On the coNP hardness of computing certain answers over locally specified incomplete DOM-trees

We consider answering queries over incomplete XML trees. Barceló et al. identified a class of shallow queries for which the problem is efficiently solvable with node ids on trees while it is coNP-complete without them. We show that their result is essentially tight. In other words, we provide a slightly extended class of queries where node ids help no more.     

Computing answers with model elimination

We demonstrate that theorem provers using model elimination (ME) can be used as answer-complete interpreters for disjunctive logic programming. More specifically, we introduce a family of restart variants of model elimination and we introduce a mechanism for computing answers. Building on this, we develop a new calculus called ancestry restart ME. This variant admits a more restrictive regularity restriction than restart ME and, as a side-effect, it is in particular attractive for computing definite answers. The presented calculi can also be used successfully in the context of automated theorem proving. We demonstrate experimentally that it is more difficult to compute nontrivial answers to goals than to prove the existence of answers.     

支持中文医疗问答的基于注意力机制的栈卷积神经网络模型

当前的中文问答匹配技术大多都需要先进行分词,中文医疗文本的分词问题需要维护医学词典来缓解分词错误对后续任务影响,而维护词典需要大量人力和知识,致使分词问题一直具有极大的挑战性。同时,现有的中文医疗问答匹配方法都是对问题和答案分开建模,并未考虑问题和答案中各自包含的关键词汇间的关联关系。因此,提出了一种基于注意力机制的栈卷积神经网络（Att-StackCNN）模型来解决中文医疗问答匹配问题。首先,使用字嵌入对问题和答案进行编码以得到二者各自的字嵌入矩阵;然后,通过利用问题和答案的字嵌入矩阵构造注意力矩阵来得到二者各自的特征注意力映射矩阵;接着,利用栈卷积神经网络（Stack-CNN）模型同时对上述矩阵进行卷积操作,从而得到问题和答案各自的语义表示;最后,进行相似度计算,并利用相似度计算最大边际损失以更新网络参数。所提模型在cMedQA数据集上的Top-1正确率比Stack-CNN模型高接近1个百分点,比Multi-CNNs模型高接近0.5个百分点。实验结果表明,Att-StackCNN模型可以提升中文医疗问答匹配效果。     

突发灾害下可靠路径搜索模型与算法

在分析突发灾害爆发时可靠路径搜索问题特点的基础上,提出了一种在不确定网络中不依赖于弧的旅行时间概率分布的可靠路径搜索方法。该方法通过场景集描述网络旅行时间的不确定性,应用Minimax理论构建求解所有场景下可靠路径的数学模型,并设计了问题求解算法,分析了算法的时间复杂性,最后通过典型算例对算法进行了验证。     

差分隐私DNA模体识别安全共享平台的设计与实现

在数据共享平台进行DNA模体识别的过程中,如何防止个体信息泄露已成为该领域发展的研究热点。对此,设计并实现了基于差分隐私的DNA模体识别安全共享平台,内置多种满足差分隐私保护模型的DNA模体识别算法,实现数据源选择、算法选择、隐私预算设置、结果评估、图形化结果展示等功能。同时,除具备对内置DNA数据的模体识别外,还允许科研人员自主上传、共享DNA数据库,并对共享的DNA数据进行差分隐私模体识别,为科研工作人员提供安全可靠的基因序列分析研究平台和数据共享平台。通过平台测试证明,安全共享平台能够实现DNA数据的有效识别和安全共享,设计方案有效可行。     

基于FPGA的相关干涉仪算法的研究与实现

提出一种利用FPGA实现相关干涉仪测向算法的方法,给出了测向系统的结构和组成框图,并详细介绍了FPGA内部模块的划分及设计流程,最后结合实际设计出一种实现方案,并讨论了该方案在宽带测向中较原有实现方式的优势。为了使算法更适于FPGA实现,提出了一种新的相位样本选取方法,并仿真验证了该方法与传统方法的等效性。     

