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101.
102.
浅谈基于Zigbee技术的无线传感器网络的应用 总被引:1,自引:0,他引:1
Zigbee技术的出现为传感器信号的无线传输提供了新的解决方案。本文简单介绍了Zigbee技术及特点,列举了几种基于Zigbee技术的无线传感器网络的典型应用,分析基于Zigbee技术的无线传感器网络的发展趋势。 相似文献
103.
基于贝叶斯网络的脆弱性状态评估方法 总被引:1,自引:0,他引:1
对网络安全性的量化评估问题是目前网络安全领域的研究热点之一。通过对现有的网络安全模型及量化分析方法的研究和比较,针对影响网络安全性的各项因素的全面脆弱性评估,提出了网络可靠度、脆弱点关键度、脆弱性状态图最低阶最小路集和最低阶最小割集4个具体的评估指标,将基于贝叶斯网络的计算方法引入脆弱性评估中,提出了量化评估计算方法。在此基础上构建了网络实例,使用SPIN验证工具对网络攻击进行模拟并对提出的评估指标及算法进行了分析验证。实验结果表明,文中提出的算法和评估指标集能够正确地量化反映网络的安全状态。 相似文献
104.
贝叶斯理论在多波段SAR图像分类融合中的应用 总被引:1,自引:0,他引:1
将贝叶斯理论用于多波段SAR图像的分类.分析了常见的乘积方法、平均方法以及 中值方法,并在贝叶斯平均方法的基础上,利用SAR图像分类精度与距离因子之间的关系,提 出3种改进方法.实验结果表明,多波段融合可以结合各波段的优势和互补信息,获得单波段 分类无法获取的分类结果.改进方法通过加权减小了错误分类信息的影响,进一步提高分类精度. 相似文献
105.
Zhu Jun 《浙江大学学报(A卷英文版)》2000,1(1):78-90
New approaches based on general mixed linear models were presented for analyzing complex quantitative traits in animal models,
seed models and QTL (quantitative trait locus) mapping models. Variances and covariances can be appropriately estimated by
MINQUE (minimum norm quadratic unbiased estimation) approaches. Random genetic effects can be predicted without bias by LUP
(linear unbiased prediction) or AUP (adjusted unbiased prediction) methods. Mixed-model based composite interval mapping (MCIM)
methods are suitable for efficiently searching QTLs along the whole genome. Bayesian methods and Markov Chain Monte Carlo
(MCMC) methods can be applied in analyzing parameters of random effects as well as their variances.
Projects supported by NSFC (39670390, 39893350) and the NIH Grant GM32518 相似文献
106.
在矿井下发生安全事故后,及时准确地获知井下作业人员的位置信息是至关重要的。本文提出将ZigBee技术运用于煤矿井内定位系统中,组成无线传感器网络,构建井下人员无线定位系统的设计方案。 相似文献
107.
108.
Roy Levy 《Educational Measurement》2020,39(1):94-95
In this digital ITEMS module, Dr. Roy Levy describes Bayesian approaches to psychometric modeling. He discusses how Bayesian inference is a mechanism for reasoning in a probability-modeling framework and is well-suited to core problems in educational measurement: reasoning from student performances on an assessment to make inferences about their capabilities more broadly conceived, as well as fitting models to characterize the psychometric properties of tasks. The approach is first developed in the context of estimating a mean and variance of a normal distribution before turning to the context of unidimensional item response theory (IRT) models for dichotomously scored data. Dr. Levy illustrates the process of fitting Bayesian models using the JAGS software facilitated through the R statistical environment. The module is designed to be relevant for students, researchers, and data scientists in various disciplines such as education, psychology, sociology, political science, business, health, and other social sciences. It contains audio-narrated slides, diagnostic quiz questions, and data-based activities with video solutions as well as curated resources and a glossary. 相似文献
109.
110.
Giangiacomo Bravo Mike Farjam Francisco Grimaldo Moreno Aliaksandr Birukou Flaminio Squazzoni 《Journal of Informetrics》2018,12(1):101-112
This paper aims to examine the influence of authors’ reputation on editorial bias in scholarly journals. By looking at eight years of editorial decisions in four computer science journals, including 7179 observations on 2913 submissions, we reconstructed author/referee-submission networks. For each submission, we looked at reviewer scores and estimated the reputation of submission authors by means of their network degree. By training a Bayesian network, we estimated the potential effect of scientist reputation on editorial decisions. Results showed that more reputed authors were less likely to be rejected by editors when they submitted papers receiving negative reviews. Although these four journals were comparable for scope and areas, we found certain journal specificities in their editorial process. Our findings suggest ways to examine the editorial process in relatively similar journals without recurring to in-depth individual data, which are rarely available from scholarly journals. 相似文献