subject:(Data analysis)

University of Georgia

1. Huang, Yining. Data analysis of the pattern information of the collective decision-making process in subterranean termites species.

Degree: MS, Statistics, 2016, University of Georgia

URL: http://purl.galileo.usg.edu/uga_etd/huang_yining_201608_ms

► Data were collected by a bioassay design to study the collective decision-making process of food searching for a subterranean termite species. The movements of termites… (more)

▼ Data were collected by a bioassay design to study the collective decision-making process of food searching for a subterranean termite species. The movements of termites were recorded by voltage-drop sensors, video-taping, and manual counting. Principal components analysis was applied to separate all the experimental replicates into three groups dependent upon termites’ final settlements. Multi-phase regression was conducted to determine the change-points in the process of food searching. The result of the data analyses indicated two general types of termite behavior. For both of these groups, termites seem to identify the food source quickly, but the movements of termites after finding the food are very different. Advisors/Committee Members: Jaxk Reeves.

Subjects/Keywords: Data Analysis

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APA (6^th Edition):

Huang, Y. (2016). Data analysis of the pattern information of the collective decision-making process in subterranean termites species. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/huang_yining_201608_ms

Chicago Manual of Style (16^th Edition):

Huang, Yining. “Data analysis of the pattern information of the collective decision-making process in subterranean termites species.” 2016. Masters Thesis, University of Georgia. Accessed July 18, 2019. http://purl.galileo.usg.edu/uga_etd/huang_yining_201608_ms.

MLA Handbook (7^th Edition):

Huang, Yining. “Data analysis of the pattern information of the collective decision-making process in subterranean termites species.” 2016. Web. 18 Jul 2019.

Vancouver:

Huang Y. Data analysis of the pattern information of the collective decision-making process in subterranean termites species. [Internet] [Masters thesis]. University of Georgia; 2016. [cited 2019 Jul 18]. Available from: http://purl.galileo.usg.edu/uga_etd/huang_yining_201608_ms.

Council of Science Editors:

Huang Y. Data analysis of the pattern information of the collective decision-making process in subterranean termites species. [Masters Thesis]. University of Georgia; 2016. Available from: http://purl.galileo.usg.edu/uga_etd/huang_yining_201608_ms

2. Dhungana, Prakash. Application for quick reduction of GPS data for urban mobility analysis.

Degree: 2014, Escola Superior Tecnologia e Gestão de Oliveira do Hospital

URL: https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521

►

The potential requirement of using data reduction application as an assistive tool for the student and researchers has been designed, developed and deployed. For that,… (more)

Subjects/Keywords: Data analysis; Data reduction

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APA (6^th Edition):

Dhungana, P. (2014). Application for quick reduction of GPS data for urban mobility analysis. (Thesis). Escola Superior Tecnologia e Gestão de Oliveira do Hospital. Retrieved from https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Dhungana, Prakash. “Application for quick reduction of GPS data for urban mobility analysis.” 2014. Thesis, Escola Superior Tecnologia e Gestão de Oliveira do Hospital. Accessed July 18, 2019. https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Dhungana, Prakash. “Application for quick reduction of GPS data for urban mobility analysis.” 2014. Web. 18 Jul 2019.

Vancouver:

Dhungana P. Application for quick reduction of GPS data for urban mobility analysis. [Internet] [Thesis]. Escola Superior Tecnologia e Gestão de Oliveira do Hospital; 2014. [cited 2019 Jul 18]. Available from: https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dhungana P. Application for quick reduction of GPS data for urban mobility analysis. [Thesis]. Escola Superior Tecnologia e Gestão de Oliveira do Hospital; 2014. Available from: https://www.rcaap.pt/detail.jsp?id=oai:comum.rcaap.pt:10400.26/17521

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Deakin University

3. Nguyen, Vu. Bayesian nonparametric multilevel modelling and applications.

Degree: School of Information Technology, 2015, Deakin University

URL: http://hdl.handle.net/10536/DRO/DU:30079715

Our research aims at contributing to the multilevel modeling in data analytics. We address the task of multilevel clustering, multilevel regression, and classification. We provide state of the art solution for the critical problem. Advisors/Committee Members: Phung, Dinh, Venkatesh, Svetha.

Subjects/Keywords: data analysis; regression analysis; multilevel data

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APA (6^th Edition):

Nguyen, V. (2015). Bayesian nonparametric multilevel modelling and applications. (Thesis). Deakin University. Retrieved from http://hdl.handle.net/10536/DRO/DU:30079715

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nguyen, Vu. “Bayesian nonparametric multilevel modelling and applications.” 2015. Thesis, Deakin University. Accessed July 18, 2019. http://hdl.handle.net/10536/DRO/DU:30079715.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nguyen, Vu. “Bayesian nonparametric multilevel modelling and applications.” 2015. Web. 18 Jul 2019.

Vancouver:

Nguyen V. Bayesian nonparametric multilevel modelling and applications. [Internet] [Thesis]. Deakin University; 2015. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/10536/DRO/DU:30079715.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nguyen V. Bayesian nonparametric multilevel modelling and applications. [Thesis]. Deakin University; 2015. Available from: http://hdl.handle.net/10536/DRO/DU:30079715

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

4. Bloemsma, M.R. Semi-automatic core characterisation based on geochemical logging data:.

Degree: 2010, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:4acf424e-6bb5-4044-a7af-2baea8108baa

► Textural variations in sediment are considered to be one of the primary controls on the geochemical composition. This relation has been widely exploited for the… (more)

