Construction of a robot control system which understands a voice and pointing actions

This research was aimed at making a robot that can go and get an object designated by the user. We produced a robot control system that uses pointing and voice control. This control system is composed of two systems. One system is the object instruction system that uses pointing, and the other is the object instruction system that uses voice. The approximate position of a designated object is recognized by the object instruction system that uses pointing, and information about the object and instructions about the operation are conveyed by the object instruction system that uses voice. This time, the object instruction system that uses pointing has been designed and verified as the first step. A calculation resource to calculate the approximate position of the designated object is obtained when the user points directly at the object. A robot can be moved around a designated object by using this system. The object instruction system that uses voice will be constructed in future work.     

基于可信计算平台的可信动态客体监管系统的设计与实现

大部分安全操作系统在处理客体时,没有区分具体的客体类型,均采用统一的方法进标识,而且多数安全操作系统中采用传统访问控制方法保护的客体均是静态客体,忽略了对动态客体的保护,使得黑客或攻击者可以进行欺骗和中间人攻击,因此,安全操作系统中的动态客体并不可信.首先分析了操作系统中客体的类型,提出了可信动态客体的概念,并分析了其特点.为了防止动态客体泄露信息,提出了基于TPM的可信动态客体监管系统.一方面,该系统要求主体必须在TPM中注册,确保主体身份合法性,才能利用可信动态客体进行信息传递;另一方面,在TPM中必须存储创建该可信动态客体的属主的身份信息,以确保可信动态客体身份的合法性.最后进行了安全和性能分析,分析表明该可信动态客体监管系统可以阻止黑客利用动态客体进行欺骗和中间人攻击,防止信息泄露,为进一步建立可信计算环境提供了基础.     

PUF-enhanced offline RFID security and privacy

RFID (Radio Frequency IDentification) based communication solutions have been widely used nowadays for mobile environments such as access control for secure system, ticketing systems for transportation, and sport events. These systems usually depend on readers that are not continuously connected to a secure backend system. Thus, the readers should be able to perform their duties even in offline mode, which generally requires the management by the readers of the susceptible data. The use of RFID may cause several security and privacy issues such as traceability of tag owner, malicious eavesdropping and cloning of tags. Besides, when a reader is compromised by an adversary, the solution to resolve these issues getting worse. In order to handle these issues, several RFID authentication protocols have been recently proposed; but almost none of them provide strong privacy for the tag owner. On the other hand, several frameworks have been proposed to analyze the security and privacy but none of them consider offline RFID system.Motivated by this need, in this paper, we first revisit Vaudenay's model, extend it by considering offline RFID system and introduce the notion of compromise reader attacks. Then, we propose an efficient RFID mutual authentication protocol. Our protocol is based on the use of physically unclonable functions (PUFs) which provide cost-efficient means to the fingerprint chips based on their physical properties. We prove that our protocol provides destructive privacy for tag owner even against reader attacks.     

Put: language-based interactive manipulation of objects

Our approach to scene generation capitalizes the expressive power of natural language by separating its aptness in specifying spatial relations from the difficulties of understanding text. We are implementing an object-placement system called Put that uses a combination of linguistic commands and direct manipulation. The system is language-based, meaning that its design and structure are guided by natural language. Our approach (inspired by research in cognitive linguistics) is to analyze the natural use of spatial relations, define a well-understood class of fundamental relationships, and gradually build a coherent and natural spatial-manipulation system. Just a few simple spatial relationships, such as in, on, and at, parameterized by a limited number of environmental variables can provide comfortable object manipulation. These natural commands can be used to quickly prototype a complex scene and constrain object placement. We believe that we have an extensible, predictable, and computationally feasible environment for object manipulation. We have focused first on spatial relationships because they are fundamental to many conceptual domains beyond object placement, including motion and time. These particular domains are very important to areas of computer graphics such as animation. Uses of spatial relationships in these areas can be quite complex. We briefly introduce the complexities of understanding spatial relations and summarize related work. Then we describe the core of the Put placement system, followed by its linguistic, procedural, and interactive interfaces. We conclude by discussing future enhancements to the system     

A robust object category detection system using deformable shapes

An object can often be uniquely identified by its shape, which is usually fairly invariant. However, when the search is for a type of object or an object category, there can be variations in object deformation (i.e. variations in body shapes) and articulation (i.e. joint movement by limbs) that complicate their detection. We present a system that can account for this articulation variation to improve the robustness of its object detection by using deformable shapes as its main search criteria. However, existing search techniques based on deformable shapes suffer from slow search times and poor best matches when images are cluttered and the search is not initialised. To overcome these drawbacks, our object detection system uses flexible shape templates that are augmented by salient object features and user-defined heuristics. Our approach reduces computation time by prioritising the search around these salient features and uses the template heuristics to find truer positive matches.

