觉察上下文计算平台的研究

由于缺少通用的觉察上下文计算平台,觉察上下文应用发展缓慢.通过研究基于本体的上下文模型,实现了基于本体的推理、基于规则的推理和不一致性验证三种上下文推理方法,采用关注分离的思想和插件技术构建了觉察上下文计算平台.该平台推理功能全面,具有较好的通用性,可以满足觉察上下文计算应用的需要.     

Context-aware platform for mobile data management

Interaction design is a major issue for mobile information systems in terms of not only the choice of input/output channels and presentation of information, but also the application of context-awareness. To support experimentation with these factors, we have developed platforms to support the rapid prototyping of multi-channel, multi-modal, context-aware applications. The Java-based platform presented here is based on an integration of a cross-media link server and an object-oriented framework for advanced content publishing, along with a Client Controller and Context Engine. We also describe how this platform was used to develop a mobile tourist information system for an international arts festival where interaction was based on a combination of interactive paper and speech output. Moira C. Norrie is a Professor at ETH Zurich where she is head of the Institute for Information Systems and leads the Global Information Systems research group. Her research interests include object-oriented models and systems for data management, web engineering, mobile and personal information systems and interactive paper as a medium for integrating printed and digital information. Beat Signer is a Post-Doctoral researcher in the Global Information Systems research group at ETH Zurich. He received a Ph.D. from ETH Zurich in 2005 for his work investigating fundamental concepts for interactive paper and cross-media information management. His research interests include interactive paper, cross-media information management, object-oriented technologies and software engineering. Michael Grossniklaus is a research assistant in the Global Information Systems research group at ETH Zurich. He received a Diploma (M.Sc.) in Computer Science from ETH Zurich in 2001 and is currently completing his Ph.D. His main research interest is empowering information systems for context-aware data management and delivery in the domain of web engineering and mobile computing. Rudi Belotti was a research assistant in the Global Information Systems research group at ETH Zurich from 2004–2006. He received a Diploma (M.Sc.) in Computer Science from ETH Zurich in 2004. In his research, he developed a general model and engine for the management of context information in mobile information systems. He is currently working for an e-business services company in Ticino, Switzerland. Corsin Decurtins is a research assistant in the Global Information Systems research group at ETH Zurich. He received a Diploma (M.Sc.) in Computer Science from ETH Zurich in 2002. His research focusses on model-based approaches and infrastructure for ubiquitous and mobile information environments. In addition to his Ph.D. Corsin also works part-time as a senior software engineer at the software company Netcetera. Nadir Weibel is a research assistant in the Global Information Systems research group at ETH Zurich. He received a Diploma (M.Sc.) in Computer Science from ETH Zurich in 2003 and is currently working on his Ph.D. His research is in the area of interactive paper, particularly on the authoring and publishing infrastructure for interactive documents as well as issues of human computer interaction and mobile environments.     

Context-aware middleware for pervasive elderly homecare

The growing aging population faces a number of challenges, including rising medical cost, inadequate number of medical doctors and healthcare professionals, as well as higher incidence of misdiagnosis. There is an increasing demand for a better healthcare support for the elderly and one promising solution is the development of a context-aware middleware infrastructure for pervasive health/wellness-care. This allows the accurate and timely delivery of health/medical information among the patients, doctors and healthcare workers through a widespread deployment of wireless sensor networks and mobile devices. In this paper, we present our design and implementation of such a Context-Aware Middleware for Pervasive Homecare (CAMPH). The middleware offers several key-enabling system services that consist of P2P-based context query processing, context reasoning for activity recognition and context-aware service management. It can be used to support the development and deployment of various homecare services for the elderly such as patient monitoring, location-based emergency response, anomalous daily activity detection, pervasive access to medical data and social networking. We have developed a prototype of the middleware and demonstrated the concept of providing a continuing-care to an elderly with the collaborative interactions spanning multiple physical spaces: person, home, office and clinic. The results of the prototype show that our middleware approach achieves good efficiency of context query processing and good accuracy of activity recognition.     

Context-aware features and robust image representations

Local image features are often used to efficiently represent image content. The limited number of types of features that a local feature extractor responds to might be insufficient to provide a robust image representation. To overcome this limitation, we propose a context-aware feature extraction formulated under an information theoretic framework. The algorithm does not respond to a specific type of features; the idea is to retrieve complementary features which are relevant within the image context. We empirically validate the method by investigating the repeatability, the completeness, and the complementarity of context-aware features on standard benchmarks. In a comparison with strictly local features, we show that our context-aware features produce more robust image representations. Furthermore, we study the complementarity between strictly local features and context-aware ones to produce an even more robust representation.     