▼ Textural variations in sediment are considered to be one of the primary controls on the geochemical composition. This relation has been widely exploited for the climatological interpretation of unconsolidated Quartenary sediment cores. Despite the common objectives in respectively unconsolidated and consolidated sedimentological studies, for the latter the use of novel techniques to acquire geochemical data, such as non-destructive XRF on cores, has not been applied yet. Because there is an ever increasing need for detailed (textural) sedimentological data, this study investigated the possibilities of in-situ XRF for semi-automatic textural characterization. An improvement to the current work flow of XRF core scanning data acquisition was suggested by a pre-calibration filtering step, in order to increase the signal to noise ratio. Apart from that, a sample selection routine was developed which, given the underlying calibration strategy, was expected to yield improved calibration results. Embedding the two algorithms into the calibration work flow proved that the sample selection algorithm as well as the pre-calibration filtering step result in improved calibration output. They are also found to be effective for real data; when applied to two datasets of unconsolidated cores, similar results were obtained. The second part of this study included the design of a sedimentary basin infill model ”LINMIX”, based on the mixing of different sediment sources with a grain size dependent chemical composition. By doing so, the observed geochemical signal is decomposed into a portion that is the result of textural variations and a portion that reflects differences in provenance. When applying LINMIX to a record of Quaternary sediment (offshore Senegal) as a proof-of-concept, the model was able to reconstruct the geochemical record satisfyingly by linear mixing of 3 endmembers with 3 unique Grain Size Distributions (GSD’s) and 2 unique functions characterising the compositional change in the grain size spectrum (Transfer function or ’TF’). This result implies that the chemical variation induced by the relative mixing of two endmembers was only the result of grain size variation and not of source material variation. The two endmembers that were designated a common TF, have in a previous study been interpreted as both reflecting material from the same sediment source. This implies that the LINMIX model has potential for semi-automatic provenance interpretation of sediment cores. Additionally the endmember compositions correspond fairly well with the present-day composition of the Senegal river and African eolian dust. Finally it was investigated how geochemical data can support semi-automatic grain size prediction of consolidated sediment, for which holds that there is no sediment source variation. This was done using a dataset of Carboniferous material, which is highly variable in terms of lithofacies. Around 11 meter of core has been geochemically logged with an XRF core scanner and successfully calibrated using 40 calibration… Advisors/Committee Members: Weltje, G.J., Lindenbergh, R.C..

Subjects/Keywords: compositional data analysis; provenance analysis

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APA (6^th Edition):

Bloemsma, M. R. (2010). Semi-automatic core characterisation based on geochemical logging data:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:4acf424e-6bb5-4044-a7af-2baea8108baa

Chicago Manual of Style (16^th Edition):

Bloemsma, M R. “Semi-automatic core characterisation based on geochemical logging data:.” 2010. Masters Thesis, Delft University of Technology. Accessed July 18, 2019. http://resolver.tudelft.nl/uuid:4acf424e-6bb5-4044-a7af-2baea8108baa.

MLA Handbook (7^th Edition):

Bloemsma, M R. “Semi-automatic core characterisation based on geochemical logging data:.” 2010. Web. 18 Jul 2019.

Vancouver:

Bloemsma MR. Semi-automatic core characterisation based on geochemical logging data:. [Internet] [Masters thesis]. Delft University of Technology; 2010. [cited 2019 Jul 18]. Available from: http://resolver.tudelft.nl/uuid:4acf424e-6bb5-4044-a7af-2baea8108baa.

Council of Science Editors:

Bloemsma MR. Semi-automatic core characterisation based on geochemical logging data:. [Masters Thesis]. Delft University of Technology; 2010. Available from: http://resolver.tudelft.nl/uuid:4acf424e-6bb5-4044-a7af-2baea8108baa

University of Ottawa

5. Nhogue Wabo, Blanche Nadege. Hedge Funds and Survival Analysis .

Degree: 2013, University of Ottawa

URL: http://hdl.handle.net/10393/26257

► Using data from Hedge Fund Research, Inc. (HFR), this study adapts and expands on existing methods in survival analysis in an attempt to investigate whether… (more)

Subjects/Keywords: Survival Analysis; HedgeFunds; Data analysis

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APA (6^th Edition):

Nhogue Wabo, B. N. (2013). Hedge Funds and Survival Analysis . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/26257

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nhogue Wabo, Blanche Nadege. “Hedge Funds and Survival Analysis .” 2013. Thesis, University of Ottawa. Accessed July 18, 2019. http://hdl.handle.net/10393/26257.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nhogue Wabo, Blanche Nadege. “Hedge Funds and Survival Analysis .” 2013. Web. 18 Jul 2019.

Vancouver:

Nhogue Wabo BN. Hedge Funds and Survival Analysis . [Internet] [Thesis]. University of Ottawa; 2013. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/10393/26257.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nhogue Wabo BN. Hedge Funds and Survival Analysis . [Thesis]. University of Ottawa; 2013. Available from: http://hdl.handle.net/10393/26257

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Georgia

6. Le-Rademacher, Jennifer Giaothuy. Principal component analysis for interval-valued and histogram-valued data and likelihood functions and some maximum likelihood estimators for symbolic data.