信任攻击建模方法

针对信任环境系统中存在的客观弱点和主观弱点,使用弱点利用规则和信任关系盗用规则来描述信任关系状态之间的转移过程,构建了信任攻击模型TAM。在该模型中,攻击者将客观弱点用于信任级别的提升,将主观弱点用于信任关系传递,将主、客观弱点的综合利用将导致信任关系的渗透与扩散,从而可导致攻击可达距离更大;提出了复杂度为多项式时间的TAM信任关系传递闭包生成算法,该算法可以给出当前弱点状态下的所有信任攻击路径。通过对真实弱点的建模,证明此模型可以对信任的安全性进行综合分析,生成信任攻击图、信任攻击路径等详细信息,展示攻击者和信任主体之间的交互过程,对攻击特征有更好的描述能力,帮助管理者预测所有可能的信任攻击,进而为相应的安全措施的制定提供依据。     

Crisis management using MAS-based wireless sensor networks

Wireless communication is increasingly used to manage large-scale crises (e.g., natural disasters or a large-scale city fire). Communication has traditionally been based on cellular networks. However, real-life experience has proven that the base stations of these networks may collapse or become unreachable during a crisis. An incident commander must also know as much information as possible about the occurring events to control them quickly and efficiently. This paper thus proposes a crisis management approach that overcomes the problems encountered by the base stations and insures relevant, rich and real-time information about events. This approach is based on wireless sensor networks, which are distributed in nature with no need for infrastructure and could be deployed in dangerous and inaccessible zones to gather information. Our proposal uses a multi-agent system as a software layer. The multi-agent system aims to improve the wireless sensor network performance by allowing cooperation between sensor nodes, offering better lifetime management and virtualizing the application layer. This virtualization supports several required applications simultaneously, including event monitoring and object tracking. Through successive simulations, we prove the importance of our approach in crisis management using several criteria to estimate the position’s error in object tracking, end-to-end delay and wireless sensor network lifetime management.     

GPARS: a general-purpose activity recognition system

The fundamental problem of the existing Activity Recognition (AR) systems is that these are not general-purpose. An AR system trained in an environment would only be applicable to that environment. Such a system would not be able to recognize the new activities of interest. In this paper we propose a General-Purpose Activity Recognition System (GPARS) using simple and ubiquitous sensors. It would be applicable to almost any environment and would have the ability to handle growing amounts of activities and sensors in a graceful manner (Scalable). Given a set of activities to monitor, object names (with embedded sensors) and their corresponding locations, the GPARS first mines activity knowledge from the web, and then uses them as the basis of AR. The novelty of our system, compared to the existing general-purpose systems, lies in: (1) it uses more robust activity models, (2) it significantly reduces the mining time. We have tested our system with three real world datasets. It is observed that the accuracy of activity recognition using our system is more than 80%. Our proposed mechanism yields significant improvement (more than 30%) in comparison with its counterpart.     

Handling of Alternatives and Events in Temporal Databases

Planning for the future is an important activity both at the individual and organizational levels. Planning consists of defining alternative actions to handle various events in the future. The alternatives arise becau]se of different possible outcomes of events. A plan consists of a sequence of actions to be carried out for each possible outcome. In the context of database modeling, the actions are operations on a database. A database management system should enable its users to define events and alternatives, and also allow them to interact with the database under different alternatives (possibly to evaluate different plans). The existing temporal data models treat the future analogous to the past or present; they provide for one future path (in the sense that facts valid at some future time can be stored), but do not provide support for alternatives in the future. In this paper, we present a model for incorporating events and alternatives by extending the temporal data model to support branching time. The extended model permits definitions of events, their interdependencies and associated actions. The events that affect an object are modeled by a tree, permitting an object to have different states at the same valid time but under different alternatives. The branching time paradigm is obtained by superimposing a linear valid time on the event tree. We extend the temporal relational algebra and the Temporal SQL2 to support a branching time data model. The paper also briefly deals with the uncertainties associated with future planning as well as probabilities of possible event outcomes. Finally, we sketch an implementation strategy for the branching time data model.     

