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.     

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.     

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.     

Remarks on Network Community Properties

This paper discusses a popular community definition in complex network research in terms of the conditions under which a community is minimal, that is, the community cannot be split into several smaller communities or split and reorganized with other network elements into new communities. The result provides a base on which further optimization computation of the quantitative measure for community identification can be realized.     

A multiyear lags input-holding-output model on education with excluding idle capital

This paper develops a multi-year lag Input-Holding-Output (I-H-O) Model on education with exclusion of the idle capital to address the reasonable education structure in support of a sustainable development strategy in China. First, the model considers the multiyear lag of human capital because the lag time of human capital is even longer and more important than that of fixed capital. Second, it considers the idle capital resulting from the output decline in education, for example, student decrease in primary school. The new generalized Leonitief dynamic inverse is deduced to obtain a positive solution on education when output declines as well as expands. After compiling the 2000 I-H-O table on education, the authors adopt modifications-by-step method to treat nonlinear coefficients, and calculate education scale, the requirement of human capital, and education expenditure from 2005 to 2020. It is found that structural imbalance of human capital is a serious problem for Chinese economic development. This research was supporting by the Key Project of National Natural Science Foundation of China under Grant No. 60874119, Innovation Funds of Chinese Academy of Sciences, Research Fund for Humanities and Social Sciences in colleges under Grant No. 06BJY102, Key project in Jiangxi Soft Science Project under Grant No. [2006]188, Jiangxi Research Fund for Humanities and Social Sciences in colleges under Grant No. 03JJ01, and Henan Research Fund for Humanities and Social Sciences in colleges under Grant No. 2008-ZD-002.     

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.     

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.     

Estimation on semivarying coefficient models with different degrees of smoothness

Semivarying coefficient models are frequently used in statistical models. In this paper, under the condition that the coefficient functions possess different degrees of smoothness, a two-step method is proposed. In the case, one-step method for the smoother coefficient functions cannot be optimal. This drawback can be repaired by using the two-step estimation procedure. The asymptotic mean-squared error for the two-step procedure is obtained and is shown to achieve the optimal rate of convergence. A few simulation studies are conducted to evaluate the proposed estimation methods. This research is supported in part by the National Natural Science Foundation of China under Grant No. 10871072 and Shanxi's Natural Science Foundation of China under Grant No. 2007011014.     

A modified likelihood ratio test for homogeneity in bivariate normal mixtures of two samples

This paper investigates the asymptotic properties of a modified likelihood ratio statistic for testing homogeneity in bivariate normal mixture models of two samples. The asymptotic null distribution of the modified likelihood ratio statistic is found to be χ₂², where χ₂² is a chi-squared distribution with 2 degrees of freedom. This research was supported by the National Natural Science Foundation of China under Grant No. 10661003, SRF for ROCS, SEM under Grant No. [2004]527, and the Natural Science Foundation of Guangxi under Grant No. 0728092.     

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.     

A STAGE-STRUCTURED SI ECO-EPIDEMIOLOGICAL MODEL WITH TIME DELAY AND IMPULSIVE CONTROLLING*

This paper formulates a robust stage-structured SI eco-epidemiological model with periodic constant pulse releasing of infectious pests with pathogens. The authors show that the conditions for global attractivity of the ＇pest-eradication＇ periodic solution and permanence of the system depend on time delay, hence, the authors call it ＂profitless＂. Further, the authors present a pest management strategy in which the pest population is kept under the economic threshold level （ETL） when the pest population is uniformly persistent. By numerical analysis, the authors also show that constant maturation time delay for the susceptible pests and pulse releasing of the infectious pests can bring obvious effects on the dynamics of system.     

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.     

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.     

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.     

FLOCKING OF MULTI-AGENT DYNAMIC SYSTEMS WITH GUARANTEED GROUP CONNECTIVITY*

This paper investigates distributed flocking problem where the information exchange among agents is modeled by the communication topology changing with time. Previous research on this problem establishes group stabilization by assuming that the dynamic topology is connected all the time, which however cannot be guaranteed by most proposed distributed control laws. In this paper, a distributed algorithm to distill a necessary subgraph of the initial communication topology is presented. This subgraph covers all the vertices of the communication topology and is proved to be connected as long as the initial communication topology is connected. A distributed control law is then designed to pursue the flocking motion while preserving all the edges in this subgraph. In this way, connectivity can be preserved all the time, and flocking problem is thus solved only provided the initial communication topology of multi-agent system is connected.     

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.     

New results about the relationship between optimally weighted least squares estimate and linear minimum variance estimate

The optimally weighted least squares estimate and the linear minimum variance estimate are two of the most popular estimation methods for a linear model. In this paper, the authors make a comprehensive discussion about the relationship between the two estimates. Firstly, the authors consider the classical linear model in which the coefficient matrix of the linear model is deterministic, and the necessary and sufficient condition for equivalence of the two estimates is derived. Moreover, under certain conditions on variance matrix invertibility, the two estimates can be identical provided that they use the same a priori information of the parameter being estimated. Secondly, the authors consider the linear model with random coefficient matrix which is called the extended linear model; under certain conditions on variance matrix invertibility, it is proved that the former outperforms the latter when using the same a priori information of the parameter. This research is supported in part by the National Natural Science Foundation of China under Grant Nos. 60232010, 60574032, and the Project 863 under Grant No. 2006AA12A104.     

A low order nonconforming anisotropic finite element approximation to parabolic problem

A low order nonconforming finite element is applied to the parabolic problem with anisotropic meshes. Both the semidiscrete and fully discrete forms are studied. Some superclose properties and superconvergence are obtained through some novel approaches and techniques. This research was supported by the National Natural Science Foundation of China under Grant No. 10671184.     

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.