Science Foundation of China under Grant No. 10671112 and Shandong Province under Grant No. Z2006A01, and Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20060422018.     

The projective plane crossing numbers of circular graphs*

The authors give an upper bound for the projective plane crossing number of a circular graph. Also, the authors prove the projective plane crossing numbers of circular graph C （8, 3） and C （9, 3） are 2 and 1, respectively.     

PRE-IMAGE ENTROPY OF NONAUTONOMOUS DYNAMICAL SYSTEMS*

The authors define and study topological pre-image entropy for the non-autonomous discrete dynamical systems given by a sequence {fi}i=1^∞ of continuous self-maps of a compact topological space. The basic properties and the invariant with respect to equiconjugacy of pre-image entropy for the non-autonomous discrete dynamical systems are obtained.     

On the complexity of the normal bases via prime Gauss period over finite fields

A formula on the complexity of the normal bases generated by prime Gauss period over finite fields is presented in terms of cyclotomic numbers. Then, the authors determine explicitly the complexity of such normal bases and their dual bases in several cases where the related cyclotomic numbers have been calculated. Particularly, the authors ˉnd several series of such normal bases with low complexity. This research is supported by the National Fundamental Science Research Program 973 of China under Grant No. 2004 CB3180000 and the State Key Lab. (Information Security) of China.     

Nonmonotonic Reduced Projected Hessian Method Via an Affine Scaling Interior Modified Gradient Path for Bounded-Constrained Optimization

The authors propose an affine scaling modified gradient path method in association with reduced projective Hessian and nonmonotonic interior backtracking line search techniques for solving the linear equality constrained optimization subject to bounds on variables. By employing the QR decomposition of the constraint matrix and the eigensystem decomposition of reduced projective Hes- sian matrix in the subproblem, the authors form affine scaling modified gradient curvilinear path very easily. By using interior backtracking line search technique, each iterate switches to trial step of strict interior feasibility. The global convergence and fast local superlinear/quadratical convergence rates of the proposed algorithm are established under some reasonable conditions. A nonmonotonic criterion should bring about speeding up the convergence progress in some ill-conditioned cases. The results of numerical experiments are reported to show the effectiveness of the proposed algorithm.     

Inverse Center Location Problem on a Tree

This paper discusses the inverse center location problem restricted on a tree with different costs and bound constraints. The authors first show that the problem can be formulated as a series of combinatorial linear programs, then an O（｜V｜^2 log ｜V｜） time algorithm to solve the problem is presented. For the equal cost case, the authors further give an O（｜V｜） time algorithm.