A 15-year-Long catalog of seismicity in the Eastern Tennessee Seismic Zone(ETSZ)using matched filter detection

We present a detailed catalog of 13671 earthquakes in the Eastern Tennessee Seismic Zone(ETSZ)that spans January 1,2005 to July 31,2020.We apply a matched filter detection technique on over 15 years of continuous data,resulting in arguably the most complete catalog of seismicity in the ETSZ yet.The magnitudes of newly detected events are determined by computing the amplitude ratio between the detections and templates using a principal component fit.We also compute the b-value for the new catalog and comparatively relocate a subset of newly detected events using XCORLOC and hypoDD,which shows a more defined structure at depth.We find the greatest concentration along and to the east of the New York-Alabama Lineament,as defined by the magnetic anomaly,supporting the argument that this feature likely is related to the generation of seismicity in the ETSZ.We examine seismicity in the vicinity of the Watts Bar Reservoir,which is located about 5 km from the epicenter of the M_(W) 4.4 December 12,2018 Decatur,Tennessee earthquake,and find possible evidence for reservoir modulated seismicity in this region.We also examine seismicity in the entire ETSZ to search for a correlation between shallow earthquakes and seasonal hydrologic changes.Our results show limited evidence for hydrologicallydriven shallow seismicity due to seasonal groundwater levels in the ETSZ,which contradicts previous studies hypothesizing that most intraplate earthquakes are associated with the dynamics of hydrologic cycles.

PLS质量监控及其在Tennessee Eastman过程中的应用

研究质量监测在部分最小二乘(PLS)框架下的可检测性问题,并给出一种新的主成分确定方法.根据故障子空间和变量的显著性测度确定不同故障对质量的影响力,定义最优检测函数,进而建立PLS最优检测模型(ODM),使模型对严重影响产品质量的重要过程故障具有最优检测能力.以TennesseeEastman(TE)过程为案例进行统计质量控制研究,结果表明此方法对重要过程故障的敏感性很高,有助于及时采取补救措施,稳定产品质量.

Memphis, Tennessee： A Metonym for Rock ＇n Roll, the Child of the Blues

The 1991 Booker Prize--winning novelist Ben Okri, while traveling in the Deep South after Barack Obama＇s victory in the November 2008 presidential election, wrote that Elvis Presley was a lingering deity in the city of Memphis. The images of Elvis Presley, who earned the sobriquet ＂King of Rock＂ early in his career, and that of B. B. King, the exemplar extraordinaire of the Blues, are ubiquitous in the city of Memphis, which may be regarded as a metonym for the Blues and Rock ＇n Roll. The byline for the city of Memphis is, ＂Home of the Blues, Birthplace of Rock ＇n Roll＂, and this fact announces itself to the visitor as soon as he/she enters the arrivals concourse of the Memphis International Airport. As one proceeds towards the baggage claims area, the images which saturate the walkway create an aura that is redolent of the city＇s vibrant Rock ＇n Roll era. Drawing on Foucault＇s notion of heterotopias, as well as Jakobson＇s work on metonymy, this paper explores the hybrid musical spatiality of the city of Memphis and its environs, as well as its iconic status in the evolution of Rock ＇n Roll which was engendered by the Blues.

Tennessee River Resource Stewardship and Protection: The Tennessee River Line Trail Project and Partnerships

The Tennessee River had a long and colorful history of transporting Native Americans, settlers, armies, and cargo of all types in 1700s and 1800s. The headwaters of the Tennessee River, the largest tributary of the Ohio River, originates in the Appalachian Mountains of eastern United States. Created by the confluence of the Holston and French Broad rivers at Knoxville, the Tennessee River flows approximately 1049 km to Paducah, Kentucky where it drains into the Ohio River. This paper highlights how the landscape and geological resources of the Tennessee River and tributaries watershed contributed to the successful economic development of this historical region of North America. The Tennessee River is one of the most biologically diverse freshwater systems in the United States. Environmental challenges included an unsuccessful attempt to keep invasive species, such as the Asian carp, out of the Tennessee River and the Kentucky Lake. The 1049 river kilometer Tennessee River regional trail system with charter River Towns was designed to promote recreational tourism, increase the use of the Tennessee River and to create generations of people who care about the river and are willing to provide environmental stewardship of the watershed resources and protect the river.

