Visual field mean deviation and relevant factors in 928 Chinese retinitis pigmentosa patients

AIM: To investigate the associations between demographic and clinical factors with the rate of visual field mean derivation(MD) decline in retinitis pigmentosa(RP) patients.METHODS: Correlations of MDs with the visual acuity and retinal pigmentation were analyzed in 928 RP patients. MD decreasing rate in 10 y and potential influences of gender, age, family history and retinal pigmentation on the rate were explored in 201 RP patients. RESULTS: In the 928 patients, average MD and visual acuity were-14.44±8.61 dB and 0.79±0.35 respectively and when MD was lower than-9.18 dB the visual acuity would be below 1.0(20/20). The average MD medium between eyes with or without retinal pigmentation was-14.82 dB. In 123 non-pigmented eyes, the average MD were lower than the medium but in 153 pigmented eyes it was higher than that. In the 201 patients, the average decreasing value of MD in 10 years’ period was-8.01±3.66 dB and the value were correlated to retinal pigmentation but not to gender, age or RP family history. CONCLUSION: The rate of MD decline in RP eyes is significantly related to retinal pigmentation. Our study demonstrates the quantitative rate of MD decline in RP patients and the value of MD could well reflect the severity of RP.

Mean Difference and Mean Deviation of Tukey Lambda Distribution

The purpose of this paper is to broaden the knowledge of mean difference and, in particular, of an important distribution model known as Tukey lambda, which is generally used to choose a model to fit data. We have obtained compact formulas, which are not yet reported in literature, of mean deviation and mean difference related to the said distribution model. These results made it possible to analyze the relationships among variability indexes, namely standard deviation, mean deviation and mean difference, regarding Tukey lambda model.

MEAN SQUARE DEVIATION ANALYSIS OF INTERANNUAL SST VARIABILITY IN TROPICAL PACIFIC AND INDIAN OCEAN

Using the SST data series in tropical ocean (20N ~ 20S, 50E ~ 80W) during 1951 ~ 1997 to calculate its monthly mean square deviation, the work obtains results showing that interannual SST variability of the Pacific is more significant than that of the Indian Ocean, especially near the central and eastern equatorial Pacific (165W～90W, 6N～6S), where it ranges from 2C to 4C. The interannual SST variability is obvious in November and December but small in March and April. The interannual variability of 搘arm pool?SST is not so obvious as that of the eastern equatorial Pacific. However, interannual SST variability of the Indian Ocean ranges from 1C to 2C or so, being smaller than that of the Pacific. In the Indian Ocean, interannual SST variability of the Southern Hemisphere is more obvious than that of the Northern Hemisphere. According to above characteristics of interannual SST variability, the key sectors are determined.

The Mean Deviation from the Median of the Dagum Distribution

The Dagum model is particularly suitable for the analysis of the distributions of economic quantities, such as income, assets and consumption. The purpose of this note is to derive the expression of the mean deviation from the median of the Dagum distribution to study the behavior of the scale and shape parameters in terms of absolute variability and in terms of relative variability.

基于k-means聚类的智能电表异常动态数据检测方法

为缩小常规电表电量数据与异常测量数据之间的补偿误差水平,提出基于k-means聚类的智能电表异常动态数据检测方法。通过电量负荷异常数据预处理的方式,确定具体的密度偏差值结果,再根据聚类k值条件,提取基于k-means聚类的异常电量数据特征。在此基础上,设定电表数据异常值,根据异常数据清洗原理,得到最终的动态检测特征值计算结果,实现基于k-means聚类智能电表异常动态数据检测方法的设计与应用。实验结果表明,对于常规电表电量数据与异常测量数据而言,k-means聚类检测方法的误差百分比数值较低,能够有效缩小常规数据与异常数据之间的补偿误差水平。

Spectrum Deviation Method of Identification of Foreshocks or Generalized Foreshocks and Its Applications

