Making HCI theory work: an analysis of the use of activity theory in HCI research

This paper reports a study of the use of activity theory in human–computer interaction (HCI) research. We analyse activity theory in HCI since its first appearance about 25 years ago. Through an analysis and meta-synthesis of 109 selected HCI activity theory papers, we created a taxonomy of 5 different ways of using activity theory: (1) analysing unique features, principles, and problematic aspects of the theory; (2) identifying domain-specific requirements for new theoretical tools; (3) developing new conceptual accounts of issues in the field of HCI; (4) guiding and supporting empirical analyses of HCI phenomena; and (5) providing new design illustrations, claims, and guidelines. We conclude that HCI researchers are not only users of imported theory, but also theory-makers who adapt and develop theory for different purposes.     

Game Theory and Decision Theory in Multi-Agent Systems

In the last few years, there has been increasing interest from the agent community in the use of techniques from decision theory and game theory. Our aims in this article are firstly to briefly summarize the key concepts of decision theory and game theory, secondly to discuss how these tools are being applied in agent systems research, and finally to introduce this special issue of Autonomous Agents and Multi-Agent Systems by reviewing the papers that appear.     

Putting the ‘theory’ back into grounded theory: guidelines for grounded theory studies in information systems

Over the past decade, there has been increasing interest in the use of grounded theory in information systems research. Grounded theory is a qualitative research method that seeks to develop theory that is grounded in data systematically gathered and analysed. The purpose of this paper is to suggest guidelines for grounded theory studies in information systems. Our guidelines are based on a framework for theorizing in grounded theory studies that focuses on conceptualization and theory scope. Our hope is that the guidelines will help to raise the quality and aspirations of grounded theory studies in information systems.     

The Automated Refinement of a Requirements Domain Theory

The specification and management of requirements is widely considered to be one of the most important yet most problematic activities in software engineering. In some applications, such as in safety critical areas or knowledge-based systems, the construction of a requirements domain theory is regarded as an important part of this activity. Building and maintaining such a domain theory, however, requires a large investment and a range of powerful validation and maintenance tools. The area of theory refinement is concerned with the use of training data to automatically change an existing theory so that it better fits the data. Theory refinement techniques, however, have not been extensively used in applications because of the problems in scaling up their underlying algorithms.In our work we have applied theory refinement to assist in the problem of validation and maintenance of a requirements theory concerning separation standards in the North East Atlantic. In this paper we describe an implemented refinement algorithm, which processes a logic program automatically generated from the theory. We overcame the size and expressiveness problems typically encountered when applying theory refinement to a logic program of this kind by designing focused, composite refinement operators within the algorithm. These operators modify the auto-generated logic program by generalising or specialising clauses containing ordinal relations—that is relations which operate on totally ordered data.     

An introduction to some statistical aspects of PAC learning theory

In this paper, a brief introduction is given to some statistical aspects of PAC (probably approximately correct) learning theory. It is shown that there is a close connection between the principal results in PAC learning theory and those in empirical process theory, the latter being a well-established branch of probability theory. The main results in each area are summarized without proofs, and the reader is directed to appropriate sources in the literature.     

分层色彩校正算法研究

提出了一种基于视网膜皮层理论和颜色视觉理论分层色彩校正算法：引入颜色视觉理论中的三色学说进行全局分类,使用广义高斯混合模型计算全局系数;简化分层色彩校正模型减少计算量;引用retinex理论对三通道分别进行处理,进行高光区域提取;使用对立学说进行色差计算,根据色度距离和空间距离设置系数权重,并根据系数校正像素;采用分层色彩校正模型整合图像。所提算法融合了颜色视觉理论和视网膜皮层理论,对现有的分层色彩校正进行了进一步的改进。实验验证该算法在模拟人类视觉系统色彩恒常性方面具有很好的合理性和实用性,实验表明该算法对非均匀多光源色偏图像有很好的校正效果。     