情境感知的网络用户可信评估模型

互联网已经成为人们生活不可或缺的一部分,但是网络安全问题仍然影响着互联网发展,可信评估逐渐成为保障网络安全的核心,而网络用户又是可信评估的重点评估对象。当前网络可信评估模型没有充分考虑用户所处的情境以及用户的欺诈行为,影响网络用户可信评估的精确性,导致恶意用户的漏判和误判。针对该问题,提出了一种情境感知的网络用户可信评估模型(CAMETNU)。该模型通过对用户访问时所处的情境计算恶意行为的惩罚力度,而又依据用户累计恶意行为加大惩罚力度。实验结果证明了所述方法的有效性。     

Context-aware vocabulary tree for mobile landmark recognition

This paper presents an effective approach that incorporates contextual information into vocabulary tree learning for mobile landmark recognition. For most existing mobile landmark recognition works, the context information (GPS or direction) is mainly used to reduce the search space in a heuristic and insufficient manner. Some recent work uses the context information for codebook learning but only the GPS information is explored. We propose an effective mobile landmark recognition approach which exploits both context (direction and location) and content information for vocabulary tree learning and image recognition. The proposed approach has two major contributions: (i) it proposes an information gain-based codeword discrimination learning method to evaluate the discriminative capability of each direction-aware codeword, as generated by a context-aware vocabulary tree, and (ii) it develops a context-aware image scoring technique based on an inverted file structure that speeds up the image matching process greatly. Experimental results on the NTU and San Francisco database show that the proposed method can achieve good recognition performance with fast speed.     

融合重检测机制的上下文感知目标跟踪算法

为了解决目标跟踪中常见的遮挡、旋转和背景杂乱等问题,提出了一种融合重检测机制的上下文感知目标跟踪算法.首先在相关滤波算法的基础上引入上下文信息供滤波器学习以丰富样本信息,构造上下文感知相关滤波器,提高滤波器的学习能力;然后引入重检测机制判断检测结果的可靠性,解决遮挡情况下模型被污染的问题.最后在公开数据集上对算法的性能...     

基于上下文学习的电力物联网接入控制方法

针对6G时代电力物联网海量终端接入冲突严重、队列积压大、能量效率低等问题,提出了一种基于上下文学习的接入控制算法。所提算法基于强化学习和快速上行链路授权技术,考虑终端活跃与休眠2种状态,优化目标为在终端接入服务质量需求的长期约束下最大化网络总能量效率。利用李雅普诺夫优化对长期优化目标与约束进行解耦,将长期优化问题转化为单时隙独立的确定性子问题,并利用基于终端状态感知的上置信界算法进行求解。仿真结果表明,所提算法能够在满足终端接入服务质量需求的同时,有效提高网络总能量效率。相较于传统快速上行链路授权算法,所提算法可提高平均能量效率48.11%,提高满足接入服务质量需求的终端比例54.95%,降低平均队列积压83.83%。     

Context-aware parallel handover optimization in heterogeneous wireless networks

Annals of Telecommunications - The key idea of this paper is to a use cross-layer triggering concept in order to control the vertical handover (VHO) in heterogeneous networks. Current mobility...     

普适计算中一种上下文感知的自适应可信模型

针对普适计算环境中涌现出的行为可信问题,提出了一种适合于普适计算网络环境的上下文感知的自适应可信模型CASATM,该可信模型能够自适应地对不同的服务提供不同层次的安全保障,能有效地对时间、地点、服务内容等上下文感知.同时提出了一种简单高效的风险评估模型来完成对一些完全陌生客体的可信度初始化.仿真实验表明该可信模型能有效地感知上下文并抵抗恶意客体的周期性欺骗行为.     

Context-aware joint dictionary learning for color image demosaicking

Most digital cameras are overlaid with color filter arrays (CFA) on their electronic sensors, and thus only one particular color value would be captured at every pixel location. When producing the output image, one needs to recover the full color image from such incomplete color samples, and this process is known as demosaicking. In this paper, we propose a novel context-constrained demosaicking algorithm via sparse-representation based joint dictionary learning. Given a single mosaicked image with incomplete color samples, we perform color and texture constrained image segmentation and learn a dictionary with different context categories. A joint sparse representation is employed on different image components for predicting the missing color information in the resulting high-resolution image. During the dictionary learning and sparse coding processes, we advocate a locality constraint in our algorithm, which allows us to locate most relevant image data and thus achieve improved demosaicking performance. Experimental results show that the proposed method outperforms several existing or state-of-the-art techniques in terms of both subjective and objective evaluations.     