一种新型的磁定向系统及其定向算法研究

为了提高基于地磁检测的定向精度,通过引入高精度步进电机控制,设计了一种新型的平面单轴磁定向系统。该系统仅需要一个磁性传感器输出信号,通过步进电机带动磁传感器在水平面内做等间隔转动,求取最大值位置以确定磁方位。针对干扰和测试噪声的影响,研究了基于遗传算法和最优化理论的混合数据处理方法。通过对测试数据正弦曲线的四参数拟合,获取初始相位,提高了测角精度。仿真研究和工程实验表明：该定向方法有着较高的精度和较好的稳定性。     

基于概率和可信度方法的普适计算信任模型

根据普适计算环境下信任的特点以及现有信任模型存在的不足,提出一种基于概率和可信度方法的信任模型。模型综合考虑影响信任的主观和客观因素,通过主观信任、直接信任和推荐信任得到总体信任。计算推荐信任时引入基于可信度的匹配度算法对多个推荐实体进行取舍,在计算前就把不符合推荐条件的实体排除,再结合对推荐链路的更新,能够更有效地避免恶意推荐的影响,计算出来的信任值可靠度更高。     

Soft computing and fuzzy logic

What is soft computing? What is fuzzy computing? What is the relationship between them? This paper intends to provide clear answers to these questions. We focus on exploring the notions of the fuzzy coordinate system and the related transformations between qualitative and quantitative information. These notions are considered to be the core ideas of fuzzy computing. Then the three novel theories of fuzzy computing and soft computing developed by the first author of this paper, namely, the Falling Shadow Representation of fuzzy theory, the Factors Space theory and the Truth Value Flow Inference theory are introduced.     

On forming joint variables in computing with words

Abstract

We discuss Zadeh’s idea of computing with words and emphasize its perspective that information provides a restriction on the values variables can assume. We describe the role that the constraint-based semantics plays in translating natural language statements into formal mathematical objects. One task that arises in using this approach is the formulation of joint restrictions on multiple variables from individual information about each of the variables. Our interest here is to extend the capability of the framework of computing with words in the task of forming joint variables with the introduction of the idea of perceived relatedness between variables, a concept closely related to the idea of correlation. We are particularly interested in role that knowledge about perceived relatedness between variables can play in further restricting the possible values of joint then that simple provided by the individual constraints. We look at the problem of joining various types of uncertain variables, possibilistic, probabilistic and Dempster-Shafer belief structures.     

四元声传感器面阵快速测向算法及误差分析

为了对低速移动的声源目标进行较高实时性的方向跟踪,把四元声传感器面阵分为两个二元线阵,分别对目标进行测向,然后融合两组测量结果,给出了目标方位角的计算公式.根据线阵在被跟踪目标方位角不同时测向精度的不同,用加权因子增加较高精度的线阵测量结果的影响,降低误差较大的线阵测量结果的影响.该算法可对传感器阵列所在平面内任意方位的声源快速进行测向,完成一次测向只需对两对时间采样序列分别进行互相关运算,并可获得较高的定向精度,通过实验验证了该算法的精度和有效性.     

基于定位点和路径复用的大型多人在线游戏寻路算法

针对当前寻路算法不能很好满足大型多人在线游戏对于可靠性和低消耗的要求,提出一种基于定位点和路径复用的大型多人在线游戏寻路算法。通过定位点的使用和路径复用,使得无用空间的探索大幅减少,降低了服务器的负载,最终探索出一条接近最优的路径。实验结果表明,该算法具有更高的效率,对于大型多人在线游戏寻路是一个切实可行的解决方案。     

Binary search with delayed and missing answers

How many questions are necessary and sufficient to guess an unknown number x in the set S={1,2,…,n}, by using only comparison questions, that is questions of the type “Is x?a?”, a∈S, when answers to questions are received with a delay of d time units and up to c of the answers can be lost, i.e., can not be received at all? We exactly solve this problem for all integers d?0 and c=1.     

