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Data Visualization and Visualization-Based Fault Detection for Chemical Processes

Ray Wang, Michael Baldea, Thomas Edgar
2017 Processes  
The chemical processes industry is one such field, with high volume and high-dimensional time series data.  ...  We consider three common types of processes and compare visualization-based fault detection performance to methods used currently.  ...  The funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.  ... 
doi:10.3390/pr5030045 fatcat:hgftqunhibgxnongc52nwqpqve

A wavelet-based approach to streamflow event identification and modeled timing error evaluation

Erin Towler, James L. McCreight
2021 Hydrology and Earth System Sciences  
The methodology is illustrated using real and simulated stream discharge data from several locations to highlight key method features.  ...  Step 1 applies the wavelet transform to the observations and uses statistical significance to identify observed events.  ...  The authors would like to thank Dave Gochis, for the useful discussions, and Aubrey Dugger, for providing the NWM data. We thank the NOAA/OWP and NCAR NWM team for their support of this research.  ... 
doi:10.5194/hess-25-2599-2021 fatcat:iajl3le3nfbkpmkor4hl4sg42a

Precipitation Estimation Methods in Continuous, Distributed Urban Hydrologic Modeling

Woodson, Adams, Dymond
2019 Water  
Simulations forced with MFB-corrected radar data consistently and significantly overpredicted discharge, but had the highest accuracy in predicting the timing of peak flows.  ...  gauge data, uncorrected radar data, and a basin-uniform estimate from a single gauge inside the watershed.  ...  Similarly, since the Level III DPR radar data also had an irregular time series, any missing data periods would be filled during the temporal interpolation process.  ... 
doi:10.3390/w11071340 fatcat:t6bu75coj5dtrexvfhb6zzhefi

Using Artificial Neural Network Models to Assess Water Quality in Water Distribution Networks

G.A. Cuesta Cordoba, L. Tuhovčák, M. Tauš
2014 Procedia Engineering  
The purpose of the research is to assess chlorine concentration in WDS using statistical models based on ANN in combination with Monte-Carlo.  ...  The model was tested on one specific location using the hydraulic and water quality parameters such as flow, pH, temperature, etc.  ...  For the model calibration it was used the time series data in tank Bosonohy and the pump station from Bosonohy to Kohoutovice.  ... 
doi:10.1016/j.proeng.2014.02.045 fatcat:gb7i636dt5e5ld77falefw2ixy

Metabolome progression during early gut microbial colonization of gnotobiotic mice

Angela Marcobal, Tahir Yusufaly, Steven Higginbottom, Michael Snyder, Justin L. Sonnenburg, George I. Mias
2015 Scientific Reports  
analysis to urine metabolomics data.  ...  High-throughput mass spectrometry profiling of urine samples revealed dynamic changes in the metabolome makeup, associated with the gut bacterial colonization, enabled by our adaptation of non-linear time-series  ...  Each signal set was allowed to have up to one time point missing (except the first time point in all series, which was used as a reference point, in analogy of using the GF mice as a comparison reference  ... 
doi:10.1038/srep11589 pmid:26118551 pmcid:PMC4484351 fatcat:pcpufavzg5hwpl3oipqj7osmki

Data Quality Control for St. Petersburg Flood Warning System

Jose Luis Araya Lopez, Anna V. Kalyuzhnaya, Sergey S. Kosukhin, Sergey V. Ivanov
2016 Procedia Computer Science  
Petersburg FWS contains blocks of technical control, human mistakes control, statistical control of simulated fields, statistical control and restoration of measurements and control using alternative models  ...  time data assimilation, calibration, etc.  ...  The first type is those methods that make use of incomplete time series for estimating its own missing data.  ... 
doi:10.1016/j.procs.2016.05.532 fatcat:rl2g4sgbffdb3fwu3frycwjqq4

Operation and characterization of a windowless gas jet target in high-intensity electron beams [article]

B. S. Schlimme, S. Aulenbacher, P. Brand, M. Littich, Y. Wang, P. Achenbach, M. Ball, J. C. Bernauer, M. Biroth, D. Bonaventura, D. Bosnar, S. Caiazza (+45 others)
2021 arXiv   pre-print
data taken at a low gas flow rate.  ...  The pressure inside the target chamber is shown as well. The data points were linearly connected to guide the eye.  ... 
arXiv:2104.13503v2 fatcat:yagp7th2ujgzpfiajdsv2pzbdi

PTLsim: A Cycle Accurate Full System x86-64 Microarchitectural Simulator

Matt T. Yourst
2007 2007 IEEE International Symposium on Performance Analysis of Systems & Software  
We describe why PTLsim's x86 focus is highly relevant, and we use our full system simulation results to demonstrate the pitfalls of userspace only simulation.  ...  We compare the statistics generated by our model with the actual numbers from the real processor to demonstrate PTLsim is accurate to within 5% across all major parameters.  ...  For each benchmark and trial environment, several key statistics were analyzed, including total number of cycles, total number of x86 instructions, L1 cache miss rate, branch mispredict rate and DTLB miss  ... 
doi:10.1109/ispass.2007.363733 dblp:conf/ispass/Yourst07 fatcat:dgcsvagns5fslkgz6hbch5jxja