Based on previous research work,we present a spectrum deviation method to recognize a foreshock or generalized foreshock in this paper. The criterion to determine whether an event is a foreshock is a wide spectrum for an ordinary event,however,a moderate earthquake with foreshock or generalized foreshock has the characteristics of a narrow frequency band,and it deviates to the low frequency. It may be explained by metastable extension in the rupture source or related area of the main shock or regional fragmentation damage and crack nucleation process. The calculation results of two foreshocks,the M_S4. 7 event which occurred before the Yushu M_S7. 1 earthquake on April 14,2010 and the M_S5. 3 event which occurred before the Yutian M_S7. 3 earthquake on February 12,2014,show that the spectra of foreshocks shift,and they are quite different from the nonforeshock seismic spectrum of equivalent size. Therefore,this result can verify the validity of the spectrum deviation method.

An Efficient Frontier for Sum Deviation JIT Sequencing Problem in Mixed-model Systems via Apportionment

In this paper, the sum deviation just-in-time （JIT） sequencing problem in mixed-model production systems is studied relating with the discrete apportionment problem together with their respective mathematical formulations. The assignment formulation for the first problem is briefly discussed followed by the existence of JIT cyclic sequences. Presenting the concise discussion on divisor methods for the discrete apportionment problem, we have proposed two mean-based divisor functions for this problem claiming that they are better than the existing divisors; hence, we found a better bound for the JIT sequencing problem. The linkage of both the problems is characterized in terms of similar type of objective functions. The problems are shown equivalent via suitable transformations and similar properties. The joint approaches for the two problems are discussed in terms of global and local deviations proposing equitably efficient solution.

基于互信息量均方差提取关键帧的激光视频图像检索研究

为保证激光视频图像检索结果中不存在重复性冗余图像,提出了基于互信息量均方差提取关键帧的激光视频图像检索方法。基于互信息量均方差的关键帧提取方法,以激光视频图像颜色的互信息量均方差最大化,为激光视频图像关键帧的聚类中心设置标准,以此聚类提取不重复的视频图像关键帧;通过基于关键帧的激光视频图像检索方法,将所提取关键帧作为激光视频图像检索的核心判断内容,提取与所需图像关键帧相似度显著的激光视频图像,完成激光视频图像检索。实验结果显示:此方法使用后,提取的激光视频图像关键帧冗余度仅有0.01,激光视频图像检索结果的MAP指标测试值高达0.98,检索结果中不存在重复性冗余图像。

控制图在车用催化器中贵金属测定中的应用

研究建立一种应用于催化器中贵金属测定过程监控的均值-标准差质控图,以确保实验室日常分析结果的准确、可靠。采用标准HJ 509-2009中电感耦合等离子体质谱法测定催化转化器中的铑、钯、铂等3种贵金属元素的含量,收集近两年的质控样的60组数据,进行了正态分布检验,计算了各元素含量结果的平均值、标准偏差,绘制了均值控制图和标准差控制图。结果表明,质控样中铑、钯、铂贵金属元素的数据结果均在均值控制图、标准差控制图的上下限范围内,表明实验室在该段期间内利用电感耦合等离子体质谱法对催化转化器样品中的铑、钯、铂的测定结果的准确可靠。均值-标准差控制图可以有效地观察整个贵金属元素测定过程中的数据变化趋势,有助于判断检测过程是否受控,以保证日常的报告检测结果符合实验室报出的要求,确保结果的准确可靠。

嫦娥4/5号月球探测器VLBI观测数据质量分析

在中国探月工程(China’s Lunar Exploration Program,CLEP)中,甚长基线干涉测量技术(very long baseline interferometry,VLBI)具有重要作用。为获得月球探测器的准确定位、实现精确的测定轨功能并以此在探测器飞行过程中完成轨道修正,需要利用VLBI测站对月球探测器进行实时观测。首先以均值(arithmetic mean,AM)以及标准差(standard deviation,STD)作为主要的精度指标,对来源于上海天文台的嫦娥4号探测器、中继星以及嫦娥5号探测器的VLBI实测数据进行总观测时段的数据稳定性分析,并基于嫦娥4号探测器同时段S、X双频段观测,着重进行该探测器不同频率各项数据的质量分析;然后对探测器各工作时段分别进行时延、时延率测量形式误差以及残差分析,了解各时段探测器运动情况与数据变化的相关性。结果表明,3类探测器中,嫦娥4号的实测精度最高,达到1 ns量级;嫦娥5号的观测稳定性优于其他两类探测器;不同地面站对探测器的观测精度有所差异,并且在探测器不同的工作时段,实测数据表现出不同特征。

