智能热交换器与空调系统构建的“绿色基站”解决方案与实践

在分析基站耗电的主要构成、机房内外气温变化统计情况的基础上,介绍"绿色基站"节能散热解决方案的架构和实践情况。应用情况表明,该解决方案可在保证机房环境温湿度、洁净度等要求的同时,充分利用自然冷源,大幅降低基站空调耗电,给通信企业带来显著的经济和社会效益。     

Scheduling on same-speed processors with at most one downtime on each machine

We consider the problem of scheduling a set of independent tasks on multiple same-speed processors with planned shutdown times with the aim of minimizing the makespan. We give an LPT-based algorithm, LPTX, which yields a maximum completion time that is less than or equal to 3/2 the optimal maximum completion time or 3/2 the time that passes from the start of the schedule until the latest end of a downtime. For problems where the optimal schedule ends after the last downtime, and when the downtimes represent fixed jobs, the LPTX maximum completion time is within 3/2 of the optimal maximum completion time. In addition, we show that this result is asymptotically tight for the class of polynomial algorithms assuming that P≠NP. We also show that the bound obtained previously for a similar problem, when no more than half of the machines are shut down at the same time, for the LPT algorithm is asymptotically tight in the class of polynomial algorithms if P≠NP.     

贴片电阻表面缺陷自动识别方法

贴片电阻生产过程中的缺陷主要依靠人工在显微镜下检测,速度慢、长期成本高、误检率高.针对贴片电阻单元具有排列整齐、结构简单、图像灰度级少的特点,在贴片电阻图像二值化、边缘提取、直线检测基础上,以相邻电阻单元的相关系数作为电阻缺陷判别依据,提出基于子图投影匹配的快速缺陷检测方法.采用主分量分析法压缩图像数据量,提取缺陷特征,以基于支持向量机对贴片电阻缺陷进行分类并建立实验系统.缺陷检测及识别实验表明,缺陷检测正确率为92.5oo,算法的快速性和识别准确度满足系统快速高精的要求.     

A General Framework for Mining Massive Data Streams

In many domains, data now arrive faster than we are able to mine it. To avoid wasting these data, we must switch from the traditional “one-shot” data mining approach to systems that are able to mine continuous, high-volume, open-ended data streams as they arrive. In this article we identify some desiderata for such systems, and outline our framework for realizing them. A key property of our approach is that it minimizes the time required to build a model on a stream while guaranteeing (as long as the data are iid) that the model learned is effectively indistinguishable from the one that would be obtained using infinite data. Using this framework, we have successfully adapted several learning algorithms to massive data streams, including decision tree induction, Bayesian network learning, k-means clustering, and the EM algorithm for mixtures of Gaussians. These algorithms are able to process on the order of billions of examples per day using off-the-shelf hardware. Building on this, we are currently developing software primitives for scaling arbitrary learning algorithms to massive data streams with minimal effort.     

Self-organized criticality and color vision: A guide to water–protein landscape evolution

We focus here on the scaling properties of small interspecies differences between red cone opsin transmembrane proteins, using a hydropathic elastic roughening tool previously applied to the rhodopsin rod transmembrane proteins. This tool is based on a non-Euclidean hydropathic metric realistically rooted in the atomic coordinates of 5526 protein segments, which thereby encapsulates universal non-Euclidean long-range differential geometrical features of water films enveloping globular proteins in the Protein Data Bank. Whereas the rhodopsin blue rod water films are smoothest in humans, the red cone opsins’ water films are optimized for smoothness in cats and elephants, consistent with protein species landscapes that evolve differently in different contexts. We also analyze red cone opsins in the chromatophore-containing family of chameleons, snakes, zebrafish and goldfish, where short- and long-range (BLAST and hydropathic) amino acid (aa) correlations are found with values as large as 97%–99%. We use hydropathic aa optimization to estimate the maximum number _Nmax$N_{max}$ of color shades that the human eye can discriminate, and obtain 10⁶<_Nmax<10⁷${10}^6<N_{max}<{10}^7$, in good agreement with experiment.     

LabVIEW RT在多任务控制系统中的应用

本文详细描述了利用NI公司的LabVIEW RT软件和E系列的控制器、高精度数据采集卡、执行程序生成器和LabVIEW来开发一个实时控制器,同时实现对位移、扭转,温度,流量的高速,精确控制并完成数据采集和存储.     

引入模块化概念的贴装设备

向模块化组装生产线方向发展正获得愈来愈多人们的关注。一条由多种“高速模块”所组成的生产线具有许多优点,将对现有的装配厂商具有很大的诱惑力。由高速柔性化贴装设备所组成的组装生产线可以超越传统的芯片射手和微细间距贴装设备。     

基于ARM7的数控机床人机界面的设计

介绍了基于ARM7并辅以DSP和FPGA的数控机床的人机对话通道的设计,主要包括键盘输入和LCD显示两个模块的设计.键盘输入方面主要讨论了满足数控机床应用需要的基于89C51的智能化键盘的设计方法.数控机床的主处理器采用三星S3C44BOX微控制器,软件平台采用μCOS-Ⅱ实时操作系统.论文着重讨论了在该嵌入式平台下LCD显示模块的设计方法.键盘输入结合LCD显示模块可以实时监视机床的运行状态,管理和编辑加工程序,完成各种参数的录入等功能.     

A new sequence based encoding for prediction of host–pathogen protein interactions

Pathogen–host interactions are very important to figure out the infection process at the molecular level, where pathogen proteins physically bind to human proteins to manipulate critical biological processes in the host cell. Data scarcity and data unavailability are two major problems for computational approaches in the prediction of pathogen–host interactions. Developing a computational method to predict pathogen–host interactions with high accuracy, based on protein sequences alone, is of great importance because it can eliminate these problems. In this study, we propose a novel and robust sequence based feature extraction method, named Location Based Encoding, to predict pathogen–host interactions with machine learning based algorithms. In this context, we use Bacillus Anthracis and Yersinia Pestis data sets as the pathogen organisms and human proteins as the host model to compare our method with sequence based protein encoding methods, which are widely used in the literature, namely amino acid composition, amino acid pair, and conjoint triad. We use these encoding methods with decision trees (Random Forest, j48), statistical (Bayesian Networks, Naive Bayes), and instance based (kNN) classifiers to predict pathogen–host interactions. We conduct different experiments to evaluate the effectiveness of our method. We obtain the best results among all the experiments with RF classifier in terms of F1, accuracy, MCC, and AUC.