Ordered seminormal default theories and their extensions

Abstract

The concept of extension plays an important role in default logic. The notion of an ordered seminormal default theory has been introduced (Etherington 1987) to characterize a class of seminormal default theories which have extensions. However, the original definition has a drawback because of its dependence on specific representations of the default theory. We introduce the ‘canonical representation’ of a default theory and redefine the orderedness of a default theory based on its canonical representation. We show that under the new definition, the orderedness of a default theory Δ = (W,D) is intrinsic to the theory itself, independent of the specific representations of W and D. We present a modification of the algorithm in Etherington (1987) for computing extensions of a default theory. More importantly, we prove the conjecture (Etherington 1987) that a modified version of the algorithm in Etherington (1987) converges for general ordered, finite seminormal default theories, while the original algorithm was proven (Etherington 1987) to converge for ordered, finite network default theories which form a proper subset of the theories considered in this paper.     

竞争与合作——复杂网络结构化形成的内因

采用博弈理论来探究复杂网络进化过程中结构化形成的内在原因.如今用于研究复杂网络的基本方法有3类:随机图模型(ER模型)、小世界模型、无尺度模型.但这3类方法都没有从根本上解释复杂网络结构化形成的原因,毕竟在现实世界中网络的演化过程并不是一个纯粹的优化过程.考虑到博弈论强调博弈者通过按照既定规则选择不同策略形成各自的博弈结果,认为它是一种用来解释不确定性演化过程的理想工具,而图论又可以很好地表示复杂系统以及系统内部的相互关系和相关属性,故将博弈论和图论结合到一起,对复杂网络进化过程中结构化形成的内在原因进行探讨,得出"参与者之间的竞争和合作是促成复杂网络结构化形成的内因"这个结论.     

在一类缺省理论中关于证明理论的完备性问题

缺省推理是各种非单调推理系统中最在影响的系统之一。Ｒ。Ｒｅｉｔｅｒ对规范缺省理论作了一系列的研究。他还提出了证明理论，并证明了这一证明理论对于规范缺省理论来说是完备的。Ｗ。Ｅｔｈｅｒｉｎｇｔｏｎ则提出了应用范围更为广泛的有序半规范缺省理论。本文先证明了这类缺省理论具有半单调性等各种性质，然后证明了Ｒ。Ｒｅｉｔｅｒ的证明理论对于有序半规范缺省理论也是完备的。     

Lukasiewicz逻辑系统中理论的平均真度及偏差

在[n]值Lukasiewicz命题逻辑系统中引入了有限理论的平均真度和偏差的概念,讨论了有限理论的平均真度和偏差各自的重要性质。研究表明,利用平均真度可以刻画有限理论的可靠度,而利用偏差可以刻画有限理论的稳定性,因此将理论的平均真度和偏差相结合就可以对有限理论的好坏进行全面且综合的评判。     

Institution中自由理论态射的合成

本文在一定的条件下建立了Institution中理论态射的粘合与各因子态射的自由性之间的联系.并证明了自由理论态射的复合仍为自由的.     

认证协议的必要条件证明

提出绑定项理论并用该理论构建认证协议的必要条件定理,使用串空间理论证明该定理和3个典型认证协议。该理论能够迅速、有效地判定有缺陷的认证协议的认证属性,除了能够对认证协议的新鲜性、主体进行判定外,还能够对具有类型攻击缺陷的认证协议进行判定,为认证协议的安全判定提供一种简单、有效的理论方法。     

Constructive Sets in Computable Sets

The original interpretation of the constructive set theory CZF in Martin-Loef‘s type theory uses the‘extensional identity types’.It is generally believed that these‘types’do not belong to type theory.In this paper it will be shown that the interpretation goes through without identity types.This paper will also show that the interpretation can be given in an intensional type theory.This reflects the computational nature of the interpretation.This computational aspect is reinforced by an ω-Set moel of CZF.     

