Relevant bibliographies by topics / Outlier analyses

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Outlier analyses'

Author: Grafiati
Published: 10 March 2023

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Journal articles on the topic "Outlier analyses"

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Bhushan, A., M. H. Sharker, and H. A. Karimi. "INCREMENTAL PRINCIPAL COMPONENT ANALYSIS BASED OUTLIER DETECTION METHODS FOR SPATIOTEMPORAL DATA STREAMS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-4/W2 (July 10, 2015): 67–71. http://dx.doi.org/10.5194/isprsannals-ii-4-w2-67-2015.

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In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud
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Singal, J., G. Silverman, E. Jones, T. Do, B. Boscoe, and Y. Wan. "Machine Learning Classification to Identify Catastrophic Outlier Photometric Redshift Estimates." Astrophysical Journal 928, no. 1 (2022): 6. http://dx.doi.org/10.3847/1538-4357/ac53b5.

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Abstract We present results of using a basic binary classification neural network model to identify likely catastrophic outlier photometric redshift estimates of individual galaxies, based only on the galaxies’ measured photometric band magnitude values. We find that a simple implementation of this classification can identify a significant fraction of galaxies with catastrophic outlier photometric redshift estimates while falsely categorizing only a much smaller fraction of non-outliers. These methods have the potential to reduce the errors introduced into science analyses by catastrophic outl
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Svabova, Lucia, and Marek Durica. "Being an outlier: a company non-prosperity sign?" Equilibrium 14, no. 2 (2019): 359–75. http://dx.doi.org/10.24136/eq.2019.017.

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Research background: The state of financial distress or imminent bankruptcy are very difficult situations that the management of every company wants to avoid. For these reasons, prediction of company bankruptcy or financial distress has been recently in a focus of economists and scientists in many countries over the world.
 Purpose of the article: Various financial indicators, mostly financial ratios, are usually used to predict the financial distress. In order to create a strong prediction model and a statistically significant prediction of bankruptcy, it is advisable to use a deep stati
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Wu, Zifeng, Zhouxiang Wu, and Laurence R. Rilett. "Innovative Nonparametric Method for Data Outlier Filtering." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (2020): 167–76. http://dx.doi.org/10.1177/0361198120945697.

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Outlier filtering of empirical travel time data is essential for traffic analyses. Most of the widely applied outlier filtering algorithms are parametric in nature and based on assumed data distributions. The assumption, however, might not hold under unstable traffic conditions. This paper proposes a nonparametric outlier filtering method based on a robust locally weighted regression scatterplot smoothing model. The proposed method identifies outliers based on a data point’s standard residual in the robust local regression model. This approach fits a regression surface with no constraint on pa
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Bae, Inhyeok, and Un Ji. "Outlier Detection and Smoothing Process for Water Level Data Measured by Ultrasonic Sensor in Stream Flows." Water 11, no. 5 (2019): 951. http://dx.doi.org/10.3390/w11050951.

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Water level data sets acquired by ultrasonic sensors in stream-scale channels exhibit relatively large numbers of outliers that are off the measurement range between the ultrasonic sensor and water surface, as well as data dispersion of approximately 2 cm due to random errors such as water waves. Therefore, this study develops a data processing algorithm for outlier removal and smoothing for water level data measured by ultrasonic sensors to consider these characteristics. The outlier removal process includes an initial cutoff process to remove outliers out of the measurement range and an outl
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Cobb, Natalie L., Sigrid Collier, Engi F. Attia, Orvalho Augusto, T. Eoin West, and Bradley H. Wagenaar. "Global influenza surveillance systems to detect the spread of influenza-negative influenza-like illness during the COVID-19 pandemic: Time series outlier analyses from 2015–2020." PLOS Medicine 19, no. 7 (2022): e1004035. http://dx.doi.org/10.1371/journal.pmed.1004035.

