Stabilization of all-pole unstable delay processes by simple controllers

The stabilization of a class of all-pole unstable delay processes of arbitrary order with single unstable pole by means of simple controllers is investigated in details. Complete stabilizability conditions are established and the computational methods for determining stabilizing controller parameters presented. They provide theoretical understanding of such a stabilization problem and can also serve as practical guidelines for actual controller design.     

基于IXP422平台的Redboot移植分析

Redboot是一个常用在嵌入式系统上的开机启动引导程序,由于不同的嵌入式平台在硬件上存在着很大的差异,因此需要对Redboot进行移植来满足不同的平台硬件要求。该文阐述了Redboot在IntelIXP422平台移植的一般方法及步骤,移植过程同样适用于IXP系列的其它平台。     

采用商业卫星构建虚拟星座

提出了虚拟星座的概念,从商业卫星资源优势、卫星参数差异和传感器特征差异3个方面分析了构建虚拟星座的可行性。以LANDSAT-7卫星和SPOT5卫星为试验对象,验证了构建虚拟星座的可操作性。     

Activity recognition and intensity estimation in youth from accelerometer data aided by machine learning

Physical activity monitoring for youth is an area of increasing scientific and public health interest due to the high prevalence of obesity and downward trend in physical activity. However, accurate assessment of such activity remains a challenging problem because of the complex nature in which certain activities are performed. In this study, we formulated the issue as a machine learning problem—using a diverse set of 19 physical activities commonly performed by youth—via two approaches: activity recognition and intensity estimation. With the aid of training data, we implemented a distance metric learning method called DML-KNN that utilizes time-frequency features and is capable of effectively classifying both continuous and intermittent movement in youth subjects. Four different time-frequency feature extraction methods were then systematically evaluated. Our results show that the DML-KNN method performed competitively, especially when using features extracted by the Tamura method for intensity estimation, and by the Square Coefficient method for activity recognition.     

Online learning of dynamic multi-view gallery for person Re-identification

Person re-identification receives increasing attentions in computer vision due to its potential applications in video surveillance. In order to alleviate wrong matches caused by misalignment or missing features among cameras, we propose to learn a multi-view gallery of frequently appearing objects in a relatively closed environment. The gallery contains appearance models of these objects from different cameras and viewpoints. The strength of the learned appearance models lies in that they are invariant to viewpoint and illumination changes. To automatically estimate the number of frequently appearing objects in the environment and update their appearance models online, we propose a dynamic gallery learning algorithm. We specifically build up two datasets to validate the effectiveness of our approach in realistic scenarios. Comparisons with benchmark methods demonstrate promising performance in accuracy and efficiency of re-identification.     

A content-adaptive video quality assessment method for online media service

Multimedia Tools and Applications - Video quality assessment is an important issue for Internet Content Providers (ICPs) to improve their service. Some research has been done on objective video...     

An adaptive surrogate model based on support vector regression and its application to the optimization of railway wind barriers

This study provides evidence supporting the use of the update strategies for the support vector regression (SVR) model. Firstly, the fitting and interpolation method (FIM) is presented to select SVR parameters, and three infill strategies are adopted to search for update points. Secondly, the infill strategy and parameter selection method are illustrated by test functions that illustrate their dependability. The distribution of update points, the sample density and the proportion of update points are discussed. Finally, the adaptive SVR surrogate model is applied to optimize the protective effect of railway wind barriers. The result shows that the parameter selection method has high stability. On the whole, the accuracy of the adaptive SVR model using a suitable infill strategy will be improved with an increasing proportion of update points if the final number of training points is identical. The optimization result shows an optimal porosity of 0.117 when the height of the railway wind barrier is 2.05 m (full scale).

     

一种中文文档的非受限无词典抽词方法

本文提出了一种非受限无词典抽词模型,该模型通过自增长算法获取中文文档中的汉字结合模式,并引入支持度、置信度等概念来筛选词条。实验表明:在无需词典支持和利用语料库学习的前提下,该算法能够快速、准确地抽取中文文档中的中、高频词条。适于对词条频度敏感,而又对计算速度要求很高的中文信息处理应用,例如实时文档自动分类系统。     

谈局域网的性能优化

在局域网运行和维护的过程中,网络管理员不仅要确保网络能够提供正常的服务,还要采取各种措施保证网络能够可靠、安全、高效地运行,从整个网络的角度提高网络的性能。