不同信任环境下在线知识社区知识系统演化研究

信任作为在线知识社区中的社会影响因素,对社区中的成员进行沟通学习、知识共享有着重要的作用。不同的在线知识社区有着不同的信任环境,而信任环境的不同会影响社区中用户的学习模式和观点传播。基于此,本文提出了基于信任与Deffaunt的组合观点影响模型。信任模型主要将社区中的信任分为认知信任和情感信任,通过调节参数结构,对应不同信任环境中信任的动态演化过程。Deffaunt模型作为基本观点影响模型,模拟了不同信任环境下的在线知识社区的知识观点的演化过程。实验结果发现,信任环境的高低决定了社区中的观点是否收敛,并且社区中的群体理性人占比和信任程度都能影响观点的收敛速度。     

Evaluating the effect of gap size in a single function mathematical programming model for the three-group classification problem

This study examines the impact that the size of the classification gap can have on the classificatory performance of a mathematical programming based discriminant model. In mathematical programming based models that project the discriminant scores onto a line, the discriminant score of an observation may fall into the gap between adjacent group intervals; thus there is no clear cut way to determine the group in which the observation should be classified. We examine a procedure that we refer to as the split gap approach. The split gap approach is defined as a strategy of estimating the performance of a mathematical programming based model using a nonzero gap size to separate group intervals and then splitting the gap between adjacent group intervals to classify future observations. Studies that propose models with a classification gap generally do not assess the effect of the gap on the performance of the model. This paper investigates this effect. A theoretical assessment and a Monte Carlo simulation are used to determine the impact of different gap sizes on a mixed integer programming model using a single function classification model for the three-group case.     

Modified Logarithmic Sobolev Inequalities in Discrete Settings

Motivated by the rate at which the entropy of an ergodic Markov chain relative to its stationary distribution decays to zero, we study modified versions of logarithmic Sobolev inequalities in the discrete setting of finite Markov chains and graphs. These inequalities turn out to be weaker than the standard log-Sobolev inequality, but stronger than the Poincare’ (spectral gap) inequality. We show that, in contrast with the spectral gap, for bounded degree expander graphs, various log-Sobolev constants go to zero with the size of the graph. We also derive a hypercontractivity formulation equivalent to our main modified log-Sobolev inequality. Along the way we survey various recent results that have been obtained in this topic by other researchers.      

Chaos and order in stateless societies: Intercommunity exchange as a factor impacting the population dynamical patterns

The once abstract notions of dynamical chaos now appear naturally in various systems [Kaplan D, Glass L. Understanding nonlinear dynamics. New York: Springer; 1995]. As a result, future trajectories of the systems may be difficult to predict. In this paper, we demonstrate the appearance of chaotic dynamics in model human communities, which consist of producers of agricultural product and producers of agricultural equipment. In the case of a solitary community, the horizon of predictability of the human population dynamics is shown to be dependent on both intrinsic instability of the dynamics and the chaotic attractor sizes. Since a separate community is usually a part of a larger commonality, we study the dynamics of social systems consisting of two interacting communities. We show that intercommunity barter can lead to stabilization of the dynamics in one of the communities, which implies persistence of stable equilibrium under changes of the maximum value of the human population growth rate. However, in the neighboring community, the equilibrium turns into a stable limit cycle as the maximum value of the human population growth rate increases. Following an increase in the maximum value of the human population growth rate leads to period-doubling bifurcations resulting in chaotic dynamics. The horizon of predictability of the chaotic oscillations is found to be limited by 5 years. We demonstrate that the intercommunity interaction can lead to the appearance of long-period harmonics in the chaotic time series. The period of the harmonics is of order 100 and 1000 years. Hence the long-period changes in the population size may be considered as an intrinsic feature of the human population dynamics.     

Communities of practice: Performance and evolution

We present a detailed model of collaboration in communities of practice and we examine its dynamic consequences for the group as a whole. We establish the existence of a novel mechanism that allows the community to naturally adapt to growth, specialization, or changes in the environment without the need for central controls. This mechanism relies on the appearance of a dynamic instability that initiates an exploration of novel interactions, eventually leading to higher performance for the community as a whole.     

Communicability graph and community structures in complex networks

We use the concept of the network communicability [E. Estrada, N. Hatano, Communicability in complex networks, Phys. Rev. E 77 (2008) 036111] to define communities in a complex network. The communities are defined as the cliques of a “communicability graph”, which has the same set of nodes as the complex network and links determined by the communicability function. Then, the problem of finding the network communities is transformed to an all-clique problem of the communicability graph. We discuss the efficiency of this algorithm of community detection. In addition, we extend here the concept of the communicability to account for the strength of the interactions between the nodes by using the concept of inverse temperature of the network. Finally, we develop an algorithm to manage the different degrees of overlapping between the communities in a complex network. We then analyze the USA airport network, for which we successfully detect two big communities of the eastern airports and of the western/central airports as well as two bridging central communities. In striking contrast, a well-known algorithm groups all but two of the continental airports into one community.     