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Background Surveillance systems are important in detecting changes in disease patterns and can act as early warning systems for emerging disease outbreaks. We hypothesized that analysis of data from existing global influenza surveillance networks early in the COVID-19 pandemic could identify outliers in influenza-negative influenza-like illness (ILI). We used data-driven methods to detect outliers in ILI that preceded the first reported peaks of COVID-19. Methods and findings We used data from the World Health Organization’s Global Influenza Surveillance and Response System to evaluate time se
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Reddy, Y. Harshavardhan, M. Hari Srinivas, Adnan Ali, and A. Zaheer Sha. "A Review on Outliers in IoT." South Asian Research Journal of Engineering and Technology 4, no. 6 (2022): 134–41. http://dx.doi.org/10.36346/sarjet.2022.v04i06.001.

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In recent decades, the Internet of Things (IoT) has grown rapidly, attracting the attention of scientists and businesspeople. In extreme conditions, autonomously scattered sensor nodes pose a high risk of failure and intrusion into the IoT, skewing sensor values. Abnormal data, anomalies, or outliers are sensor values that depart from norms. When abnormalities are factored into data analytics, the ultimate judgment is affected. Using data-driven algorithms for IoT outlier detection is a cutting-edge tactic in Machine Learning (ML). However, evaluating the effectiveness of implemented ML techni
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Höhne, Jan Karem, and Stephan Schlosser. "Investigating the Adequacy of Response Time Outlier Definitions in Computer-Based Web Surveys Using Paradata SurveyFocus." Social Science Computer Review 36, no. 3 (2017): 369–78. http://dx.doi.org/10.1177/0894439317710450.

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Web surveys are commonly used in social research because they are usually cheaper, faster, and simpler to conduct than other modes. They also enable researchers to capture paradata such as response times. Particularly, the determination of proper values to define outliers in response time analyses has proven to be an intricate challenge. In fact, to a certain degree, researchers determine them arbitrarily. In this study, we use “SurveyFocus (SF)”—a paradata tool that records the activity of the web-survey pages—to assess outlier definitions based on response time distributions. Our analyses re
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Mao, Jialin, Frederic Scott Resnic, Leonard N. Girardi, Mario Fl Gaudino, and Art Sedrakyan. "Challenges in outlier surgeon assessment in the era of public reporting." Heart 105, no. 9 (2018): 721–27. http://dx.doi.org/10.1136/heartjnl-2018-313650.

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ObjectiveTo assess the effect of various evaluation and reporting strategies in determining outlier surgeons, defined by having worse-than-expected mortality after cardiac surgery.MethodsOur study included 33 394 isolated coronary artery bypass graft (CABG) procedures performed by 136 surgeons and 12 172 surgical aortic valve replacement (SAVR) procedures performed by 113 surgeons between 2010 and 2014. Three current methodologies based on the framework of comparing observed and expected (O/E ratio) mortality, with different distributional assumptions, were examined. We further assessed the co
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Beasley, Charles M., Brenda Crowe, Mary Nilsson, et al. "Reference Limits for Outlier Analyses in Randomized Clinical Trials." Therapeutic Innovation & Regulatory Science 51, no. 6 (2017): 683–737. http://dx.doi.org/10.1177/2168479017700679.

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Dissertations / Theses on the topic "Outlier analyses"

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Zhang, Ji. "Towards outlier detection for high-dimensional data streams using projected outlier analysis strategy." University of Southern Queensland, Faculty of Sciences, 2008. http://eprints.usq.edu.au/archive/00005645/.

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[Abstract]: Outlier detection is an important research problem in data mining that aims to discover useful abnormal and irregular patterns hidden in large data sets. Most existing outlier detection methods only deal with static data with relatively low dimensionality.Recently, outlier detection for high-dimensional stream data became a new emerging research problem. A key observation that motivates this research is that outliersin high-dimensional data are projected outliers, i.e., they are embedded in lower-dimensional subspaces. Detecting projected outliers from high-dimensional streamdata i
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Cheng, Gongxian. "Outlier management in intelligent data analysis." Thesis, Birkbeck (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.417120.

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Abghari, Shahrooz. "Data Modeling for Outlier Detection." Licentiate thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16580.