一种基于多站测向和多参数信息的联合分选算法

针对信号分选问题, 提出一种多站测向和多参数信息联合分选算法. 该算法基于多个观测站共同接收到辐射源脉冲的情况, 首先, 主站确定基准脉冲, 通过多参数信息搜索副站中的匹配脉冲; 然后, 通过位置和多参数信息联合搜索与主站可能是同一辐射源的脉冲, 并在副站脉冲序列中搜索与之匹配的脉冲; 最后提取匹配脉冲. 实验表明, 所提出的算法在观测站接收脉冲数量较少, 即利用脉冲重频统计规律的分选算法不适用时, 仍能准确分选出辐射源, 避免漏警的出现.

     

Time-varying square roots finding via Zhang dynamics versus gradient dynamics and the former's link and new explanation to Newton-Raphson iteration

Different from conventional gradient-based neural dynamics, a special class of neural dynamics have been proposed by Zhang et al. since 12 March 2001 for online solution of time-varying and static (or termed, time-invariant) problems (e.g., nonlinear equations). The design of Zhang dynamics (ZD) is based on the elimination of an indefinite error-function, instead of the elimination of a square-based positive or at least lower-bounded energy-function usually associated with gradient dynamics (GD) and/or Hopfield-type neural networks. In this paper, we generalize, develop, investigate and compare the continuous-time ZD (CTZD) and GD models for online solution of time-varying and static square roots. In addition, a simplified continuous-time ZD (S-CTZD) and discrete-time ZD (DTZD) models are generated for static scalar-valued square roots finding. In terms of such scalar square roots finding problem, the Newton iteration (also termed, Newton-Raphson iteration) is found to be a special case of the DTZD models (by focusing on the static-problem solving, utilizing the linear activation function and fixing the step-size to be 1). Computer-simulation results via a power-sigmoid activation function further demonstrate the efficacy of the ZD solvers for online scalar (time-varying and static) square roots finding, in addition to the DTZD's link and new explanation to Newton-Raphson iteration.     

Priorities on defaults with prerequisites,and their application in treating specificity in terminological default logic

In a recent paper we have proposed terminological default logic as a formalism that combines means both for structured representation of classes and objects and for default inheritance of properties. The major drawback that terminological default logic inherits from general default logic is that it does not take precedence of more specific defaults over more general ones into account. This behavior has already been criticized in the general context of default logic, but it is all the more problematic in the terminological case where the emphasis lies on the hierarchical organization of concepts.The present paper addresses the problem of modifying terminological default logic such that more specific defaults are preferred. We assume that the specificity ordering is induced by the hierarchical organization of concepts, which means that default information is not taken into account when computing priorities. It turns out that the existing approaches for expressing priorities between defaults do not seem to be appropriate for defaults with prerequisites. Therefore we shall consider an alternative approach for dealing with prioritization in the framework of Reiter's default logic. The formalism is presented in the general setting of default logic where priorities are given by an arbitrary partial ordering on the defaults. We shall exhibit some interesting properties of the new formalism, compare it with existing approaches, and describe an algorithm for computing extensions. In the terminological case, we thus obtain an automated default reasoning procedure that takes specificity into account.This is an extended version of a paper presented at the13th International Joint Conference on Artificial Intelligence, August 1993, Chambery, France.     

Theorising about gender and computing interventions through an evaluation framework

Despite over 20 years of intervention programmes, the gender balance in the computing profession is not improving. It has been suggested that the problem with much of the research on gender and computing is that it is under‐theorised. The contribution of this study is an evaluation framework, designed to evaluate gender and computing interventions, which will advance the theorisation of research through programme evaluation. This study was undertaken in three phases: The first involved theory building through an extensive review of the literature resulting in a conceptual framework for intervention programme evaluation. The second phase consisted of a multiple‐case study of 14 major intervention programmes in Australia. Subsequent modifications to the conceptual framework resulted in the gender and computing intervention evaluation framework. The value of the framework was confirmed in phase three by intervention experts and showed that applying the framework will help programme champions to evaluate their programmes more thoroughly. The dissemination of sound evaluation results will then enable a deeper theorisation of the issues surrounding gender and computing interventions.