粒度计算的三种主要方法

粒度计算(Granular Computing,GrC)是新近兴起的人工智能研究领域的一个方向,它覆盖了所有有关粒度的理论、方法、技术和工具的研究。它是词计算理论、粗糙集理论、商空间理论、区间计算等的超集。词计算理论、粗糙集理论、商空间理论是粒度计算的三种主要方法。文中着重介绍了这三种粒度计算的基本理论、模型和方法,以及它们之间的关系,并展望了进一步的研究方向。     

具有比率依赖的捕食食饵模型的分歧研究

研究了一类基于比率依赖的Holling-Leslie捕食-食饵模型。利用分歧理论和度理论结合极值原理,以[d2]为分歧参数,得到了系统非常正解的存在性;同时得出局部分歧可以延拓到整体分歧,并给出了一维情况下整体分歧的性态。     

DS 证据理论研究进展及相关问题探讨

在对证据理论的建模、推理、决策到评估各层面最新进展梳理的基础上, 针对证据理论现有研究中存在的 一些问题、混淆和误解, 结合仿真算例进行了分析和探讨, 包括据理论与概率论的关系, 证据冲突与反直观结果的 关系, 证据距离的定义以及证据理论的评价准则问题等. 最后对证据理论的发展方向进行了展望. 该研究旨在为人们正确理解和使用证据理论提供参考和借鉴作用.     

软件可靠性测试的理论分析

目前软件可靠性测试没有真正开展起来,即使重要的军用软件也没有进行软件可靠性测试。软件可靠性模型的不一致性以及软件可靠性测试时间长、费用高、资源消耗大是造成这种局面的两个主要问题。而这两个问题很大程度是由传统基于随机系统假设的软件可靠性理论导致的。因此,在该理论下对可靠性测试方法及可靠性模型的修补与改善工作很难从根本上解决问题。只有从软件可靠性理论本身入手,提出新的研究思路,才有可能摆脱目前软件可靠性测试的困境。首先介绍了软件可靠性测试的现状,然后重点对现有可靠性理论进行了分析和总结,在此基础上,提出了软件可靠性测试研究的一些新思路。     

基于属性论的特征提取方法及其在人脸识别中的应用

该文提出一种基于属性论的人脸识别方法,主要应用于提高复杂背景下的多姿态人脸检测的识别效果。首先介绍了属性论的基石——定性映射理论,讨论了定性映射、经典集合论和特征函数之间的关系,然后讨论了基于定性映射的模式生成与识别模型,经过对人脸及人脸的特征点进行定位后,即可利用属性计算网格的定性基准网格对人脸的各特征点进行建模。研究发现基于属性论的人脸识别算法,识别率较高。在复杂背景下的多姿态人脸检测(如侧面人脸、遮挡脸)仍然取得较好的效果。     

Representation of analysis results involving aleatory and epistemic uncertainty

Procedures are described for the representation of results in analyses that involve both aleatory uncertainty and epistemic uncertainty, with aleatory uncertainty deriving from an inherent randomness in the behaviour of the system under study and epistemic uncertainty deriving from a lack of knowledge about the appropriate values to use for quantities that are assumed to have fixed but poorly known values in the context of a specific study. Aleatory uncertainty is usually represented with probability and leads to cumulative distribution functions (CDFs) or complementary CDFs (CCDFs) for analysis results of interest. Several mathematical structures are available for the representation of epistemic uncertainty, including interval analysis, possibility theory, evidence theory and probability theory. In the presence of epistemic uncertainty, there is not a single CDF or CCDF for a given analysis result. Rather, there is a family of CDFs and a corresponding family of CCDFs that derive from epistemic uncertainty and have an uncertainty structure that derives from the particular uncertainty structure (e.g. interval analysis, possibility theory, evidence theory or probability theory) used to represent epistemic uncertainty. Graphical formats for the representation of epistemic uncertainty in families of CDFs and CCDFs are investigated and presented for the indicated characterisations of epistemic uncertainty.     

TOPOLOGICAL METHODS FOR SOCIAL AND BEHAVIORAL SYSTEMS†

Abstract

Methods based in algebra and geometry are introduced for the mathematical formulation of problems in the social and behavioral sciences. Specifically, the paper introduces the main concepts of singularity theory, catastrophe theory and q-analysis for the characterization of the global structure of social systems. Applications in urban land development, electric power generation and international conflict are given to illustrate the methodology. The paper concludes with an outline for a general mathematical theory of surprises, together with a program for investigating the systemic property of resilience.