基于卷积神经网络的电力市场短期售电量预测方法

电力市场短期售电量预测的精度对优化用电结构以及提高供电可靠性具有重要意义,传统短期售电量预测方法没有考虑偏差电量考核影响、用电行为差异导致电预测精度低,提出基于卷积神经网络的电力市场短期售电量预测方法,首先根据用户的用电负荷率进行分类,获取不同行业的用电特征和需求模式,然后考虑正负偏差电量的影响,设计基于CNN-ResNet的短期售电量预测方法,通过实验分析表明,该方法能够有效提高多因素影响下售电量预测的准确率。

CO_(2)状态方程适应性对比研究

气体状态方程被广泛应用于计算CO_(2)的各项物性参数,但CO_(2)物性参数对温度和压力较敏感,不同状态方程计算的结果有偏差。针对目前常用的状态方程开展适应性研究,基于不同温度和压力条件下CO_(2)物性参数实验值对比分析了不同状态方程的计算结果。结果表明:1)GERG对CO_(2)密度及压缩因子具有较高的计算精度。计算CO_(2)密度时蒸汽区平均相对偏差小于0.5%,气相区小于1%;2)SW方程计算CO_(2)定压比热的平均相对偏差为0.29%,计算焦汤系数的平均相对偏差为0.87%;3)Fenghour法计算的黏度最大相对偏差不超过0.5%,平均相对偏差为0.34%,计算结果误差较小;4)V-W法对CO_(2)导热系数的计算结果与实验值较吻合,其平均相对偏差仅为1.24%。研究结果为油气田开发过程中涉及的CO_(2)物性参数计算提供了一定的参考依据。

最小方差优化初始聚类中心的K-means算法

传统K-means算法随机选取初始聚类中心,容易导致聚类结果不稳定,而优化初始聚类中心的K-means算法需要一定的参数选择,也会使聚类结果缺乏客观性。为此,根据样本空间分布紧密度信息,提出利用最小方差优化初始聚类中心的K-means算法。该算法运用样本空间分布信息,通过计算样本空间分布的方差得到样本紧密度信息,选择方差最小(即紧密度最高)且相距一定距离的样本作为初始聚类中心,实现优化的K-means聚类。在UCI机器学习数据库数据集和含有噪音的人工模拟数据集上的实验结果表明,该算法不仅能得到较好的聚类结果,且聚类结果稳定,对噪音具有较强的免疫性能。

一种基于熵和均方差法综合赋权的K-means算法

在传统的K-means聚类算法基础上,本文提出一种基于熵和均方差法综合赋权的Syn-K-means算法。引入综合权重提高聚类结果的类内相似度,从而提高聚类精度。算法中特征权重的计算基于概率论中数字特征的基本描述方法——均方差和信息论中信息特征的基本度量方法——熵;综合赋权系数的选择采用主观设定法求解。实验结果表明,Syn-K-means算法在聚类精度方面优于标准的K-means算法。

当前我国大学生学习意义感的偏离与校正

学习意义感是大学生在学习中建构的意义系统,包括理解并认同自我作为学习主体的力量和价值,追求对自身学习意义的内容诠释,并体验到学习有用、有价值、值得付出努力等积极情感。学习意义感作为一种指引大学生成长成人的内在精神性力量,具有主体性、异质性、生命性以及整体性四大属性,但现实中存在主体性离场、内容同质性、价值工具化、体悟片面性等偏离现象。因此,大学需要以重成人的教育使命、高质量的教育活动、支持性的人际互动、教育性的学校文化实现大学生学习意义感的校正。