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This thesis explores the data modeling for outlier detection techniques in three different application domains: maritime surveillance, district heating, and online media and sequence datasets. The proposed models are evaluated and validated under different experimental scenarios, taking into account specific characteristics and setups of the different domains. Outlier detection has been studied and applied in many domains. Outliers arise due to different reasons such as fraudulent activities, structural defects, health problems, and mechanical issues. The detection of outliers is a challenging
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Birch, Gary Edward. "Single trial EEG signal analysis using outlier information." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28626.

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The goal of this thesis work was to study the characteristics of the EEG signal and then, based on the insights gained from these studies, pursue an initial investigation into a processing method that would extract useful event related information from single trial EEG. The fundamental tool used to study the EEG signal characteristics was autoregressive modeling. Early investigations pointed to the need to employ robust techniques in both model parameter estimation and signal estimation applications. Pursuing robust techniques ultimately led to the development of a single trial processing meth
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Mitchell, Napoleon. "Outliers and Regression Models." Thesis, University of North Texas, 1992. https://digital.library.unt.edu/ark:/67531/metadc279029/.

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The mitigation of outliers serves to increase the strength of a relationship between variables. This study defined outliers in three different ways and used five regression procedures to describe the effects of outliers on 50 data sets. This study also examined the relationship among the shape of the distribution, skewness, and outliers.
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Soon, Shih Chung. "On detection of extreme data points in cluster analysis." Connect to resource, 1987. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1262886219.

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Robson, Geoffrey. "Multiple outlier detection and cluster analysis of multivariate normal data." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53508.

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Thesis (MscEng)--Stellenbosch University, 2003.<br>ENGLISH ABSTRACT: Outliers may be defined as observations that are sufficiently aberrant to arouse the suspicion of the analyst as to their origin. They could be the result of human error, in which case they should be corrected, but they may also be an interesting exception, and this would deserve further investigation. Identification of outliers typically consists of an informal inspection of a plot of the data, but this is unreliable for dimensions greater than two. A formal procedure for detecting outliers allows for consistency when
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Halldestam, Markus. "ANOVA - The Effect of Outliers." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-295864.

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This bachelor’s thesis focuses on the effect of outliers on the one-way analysis of variance and examines whether the estimate in ANOVA is robust and whether the actual test itself is robust from influence of extreme outliers. The robustness of the estimates is examined using the breakdown point while the robustness of the test is examined by simulating the hypothesis test under some extreme situations. This study finds evidence that the estimates in ANOVA are sensitive to outliers, i.e. that the procedure is not robust. Samples with a larger portion of extreme outliers have a higher type-I er
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Astl, Stefan Ludwig. "Suboptimal LULU-estimators in measurements containing outliers." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85833.

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Thesis (MSc)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: Techniques for estimating a signal in the presence of noise which contains outliers are currently not well developed. In this thesis, we consider a constant signal superimposed by a family of noise distributions structured as a tunable mixture f(x) = α g(x) + (1 − α) h(x) between finitesupport components of “well-behaved” noise with small variance g(x) and of “impulsive” noise h(x) with a large amplitude and strongly asymmetric character. When α ≈ 1, h(x) can for example model a cosmic ray striking an experimental detector
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Lipkovich, Ilya A. "Bayesian Model Averaging and Variable Selection in Multivariate Ecological Models." Diss., Virginia Tech, 2002. http://hdl.handle.net/10919/11045.

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Bayesian Model Averaging (BMA) is a new area in modern applied statistics that provides data analysts with an efficient tool for discovering promising models and obtaining esti-mates of their posterior probabilities via Markov chain Monte Carlo (MCMC). These probabilities can be further used as weights for model averaged predictions and estimates of the parameters of interest. As a result, variance components due to model selection are estimated and accounted for, contrary to the practice of conventional data analysis (such as, for example, stepwise model selection). In addition, variable acti
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Books on the topic "Outlier analyses"

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Aggarwal, Charu C. Outlier Analysis. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-47578-3.

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Aggarwal, Charu C. Outlier Analysis. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6396-2.

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Aggarwal, Charu C. Outlier Analysis. Springer New York, 2013.