Degree: PhD, Statistics, 2008, University of Georgia

URL: http://purl.galileo.usg.edu/uga_etd/le-rademacher_jennifer_g_200812_phd

► Unlike a classical random variable which takes a single value, a symbolic random variable takes multiple values. The values within a symbolic random variable form… (more)

▼ Unlike a classical random variable which takes a single value, a symbolic random variable takes multiple values. The values within a symbolic random variable form an internal distribution that does not exist in a classical random variable. Statistical methodologies developed for classical data can not be readily applied to symbolic data. Therefore, new methodologies must be developed to take into account the internal structure of symbolic variables. In this dissertation, we propose three methods of symbolic data analysis. The first proposed method extends classical principal component analysis (PCA) to an analysis of interval-valued observations, using a so-called symbolic variance-covariance structure. Using the symbolic covariance structure ensures that the principal components explain the total variance of interval-valued data. Furthermore, two representations of the principal components resulting from the proposed PCA method are introduced. The first representation shows interval-valued observations as polytopes in a principal components space. The polytopes constructed in this method represent the true structure of interval-valued observations in a principal components space. The second representation gives histogram-valued principal components constructed from a 2-dimensional projection of the polytopes resulting from the first representation. Algorithms to construct the polytopes and to compute the histograms representing the principal components are given in this dissertation along with two examples to illustrate the method. The second method extends the PCA method proposed for interval-valued data to a PCA method for histogram-valued data. This method treats histogram-valued observations as a generalization of interval-valued observations. The two representations proposed for interval-valued observations are then extended to represent histogram-valued observations. An algorithm for the extension along with an example to illustrate this method are included. The third method proposes a construction of likelihood functions for symbolic data. The proposed likelihood function is then used to derive maximum likelihood estimators for the mean and the variance of three common types of symbolic data: interval-valued data, histogram-valued data, and triangular-distribution-valued data. Advisors/Committee Members: Lynne Billard.

Subjects/Keywords: Symbolic data analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Le-Rademacher, J. G. (2008). Principal component analysis for interval-valued and histogram-valued data and likelihood functions and some maximum likelihood estimators for symbolic data. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/le-rademacher_jennifer_g_200812_phd

Chicago Manual of Style (16^th Edition):

Le-Rademacher, Jennifer Giaothuy. “Principal component analysis for interval-valued and histogram-valued data and likelihood functions and some maximum likelihood estimators for symbolic data.” 2008. Doctoral Dissertation, University of Georgia. Accessed July 18, 2019. http://purl.galileo.usg.edu/uga_etd/le-rademacher_jennifer_g_200812_phd.

MLA Handbook (7^th Edition):

Le-Rademacher, Jennifer Giaothuy. “Principal component analysis for interval-valued and histogram-valued data and likelihood functions and some maximum likelihood estimators for symbolic data.” 2008. Web. 18 Jul 2019.

Vancouver:

Le-Rademacher JG. Principal component analysis for interval-valued and histogram-valued data and likelihood functions and some maximum likelihood estimators for symbolic data. [Internet] [Doctoral dissertation]. University of Georgia; 2008. [cited 2019 Jul 18]. Available from: http://purl.galileo.usg.edu/uga_etd/le-rademacher_jennifer_g_200812_phd.

Council of Science Editors:

Le-Rademacher JG. Principal component analysis for interval-valued and histogram-valued data and likelihood functions and some maximum likelihood estimators for symbolic data. [Doctoral Dissertation]. University of Georgia; 2008. Available from: http://purl.galileo.usg.edu/uga_etd/le-rademacher_jennifer_g_200812_phd

University of Georgia

7. Yanosky, Daniel J. Comparability of covariance structures and accuracy of information criteria in mixed model methods for longitudinal data analysis.

Degree: PhD, Educational Psychology, 2007, University of Georgia

URL: http://purl.galileo.usg.edu/uga_etd/yanosky_daniel_j_200705_phd

► Modern mixed model methods for analyzing longitudinal data require researchers to select a covariance structure for the data to fully specify the model and obtain… (more)

▼ Modern mixed model methods for analyzing longitudinal data require researchers to select a covariance structure for the data to fully specify the model and obtain statistical tests of the fixed effects. The current study is a Monte Carlo simulation with primary purposes to 1) identify surrogate covariance structures for seven known models and estimate the severity of committing an error in covariance specification in terms of empirical Type I error rates and statistical power, 2) estimate accuracy rates of five information criteria in selecting appropriate covariance structures, and 3) estimate the empirical Type I error rates and power for models chosen by each information criterion. Data were generated corresponding to a single group repeated measures design with N = 10, 30, or 60 subjects and a quantitative response variable measured over t = 3 or 6 occasions. Other salient variables included the magnitude of serial correlation, presence of non-constant variance, and so forth. Data were generated under 72 conditions with 10,000 replications per condition. Statistical Analysis System (SAS) version 9.1 and R version 2.4.0 were used to generate and analyze the data. A preliminary investigation demonstrated that the Kenward-Roger degrees of freedom approximation yields F-tests for the mixed models with superior Type I error control compared to the Between/Within method, Satterthwaite approximation, and the sandwich estimator. Results corresponding to the primary research questions demonstrated 1) seven covariance structures were found to be acceptable approximations of a given true model in 14 instances, 2) rates of selecting appropriate covariance structures for information criteria were found to be substantially influenced by accounting for surrogate structures with a rate of 69% for both AIC and BIC, 3) empirical Type I error rates were found to be slightly conservative and therefore well controlled and power estimates comparable when models were selected by AIC, AICC, HQIC, BIC, and CAIC. Secondary investigations compared the performance of mixed models with classical methods and evaluated the empirical Type I error control of the Group x Time interaction test. The implications of these findings are discussed and heuristics for applied researchers working with this variety of data are suggested. Advisors/Committee Members: Stephen Olejnik.

Subjects/Keywords: Longitudinal data analysis

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APA (6^th Edition):

Yanosky, D. J. (2007). Comparability of covariance structures and accuracy of information criteria in mixed model methods for longitudinal data analysis. (Doctoral Dissertation). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/yanosky_daniel_j_200705_phd

Chicago Manual of Style (16^th Edition):

Yanosky, Daniel J. “Comparability of covariance structures and accuracy of information criteria in mixed model methods for longitudinal data analysis.” 2007. Doctoral Dissertation, University of Georgia. Accessed July 18, 2019. http://purl.galileo.usg.edu/uga_etd/yanosky_daniel_j_200705_phd.