氯化两面针碱潜在靶标极光激酶A在结直肠癌组织中的临床病理价值

目的:探究极光激酶A(AURKA)在结直肠癌中的临床病理价值。方法:通过分子对接探究AURKA与氯化两面针碱(NC)结合强度。结合免疫组织化学数据和全球高通量数据集分析结直肠癌中AURKA蛋白和mRNA表达水平,计算标准平均偏差(SMD)和总结受试者操作特征(sROC),以探讨AURKA在结直肠癌和放疗抵抗中综合表达水平,利用CRISPR敲除筛选以及体外敲低AURKA后的基因芯片数据,分析AURKA促癌潜在分子机制。结果:AURKA与NC结合能为-10kcal/mol, AURKA蛋白在结直肠癌中表达上调,mRNA在2 511个结直肠癌样本和41个放疗抵抗样本中表达上调,显示结直肠癌中SMD为2.07,放疗抵抗中SMD为0.73。敲低AURKA在结直肠癌LS123细胞系中生长抑制最显著。体外敲低AURKA mRNA后基因主要富集于肌动蛋白、线粒体膜、细胞周期检查点通路。结论:在结直肠癌中,AURKA是潜在的NC和放疗增敏靶点,下调AURKA有望用于临床治疗。

一种基于均方差属性加权的K-means算法

在传统的K-means聚类算法基础上提出了一种基于均方差属性加权的MWS-K-means算法。引入特征权重以提高聚类结果的类内相似度(intra-similarities),从而提高聚类精度。考虑到K-means算法采用误差平方和作为聚类准则函数,而误差平方和与概率论中数字特征的基本描述方法———均方差具有较高相似性,算法中特征权重的计算采用均方差法。根据属性的离散程度对欧氏距离进行加权处理,从而用相对距离代替绝对距离来计算类间相似度。实验结果表明:MWS-K-means算法在聚类精度方面优于标准的K-means算法。

浙江楠1年生容器苗质量分级研究

本研究以浙江楠容器苗为试验材料,采用地径和苗高作为分级指标,应用平均值±标准差法和逐步聚类法开展了1 a生实生苗的苗木质量分级研究,发现标准差法计算的Ⅰ级苗下限值偏高,逐步聚类法计算的Ⅱ级苗下限值偏高;综合确定浙江楠1 a生容器苗质量分级标准:Ⅰ级苗地径0.24 cm以上,苗高13.0 cm以上;Ⅱ级苗地径在0.15~0.24 cm之间,苗高在8.0~13.0 cm之间;Ⅰ、Ⅱ级苗为合格苗,确定的合格苗木接近85%的控制率。

基于Fourier变换红外光谱分析咖啡豆成分

采用Fourier变换红外光谱对不同产区、不同海拔的5组浅中烘焙的咖啡豆样品进行分析,根据官能团的红外光谱特征峰分析样品主要成分;为进一步分析5组样品的成分差异,对原始光谱进行二阶导数处理,结合聚类分析理论建立平均偏离分析方法,计算出5组样品间的平均偏离大小并进行分析.结果表明:5组样品的红外光谱特征峰峰形相似,即主要成分相同;根据红外光谱得到平均偏离大小与产区海拔差值呈正相关.研究结果为分析咖啡豆产区和海拔提供鉴别依据,并对红外光谱研究提供一定参考.

基于模糊自适应反步算法的多电机同步控制

针对多电机系统中,参数摄动和负载转矩变化会影响整个系统的跟踪精度和速度同步问题,论文设计一种模糊自适应反步控制方法。三台电机采用平均偏差耦合的结构,将其速度进行均值处理,然后再通过速度误差补偿器进一步地增强系统速度的同步效果。将模糊自适应反步算法应用到控制结构中,对系统由于扰动所带来的速度误差进行精准调节。在仿真实验中与传统滑模算法、传统的反步算法进行对比分析,研究结果表明:模糊自适应反步控制策略具有精度高、同步误差低、抗干扰性能好等特点。