Context-aware systems — a primer for user-centred services

Convergence in the telecommunications industry provides an excellent platform and opportunity for new context-aware services. Context awareness, i.e. being able to harvest environmental information and use it to meet or anticipate user needs, is a key enabler for personalised applications and services that will be attractive to users in the future. This paper explores relevant research studies that have been undertaken, and proposes a new architecture for realisation of a context-aware system.     

Context-aware location discovery exchange in a ubiquitous environment

It becomes challenging in order to represent,discover and exchange location information in a ubiquitous environment due to dynamic movement and interaction between mobile nodes inside.In this paper,a new method is presented in order to make location information context-aware so that organizing the format of location information and maintaining the communication between direct connected nodes in a ubiquitous environment is enabled.The structure of a contextual location information repository and a context information communication protocol is manipulated to implement the proposed features.According to the simulation results in network simulator version2(NS2),the new method has depicted good discovery success and consumed efficient service discovery bandwidth.Other network traffic,i.e.transmission control protocol,(TCP) has been simulated in the scenarios but the new location-aware method has shown its robustness with continuous context discovery process.     

Context-aware security framework based on Traffic Anomaly Detection Indicator

Context-aware security utilizes external data, such as time of the day or user information, to improve its capability of detecting a security breach. In this paper we present a Context-aware security framework based on a Traffic Anomaly Detection Indicator (TADI) which indicates when a threat can occur. The main novelty of our approach is that we use as a context the time-based information derived from profile analysis of a typical day to determine more accurately the presence of an anomaly based on the time of day it occurs. This 24-h typical daily analysis helps us to consider the time interval (night-time, working hours, etc.) in which a potential threat occurs, in contrast to traditional sudden peak changes. First, a preliminary analysis based on historical data shows how traffic typically behaves at each particular period of the day. We subsequently calibrate our procedure by checking the effectiveness of different algorithms so that we are aware of which ones gets better performance in each period of the day. Finally the TADI is calculated from the time-based contextual information. We also present the results based on actual traffic traces collected from a campus university that show the effectiveness of the proposed method.     

基于环境感知与MIH的无缝切换优化研究

网络多样化已经是当今接入网的一大特点,完成各种网络的准确切换和会话连续性保障是其中关键的两项。IEEE802.21框架能够保证移动终端(Mobile Node,MN)在多网络中自由移动,然而保证切换过程中QoS连续性仍是需要解决的问题。针对切换过程中的这两个要求,提出动态阈值和被动资源预留方法保证准时切换和会话连续性,通过仿真可以看到相对传统的固定阈值和无资源预留方法的情况,该方法对切换连续性有一定的改善。     

Context-aware mobile image annotation for media search and sharing

In recent years, rapid advances in media technology including acquisition, processing and distribution have led to proliferation of many mobile applications. Amongst them, one of the emerging applications is mobile-based image annotation that uses camera phones to capture images with system-suggested tags before uploading them to the media sharing portals. This procedure can offer information to mobile users and also facilitate the retrieval and sharing of the image for Web users. However, context information that can be acquired from mobile devices is underutilized in many existing mobile image annotation systems. In this paper, we propose a new mobile image annotation system that utilizes content analysis, context analysis and their integration to annotate images acquired from mobile devices. Specifically, three types of context, location, user interaction and Web, are considered in the tagging processes. An image dataset of Nanyang Technological University (NTU) campus has been constructed, and a prototype mobile image tag suggestion system has been developed. The experimental results show that the proposed system performs well in both effectiveness and efficiency on NTU dataset, and shows good potential in domain-specific mobile image annotation for image sharing.     

上下文感知自治QoS框架中的新型包标记算法

Autonomic networking is one of the hot research topics in the research area of future net- work architectures. In this paper, we introduce context-aware and autonomic attributes into DiffServ QoS framework, and propose a novel autonomic packet marking （APM） algorithm. In the proposed autonomic QoS framework, APM is capable of collecting various QoS related contexts, and adaptively adjusting its behavior to provide better QoS guarantee according to users＇ requirements and network conditions. Simulation results show that APM provides better performance than traditional packet marker, and significantly improves user＇s quality of experience.