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Rousseeuw, Peter J. Robust regression and outlier detection. Wiley, 1987.

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Meier, Alan. An analysis of outliers in the RSDP. Applied Science Division, Lawrence Berkeley Laboratory, University of California, 1988.

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Marchand, J. P. Distributions: An outline. Dover Publications, 2007.

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Weissmuller, Johnny J. Automated test outline development: Research findings. Air Force Human Resources Laboratory, Air Force Systems Command, 1989.

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R, Spiegel Murray, and Wrede Robert C, eds. Schaum's outline of advanced calculus. 3rd ed. McGraw-Hill, 2010.

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Schaum's outline of theory and problems of vector analysis. McGraw-Hill, 1988.

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Toby, Lewis, ed. Outliers in statistical data. 3rd ed. Wiley, 1994.

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Book chapters on the topic "Outlier analyses"

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Kontala, Janne, Mika Lassander, and Nurit Novis-Deutsch. "Searching for Uncommon Worldviews: ‘Idiosyncratic’ and ‘Divided’ Outlooks in a Global Sample of Young Adults." In The Diversity Of Worldviews Among Young Adults. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94691-3_6.

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AbstractIn this chapter, we explore uncommon worldviews, meaning that we take a closer look at outlier respondents in a larger international sample from 12 countries. These outliers are the ones whose personal outlooks did not match any of the major worldview types found in the national case studies. First, we identify shared patterns amongst these respondents. Second, we place these outlier outlook types on a broader worldview map. Juxtaposing the outlier outlooks with the results from other case studies allows us to identify idiosyncratic worldviews. Certain outlooks would not stand out in analyses of single case studies, but bringing them together in a cross-cultural comparison enables us to see patterns shared by individuals across different national contexts. This also reveals better such worldviews that incorporate those elements, which normally are distributed amongst opposing viewpoints. The emergence of these outlook types can support the development of a nuanced theory of religious subjectivities.
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Aggarwal, Charu C. "An Introduction to Outlier Analysis." In Outlier Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_1.

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Aggarwal, Charu C. "Outlier Detection in Discrete Sequences." In Outlier Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_10.

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Aggarwal, Charu C. "Spatial Outlier Detection." In Outlier Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_11.

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Aggarwal, Charu C. "Outlier Detection in Graphs and Networks." In Outlier Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_12.

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Aggarwal, Charu C. "Applications of Outlier Analysis." In Outlier Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_13.

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Aggarwal, Charu C. "Probabilistic and Statistical Models for Outlier Detection." In Outlier Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_2.

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Aggarwal, Charu C. "Linear Models for Outlier Detection." In Outlier Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_3.

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Aggarwal, Charu C. "Proximity-Based Outlier Detection." In Outlier Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_4.

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Aggarwal, Charu C. "High-Dimensional Outlier Detection: The Subspace Method." In Outlier Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47578-3_5.

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Conference papers on the topic "Outlier analyses"

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Kim, Hyun-Ki, and Si-Yeol Shin. "Application of Statistical Geo-Sapatial Information Analyses to Outlier Detection." In 5th Asian-Pacific Symposium on Structural Reliability and its Applications. Research Publishing Services, 2012. http://dx.doi.org/10.3850/978-981-07-2219-7_p147.

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Gao, Rui, Li Shen, Kwee-Yan Teh, Penghui Ge, Fengnian Zhao, and David L. S. Hung. "Effects of Outlier Flow Field on the Characteristics of In-Cylinder Coherent Structures Identified by POD-Based Conditional Averaging and Quadruple POD." In ASME 2018 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icef2018-9561.

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Proper Orthogonal Decomposition (POD) offers an approach to quantify cycle-to-cycle variation (CCV) of the flow field inside the internal combustion engine cylinder. POD decomposes instantaneous flow fields (also called snapshots) into a series of orthonormal flow patterns (called POD modes) and the corresponding mode coefficients. The POD modes are rank-ordered by decreasing kinetic energy content, and the low-order, high-energy modes are interpreted as constituting the large-scale coherent flow structure that varies from engine cycle to engine cycle. Various POD-based analysis techniques hav
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Flamini, Vittoria, and Boyce E. Griffith. "Optimal Constitutive Parameters and Subject Specific Variability: An Application to the Aortic Sinuses." In ASME 2013 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/sbc2013-14633.

