Efficient Computation of k-Medians over Data Streams Under Memory Constraints

In this paper, we study the problem of efficiently computing k-medians over high-dimensional and high speed data streams. The focus of this paper is on the issue of minimizing CPU time to handle high speed data streams on top of the requirements of high accuracy and small memory. Our work is motivated by the following observation： the existing algorithms have similar approximation behaviors in practice, even though they make noticeably different worst case theoretical guarantees. The underlying reason is that in order to achieve high approximation level with the smallest possible memory, they need rather complex techniques to maintain a sketch, along time dimension, by using some existing off-line clustering algorithms. Those clustering algorithms cannot guarantee the optimal clustering result over data segments in a data stream but accumulate errors over segments, which makes most algorithms behave the same in terms of approximation level, in practice. We propose a new grid-based approach which divides the entire data set into cells （not along time dimension）. We can achieve high approximation level based on a novel concept called （1 - ε）-dominant. We further extend the method to the data stream context, by leveraging a density-based heuristic and frequent item mining techniques over data streams. We only need to apply an existing clustering once to computing k-medians, on demand, which reduces CPU time significantly. We conducted extensive experimental studies, and show that our approaches outperform other well-known approaches.     

Downlink multiple access schemes for transmitted reference pulse cluster UWB systems

Transmitted reference pulse cluster (TRPC) signaling was recently proposed for low data rate ultra‐wideband communications. Compared with the conventional transmitted reference (TR), TRPC has a more compact and uniform spacing for the reference and data pulses and therefore solves the implementation problem posed by the long delay line requirement in the conventional TR. In this paper, downlink multiple access issue is further investigated for TRPC systems. According to the TRPC signaling structure, both code division multiple access (CDMA) and time division multiple access (TDMA) methods are discussed. Theoretical analysis and simulation results show that TDMA outperforms CDMA in both bit error rate performance and throughput. Copyright © 2010 John Wiley & Sons, Ltd.     

MDS与三边定位相结合的多点相对定位算法

结合当下导航系统对备份导航的需求,为了完善备份导航体系,针对拒止环境下网络集群定位算法开展相关研究,以MDS为基础研究相关的定位方法,推导了MDS用于集群定位的过程,分析了传统MDS用于网络集群定位的局限和不足,提出了一种MDS和三边定位相结合的网络定位方法,根据传统MDS对节点间距离的需求特性,用三边定位弥补缺失的距离信息,对相应的定位原理进行了论述,既减小了MDS中使用最短路径带来的观测误差,也减小了三边定位中的观测误差的传递层数,从而提高了定位精度。通过对不同分布环境条件下进行仿真验证了该方法的正确性与可行性,对比分析了该算法较之传统MDS定位的优越性,并从算法的复杂度和资源消耗等方面提出了该方法后续的优化方向。     

基于簇半径差异化和节点能量区间的分簇算法

提出一种基于簇半径差异化和节点能量区间的分簇算法——CRDNE算法.该算法用于解决电子导游系统能量均衡问题,从而尽可能的延长网络寿命.算法首先利用路由跳数将整个网络划分热点和非热点区域,并根据不同区域的通信开销不同的特点,定义了不同的区域簇半径.然后,根据区域簇半径和节点剩余能量所处的能量区间,分布式地选取簇首.最后,将CRDNE算法与LDCR、Leach-V算法在Matlab平台进行多个方面仿真比较,进一步证明了本文算法的优越性.     

Optimal power system operation using parallel processing system and PSO algorithm

In recent studies, PSO algorithm is applied to solve OPF problem. However, population based optimization method requires higher computing time to find optimal point. This shortcoming is overcome by a straightforward parallelization of PSO algorithm. The developed parallel PSO algorithm is implemented on a PC-cluster system with 8 Intel Pentium IV 2 GHz processors. The proposed approach has been tested on the test systems. The results showed that computing time of parallelized PSO algorithm can be reduced by parallel processing without losing the quality of solution.     

智能电表家用负荷识别技术综述

智能电表是智能电网发展的基础,负荷识别是智能电表的重要功能之一。简单介绍了在家用负荷识别中的负荷特征,阐述了目前比较常用的几种非侵入式负荷识别方法,分析了各种负荷识别方法的优缺点,讨论了负荷识别技术研究的意义以及在实际应用中面临的问题。     

An Improved Method for Load Taxonomy Using Sample Shifting Technique and Signature Analysis

This paper illustrates an improved method of classification of electrical appliances, particularly for domestic loads, to construct load taxonomy on the basis of their signature analysis. Each electrical load is characterized by its own distinct signature and hence load signature analysis is useful in monitoring the health of the equipment, power quality, in determining individual energy usage etc. type of services. On the other hand, load taxonomy classifies these loads in several clusters on the basis of some features extracted from their signatures. In traditional methods of construction of load taxonomy, different signature patterns based on power metrics, V-I trajectories, Eigen vectors, etc. In this proposed method, with the adoption of sample shifting technique the required number of feature extraction is reduced to a lower value to find out various signature patterns than those are required in traditional load taxonomies. Moreover, a better taxonomy, having well separated groups of loads is achieved with lower number of extracted features.     

基于几何特征的飞机部位识别跟踪算法

针对复杂天气情况下形状可辨的飞机,提出了一种对飞机部位的识别跟踪算法。该算法利用飞机的几何特征,通过数学形态学的原理,在存有噪声干扰的运动图像中简单快速有效地识别出所需目标的重要部位,自动获取其跟踪模板,通过相关匹配技术实现对飞机重要部位的稳定跟踪。给出了应用该算法的具体步骤,并通过实验证明了该算法的有效性。     

馈源阵面排列对偏置多波束天线特性的影响

以３７单元馈源阵为例,就用于卫星移动通信系统中的偏置多波束天线进行分析探讨：在原有两种馈源阵阵面排列形式的基础上,又提出了第三种排列形式,即馈源阵的球面排列形式,并对这三种形式下偏置多波束天线的远场特征进行了计算比较,得出了一些有益的结论;另外,将馈源阵阵面适当地偏离焦点也可使多波束天线的远场特性得以改善。     

基于四粒子团簇态的可控量子隐形传态

提出利用四粒子团簇态传送一个未知单粒子态从而实现可控量子隐形传态的方案,发送者对她自己拥有的两个粒子做一次Bell基联合测量,两控制者合作对其两粒子进行Bell基联合测量,接收者在两个控制者的帮助下对其自己的粒子做相应的幺正变换,即可得到要传送的单粒子态,完成可控量子隐形传态.