On dual molecules and convolution-dominated operators

We show that sampling or interpolation formulas in reproducing kernel Hilbert spaces can be obtained by reproducing kernels whose dual systems form molecules, ensuring that the size profile of a function is fully reflected by the size profile of its sampled values. The main tool is a local holomorphic calculus for convolution-dominated operators, valid for groups with possibly non-polynomial growth. Applied to the matrix coefficients of a group representation, our methods improve on classical results on atomic decompositions and bridge a gap between abstract and concrete methods.     

Coxeter-Dynkin diagrams of some space curve singularities

The so called wedge singularities, that consist of a plane curve singularity C and a line transverse to the plane of C, are the simplest space curve singularities which are not a complete intersection. We show that for every wedge singularity X there is an isolated complete intersection singularity Y related to X and we describe the discriminant of X in terms of Y. We also show that the monodromy group of X corresponds to the one of Y.Furthermore, we calculate Coxeter-Dynkin diagrams for some space curve singularities of multiplicity three. To this end we apply real-morsification-techniques.     

A sequential elimination algorithm for computing bounds on the clique number of a graph

We consider the problem of determining the size of a maximum clique in a graph, also known as the clique number. Given any method that computes an upper bound on the clique number of a graph, we present a sequential elimination algorithm which is guaranteed to improve upon that upper bound. Computational experiments on DIMACS instances show that, on average, this algorithm can reduce the gap between the upper bound and the clique number by about 60%. We also show how to use this sequential elimination algorithm to improve the computation of lower bounds on the clique number of a graph.     

A general view on computing communities

We define a community structure of a graph as a partition of the vertices into at least two sets with the property that each vertex has connections to relatively many vertices in its own set compared to any other set in the partition and refer to the sets in such a partition as communities  . We show that it is NP-hard to compute a community containing a given set of vertices. On the other hand, we show how to compute a community structure in polynomial time for any connected graph containing at least four vertices except the star graph _Sn$S_n$. Finally, we generalize our results and formally show that counterintuitive aspects are unavoidable for any definition of a community structure with a polynomial time algorithm for computing communities containing specific vertices.     

Cotensor Coalgebras in Monoidal Categories

We introduce the concept of cotensor coalgebra for a given bicomodule over a coalgebra in an Abelian monoidal category ?. If ? is also cocomplete, complete, and AB5, we show that such a cotensor coalgebra exists and satisfies a meaningful universal property which resembles the classical one. Here the lack of the coradical filtration is filled by considering a direct limit of a filtration consisting of wedge products. We prove that this coalgebra is formally smooth whenever the comodule is relative injective and the coalgebra itself is formally smooth.     

非对称视角下技术创新网络社群结构涌现及其对双元创新的影响研究

针对介于全局网络与自中心网络间的社群现象及其网络结构的创新悖论,分析了不同层面网络社群结构的涌现特征,从组织间关系的非对称视角,探究网络社群动态变化对双元创新的差异性影响。利用高科技生物制药行业的合作与专利数据,使用快速压缩社群识别算法和多元回归模型进行实证检验。研究结果表明:宏观层面的全局网络存在显著“抱团”的多社群巨元组结构;中观层面的网络社群存在选择偏好的核心-边缘结构;微观层面社群组织动态的跨社群运动和成员流动二维变化加剧;社群动态的二维变化对突破式创新具有正向影响,与渐进式创新呈现倒U型关系;位置非对称性正向调节社群动态对双元创新的影响,技术非对称性的调节作用不显著。研究结论有助于揭示技术创新网络社群的合作创新模式,对提升组织创新能力,维持创新网络平稳运行具有重要意义。     

Stackelberg strategy solution for optimal software release policies

We present a software release policy which is based on the Stackelberg strategy solution concept. The model formulated assumes the existence of two type of producers in the market, the leader and follower. The resulting release policy combines both cost factors and a loss of opportunity factor which is the result of competition between the rival producers. We define a Stackelberg strategy pair in the context of our model and, through a series of preliminary results, show that an optimal strategy pair exists. We also present a numerical example which utilizes a software reliability growth model based on the nonhomogeneous Poisson process. Finally, we explore the relative leadership property of the optimal strategies.This work was supported in part by a FOAS Research Grant provided by RMIT. The author would like to thank the referees for constructive suggestions which helped to improve a previous version of this paper.     

Information dynamics algorithm for detecting communities in networks

The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network-inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen’s Markov Cluster algorithm (MCL) method [4] by considering networks’ nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.     