VPLS Based Quality and Cost Control for Tennessee Eastman Process

Product quality and operation cost control obtain increasing emphases in modern chemical system engineering. To improve the fault detection power of the partial least square (PLS) method for quality control, a new QRPV statistic is proposed in terms of the VP (variable importance in projection) indices of monitored process variables, which is significantly advanced over and different from the conventional Q statistic. QRPV is calculated only by the residuals of the remarkable process variables (RPVs). Therefore, it is the dominant relation between quality and RPV not all process variables (as in the case of the conventional PLS) that is monitored by this new VP-PLS (VPLS) method. The combination of QRPV and T2 statistics is applied to the quality and cost control of the Tennessee Eastman (TE) process, and weak faults can be detected as quickly as possible. Consequently, the product quality of TE process is guaranteed and operation costs are reduced.

Cathodoluminescence Characteristics and Mineral Chemistry of Tennessee Sphalerites (Tn-Usa)

Optical cathodoluminescence microscopy (CLM) can provide very useful information both on mineral zoning formed during crystal growth and on variations in chemical composition of sphalerites which is reflected by their visible colors. Gem quality sphalerite crystals associated with dolomite, calcite and fluorite having 3 different visible colors - green, honey and brown - were studied to compare their mineral chemistry and CL characteristics. Electron microprobe analyses indicated essentially no significant differences in terms of major components. Although the common CL-quencher ferrous iron contents of all three were lower than 0.25 wt %, none of the sphalerites cathodoluminescenced: two (brown and honey) were non-CL, the green sphalerite showed very week CL in faint brown color. Other trace elements that were analyzed include Fe, Cd, Mn, Ag, Hg, In, Bi, Cu, Ge, and Ga. Fe, Cd, Ga and Cu were relatively higher than the others. Most significant differences with respect to the common trace elements include honey colored sphalerites are essentially Fe- and Cd-poor but rich in Ga, green sphalerites are Fe- and Cd- rich but poor in all the others, and brown sphalerites are rich in Cd. No conclusive relation between non-CL behavior of all three sphalerites and their trace element chemistry was established, however; low quantities of common CL activators in sphalerite crystal structures such as Mn, Cu, and In were the main cause of the non-CL behavior.

The Effect of Trihalomethanes in Contaminating the Major Watersheds of Middle Tennessee

We have analyzed the contamination of the three major watersheds in Middle Tennessee (Middle Cumberland River Watershed, Stones River Watershed, and Harpeth River Watershed) by trihalomethanes, such as chloroform, bromodichloromethane, dibromochloromethane, and bromoform. These chemicals play an important role in the develop-ment of cancer and adverse reproductive outcomes, and were found to be present above the threshold established by the Environmental Protection Agency. Certain portions of each watershed were found to be contaminated by the trihalomethanes, and deemed un-healthy. The household incomes in the major areas in the three watershed regions were also examined to determine a possible relationship with the level of water contamination. We concluded that income did not necessarily relate to water quality. Specific areas within each watershed that had lower average household incomes were found to have a higher concentration of the trihalomethanes in their drinking water, while other high-income areas were also affected by unhealthy water. However, these effects were random, and the level of contamination remained below the guidelines regulated by the State of Tennessee.

Vitamin D Deficiency and Insufficiency in Northeast Tennessee

Background: The role of vitamin D in population subgroups throughout the world continues to be a topic of interest among researchers. Current evidence demonstrates that treating vitamin D deficiency plays a significant role in improving mortality in hospitalized patients, reducing hospital length of stay, and boosting innate immune system. Vitamin D levels vary with age, gender, body mass index (BMI) and geographical area. The purpose of this study is to evaluate vitamin D levels in a cohort of patients in Northeast Tennessee. Study: This institutional review board-approved, retrospective study evaluated vitamin D levels of patients obtained from Mcleod Cancer and Blood Center. Vitamin D levels were collected over a 2-year period and classified as deficient (<20 ng/mL), insufficient (20 - 30 ng/mL), or replete (>30 ng/mL). Data were then stratified based on patient characteristics (age, gender, body mass index (BMI), race, seasons, and place of residence) and compounds of vitamin D (D2 and D3). Results: There were 2011 individuals included, with only 44.3% having replete levels and 21.4% with levels less than 20 ng/mL. Females with vitamin D deficiency are more likely to have levels below 20 ng/ml compared to males (18.6% vs. 23%, respectively, p = 0.003). Regarding BMI, the highest levels were reported in normal weight and overweight. With regards to age, advanced age (≥70) was associated with the highest levels and most replete patients. Winter months were associated with the lowest levels of vitamin D. Higher vitamin D levels were found in individuals over 70 years, normal weight and overweight category. Conclusion: Testing vitamin D levels in high-risk groups becomes of utmost importance in areas with longer winter months, obese and underweight patients. Vitamin D levels should be routinely tested and treated in vulnerable populations.

