Gradient Boundary Detection for Time Series Snapshot Construction in Sensor Networks

In many applications of sensor networks, the sink needs to keep track of the history of sensed data of a monitored region for scientific analysis or supporting historical queries. We call these historical data a time series of value distributions or snapshots. Obviously, to build the time series snapshots by requiring all of the sensors to transmit their data to the sink periodically is not energy efficient. In this paper, we introduce the idea of gradient boundary and propose the gradient boundary detection (GBD) algorithm to construct these time series snapshots of a monitored region. In GBD, a monitored region is partitioned into a set of subregions and all sensed data in one subregion are within a predefined value range, namely, the gradient interval. Sensors located on the boundaries of the subregions are required to transmit the data to the sink and, then, the sink recovers all subregions to construct snapshots of the monitored area. In this process, only the boundary sensors transmit their data and, therefore, energy consumption is greatly reduced. The simulation results show that GBD is able to build snapshots with a comparable accuracy and has up to 40 percent energy savings compared with the existing approaches for large gradient intervals.     

A novel methanol-tolerant Ir-Se chalcogenide electrocatalyst for oyxgen reduction

A novel methanol-tolerant oxygen-reduction catalyst, Iridium-selenium (Ir-Se) chalcogenide, was synthesized by chemical precipitation in an organic solvent. Auger electron spectroscopy (AES) analysis confirmed that the synthesized Ir-Se chalcogenide had a chemical formula of Ir₄Se. This chalcogenide showed strong catalytic activity towards the oxygen reduction reaction (ORR) and a high methanol tolerance. It was found that most of the oxygen could be directly reduced to water through a four-electron pathway with less than 10% hydrogen peroxide (H₂O₂) being produced during the ORR. The improvement in catalytic activity of the Ir-Se chalcogenide in comparison with that of pure Ir might be attributed to the effect of a bimetallic interaction.     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

基于老年群体的健身器材交互设计研究

当今社会,人口老龄化已经成为全世界共同的社会问题,中国也在逐步迈入老龄化社会行列,然而现代信息社会正向年轻化发展。两者的矛盾不言而喻,这让老年人与现代社会脱节越来越严重。文章以老年人健身器材为研究对象,在了解老年人特点的基础上,分析老年人交互式产品的设计原则,总结老年人健身器材设计现状,并提出老年人健身器材交互设计的方法,希望对解决当今社会老龄化问题有一定的推动作用。     

一种基于几何分布的新支持向量机多分类方法

二叉树支持向量机是多分类问题的一种有效方法,然而分类的效果与二叉树的结构密切相关。获得更好的分类效果和更高的效率,要使得二叉树高度尽量小而两个子类尽量易分。距离通常用来衡量两个类的分离程度,但不能反映类的分布情况。考虑到多分类中类的分布,文中定义新的分离度和相似度来衡量两个类的分离度,并且提出了一中新的基于几何分布二叉树支持向量机多分类算法,该方法使得二叉树高度尽量小而两个子类尽量易分。实验表明该方法具有较高的分类准确率和效率。     

BOSCH伺服控制系统在ZJ19B卷接机组中的应用

介绍BOSCH伺服控制系统成功应用于ZJ19B卷接机组传动系统中,使机器供丝、供纸、刀头、嘴机部分各个电机的运行更加稳定,控制精度显著提高;减少因控制精度不够而引起的非正常停机次数,提高机器的有效作业率,节约原料;同时使烟支的重量、圆周、紧头等各项指标合格率显著提高。     

3G技术在地震网络系统的安全应用价值探析

从地震的发生频率上来看,我国是一个多发的国家。同时在地震中由于受到各种灾害而引起的损失也是最严重的。所以,对地震的信号进行实时性监测并完成信号数据的快速传输必须要应用先进的技术手段。文章主要介绍的就是目前应用十分广泛的3G技术在地震的网络系统中的安全应用。     

A new parallel particle filter face tracking method based on heterogeneous system

This paper proposed a multi-cue-based face-tracking algorithm with the supporting framework using parallel multi-core and one Graphic Processing Unit (GPU). Due to illumination and partial-occlusion problems, face tracking usually cannot stably work based on a single cue. Focusing on the above-mentioned problems, we first combined three different visual cues??color histogram, edge orientation histogram, and wavelet feature??under the framework of particle filters to considerably improve tracking performance. Furthermore, an online updating strategy made the algorithm adaptive to illumination changes and slight face rotations. Subsequently, attempting two parallel approaches resulted in real-time responses. However, the computational efficiency decreased considerably with the increase of particles and visual cues. In order to handle the large amount of computation costs resulting from the introduced multi-cue strategy, we explored two parallel computing techniques to speed up the tracking process, especially the most computation-intensive observational steps. One is a multi-core-based parallel algorithm with a MapReduce thread model, and the other is a GPU-based speedup approach. The GPU-based technique uses features-matching and particle weight computations, which have been put into the GPU kernel. The results demonstrate that the proposed face-tracking algorithm can work robustly with cluttered backgrounds and differing illuminations; the multi-core parallel scheme can increase the speed by 2?C6 times compared with that of the corresponding sequential algorithms. Furthermore, a GPU parallel scheme and co-processing scheme can achieve a greater increase in speed (8×?C12×) compared with the corresponding sequential algorithms.