Controlled predatory pricing in a multiperiod Stackelberg game: an MPEC approach

We analyze a multiperiod oligopolistic market where each period is a Stackelberg game between a leader firm and multiple follower firms. The leader chooses his production level first, taking into account the reaction of the followers. Then, the follower firms decide their production levels after observing the leader’s decision. The difference between the proposed model and other models discussed in literature is that the leader firm has the power to force the follower firms out of business by preventing them from achieving a target sales level in a given time period. The leader firm has an incentive to lower the market prices possibly lower than the Stackelberg equilibrium in order to push the followers to sell less and eventually go out of business. Intentionally lowering the market prices to force competitors to fail is known as predatory pricing, and is illegal under antitrust laws since it negatively affects consumer welfare. In this work, we show that there exists a predatory pricing strategy where the market price is above the average cost and consumer welfare is preserved. We develop a mixed integer nonlinear problem (MINLP) that models the multiperiod Stackelberg game. The MINLP problem is transformed to a mixed integer linear problem (MILP) by using binary variables and piecewise linearization. A cutting plane algorithm is used to solve the resulting MILP. The results show that firms can engage in predatory pricing even if the average market price is forced to remain higher than the average cost. Furthermore, we show that in order to protect the consumers, antitrust laws can control predatory pricing by setting rules on consumer welfare.     

Dynamic demand fulfillment in spare parts networks with multiple customer classes

We study real-time demand fulfillment for networks consisting of multiple local warehouses, where spare parts of expensive technical systems are kept on stock for customers with different service contracts. Each service contract specifies a maximum response time in case of a failure and hourly penalty costs for contract violations. Part requests can be fulfilled from multiple local warehouses via a regular delivery, or from an external source with ample capacity via an expensive emergency delivery. The objective is to minimize delivery cost and penalty cost by smartly allocating items from the available network stock to arriving part requests. We propose a dynamic allocation rule that belongs to the class of one-step lookahead policies. To approximate the optimal relative cost, we develop an iterative calculation scheme that estimates the expected total cost over an infinite time horizon, assuming that future demands are fulfilled according to a simple static allocation rule. In a series of numerical experiments, we compare our dynamic allocation rule with the optimal allocation rule, and a simple but widely used static allocation rule. We show that the dynamic allocation rule has a small optimality gap and that it achieves an average cost reduction of 7.9% compared to the static allocation rule on a large test bed containing problem instances of real-life size.     

Equality of orthogonal transvection group and elementary orthogonal transvection group

H. Bass defined orthogonal transvection group of an orthogonal module and elementary orthogonal transvection group of an orthogonal module with a hyperbolic direct summand. We also have the notion of relative orthogonal transvection group and relative elementary orthogonal transvection group with respect to an ideal of the ring. According to the definition of Bass relative elementary orthogonal transvection group is a subgroup of the relative orthogonal transvection group of an orthogonal module with hyperbolic direct summand. Here we show that these two groups are the same in the case when the orthogonal module splits locally.     

Finding Optimal Targets for Change Agents: A Computer Simulation of Innovation Diffusion

We introduce a diffusion of innovation model based on a network threshold approach. Realistic network and threshold data were gathered regarding the diffusion of new software tools within part of a large organization. Novel model features are a second threshold for innovation rejection and a memory that allows actors to take trends into account. Computer simulations produce expected outcomes, such as the S-shaped diffusion curve, but also diffusion breakdown and oscillations. We define and compute the quality of change agent targets in terms of the impact targeted actors have on the diffusion process. Our simulations reveal considerable variance in the quality of actors as change agent targets. Certain actors can be singled out as especially important to the diffusion process. Small changes in the distribution of thresholds and changes in some parameters, such as the sensitivity for trends, lead to significant changes in the target quality measure. To illustrate these interdependencies we outline how the impact of an actor targeted by a change agent spreads through the network. We thus can explain why a good change agent target does not necessarily need to be an opinion leader. Simulations comparing the effectiveness of randomly selected targets versus a group of good change agent targets indicate that the selection of good targets can accelerate innovation diffusion.     

Stability of transonic shock for supersonic flow past a wedge

When steady supersonic flow hits a slim wedge, there may appear an oblique transonic shock attached to the vertex of the wedge, if the downstream pressure is rather large. This paper studies stability in certain weighted partial Hölder spaces of the oblique transonic shock attached to the vertex of a wedge, which is against steady supersonic flows, under perturbations of the upstream flow and the profile of the wedge. We show that under reasonable conditions on the upcoming supersonic flow and the slope of the wedge, such transonic shocks are structural stable. Mathematically, we solve an elliptic–hyperbolic mixed type in an unbounded domain, and the flow field is proved to be C¹. Copyright © 2015 John Wiley & Sons, Ltd.     

Wedging of an elastic wedge by a rigid plate under conditions of contact with detaching

We consider a problem of wedging of an elastic wedge by a rigid plate along an edge crack that is located on the axis of symmetry of the wedge and reaches its vertex. The detachment of the crack faces from the surfaces of the plate is taken into account. Using the Wiener–Hopf method, we obtain an analytic solution of the problem. The size of the detachment zone, the stress intensity factor, the distribution of stresses on the line of continuation of the crack and in the contact domain, and circular displacements of the crack faces are determined.