你的智慧，我的成功

CIO对于IT的理解,已经不仅仅停留在技术层面, 他们需要在业务层面来证明IT的价值。 与此形成呼应,IT供应商不能仅仅停留在一个产品或是技术解决方案供应者的位置。 将自身塑造成客户的战略业务伙伴,才是当下IT供应商在中国发展的转型方向。     

最重要的是把负的变成正的

热闹喧嚣后的圣诞瘦街头,Reka Lorincz漫步在无人的巴塞罗那的一条小巷里,她独自伫立在橱窗前良久,端详着跳舞的圣诞老人,“为什么你只会在一年年末才来到我们的身边,然后销声匿迹一整年？那这一整年中,你都在哪里？”于是,在2004年,Reka把这些平日圣诞节过后被废弃的树、包装,甚至圣诞老人的头发,做成一系列作品。而她,也就这样走进了大众视野。     

基于ESLS的顾客定位系统的设计与实现

为了收集消费者在商场中经过的位置信息,顾客在商场中某一区域驻留的时间,结合消费者最终购买的商品信息进行数据分析。为此在电子货架标签系统基础上,设计了一套适用于商场中,顾客定位系统。该系统在智能网关端通过采集蓝牙的RSSI,经过Http请求,传输到后台定位服务器,最后经过测距的方法,进行定位。实现结果表明,管理员不仅能够在页面上查询到顾客的位置,而且还能查询顾客在商场中驻留的时间。     

树的数据结构的改进研究

本文首先简单介绍了树的原理,然后在分析目录树的基础上给出了一种改进后的树存储数据结构,它在维护大量数据的同时,降低了数据冗余度。在建立树的经典数据结构的基础上提出了一种基于哈希算法的树构建数据结构。通过分析它们的时间复杂度,均较改进前有了较大减少。     

基于泳道的CSWF的访问控制模型

在工作流中应用访问控制,数据在工作流中流动,执行操作的用户在改变,用户的权限也在改变,这与数据处理的上下文环境相关。采用传统的访问控制技术,如DAC,MAC,则难以做到这一点,若采用RBAC,也需要频繁地更换角色,且不适合工作流程的运转。文章在契约式的安全业务流程设计的基础上,利用泳道,建立基于泳道的安全工作流的访问控制模型。     

三维的世界：立体的互联网

在显示领域中,一共有两条线在发展,一条线的发展是轻薄、易用。从CRT技术到平板技术到超薄LED、OLED的技术过渡,代表着在个人消费显示领域的技术发展。     

绵延12000公里的温暖

退休以后,去自驾支教。……六年前,一位信息技术教师,有一个愿望。……利用信息技术,将教育的温暖与欢乐,绵延到12000公里以外的大山中。……因为在那里。有人卖掉房子,盖起学校。有人背井离乡,前往支教。也有人只身千里,送去欢笑。……因为在那里。没有网络,甚至没有公路,教育面临着挑战。但对于孩子而言,鞋子破了,也要徒步去上学。……于是,"十八道弯"山路崎岖,"云海"翻腾。驱车驶过,转眼间12000公里行于脚下。……在北川,在汶川,在凉山彝族自治州。……在宁强,在临沧,在普洱。     

当下的力量

觉醒"你生存在这个世界就是要使宇宙的神圣目标得以实现。你看,你是多么重要!"——埃克哈特·托利。埃克哈特·托利从伦敦大学毕业后,在剑桥大学担任研究员和导师,他曾讲述自己29岁时的经历。以前他生活在一种焦躁不安的状态中,甚至有过自杀的想法,然而那种压抑和焦虑在他29岁生日过后不久的一个晚上突然消失了。其中,没有什么魔法或者奇异力量,只是因为在那一刻他对生命和本体有了新的认识。     

基于知识距离的粗糙粒结构的评价模型

在粒计算理论中,通过不同的粒计算机制可以生成不同的粒结构。在粗糙集中,对于同一个信息表而言,通过不同的属性添加顺序可以得到由不同的序贯层次结构,即粗糙粒结构。在粗糙粒结构中,不同的属性获取顺序导致了对不确定性问题求解的不同程度。因此,如何有效评价粗糙粒结构是一个值得研究的问题。本文将从知识距离的角度研究这个问题。首先,在前期工作所提出的知识距离框架上提出了一种粗糙近似空间距离,用于度量粗糙近似空间之间差异性。基于提出的知识距离,研究了粗糙粒结构的结构特征。在粗糙粒结构中,在对不确定性问题进行求解时,本文希望在约束条件下可以利用尽可能少的知识空间使不确定性降低达到最大化。基于这个思想并利用以上得出的结论,在属性代价约束条件下,引入了一个评价参数λ,并在此基础建立了一种粗糙粒结构的评价模型,该方法实现了在属性代价约束条件下选择粗糙粒结构的功能。最后,通过实例验证了本文提出的模型的有效性。     

