Neural mechanisms of belief inference during cooperative games.

Humans have the arguably unique ability to understand the mental representations of others. For success in both competitive and cooperative interactions, however, this ability must be extended to include representations of others' belief about our intentions, their model about our belief about their intentions, and so on. We developed a "stag hunt" game in which human subjects interacted with a computerized agent using different degrees of sophistication (recursive inferences) and applied an ecologically valid computational model of dynamic belief inference. We show that rostral medial prefrontal (paracingulate) cortex, a brain region consistently identified in psychological tasks requiring mentalizing, has a specific role in encoding the uncertainty of inference about the other's strategy. In contrast, dorsolateral prefrontal cortex encodes the depth of recursion of the strategy being used, an index of executive sophistication. These findings reveal putative computational representations within prefrontal cortex regions, supporting the maintenance of cooperation in complex social decision making.

Dialogical strategies for orchestrating strategic innovation networks: the case of the Internet of Things

Strategic innovation has been shown to provide significant value for organisations whilst at the same time challenging traditional ways of thinking and working. There is less known, however, as to how organisations collaborate in innovation networks to achieve strategic innovation. In this paper we explore how innovation networks are orchestrated in developing a strategic innovation initiative around the Internet of Things. We show how a hub actor brings together a diverse group of actors to initially create and subsequently orchestrate the strategic innovation network through the employ of three dialogical strategies, namely persuasive projection, reflective development, and definitional control. Further, we illuminate how different types of legitimacy are established through these various dialogical strategies in orchestrating strategic innovation networks.

基于Internet工作流的复合Web服务框架

实现灵活方便的企业业务集成一直是信息领域的核心问题，也是B2B电子商务应用的关键。为此将Web服务和传统的工作流技术相结合，设计并实现了支持复合Web服务运行和管理的框架WSFlow。给出了WSFlow的总体结构，描述了其中的关键技术，包括Web服务与工作流活动的动态配置和绑定技术，复合Web服务流程的动态修改以及复合Web服务的运行监控等技术。

基于支持向量机的Internet流量分类研究

准确的网络流量分类是众多网络研究工作的基础,也一直是网络测量领域的研究热点.近年来,利用机器学习方法处理流量分类问题成为了该领域一个新兴的研究方向.在目前研究中应用较多的是朴素贝叶斯(nave Bayes,NB)及其改进算法.这些方法具有实现简单、分类高效的特点.但该方法过分依赖于样本空间的分布,具有内在的不稳定性.因此,提出一种基于支持向量机(support vector machine,SVM)的流量分类方法.该方法利用非线性变换和结构风险最小化(structural risk minimization,SRM)原则将流量分类问题转化为二次寻优问题,具有良好的分类准确率和稳定性.在理论分析的基础上,通过在实际网络流集合上与朴素贝叶斯算法的对比实验,可以看出使用支持向量机方法处理流量分类问题,具有以下3个优势:1)网络流属性不必满足条件独立假设,无须进行属性过滤;2)能够在先验知识相对不足的情况下,仍保持较高的分类准确率;3)不依赖于样本空间的分布,具有较好的分类稳定性.