MLA Handbook (7^th Edition):

Yanosky, Daniel J. “Comparability of covariance structures and accuracy of information criteria in mixed model methods for longitudinal data analysis.” 2007. Web. 18 Jul 2019.

Vancouver:

Yanosky DJ. Comparability of covariance structures and accuracy of information criteria in mixed model methods for longitudinal data analysis. [Internet] [Doctoral dissertation]. University of Georgia; 2007. [cited 2019 Jul 18]. Available from: http://purl.galileo.usg.edu/uga_etd/yanosky_daniel_j_200705_phd.

Council of Science Editors:

Yanosky DJ. Comparability of covariance structures and accuracy of information criteria in mixed model methods for longitudinal data analysis. [Doctoral Dissertation]. University of Georgia; 2007. Available from: http://purl.galileo.usg.edu/uga_etd/yanosky_daniel_j_200705_phd

UCLA

8. Wu, Xiaoxu. An Informative and Predictive Analysis of the San Francisco Police Department Crime Data.

Degree: Statistics, 2016, UCLA

URL: http://www.escholarship.org/uc/item/9113p8tw

► It is the responsibility of the San Francisco Police Department to protect the local community from various crimes and to improve the local security environment.… (more)

Subjects/Keywords: Statistics; Data analysis

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APA (6^th Edition):

Wu, X. (2016). An Informative and Predictive Analysis of the San Francisco Police Department Crime Data. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/9113p8tw

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wu, Xiaoxu. “An Informative and Predictive Analysis of the San Francisco Police Department Crime Data.” 2016. Thesis, UCLA. Accessed July 18, 2019. http://www.escholarship.org/uc/item/9113p8tw.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wu, Xiaoxu. “An Informative and Predictive Analysis of the San Francisco Police Department Crime Data.” 2016. Web. 18 Jul 2019.

Vancouver:

Wu X. An Informative and Predictive Analysis of the San Francisco Police Department Crime Data. [Internet] [Thesis]. UCLA; 2016. [cited 2019 Jul 18]. Available from: http://www.escholarship.org/uc/item/9113p8tw.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wu X. An Informative and Predictive Analysis of the San Francisco Police Department Crime Data. [Thesis]. UCLA; 2016. Available from: http://www.escholarship.org/uc/item/9113p8tw

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

9. Chen, Yu-rong. Effectively Aggregating Big Data for Visualization.

Degree: Master, Information Management, 2016, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441

► With the fast development of the internet technologies, data is easily generated and collected. Those data could be useful based on how the enterprise or… (more)

Subjects/Keywords: Data Discretization; Exploratory Data Analysis; Big data; Data Reduction; Data Visualization

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APA (6^th Edition):

Chen, Y. (2016). Effectively Aggregating Big Data for Visualization. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Chen, Yu-rong. “Effectively Aggregating Big Data for Visualization.” 2016. Thesis, NSYSU. Accessed July 18, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Chen, Yu-rong. “Effectively Aggregating Big Data for Visualization.” 2016. Web. 18 Jul 2019.

Vancouver:

Chen Y. Effectively Aggregating Big Data for Visualization. [Internet] [Thesis]. NSYSU; 2016. [cited 2019 Jul 18]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chen Y. Effectively Aggregating Big Data for Visualization. [Thesis]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0411116-090441

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Alberta

10. Luo, Dandan. Models for Univariate and Multivariate Analysis of Longitudinal and Clustered Data.

Degree: PhD, Department of Mathematical and Statistical Sciences, 2012, University of Alberta

URL: https://era.library.ualberta.ca/files/s4655h86x

► Longitudinal studies of repeated observations on subjects are commonly undertaken in medical and biological sciences. The responses on a given occasion may be either univariate… (more)

▼ Longitudinal studies of repeated observations on subjects are commonly undertaken in medical and biological sciences. The responses on a given occasion may be either univariate or multivariate. We concentrate on three topics related to longitudinal and clustered data analysis. The first topic is the development of a class of generalized linear latent variable models. The second involves the modelling of count data with excess zeros. The third is the development of a non-Gaussian linear mixed effects model for multiple outcomes. In addressing the first problem, we propose random mean models to account for correlation among repeated measures. We extend random mean models to include mixed outcomes, renaming them random mean joint models. The difficulty in joint modelling of continuous and discrete outcomes is the lack of a natural multivariate distribution. We overcome the difficulty by introducing two cross-correlated latent processes. We apply the Monte Carlo EM (MCEM) algorithm to find the MLEs of regression coefficients and variance components, by treating the latent variables as missing data. This thesis also proposes regression models for count data with excess zeros. We solve the problem from a perspective different from that of mixture model framework. By employing the zero truncated distribution and the zero modified distribution, we establish a broad class of distributions to model data with excess zeros. We consider the zero modified Poisson regression model and zero modified binomial regression model for cross-sectional data. We extend the zero modified regression models to models with random effects. We further extend random mean models to model zero-inflated data, and formulate the corresponding zero modified random mean models. A non-Gaussian linear mixed effects model for multiple outcomes is proposed to the third question. The methodology is motivated by a glaucoma study. The normality assumption for random effects may be unrealistic, raising concerns about the validity of inferences on fixed effects and random effects if it is violated. To accommodate the skewness of the responses and the associations among multiple characteristics, we propose a mixed effects model, in which non-normal random effects are assumed by the log-gamma distribution.