污水处理的谎言

如果有人能够确切地对中国的污水排放量做一个统计的话,那毫无疑问将是一个惊人的数字。因为如今作为世界工厂,中国消耗着全球30％的资源,在全球能耗中占27％的比重。在“made in china”的各种产品不断面世的同时,随之而来的副产品便是大量的工业污水。在这样的情况下,中国的污水处理环节却严重滞后,污水处理的谎言在部分地区已是众人皆知。     

基于AOA的无线传感器网络节点定位算法

在无线传感器网络节点SDP定位算法基础上,提出了一种改进的基于信号到达角(AOA)信息的无线传感器网络节点自身定位算法。本算法在所有节点的坐标轴方向都是未知的假定下,将AOA测量值用于计算信号到达差分角信息,将所有节点之间的角度关系表述为凸规划约束条件,从而将定位问题转化为一个凸集优化问题。在理想情况下,将定位问题转化为一个线性规划问题。实际情况中,考虑到测量误差,通过引入辅助变量,将定位问题转化为一个二次规划问题。仿真结果表明:改进算法与原算法相比,对AOA测量误差在10°以下时,定位精度提高约为5%~20%。     

Localization of multiple disjoint sources with prior knowledge on source locations in the presence of sensor location errors

Sensor location errors are known to be able to degrade the source localization accuracy significantly. This paper considers the problem of localizing multiple disjoint sources where prior knowledge on the source locations is available to mitigate the effect of sensor location uncertainty. The error in the priorly known source location is assumed to follow a zero-mean Gaussian distribution. When a source location is completely unknown, the covariance matrix of its prior location would go to infinity. The localization of multiple disjoint sources is achieved through exploring the time difference of arrival (TDOA) and the frequency difference of arrival (FDOA) measurements. In this work, we derive the Cramér–Rao lower bound (CRLB) of the source location estimates. The CRLB is shown analytically to be able to unify several CRLBs introduced in literature. We next compare the localization performance when multiple source locations are determined jointly and individually. In the presence of sensor location errors, the superiority of joint localization of multiple sources in terms of greatly improved localization accuracy is established. Two methods for localizing multiple disjoint sources are proposed, one for the case where only some sources have prior location information and the other for the scenario where all sources have prior location information. Both algorithms can reach the CRLB accuracy when sensor location errors are small. Simulations corroborate the theoretical developments.     

基于移动锚节点的无线传感器网络三边质心定位

探讨了无线传感器网络(WSN)定位技术的意义,研究基于移动锚节点的测距定位技术;设计了移动锚节点运动轨迹,在利用无线电与超声波到达时间差(TDOA)测得锚节点到待定位节点距离的情况下,给出了一种新的定位算法——三边质心定位算法,该算法通过求解待定位节点的定位近点所构成几何图形的质心来完成定位;仿真结果表明,该定位技术能够明显减小定位误差与锚节点数量。     

协作式无线传感器网络节点定位算法的研究

提出了一种在三个锚节点的条件下基于到达角的测距方法,利用节点之间的几何关系实现传感器网络中未知节点的定位。通过仿真验证该方法能够对未知节点进行有效的定位;同时,该方法仅依赖到达角信息来确定节点的位置,从而降低了处理的复杂度、节省了节点的能量、提高了节点的寿命。     

Improving the localization accuracy of targets by using their spatial–temporal relationships in wireless sensor networks

Due to the low cost and capabilities of sensors, wireless sensor networks (WSNs) are promising for military and civilian surveillance of people and vehicles. One important aspect of surveillance is target localization. A location can be estimated by collecting and analyzing sensing data on signal strength, time of arrival, time difference of arrival, or angle of arrival. However, this data is subject to measurement noise and is sensitive to environmental conditions, so its location estimates can be inaccurate. In this paper, we add a novel process to further improve the localization accuracy after the initial location estimates are obtained from some existing algorithm. Our idea is to exploit the consistency of the spatial–temporal relationships of the targets we track. Spatial relationships are the relative target locations in a group and temporal relationships are the locations of a target at different times. We first develop algorithms that improve location estimates using spatial and temporal relationships of targets separately, and then together. We prove mathematically that our methods improve the localization accuracy. Furthermore, we relax the condition that targets should strictly keep their relative positions in the group and also show that perfect time synchronization is not required. Simulations were also conducted to test the algorithms. They used initial target location estimates from existing signal-strength and time-of-arrival algorithms and implemented our own algorithms. The results confirmed improved localization accuracy, especially in the combined algorithms. Since our algorithms use the features of targets and not the underlying WSNs, they can be built on any localization algorithm whose results are not satisfactory.     