Government Policy and Ownership of Financial Assets

Kristian Rydqvist, Joshua D. Spizman, Ilya A. Strebulaev
2011 Social Science Research Network  
Using long time-series from eight countries, we show that the fraction of household ownership decreases with measures of the tax benefits of holding stocks inside tax-deferred plans.  ...  For this, the data from the United States are not sufficient because it provides us with only one time-series with insufficient time series variation.  ...  The reported results are based on aggregating dividend yield and GDP-per-capita time series across countries and use the same parameter for all countries at each point of time.  ... 
doi:10.2139/ssrn.1428442 fatcat:7blnl4aq2bccpeg5phkcncqbxi

Ensemble evaluation of hydrological model hypotheses

Tobias Krueger, Jim Freer, John N. Quinton, Christopher J. A. Macleod, Gary S. Bilotta, Richard E. Brazier, Patricia Butler, Philip M. Haygarth
2010 Water Resources Research  
1] It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation  ...  As a model learning exercise, the study points to a "leaking" of the fields not evident from previous field experiments.  ...  Additional funding came from the UK NERC Flood Risk from Extreme Events (FREE) programme (grant NE/E002242/1) and the UK Research Councils Rural Economy and Land Use (RELU) programme (grant RES-229-25-  ... 
doi:10.1029/2009wr007845 fatcat:7ry7kpqaxzf5ddqii2t4mlijdm

Network anomaly detection with incomplete audit data

Animesh Patcha, Jung-Min Park
2007 Computer Networks  
network traffic itself; (b) it computes the missing elements of the sampled audit data by utilizing an improved Expectation-Maximization (EM) algorithm-based clustering algorithm; and (c) it improves  ...  the speed of convergence of the clustering process by employing Bloom filters and data summaries.  ...  time series has the property that when aggregated the new series has the same autocorrelation function as the original 5 The R/S statistic is the adjusted range of partial sums of deviations of a times  ... 
doi:10.1016/j.comnet.2007.04.017 fatcat:nyqjvrscj5g23kxlzsdj2ia54a

Catching Anomalous Distributed Photovoltaics: An Edge-based Multi-modal Anomaly Detection [article]

Devu Manikantan Shilay, Kin Gwn Lorey, Tianshu Weiz, Teems Lovetty,, Yu Cheng
2017 arXiv   pre-print
This is realized by exploiting unsupervised machine learning algorithms on multiple sources of time-series data, fusing these multiple local observations and flagging anomalies when a deviation from the  ...  We use an open source power system simulation tool called GridLAB-D, loaded with real smart home and solar datasets to simulate the smart grid scenarios and to illustrate the impact of PV attacks on the  ...  In this work, we train a stacked DAE to reconstruct the time-series data at each time step using the normal dataset.  ... 
arXiv:1709.08830v1 fatcat:evkcj7ks4vbxvhgsdfgcsb2ryi

Plume Tracking Strategy in Turbulent Environment using Odor Sensor with Time Constant

Muis Muhtadi, Takamichi Nakamoto
2018 Sensors and materials  
The plume edges are estimated by evaluating the gradient of the fitting model of the frame size of the latest data points of sensor response during tracking.  ...  The problem of tracking a dynamic odor plume using a realistic odor sensor model was investigated in a computer simulation.  ...  Therefore, time-series 2D data at 5 cm above the floor was extracted from the 3D data. Moreover, only the data when odor had been released was used for the simulation.  ... 
doi:10.18494/sam.2018.1950 fatcat:zz5yrgiwgzak5jkoldi2esamdy

Monte Carlo Uncertainty Quantification Using Quasi-1D SRM Ballistic Model

Davide Viganò, Adriano Annovazzi, Filippo Maggi
2016 International Journal of Aerospace Engineering  
However, solid rocket systems are missing any throttling capability at run-time, since pressure-time evolution is defined at the design phase.  ...  The code is coupled with a Monte Carlo algorithm to evaluate statistics and propagation of some peculiar uncertainties from design data to rocker performance parameters.  ...  This process is significant when high flow speed inside combustion chamber is locally registered [3, 21, 22] .  ... 
doi:10.1155/2016/3765796 fatcat:orgaxgwbjfa47obsyzoehsg4be

Malicious Overtones: hunting data theft in the frequency domain with one-class learning [article]

Brian A. Powell
2019 arXiv   pre-print
Normal traffic flow data, in the form of a host's ingress and egress bytes over time, is used to train an ensemble of one-class learners.  ...  Simulated exfiltration samples with a variety of different timing and data characteristics were generated and used to test ensemble performance on different kinds of systems: when trained on a client workstation's  ...  times leading to the series of spikes in the spectrum at integer multiples of f * .  ... 
arXiv:1904.04895v1 fatcat:64myfstagzdn7c2356gcezntqu
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