Subjects/Keywords: Longitudinal Data Analysis; Zero-inflated Data; Clustered Data Analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Luo, D. (2012). Models for Univariate and Multivariate Analysis of Longitudinal and Clustered Data. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/s4655h86x

Chicago Manual of Style (16^th Edition):

Luo, Dandan. “Models for Univariate and Multivariate Analysis of Longitudinal and Clustered Data.” 2012. Doctoral Dissertation, University of Alberta. Accessed July 18, 2019. https://era.library.ualberta.ca/files/s4655h86x.

MLA Handbook (7^th Edition):

Luo, Dandan. “Models for Univariate and Multivariate Analysis of Longitudinal and Clustered Data.” 2012. Web. 18 Jul 2019.

Vancouver:

Luo D. Models for Univariate and Multivariate Analysis of Longitudinal and Clustered Data. [Internet] [Doctoral dissertation]. University of Alberta; 2012. [cited 2019 Jul 18]. Available from: https://era.library.ualberta.ca/files/s4655h86x.

Council of Science Editors:

Luo D. Models for Univariate and Multivariate Analysis of Longitudinal and Clustered Data. [Doctoral Dissertation]. University of Alberta; 2012. Available from: https://era.library.ualberta.ca/files/s4655h86x

Tampere University

11. Syrjärinne, Paula. Urban Traffic Analysis with Bus Location Data .

Degree: 2016, Tampere University

URL: http://tampub.uta.fi/handle/10024/98613

► Tässä työssä esitellään Tampereen alueen julkisen liikenteen linja-autoista kerätyn datan käyttöä ja analysointia. Aineistoa on analysoitu useilla eri algoritmeilla ja monesta eri näkökulmasta. Osa analyyseista… (more)

▼ Tässä työssä esitellään Tampereen alueen julkisen liikenteen linja-autoista kerätyn datan käyttöä ja analysointia. Aineistoa on analysoitu useilla eri algoritmeilla ja monesta eri näkökulmasta. Osa analyyseista mittaa julkisen liikenteen palvelutasoa, osa tarjoaa matkustajille hyödyllistä lisäinformaatiota ja osa keskittyy havainnoimaan liikenteen yleistä sujuvuutta. Työn alussa esitellään aiheeseen liittyviä taustatietoja ja aiemmin samasta aiheesta tehtyjä tutkimuksia. Erilaiset liikenteeseen liittyvät sensoriverkostot käydään läpi, keskittyen erityisesti sensoriautoverkostoihin. Kauttaaltaan työssä käsitellään Tampereen linja-autodataa liikkuvasta autosensoriverkosta kerättynä datana. Sensoriautoverkostojen analyysiin liittyvää kirjallisuutta esitellään työssä siten että tutkimukset on jaoteltu lähdedatan perusteella taksidataa, linja-autodataa ja mobiililaitedataa käsitteleviin artikkeleihin. Kuhunkin näistä liittyy erilaisia tutkimusongelmia. Taksidataa käytettäessä puuttuvat havaintopisteet ovat yleisin ongelma, kun taas henkilöautoliikenteen mallintaminen linja-autoista kerätyn datan perusteella on tyypillinen kysymys bussidataa käyttävissä tutkimuksissa. Mobiililaitteista kerättyä dataa käytettäessä pitää sen sijaan yleensä ensin selvittää onko laite ylipäätään liikkuvassa ajoneuvossa. Tampereen linja-autodata esitellään yksityiskohtaisesti. Tämä data on verrattain hyvälaatuista, koska sen päivitysnopeus on korkea, jokaiseen havaintoon on aina liittetty yksilölliset tunnisteet ja koko julkisen liikenteen verkoston alueelta on runsaasti havaintoja saatavilla. Kuten missä tahansa oikeasta lähteestä kerätyssä datassa, tässäkin aineistossa on kuitenkin ongelmia, kuten epäjohdonmukaisuuksia, virheitä ja kohinaa. Näiden virheiden odotettavissa olevat suuruusluokat on käyty datan esittelyssä läpi. Samoin esittelellään esikäsittelyprosessi, jossa dataa sekä puhdistetaan virheistä että sen kokoa ja muotoa muutetaan helpommin käytettäväksi tilastollisessa analyysissä. Työn kokeellisessa osassa tarkastellaan aluksi datan käyttöä julkisen liikenteen toimivuuden mittaamisessa. Datasta on etsitty usein esiintyviä aika-paikka-linja –joukkoja, jotka paljastavat missä, milloin ja millä linjoilla bussit ovat säännöllisesti myöhässä. Sen lisäksi reittiajoja on jaoteltu paikan ja tapahtumien (kuten pysäkillä käynnit tai liikennevaloissa odottaminen) mukaan, jotta on löydetty syitä myöhästymisille. Matkustajien kannalta tehdyissä kokeiluissa on toteutettu mm. dataan perustuvat pysäkkiaikataulut, jotka mukautuvat ajan mittaan todellisten saapumisaikojen mukaan. Saapumisajan lisäksi matkustajille annetaan arvio saapumisajan epävarmuudesta. Yleisen liikenteen sujuvuuden analysoimiseksi esitellään katuosuusprofiilien käsite. Profiili kertoo kullekin pysäkinvälille normaalin ajoajan rajat kunakin vuorokaudenaikana. Profiileja voidaan käyttää pysäkinvälien luokitteluun esimerkiksi aamu- ja iltapäiväruuhkan vaikutusten mukaan, ja ne ovat perusta reaaliaikaisen poikkeustilamonitoroinnin tarpeisiin.…

Subjects/Keywords: data-analyysi; big data; älyliikenne; data analysis; big data; ITS

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Syrjärinne, P. (2016). Urban Traffic Analysis with Bus Location Data . (Doctoral Dissertation). Tampere University. Retrieved from http://tampub.uta.fi/handle/10024/98613

Chicago Manual of Style (16^th Edition):

Syrjärinne, Paula. “Urban Traffic Analysis with Bus Location Data .” 2016. Doctoral Dissertation, Tampere University. Accessed July 18, 2019. http://tampub.uta.fi/handle/10024/98613.