Pulse-coupled time synchronization for distributed acoustic event detection using wireless sensor networks

Time synchronization has proven to be critical in sensor fusion applications where the time of arrival is utilized as a decision variable. Herein, the application of pulse-coupled synchronization to an acoustic event detection system based on a wireless sensor network is presented. The aim of the system is to locate the source of acoustic events utilizing time of arrival measurements for different formations of the sensor network. A distributed localization algorithm is introduced that solves the problem locally using only a subset of the time of arrival measurements and then fuses the local guesses using averaging consensus techniques. It is shown that the pulse-coupled strategy provides the system with the proper level of synchronization needed to enable accurate localization, even when there exists drift between the internal clocks and the formation is not perfectly maintained. Moreover, the distributed nature of pulse-coupled synchronization allows coordinated synchronization and distributed localization over an infrastructure-free ad-hoc network.     

无线传感器网络改进型节点定位算法的研究

无线传感器网络节点位置信息对于事件监测起到至关重要的作用,节点定位技术是无线传感器网络应用的支撑技术之一。为了提高无线传感器网络节点定位的精度,同时减少定位计算过程中的能耗,在RSSI,HCRL定位机制分析的基础上提出了一种改进型的节点定位算法:接收信号强度比定位算法(RSS-RL),通过仿真试验显示:RSS-RL定位算法不仅降低了节点定位复杂度,而且,提高了定位精度。     

基于动态信标生成树的传感器定位算法

节点定位是无线传感器网络中一个基础但十分重要的研究方向。实际应用场景中,传感器节点大多被随机部署,分布往往疏密不均。现存的定位算法对节点的分布密度没有敏感性,如果算法在节点密集区域和稀疏区域使用相同的定位策略,就会造成密度大的区域定位精度低,分布相对稀疏的区域定位率低,信标节点的能量得不到最大化利用等问题。针对这些问题,提出了一种基于节点密度进行定位的生成信标树算法（GBT）。信标节点组沿着规划好的路径对节点进行遍历,实现节点的全定位。通过与其他规划动态信标节点路径算法比较,证明了GBT算法在定位时间、定位精度和对信标节点能量的充分利用上均有所改善。     

一种权系数两级自调整的融合定位精度提高方法

在分布式传感器网络节点定位技术中,使用数据融合方法以提高探测系统的检测与定位精度正成为研究的热点。提出了一种应用于分布式传感器网络中的数据融合定位算法,通过对各个传感器节点的定位信息的加权求和来进行数据融合,用来提高探测系统目标定位的精度。该算法采用两级自适应调整得到最优加权因子,首先利用线性最小均方差（LMSE）算法得到权系数的初始值,然后利用训练节点和递归最小二乘（RLS）算法自适应地调整达到最优。对静态和运动目标的定位数据融合算法进行了仿真,仿真结果表明：相比单节点定位,提出的融合算法的定位精度有约1—2个数量级的提高。     

On the interaction between localization and location verification for wireless sensor networks

Secure wireless sensor networks (WSNs) must be able to associate a set of reported data with a valid location. Many algorithms exist for the localization service that determines a WSN node’s location, and current research is developing for location verification, where the network must determine whether or not a node’s claimed location is valid (or invalid). However, the interaction of these two services creates another challenge, since there is no method to distinguish between benign errors, e.g., errors that are inherent to the localization technique, and malicious errors, e.g., errors due to a node’s deceptive location report. In this paper, we study the problem of inherent localization errors and their impact on the location verification service. We propose a localization and location verification (LLV) server model, and define categories of LLV schemes for discrete and continuous resolution. We then designate two metrics to measure the impact of inherent localization errors—the probability of verification (for the discrete location verification schemes) and the CDF of the deviation distance (for the continuous location verification schemes)—to analyze the performance of each LLV category. Numerical results show that a proper tuning mechanism is needed to tolerate even small inherited estimation errors, otherwise the location verification can result in the rejection of almost all nodes. In addition, we propose several location verification feedback (LV-FEED) algorithms to improve the localization accuracy. Analysis of these algorithms shows that a significant improvement in localization accuracy can be accomplished in a few iterations of executing the location verification feedback schemes.