Translating moral orders: putting moral conflict theory in conversation with actor–network theory

Moral conflict theory explains deep moral differences and patterns of communication commonly associated with such conflicts. Moral conflict is defined as a struggle between humans, but we argue that the objects of contention in such intractable conflicts, including texts, physical objects, and places, assume a force of their own. We use actor–network theory to help explain this eventuality and to expand our understanding of moral conflict. Combining actor–network theory literature with moral conflict theory literature helps us understand the complexity of moral orders and the networks of actors involved in the construction of moral conflict. This expansion of literature also allows us to conceive of more possibilities for transcendent discourse.     

机动通信网分级分布式网络规划设计

为提高机动通信网络规划的科学性、准确性,充分发挥指战员能动性和通信装备效能,提出了一种分级分布式网络规划方法,阐明了分级资源管理和分级分布式网络规划两种应用模式。所提方法支持规划任务的分解和资源段的下发,并能融合各级规划结果,形成全网规划态势。此外,对分布式数据融合过程中必然会出现的冲突设计了检查及处理流程,并根据引起冲突的资源类型,明确了判定规则和处理办法。     

基于Pignistic概率转换和奇异值分解的证据冲突度量方法

针对常见证据冲突度量方法适应性差、准确性低的问题,提出了一种基于Pignistic概率转换和奇异值分解的证据冲突度量方法。首先通过Pignistic概率转换将证据焦元差异映射到信度差异上,构建证据复合信任函数矩阵。然后采用奇异值分解的方法提取矩阵特征,根据奇异值特性将矩阵特征空间划分为相似子空间和冲突子空间,综合考虑证据矩阵相似特性和冲突特性,将冲突子空间奇异值与相似子空间奇异值之比作为新的冲突度量因子。最后在全冲突场景、变信度场景、变焦元场景、焦元嵌套场景等多种证据冲突场景下将所提方法与常见方法进行了对比分析,结果表明所提方法具有适应性广、准确性高、稳定性好的特点。     

多源红外弱小目标灰色关联融合识别方法

针对从复杂地物背景下识别红外弱小目标的需求,提出了一种针对中/长波红外图像的多源信息融合识别方法。首先在对低信噪比红外图像的预处理中改进了去相关和分块阈值分割等算法以抑制温度场的非线性影响,有效提取出目标及其特征,再利用基于灰色理论的目标关联度计算得到基本概率赋值,进一步运用D-S证据理论组合规则对多个观测样本的信任度进行决策融合,得到同一时刻多传感器探测样本数据的最终识别结果。实验表明,该方法对复杂地物背景下的红外弱小目标具有较高的识别效率。     

Mapping ICT use at home and telecommuting practices: A perspective from work/family border theory

This study draws on the work/family border theory to investigate the role of information communication technology (ICT) use at home in shaping the characteristics of work/family borders (i.e. flexibility and permeability) and consequently influencing individuals’ perceived work-family conflict, technostress, and level of telecommuting. Data were collected from a probability sample of 509 information workers in Hong Kong who were not self-employed. The results showed that the more that people used ICT to do their work at home, the greater they perceived their work/family borders flexible and permeable. Interestingly, low flexibility and high permeability, rather than the use of ICT at home, had much stronger influences on increasing, in particular, family-to-work conflict. As expected, work-to-family conflict was significantly and positively associated with technostress. Results also showed that the telecommuters tended to be older, had lower family incomes, used ICT frequently at home, and had a permeable boundary that allowed work to penetrate their home domain. The theoretical and practical implications are discussed.     

循证护理模式对关节镜下前交叉韧带重建术患者康复锻炼遵从性的影响

目的探讨了循证护理模式对关节镜下前交叉韧带重建术患者康复锻炼遵从性的影响。方法选取在武汉科技大学附属孝感医院接受治疗的63例关节镜下前交叉韧带重建术患者,随机分为观察组32例,对照组31例,对照组行常规护理,观察组实施循证护理,比较两组护理前后康复锻炼总遵从率。结果护理后对照组总遵从率为77.42%,观察组为100%,组间比较差异具有统计学意义(P0.05)。结论对关节镜下前交叉韧带重建术患者行循证护理,可有效提高患者康复锻炼遵从性。     

Uncertain and negative evidence in continuous time Bayesian networks

The continuous time Bayesian network (CTBN) enables reasoning about complex systems by representing the system as a factored, finite-state, continuous-time Markov process. Inference over the model incorporates evidence, given as state observations through time. The time dimension introduces several new types of evidence that are not found with static models. In this work, we present a comprehensive look at the types of evidence in CTBNs. Moreover, we define and extend inference to reason under uncertainty in the presence of uncertain evidence, as well as negative evidence, concepts extended to static models but not yet introduced into the CTBN model.     

Dempster–Shafer fusion of evidential pairwise Markov fields

Hidden Markov fields (HMFs) have been successfully used in many areas to take spatial information into account. In such models, the hidden process of interest X is a Markov field, that is to be estimated from an observable process Y. The possibility of such estimation is due to the fact that the conditional distribution of the hidden process with respect to the observed one remains Markovian. The latter property remains valid when the pairwise process $(X,Y)$ is Markov and such models, called pairwise Markov fields (PMFs), have been shown to offer larger modeling capabilities while exhibiting similar processing cost. Further extensions lead to a family of more general models called triplet Markov fields (TMFs) in which the triplet $(U,X,Y)$ is Markov where U is an underlying process that may have different meanings according to the application. A link has also been established between these models and the theory of evidence, opening new possibilities of achieving Dempster–Shafer fusion in Markov fields context. The aim of this paper is to propose a unifying general formalism allowing all conventional modeling and processing possibilities regarding information imprecision, sensor unreliability and data fusion in Markov fields context. The generality of the proposed formalism is shown theoretically through some illustrative examples dealing with image segmentation, and experimentally on hand-drawn and SAR images.     

美国电信改革得失评述及对中国电信改革的思考

对美国电信改革进行了简要回顾的同时对不同阶段管理措施的功过得失进行评述：在所史分析的基础上,提出了“规模”与“创新”之间的结构性矛盾是电信业有效竞争的根本障碍;结合中国电信改革的实战,提出中国电信改革应缩续坚待循序渐进的改革原别,改革重点应该是鼓励创新而非降低价格。积极探索有效的资源共享机制,寻求电信业结构性矛盾的解决之路。     

高效混合式协同检测方法研究

针对单个节点检测性能容易受多径、阴影效应的影响,提出一种基于模糊聚类和D S证据理论的协同检测方法:首先依据协同节点的拓扑结构和距离信息,采用模糊C均值算法对节点聚类,然后利用OR准则对各聚类内的检测结果进行融合,各聚类之间采用D S证据理论进行融合;最后建立博弈概率分布,根据最大概率原则做出最终判决。仿真结果表明,在可控计算复杂度的情况下,该方法检测性能比传统方法有很大提高,而且在虚警概率为10%时,检测概率能达到90%以上。