MLA Handbook (7^th Edition):

Syrjärinne, Paula. “Urban Traffic Analysis with Bus Location Data .” 2016. Web. 18 Jul 2019.

Vancouver:

Syrjärinne P. Urban Traffic Analysis with Bus Location Data . [Internet] [Doctoral dissertation]. Tampere University; 2016. [cited 2019 Jul 18]. Available from: http://tampub.uta.fi/handle/10024/98613.

Council of Science Editors:

Syrjärinne P. Urban Traffic Analysis with Bus Location Data . [Doctoral Dissertation]. Tampere University; 2016. Available from: http://tampub.uta.fi/handle/10024/98613

University of KwaZulu-Natal

12. Vela Vela, Junior. The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban.

Degree: 2017, University of KwaZulu-Natal

URL: http://hdl.handle.net/10413/15171

► The increase of number of data available in today’s world has prompted different industries to find a way to get the value out of the… (more)

Subjects/Keywords: Big data analysis.; Technology.; Big data.; Adoption.

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APA (6^th Edition):

Vela Vela, J. (2017). The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban. (Thesis). University of KwaZulu-Natal. Retrieved from http://hdl.handle.net/10413/15171

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Vela Vela, Junior. “The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban.” 2017. Thesis, University of KwaZulu-Natal. Accessed July 18, 2019. http://hdl.handle.net/10413/15171.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Vela Vela, Junior. “The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban.” 2017. Web. 18 Jul 2019.

Vancouver:

Vela Vela J. The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban. [Internet] [Thesis]. University of KwaZulu-Natal; 2017. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/10413/15171.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vela Vela J. The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban. [Thesis]. University of KwaZulu-Natal; 2017. Available from: http://hdl.handle.net/10413/15171

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Illinois – Chicago

13. Swanlund, Andrew Peter. Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings.

Degree: 2016, University of Illinois – Chicago

URL: http://hdl.handle.net/10027/21553

► This thesis addresses the problem of non-ignorable missing ratings in judge rated data. A Bayesian bivariate probit ordinal missing data model implemented with Markov chain… (more)

Subjects/Keywords: Psychometrics; Judge-Rated Data; Missing Data Analysis

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APA (6^th Edition):

Swanlund, A. P. (2016). Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/21553

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Swanlund, Andrew Peter. “Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings.” 2016. Thesis, University of Illinois – Chicago. Accessed July 18, 2019. http://hdl.handle.net/10027/21553.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Swanlund, Andrew Peter. “Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings.” 2016. Web. 18 Jul 2019.

Vancouver:

Swanlund AP. Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings. [Internet] [Thesis]. University of Illinois – Chicago; 2016. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/10027/21553.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Swanlund AP. Correcting for Rater Bias in the Presence of Non-Ignorable Missing Ratings. [Thesis]. University of Illinois – Chicago; 2016. Available from: http://hdl.handle.net/10027/21553

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Otago

14. Turei Stanton, Worik Macky. Is Data Snooping responsible for Technical Analysis Rules Success? .

Degree: 2013, University of Otago

URL: http://hdl.handle.net/10523/4346

► Data Snooping is often suspected when effective technical analysis rules are found or presented. It is difficult to tell if a result is due to… (more)

Subjects/Keywords: data snooping; data mining; technical analysis

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APA (6^th Edition):

Turei Stanton, W. M. (2013). Is Data Snooping responsible for Technical Analysis Rules Success? . (Masters Thesis). University of Otago. Retrieved from http://hdl.handle.net/10523/4346

Chicago Manual of Style (16^th Edition):

Turei Stanton, Worik Macky. “Is Data Snooping responsible for Technical Analysis Rules Success? .” 2013. Masters Thesis, University of Otago. Accessed July 18, 2019. http://hdl.handle.net/10523/4346.

MLA Handbook (7^th Edition):

Turei Stanton, Worik Macky. “Is Data Snooping responsible for Technical Analysis Rules Success? .” 2013. Web. 18 Jul 2019.

Vancouver:

Turei Stanton WM. Is Data Snooping responsible for Technical Analysis Rules Success? . [Internet] [Masters thesis]. University of Otago; 2013. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/10523/4346.

Council of Science Editors:

Turei Stanton WM. Is Data Snooping responsible for Technical Analysis Rules Success? . [Masters Thesis]. University of Otago; 2013. Available from: http://hdl.handle.net/10523/4346

University of Connecticut

15. Ibrahim, Abdelrahman Hosny. Integrative Analysis of Heterogeneous Genomics Data for Triple Negative Breast Cancer and High Grade Serous Ovarian Cancer.