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Advanced analyses of soft biological tissues have shown substantial subject-specific variability in mechanical properties [1]. Such variability is also easily observed at a geometrical or morphological level, and has been reported also in mechanical tests on biological tissue samples [1, 2]. While there is wide interest in reproducing accurate geometries for subject-specific modeling, constitutive parameters for mechanical models often use averaged data from mechanical tests [3]. Outliers are typically neglected, and only the ‘mean’ tissue behavior is considered. However, due to an increased i
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Nigam, Nidhi, Tripti Saxena, and Vineet Richhariya. "Global high dimension outlier algorithm for efficient clustering & outlier detection." In 2016 Symposium on Colossal Data Analysis and Networking (CDAN). IEEE, 2016. http://dx.doi.org/10.1109/cdan.2016.7570924.

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Yousri, Noha A., Mohammed A. Ismail, and Mohamed S. Kamel. "Fuzzy outlier analysis a combined clustering - outlier detection approach." In 2007 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2007. http://dx.doi.org/10.1109/icsmc.2007.4413873.

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Xu, Honglong, Rui Mao, Hao Liao, Minhua Lu, and He Zhang. "Closest neighbors excluded outlier detection." In 2016 IEEE International Conference of Online Analysis and Computing Science (ICOACS). IEEE, 2016. http://dx.doi.org/10.1109/icoacs.2016.7563058.

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Ruffolo, Alessandro. "Outlier Analysis for SETI." In 54th International Astronautical Congress of the International Astronautical Federation, the International Academy of Astronautics, and the International Institute of Space Law. American Institute of Aeronautics and Astronautics, 2003. http://dx.doi.org/10.2514/6.iac-03-iaa.9.p.03.

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Xiaohui Liu. "Strategies for outlier analysis." In IEE Two-day Colloquium on Knowledge Discovery and Data Mining. IEE, 1998. http://dx.doi.org/10.1049/ic:19980546.

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Dalmia, Ayushi, Manish Gupta, and Vasudeva Varma. "Query-based Graph Cuboid Outlier Detection." In ASONAM '15: Advances in Social Networks Analysis and Mining 2015. ACM, 2015. http://dx.doi.org/10.1145/2808797.2810061.

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Shih, H. H., C. Long, M. Bushnell, and K. Hathaway. "Intercomparison of Wave Data Between Triaxys Directional Wave Buoy, ADCP, and Other Reference Wave Instruments." In ASME 2005 24th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2005. http://dx.doi.org/10.1115/omae2005-67235.

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The use of Triaxys directional wave buoy and acoustic Doppler current profiler (ADCP) for wave measurements are relatively recent. The US National Oceanic and Atmospheric Administration’s (NOAA) National Ocean Service (NOS) acquired these instruments in 2001 and systematic laboratory and field tests were conducted during 2001–2002. This paper describes the field tests conducted near the US Army Corps of Engineers’ Field Research Facility (FRF) ocean pier and near the Barren Islands in the Chesapeake Bay. At the FRF site, Triaxys buoy wave measurements were compared with FRF’s field standards o
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Reports on the topic "Outlier analyses"

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Peter, J. M., M. G. Gadd, C. Jiang, and J. Reyes. Organic geochemistry and petrology of sedimentary exhalative Pb-Zn and polymetallic hyper-enriched black shale deposits in the Selwyn Basin, Yukon. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/328017.

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Paleozoic strata of the Selwyn Basin host sedimentary exhalative (SEDEX) Pb-Zn deposits, and age-correlative strata of the Richardson trough host polymetallic hyper-enriched black shale (HEBS) deposits. In both deposit types, organic matter is spatially and temporally associated with mineralization. We investigated the characteristics of organic matter in mineralization and unmineralized host rocks in the XY Central SEDEX deposit in the Howard's Pass district, and the Nick and Peel River HEBS deposits in the Richardson trough using Rock-Eval pyrolysis, organic petrography, and solvent extracti
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Mathew, Jijo K., Christopher M. Day, Howell Li, and Darcy M. Bullock. Curating Automatic Vehicle Location Data to Compare the Performance of Outlier Filtering Methods. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317435.

