基于概念网络的文本信息监控技术

由于网上信息的迅速增长,文本信息监控已经成为网上信息管理中的热点研究课题。本文在模糊集和语义网络的理论基础上,构建了模糊值动态约束性概念网络,介绍了该概念网络的基本构建方法,并提出了基于概念网络的文本分析算法。     

Error Concealment Based on Semantic Prioritization with Hardware‐Based Face Tracking

With video compression standards such as MPEG‐4, a transmission error happens in a video‐packet basis, rather than in a macroblock basis. In this context, we propose a semantic error prioritization method that determines the size of a video packet based on the importance of its contents. A video packet length is made to be short for an important area such as a facial area in order to reduce the possibility of error accumulation. To facilitate the semantic error prioritization, an efficient hardware algorithm for face tracking is proposed. The increase of hardware complexity is minimal because a motion estimation engine is efficiently re‐used for face tracking. Experimental results demonstrate that the facial area is well protected with the proposed scheme.     

通用安全协议分析语言CPAL的研究

本文先从软件理论的角度对安全协议分析语言CPAL的语法和语义进行分析，指出这种语言控制流的缺陷，在语法和语义方面给出CPAL语言的完善方案，并从信息安全中的协议的广泛性方面说明其必要性。     

The Strategic Control of Multiple Routes in Imitation of Actions.

The aim of this study was to bring to the surface the strategic use of imitative processes in the context of a 2-route model: (a) direct imitation, used in reproducing new, meaningless actions, and (b) imitation based on stored semantic knowledge of familiar meaningful actions. Three experiments were carried out with healthy participants who reproduced meaningful and meaningless actions within an established time limit. The study investigated 3 factors that could potentially affect the selection of processes used for imitation: (a) the composition of the experimental list (blocked or mixed presentation), (b) the presence-absence of instructions (Experiments 1 and 2), and (c) the relative proportions of the stimuli (Experiment 3). Overall, the results suggest that each of these factors influences the selection of imitative strategies in healthy individuals with temporarily reduced capacities, as happens in the case of brain-damaged patients. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

High-level synthesis design flow for power side-channel security

The lack of efficient security guidance is a prominent problem in the design flow of high-level synthesis. To tackle this issue, this paper proposes a security-based high-level synthesis design flow featuring the power side-channel vulnerabilities. The side-channel leakage is quantified by establishing a secure component module library, a more efficient and secure parallel scheduling mechanism is generated by optimizing the control flow, and a more secure architecture of the storage system is achieved by optimizing the data flow. The goal is to perform tradeoffs between performance and security, reducing the side-channel risks at the early stage of design and simultaneously generating more secure and efficient cryptographic cores in hardware. Furthermore, the proposed HLS design flow is verified on a field programmable gate array platform. Experimental results show that, in comparison with the traditional design flow, this method reduces the resources by 72% and the clock cycles by 70% and increases the throughput by 88%, and that it can lower the power side-channel risks within an ongoing design to the greatest extent.     

一种基于社会网络的信任模型

社会网络是通过朋友关系、工作关系和信息交换等一组社会机制,将人、组织和其他社会团结联系在一起形成的网络,Web就是一种社会网络.在社会网络中要求有一种自然的机制对网络的真实性进行判断和评价,信任模型就是比较好的一种机制.基于社会网络,本文构建了一种网络信任模型,用来估算信任者和被信任者之间的信任等级,能够用于语义网的信任管理系统和社会网络的信任评价中.实验结果表明,该模型具有很好的效率和效果.     

基于本体的BML命令语义标注方法

作战管理语言（Battle Management Language,BML）是一种无歧义的语言规范,用于解决指控和仿真系统间的互操作问题。针对BML命令缺乏语义信息,难以被计算机理解和自动处理的问题,分析了BML的五视图体系结构,引入了BNF形式化语法,并在此基础上提出了一种语义标注方法,对命令中的对象、时间和地理位置等要素进行标注,然后整合各要素来表达整条命令的语义,系统通过解析标注文档可以实现对命令的无歧义理解,最后给出实例予以说明。论文为表达BML命令的语义提出了一种借鉴思路。     

一种基于本体概念语义相似度的查询优化方法

文章提出一种优化查询方法,该方法将本体概念语义相似度和词法之间的关系相结合。先利用语法特征对用户输入的关键字进行扩展,然后通过分析语义相似度的强弱对扩展的结果进行收敛,以这种方式来提高用户输入的关键字和本体映射的准确性和完整率。传统搜索引擎不能很好地理解用户的意图的缺陷通过此方法可以得到有效解决。同时文章针对方法实现了优化查询系统,结果显示,搜索的准确率得到有效提升。     

基于语义Web的搜索引擎研究

传统搜索引擎是基于关键字的检索,然而文档的关键字未必和文档有关,而相关的文档也未必显式地包含此关键字。基于语义Web的搜索引擎利用本体技术,可以很好地对关键字进行语义描述。当收到用户提交的搜索请求时,先在已经建立好的本体库的基础上对该请求进行概念推理,然后将推理结果提交给传统的搜索引擎,最终将搜索结果返回给用户。相对于传统的搜索引擎,基于语义Web的搜索引擎有效地提高了搜索的查全率和查准率。     

RAFNet: RGB-D attention feature fusion network for indoor semantic segmentation

Semantic segmentation based on the complementary information from RGB and depth images has recently gained great popularity, but due to the difference between RGB and depth maps, how to effectively use RGB-D information is still a problem. In this paper, we propose a novel RGB-D semantic segmentation network named RAFNet, which can selectively gather features from the RGB and depth information. Specifically, we construct an architecture with three parallel branches and propose several complementary attention modules. This structure enables a fusion branch and we add the Bi-directional Multi-step Propagation (BMP) strategy to it, which can not only retain the feature streams of the original RGB and depth branches but also fully utilize the feature flow of the fusion branch. There are three kinds of complementary attention modules that we have constructed. The RGB-D fusion module can effectively extract important features from the RGB and depth branch streams. The refinement module can reduce the loss of semantic information and the context aggregation module can help propagate and integrate information better. We train and evaluate our model on NYUDv2 and SUN-RGBD datasets, and prove that our model achieves state-of-the-art performances.