Degree: MS, Computer Science and Engineering, 2016, University of Connecticut

URL: https://opencommons.uconn.edu/gs_theses/1032

► The human body is made up of trillions of cells. Although all the human body cells contain the same DNA sequence inside their nuclei,… (more)

▼ The human body is made up of trillions of cells. Although all the human body cells contain the same DNA sequence inside their nuclei, each one carries out its own function. Normally, human cells grow and divide to form daughter cells as the body needs them. When cells grow old, or lose their ability to function properly, they die (in a very organized way called apoptosis or programmed cell death) and new cells take their role. Cancer is a disease that is caused by uncontrolled division of abnormal cells in some part of the body, breaking the natural process of growing. Old or damaged cells survive when they should die, and new (abnormal) cells form when they are not needed. Some types of cancer form solid tumors, which are masses of tissue. Others, such as leukemias, do not form solid tumors. It is widely believed that cancer is caused by the accumulation of detrimental variation in the genome over the course of a lifetime. Variations can take several forms. Single Nucleotide Polymorphism (SNP) is a mutation in a single base of the DNA. Indels describe insertions or deletions of bases in the genome. Copy Number Variation (CNV) represents multiplied and deleted segments in a genome. Most of the time, one type of mutation is not sufficient to induce cancer formation. In this study, we have investigated genomic datasets of a phase-1 clinical trial on triple-negative breast cancer and ovarian cancer patients. The goal is to identify genes that drive drug resistance. We have developed data analysis pipelines to obtain genomics variations (somatic mutations and copy number variations) from the Whole Exome Sequencing (WES) raw data of 35 triple-negative breast cancer (TNBC) and ovarian cancer patients. In addition, we have analyzed the gene expression levels and gene fusion from the RNA-Seq raw reads data for a subset of 16 patients. This study is an effort toward optimizing the integrative analysis of genomic datasets under certain limitations. The main limitation is the small number of samples in the clinical trial (as is the case in most clinical trials). Another challenge is to find an abstract way to analyze the raw sequencing data given its large size and heterogeneity. The novelty of our work comes in following a data science approach in answering such research questions. The unbiased and data-driven approach was successful in identifying genes that are most likely related to the drug resistance. Our results will guide clinicians toward having an in-depth study of the driver genes. Advisors/Committee Members: Reda Ammar, Sheida Nabavi, Sanguthevar Rajasekaran, Yufeng Wu, Reda Ammar, Sheida Nabavi.

Subjects/Keywords: cancer; data science; data analysis; genomics; NGS

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Ibrahim, A. H. (2016). Integrative Analysis of Heterogeneous Genomics Data for Triple Negative Breast Cancer and High Grade Serous Ovarian Cancer. (Masters Thesis). University of Connecticut. Retrieved from https://opencommons.uconn.edu/gs_theses/1032

Chicago Manual of Style (16^th Edition):

Ibrahim, Abdelrahman Hosny. “Integrative Analysis of Heterogeneous Genomics Data for Triple Negative Breast Cancer and High Grade Serous Ovarian Cancer.” 2016. Masters Thesis, University of Connecticut. Accessed July 18, 2019. https://opencommons.uconn.edu/gs_theses/1032.

MLA Handbook (7^th Edition):

Ibrahim, Abdelrahman Hosny. “Integrative Analysis of Heterogeneous Genomics Data for Triple Negative Breast Cancer and High Grade Serous Ovarian Cancer.” 2016. Web. 18 Jul 2019.

Vancouver:

Ibrahim AH. Integrative Analysis of Heterogeneous Genomics Data for Triple Negative Breast Cancer and High Grade Serous Ovarian Cancer. [Internet] [Masters thesis]. University of Connecticut; 2016. [cited 2019 Jul 18]. Available from: https://opencommons.uconn.edu/gs_theses/1032.

Council of Science Editors:

Ibrahim AH. Integrative Analysis of Heterogeneous Genomics Data for Triple Negative Breast Cancer and High Grade Serous Ovarian Cancer. [Masters Thesis]. University of Connecticut; 2016. Available from: https://opencommons.uconn.edu/gs_theses/1032

Carnegie Mellon University

16. Rzeszotarski, Jeffrey M. Uncovering Nuances in Complex Data Through Focus and Context Visualizations.

Degree: 2017, Carnegie Mellon University

URL: http://repository.cmu.edu/dissertations/958

► Across a wide variety of digital devices, users create, consume, and disseminate large quantities of information. While data sometimes look like a spreadsheet or network… (more)

▼ Across a wide variety of digital devices, users create, consume, and disseminate large quantities of information. While data sometimes look like a spreadsheet or network diagram, more often for everyday users their data look more like an Amazon search page, the line-up for a fantasy football team, or a set of Yelp reviews. However, interpreting these kinds of data remains a difficult task even for experts since they often feature soft or unknown constraints (e.g. ”I want some Thai food, but I also want a good bargain”) across highly multidimensional data (i.e. rating, reviews, popularity, proximity). Existing technology is largely optimized for users with hard criteria and satisfiable constraints, and consumer systems often use representations better suited for browsing than sensemaking. In this thesis I explore ways to support soft constraint decision-making and exploratory data analysis by giving users tools that show fine-grained features of the data while at the same time displaying useful contextual information. I describe approaches for representing collaborative content history and working behavior that reveal both individual and group/dataset level features. Using these approaches, I investigate general visualizations that utilize physics to help even inexperienced users find small and large trends in multivariate data. I describe the transition of physicsbased visualization from the research space into the commercial space through a startup company, and the insights that emerged both from interviews with experts in a wide variety of industries during commercialization and from a comparative lab study. Taking one core use case from commercialization, consumer search, I develop a prototype, Fractal, which helps users explore and apply constraints to Yelp data at a variety of scales by curating and representing individual-, group-, and dataset-level features. Through a user study and theoretical model I consider how the prototype can best aide users throughout the sensemaking process. My dissertation further investigates physics-based approaches for represent multivariate data, and explores how the user’s exploration process itself can help dynamically to refine the search process and visual representation. I demonstrate that selectively representing points using clusters can extend physics-based visualizations across a variety of data scales, and help users make sense of data at scales that might otherwise overload them. My model provides a framework for stitching together a model of user interest and data features, unsupervised clustering, and visual representations for exploratory data visualization. The implications from commercialization are more broad, giving insight into why research in the visualization space is/isn’t adopted by industry, a variety of real-world use cases for multivariate exploratory data analysis, and an index of common data visualization needs in industry.