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Agencies use a variety of technologies and data providers to obtain travel time information. The best quality data can be obtained from second-by-second tracking of vehicles, but that data presents many challenges in terms of privacy, storage requirements and analysis. More frequently agencies collect or purchase segment travel time based upon some type of matching of vehicles between two spatially distributed points. Typical methods for that data collection involve license plate re-identification, Bluetooth, Wi-Fi, or some type of rolling DSRC identifier. One of the challenges in each of thes
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Sadler, Brian M., and Stephen D. Casey. On Periodic Pulse Interval Analysis with Outliers and Missing Observations. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada454910.

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Montgomery, Raymond B., and Athelstan Fred Spilhaus. Examples and outline of certain modifications in isentropic analysis. Woods Hole Oceanographic Institution, 2022. http://dx.doi.org/10.1575/1912/29557.

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Isentropic analysis in this country originated with a particular purpose in view, namely as a means of using moisture distribution to determine flow patterns in the atmosphere It revealed, very successfully, certain theoretically anticipated patterns. Subsequently it has come into general use in connection with upper-air analysis but for the most part its application is dominated by the original particular purpose. A rather different approach is to use isentropic analysis in a more purely descriptive fashion as the principal tool for upper-air analysis. This demands that an isentropic chart re
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Taplin, Ross, and Adrian E. Raftery. Analysis of Agricultural Field Trials in the Presence of Outliers and Fertility Jumps. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada242454.

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Matheu, Enrique E., Robert L. Hall, and Raju V. Kala. Folsom Dam Outlet Works Modification Project: Dynamic Stress Analysis of Overflow and Nonoverflow Sections. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada427798.

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Michael G. McKellar and Edwin A. Harvego. Analysis of Reference Design for Nuclear-Assisted Hydrogen Production at 750?C Reactor Outlet Temperature. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/984544.

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Macdonald, Stuart, Kamil Yilmaz, Chamin Herath, et al. The European Far-Right Online: An Exploratory Twitter Outlink Analysis of German & French Far-Right Online Ecosystems. RESOLVE Network, 2022. http://dx.doi.org/10.37805/remve2022.2.

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Seeking to explore the nature of European far-right online ecosystems, this research report examines the outlinking activity of identified pro-far-right users among the followers of the official Twitter accounts of two prominent far-right European political parties, Germany’s Alternative für Deutschland (AfD) and France’s Rassemblement National (RN). Employing a three-layered analysis, the report explores not just the top-level domains outlinked to by its sample of AfD and RN Twitter followers but combines this with analysis of the technical specifications of the content types outlinked to and
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9

Bodnenko, Dmytro M., Halyna A. Kuchakovska, Volodymyr V. Proshkin, and Oksana S. Lytvyn. Using a virtual digital board to organize student’s cooperative learning. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4419.

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The article substantiates the importance of using a virtual digital board to organize student’s cooperative learning in the conditions of distance education, incl. social distance (for the quarantine period 2020). The main advantages of using a virtual digital board are outlined and their functions for the organization of cooperative education are compared. An analysis of the benefits of using virtual digital boards and a survey of experts made it possible to identify the most popular virtual digital boards: Wiki-Wall, Glogster, PadLet, Linoit, Twidla, Trello, Realtimeboard (Miro), Rizzoma. Th
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10

Linke, Ethan, Nazmina Mahmoudzadeh, and Darren Holland. Prioritising Foodborne Disease with Multi-Criteria Decision Analysis. Food Standards Agency, 2021. http://dx.doi.org/10.46756/sci.fsa.gex408.

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In recent years, the FSA has published a series of research projects which have produced estimates of the frequency and burden of thirteen different foodborne diseases. This document outlines the methodology and results of a multi-criteria decision analysis (MCDA) used to rank them in order of their detrimental effect on UK society.
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