基于运动方向的异常行为检测

提出了一种基于运动方向的异常行为检测方法. 根据不同行为的运动方向具有不同的规律性, 该方法采用块运动方向描述不同的动作, 并利用支持向量机(Support vector machine, SVM)对实时监控视频进行异常行为检测. 为了减少噪声运动的影响, 同时有效保留小幅度运动的前景目标, 在行为描述之前, 本文采用了背景边缘模型对每一视频帧进行前景帧(有目标出现的视频帧)判断. 在行为描述时, 先提取相应视频段的所有前景帧的块运动方向, 然后对这些运动方向进行归一化直方图统计得到该视频段的行为特征. 在走廊等公共场景中的实验结果表明, 该方法能够对单人以及多人的复杂行为进行有效检测, 对运动过程中目标大小的变化、光照的变化以及噪声等具有较好的鲁棒性, 而且计算复杂度小, 能够实现实时监控.     

Optimal adaptive bandwidth monitoring for QoS based retrieval

Network aware multimedia delivery applications are a class of applications that provide certain level of quality of service (QoS) guarantees to end users while not assuming underlying network resource reservations. These applications guarantee QoS parameters like media object transmission time limit by actively monitoring the available bandwidth of the network and adapting the object to a target size that can be transmitted within a given time limit. A critical problem is how to obtain an accurate enough estimation of available bandwidth while not wasting too much time in bandwidth testing. In this paper, we present an algorithm to determine optimal amount of bandwidth testing given a probabilistic confidence level for network-aware multimedia object retrieval applications. The model treats the bandwidth testing as sampling from an actual bandwidth population. It uses statistical estimation method to quantify the benefit of each new bandwidth-testing sample, which is used to determine the optimal amount of bandwidth testing by balancing the benefit with the cost of each sample. Our implementation and experiments shows the algorithm determines the optimal amount of bandwidth testing effectively with minimum computation overhead.     

带GPS的嵌入式报警器设计

文章介绍了使用UP—NETARM300开发平台并接入GPS模块和GSM模块从而实现带GPS嵌入式报警器的报警模型的设计方法。带GPS的嵌入式报警器的主要特点是时空变化可成为触发报警的原因，时空参数可作为报警信息的一部分。报警信息通过GSM发送短消息给代理服务器或机主，代理服务器或机主根据收到的报警信息进行相应的处理。     

RFID技术在社区管理系统中的应用研究

物联网应用已经改变了原有的社区管理模式。本研究利用射频识别技术(Radio Frequency Identification,RFID)研发新型社区管理系统。系统包含“业主进出管理系统”、“社区访客管理服务”、“业主安全管理服务系统”、“业主异常管理服务系统”四个子系统。经实际使用,发现系统不仅提高了社区服务质量,减少人力支出,还大大简化了社区管理流程,降低了行政管理过程中的复杂性。     

一种基于高斯混合模型的视频监控运动物体提取系统

现有的视频监控系统必须要依靠人对监控图像的实时观察才能发挥作用。设计并实现了一种基于高斯混合模型的自适应的视频监控运动物体提取系统,使用高斯混合模型对监控场景进行建模,利用对象形状的空间连通性和最小像素尺寸约束去除噪声影响,从而实时地分离出前景中的运动物体并对其进行追踪和计数,仿真实验的结果证明了系统的有效性。     