On Escapism in Tennessee Williams' s The Glass Menagerie

Wingfiled’s family is trapped in the cage in Tennessee Williams’s The Glass Menagerie.They want to free their bundles and each of them has taken a different way.This paper considers the theme of escapism by analyzing characters’spiritual world and their existential predicaments.The significance of their own way is explored since they add layers of meaning to the central argument:escapism.Tennessee Williams;

The Awakening Women in Tennessee Williams' s Plays

Tennessee Williams is a great American playwright. The heroines in the three plays experienced the changes of times.There are also some common threads that weave their way through these women's lives. They are different from the passive women characters in Williams' s early plays. The growth of women is an important part in the development of society. Through the research on the three plays, the causes, the procedure and the significance of their final awakening can be found.

基于CNN-LSTM-LOF的过程故障预测模型

在现代工业过程中,故障预测可以及时预测设备的潜在故障,减少事故的发生以及降低经济损失,因此故障预测对于过程系统至关重要。由于过程系统的复杂性以及运行数据集分布不均,使用正常数据集离线预测运行状态的方法没有较好的泛用性,且不太准确。针对以上问题,将卷积神经网络(CNN)与长短期记忆网络(LSTM)相结合,用于提取设备运行数据的特征,在线预测之后的运行状态;随后将预测结果送入在离线状态下训练好的局部异常因子(LOF)模型中,计算预测出时间序列的异常值;最后将异常值与离线状态下训练出的故障阈值进行比较,大于阈值则认为存在潜在故障。将模型用于田纳西-伊斯曼(TE)时间序列进行验证,并与传统的故障预测方法进行比较,实验结果表明:本文所提模型对于多故障以及单故障预测相比传统故障预测方法均具有更好的效果,可以提前1个采样窗口检测到数据异常,有应用于工业故障预测的潜力。

基于DSC-DenseNet的流程工业系统故障监测

田纳西-伊士曼过程数据高纬度、高耦合,存在数据特征难以提取的问题。为进一步提高流程工业系统中故障监测的识别率,现将一维稠密卷积网络(1D-DenseNet)与深度可分离卷积(DSC)结合,利用DenseNet的高效特征提取能力,并结合DSC减少计算参数、提高诊断效率,以提供基于DSC-DenseNet的故障监测方式。先将数据进行归一化整理,并加入随机种子避免过拟合,随后将处理后的结果作为DSC-DenseNet的输入进行特征提取,然后将输出结果传入全连接层进行故障分类;最后在TEP数据集上进行准确率测试。结果证明:基于DSC-DenseNet的方法能有效分辨故障类型,故障分类准确率达到98.8%。并证明DSC-DenseNet比传统DenseNet有更好的故障识别效果。

基于灰狼算法优化卷积神经网络的工业过程故障诊断

针对工业过程故障诊断中数据规模的逐渐增大以及数据之间映射关系、复杂程度的增加,文中以TE过程为数据背景提出一种基于灰狼算法(Grey Wolf Optimizer,GWO)优化卷积神经网络(GWO Convolutional Neural Networks,GWO-CNN)的模型,结合GWO算法具有搜索能力强、结构清晰、容易实现等特点,寻找CNN卷积核的个数等参数的最优解,并利用所寻得的最优参数搭建GWO-CNN模型并将其应用于工业过程的故障诊断。仿真结果表明,相比传统的卷积神经网络,GWO-CNN算法能够从原始数据中提取更多故障特征,从而提升原有的故障诊断的准确率。

基于KPCA融合AdaBoost-IBOA-ELM模型的TE过程故障诊断

为了保障化工系统的安全运行和高质量生产,准确判别化工过程的故障就显得尤为重要。针对田纳西-伊斯曼(Tennessee Eastman,TE)过程故障难以区分以及神经网络等方法在故障诊断中分类准确率较低、分类不稳定等问题,提出一种优化改进极限学习机(extreme learning machine,ELM)的TE过程故障诊断模型。首先利用核主成分分析(kernel principal components analysis,KPCA)方法对TE过程数据进行降维和特征提取,然后采用改进蝴蝶算法(improved butterfly optimization algorithm,IBOA)优化ELM的权值和阈值,最后利用自适应提升(adaptive boosting,AdaBoost)算法对分类器进行集成,完成故障分类。仿真结果表明,IBOA比其他优化算法具有更好的寻优能力,改进效果显著,AdaBoost-IBOA-ELM模型能够对测试集中的不同故障进行准确分类,最后的分类准确率高达98.5%,通过和其他网络对比,进一步验证了模型的合理性和优越性。