A Neural Network Approach to Planar-Object Recognition in 3D Space

Most existing 2D object recognition algorithms are not perspective (or projective) invariant, and hence are not suitable for many real-world applications. By contrast, one of the primary goals of this research is to develop a flat object matching system that can identify and localise an object, even when seen from different viewpoints in 3D space. In addition, we also strive to achieve good scale invariance and robustness against partial occlusion as in any practical 2D object recognition system. The proposed system uses multi-view model representations and objects are recognised by self-organised dynamic link matching. The merit of this approach is that it offers a compact framework for concurrent assessments of multiple match hypotheses by promoting competitions and/or co-operations among several local mappings of model and test image feature correspondences. Our experiments show that the system is very successful in recognising object to perspective distortion, even in rather cluttered scenes. Receiveed: 29 May 1998?,Received in revised form: 12 October 1998?Accepted: 26 October 1998     

隐文加密系统中的隐文B+树加密索引方法

传统方法使用对文件或整个磁盘进行加密来保护数据信息，加密后的信息本身无法隐藏自身的存在，文件本身的存在会促使感兴趣的攻击者破解加密信息。在某些情况下攻击者可以使用强迫手段迫使文件的主人公开他的加密密钥，这使得复杂的加密技术变得毫无意义。该文介绍了一种着重于隐藏数据存在性的加密手段——隐文加密，对重要文件的存储进行加密，该方法采用隐文B+树建立Unix系统文件索引，通过隐藏表将隐文B+树索引隐蔽起来，使攻击者无法知道重要信息的存在，保障了信息的安全性。     

An internet of old things as an augmented memory system

The interdisciplinary Tales of Things and electronic Memory (TOTeM) project investigates new contexts for augmenting things with stories in the emerging culture of the Internet of Things (IoT). Tales of Things is a tagging system which, based on two-dimensional barcodes (also called Quick Response or QR codes) and Radio Frequency Identification (RFID) technology, enables the capturing and sharing of object stories and the physical linking to objects via read and writable tags. Within the context of our study, it has functioned as a technology probe which we employed with the aim to stimulate discussion and identify desire lines that point to novel design opportunities for the engagement with personal and social memories linked to everyday objects. In this paper, we discuss results from fieldwork with different community groups in the course of which seemingly any object could form the basis of a meaningful story and act as entry point into rich inherent ‘networks of meaning’. Such networks of meaning are often solely accessible for the owner of an object and are at risk of getting lost as time goes by. We discuss the different discourses that are inherent in these object stories and provide avenues for making these memories and meaning networks accessible and shareable. This paper critically reflects on Tales of Things as an example of an augmented memory system and discusses possible wider implications for the design of related systems.     

基于PSoC的汽车防盗报警系统设计

现在汽车报警装置普遍存在着误报率和无法有效通知车主的缺陷,为此,设计了一种基于可编程片上系统(PSoC)的汽车防盗报警系统。该系统利用PSoC作为主控芯片,实现了系统的单片化,减少了PCB面积,降低了成本;并且利用GSM网络可让车主及时获悉汽车安全状况;同时运用SC—1振动传感器,提高了汽车防盗报警系统的灵敏度。这些优点很好地解决了误报率和与车主通信的问题。经过实际模拟与测试,证明该系统性能稳定,颇具应用价值。     

Addressing the assessment challenge with an online system that tutors as it assesses

Secondary teachers across the United States are being asked to use formative assessment data (Black and Wiliam 1998a,b; Roediger and Karpicke 2006) to inform their classroom instruction. At the same time, critics of US government’s No Child Left Behind legislation are calling the bill “No Child Left Untested”. Among other things, critics point out that every hour spent assessing students is an hour lost from instruction. But, does it have to be? What if we better integrated assessment into classroom instruction and allowed students to learn during the test? We developed an approach that provides immediate tutoring on practice assessment items that students cannot solve on their own. Our hypothesis is that we can achieve more accurate assessment by not only using data on whether students get test items right or wrong, but by also using data on the effort required for students to solve a test item with instructional assistance. We have integrated assistance and assessment in the ASSISTment system. The system helps teachers make better use of their time by offering instruction to students while providing a more detailed evaluation of student abilities to the teachers, which is impossible under current approaches. Our approach for assessing student math proficiency is to use data that our system collects through its interactions with students to estimate their performance on an end-of-year high stakes state test. Our results show that we can do a reliably better job predicting student end-of-year exam scores by leveraging the interaction data, and the model based on only the interaction information makes better predictions than the traditional assessment model that uses only information about correctness on the test items.