基于改进乌鸦算法优化SCN的TE过程故障诊断

现代化工过程变得越来越复杂,及时准确发现故障显得尤为重要。针对随机配置网络(SCN)泛化能力差、分类准确率低以及乌鸦搜索算法(CSA)寻优能力差等问题,提出了改进乌鸦算法(ICSA)优化随机配置网络的田纳西-伊斯曼(TE)过程故障诊断方法,结合ICSA算法和其它优化算法的寻优对比试验以及优化SCN网络对TE过程中不同故障的分类结果,可以得出,将所提方法应用于TE过程中,可以明显提高不同故障的分类准确率,整个测试集的分类准确率也高达97.6%,具有较好的分类效果,也更符合现代化工生产的需求。

基于最大信息系数和深度残差图卷积的工业过程故障诊断方法

针对工业数据非线性、时变性、时空特征耦合的特点,提出一种基于最大信息系数和残差图卷积网络的工业过程故障诊断算法(MIC-RGCN)。引入最大信息系数(MIC)挖掘变量之间的相关关系,将高维变量之间的相关信息转换为空间距离信息,构建相关性矩阵作为图卷积层的邻接矩阵输入;构建改进的深度残差图卷积网络(GCN)模型对数据的时空特征进行深度融合提取并精准分类。在田纳西-伊斯曼过程和三相流过程数据集上将该算法与4种典型机器学习和深度学习算法进行对比测试。实验结果表明,该算法有效地提升了故障诊断的准确率。

基于mini-1D-CNN模型的TE过程故障诊断

为提升石化企业过程监测与故障诊断系统性能,满足化工过程故障诊断实时性、时效性的要求,提出一种基于过程历史数据驱动的最小一维卷积神经网络(mini-1D-CNN)的故障诊断模型。首先,通过一维卷积核学习和识别不同故障类型的数据特征,自动提取优势特征并进行故障分类;其次,通过逐步向后回归选择重要特征参数,优化模型结构。利用可实时获取的31个过程变量与操作参数,输入一维卷积神经网络(1D-CNN),监测与诊断田纳西-伊斯曼(TE)过程的主要故障。结果表明:相对于其他故障诊断模型,mini-1D-CNN模型在测试集上故障诊断率(FDR)较高,可达到96.50%;同时,mini-1D-CNN模型关注于TE过程故障诊断的重要特征参数,在降低参数量及降低训练和测试时间上具有显著优势。

增值性评价在临床教学基地质量管理中的应用研究

目的:证明“田纳西增值评价方法”在临床教学基地质量管理中的价值。方法:以浙江中医药大学临床医学专业2015级、2016级学生为研究对象,运用田纳西增值评价法对学生三、四年级的学业绩点及学生对临床教学基地各方面满意度进行分析,并将结果进行比较。结果:2016级学生的评价指标明显优于2015级学生,两组学生的评价指标存在统计学差异(P<0.05)。结论:“田纳西增值评价方法”在一定程度上可以客观评价临床教学基地教学质量的增长程度,能够科学地评估相关教育改革措施与教学质量提升的相关性,值得进一步探索研究。

基于稀疏自编码器的工控系统态势理解算法

态势感知对提高工控系统的安全性有着重要作用。结合深度学习理论,提出基于稀疏自编码器的工控系统态势理解算法。算法使用稀疏自编码器对工业控制系统现场控制层数据降维,提取有效特征;随后使用K-means聚类算法对系统正常安全态势建模;最后通过对比工业控制系统现场控制层实时监控数据进行分析,对系统当前安全态势进行判断。将上述方法应用于田纳西-伊斯曼过程数据集进行验证,结果表明,所提方法可以准确有效地提出系统当前安全态势。

基于集成KPCA的非线性工业过程状态监测

传统的KPCA(Kernel Principal Component Analysis)过程监测方法一般根据经验选取需要的核函数及一定宽度的参数,这样做是非常盲目的。同时单一KPCA模型不能对所有故障都有好的监测效果。为了解决此问题,提出基于集成KPCA的非线性工业过程状态监测方法。通过选取一系列的核函数及其参数构建不同的KPCA模型得到子模型,用贝叶斯方法将众多子模型的监测统计量转化为故障概率,分两步进行融合,得到最终监测结果。实验结果表明,该方法显著地提高了监测性能,同时减小核函数及参数选取对故障监测的影响。