Subjects/Keywords: Human-Computer Interaction; Data Visualization; Big Data; Small Data; Medium Data; Exploratory Data Analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Rzeszotarski, J. M. (2017). Uncovering Nuances in Complex Data Through Focus and Context Visualizations. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/958

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Rzeszotarski, Jeffrey M. “Uncovering Nuances in Complex Data Through Focus and Context Visualizations.” 2017. Thesis, Carnegie Mellon University. Accessed July 18, 2019. http://repository.cmu.edu/dissertations/958.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Rzeszotarski, Jeffrey M. “Uncovering Nuances in Complex Data Through Focus and Context Visualizations.” 2017. Web. 18 Jul 2019.

Vancouver:

Rzeszotarski JM. Uncovering Nuances in Complex Data Through Focus and Context Visualizations. [Internet] [Thesis]. Carnegie Mellon University; 2017. [cited 2019 Jul 18]. Available from: http://repository.cmu.edu/dissertations/958.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rzeszotarski JM. Uncovering Nuances in Complex Data Through Focus and Context Visualizations. [Thesis]. Carnegie Mellon University; 2017. Available from: http://repository.cmu.edu/dissertations/958

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Utah

17. Gueye, Abdou Salam. Mapping economic and health data: integration and analysis challenges.

Degree: PhD, Biomedical Informatics;, 2007, University of Utah

URL: http://content.lib.utah.edu/cdm/singleitem/collection/etd2/id/320/rec/730

► This work included four separate studies that each led to a publication. These studies shared a common relationship between economy or lifestyle and health while… (more)

▼ This work included four separate studies that each led to a publication. These studies shared a common relationship between economy or lifestyle and health while employing different research methods using data integration. Each study addressed certain aspects of public health informatics. The cost-effectiveness of incorporating a Clinical Decision Support System (CGSS) in a multidimensional rural community intervention aimed to reduce inappropriate antibiotic prescription with calculated during the first study. The three additional studies integrated different levels of ecological and individual data in order to described relationship between economy and health. First, ecological data integration was utilized to create a dataset containing countries’ health and economic indicators in order to develop a prediction model of HIV sero-prevalence across Africa. Second, individual data integration was used to assess the role of a single lifestyle indicator (alcohol dependency) on health outcome. Third, ecological and individual data integration was used in order to measure the association between global economy and individual data. The first study demonstrated the cost-effectiveness of using a clinical decision support system in public health interventions. The three additional studies demonstrated, respectively, 1) the possibility to combine multivariate modeling and spatial clustering for predicting HIV sero-prevalence in different countries in sub-Saharan Africa; 2) that alcohol dependency at the time of end-stage renal disease onset is a risk factor for rental graft failure and recipient death; and 3) that, beyond 3 years post transplantation, when some recipients lose Medicare benefits, economic downturns might negatively affect the kidney graft and recipient survival. These studies provide diverse and rigorous research experiences related to public health, epidemiology, and informatics. Further development of the methods used would certainly help explain the relationship between the macroeconomic situation, population health, and individual health as it would facilitate data integration crossing temporal, geographic, and sciences.

Subjects/Keywords: Automatic Data Processing; Statistical Analysis

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APA (6^th Edition):

Gueye, A. S. (2007). Mapping economic and health data: integration and analysis challenges. (Doctoral Dissertation). University of Utah. Retrieved from http://content.lib.utah.edu/cdm/singleitem/collection/etd2/id/320/rec/730

Chicago Manual of Style (16^th Edition):

Gueye, Abdou Salam. “Mapping economic and health data: integration and analysis challenges.” 2007. Doctoral Dissertation, University of Utah. Accessed July 18, 2019. http://content.lib.utah.edu/cdm/singleitem/collection/etd2/id/320/rec/730.

MLA Handbook (7^th Edition):

Gueye, Abdou Salam. “Mapping economic and health data: integration and analysis challenges.” 2007. Web. 18 Jul 2019.

Vancouver:

Gueye AS. Mapping economic and health data: integration and analysis challenges. [Internet] [Doctoral dissertation]. University of Utah; 2007. [cited 2019 Jul 18]. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd2/id/320/rec/730.

Council of Science Editors:

Gueye AS. Mapping economic and health data: integration and analysis challenges. [Doctoral Dissertation]. University of Utah; 2007. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd2/id/320/rec/730

Dalhousie University

18. Ni, Wenjia. Application of Clustering, Logistic Regression and Decision Tree Induction on EGM Data for Detection and Prediction of At-Risk and Problem Gamblers.

Degree: Master of Electronic Commerce, Faculty of Computer Science, 2014, Dalhousie University

URL: http://hdl.handle.net/10222/53596

► The use of data mining techniques for problem gambling behaviour analysis has huge potential to offer players protection and to reduce the risk of gambling-related… (more)

Subjects/Keywords: Data Mining; Gambling behaviour analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Ni, W. (2014). Application of Clustering, Logistic Regression and Decision Tree Induction on EGM Data for Detection and Prediction of At-Risk and Problem Gamblers. (Masters Thesis). Dalhousie University. Retrieved from http://hdl.handle.net/10222/53596

Chicago Manual of Style (16^th Edition):

Ni, Wenjia. “Application of Clustering, Logistic Regression and Decision Tree Induction on EGM Data for Detection and Prediction of At-Risk and Problem Gamblers.” 2014. Masters Thesis, Dalhousie University. Accessed July 18, 2019. http://hdl.handle.net/10222/53596.

MLA Handbook (7^th Edition):

Ni, Wenjia. “Application of Clustering, Logistic Regression and Decision Tree Induction on EGM Data for Detection and Prediction of At-Risk and Problem Gamblers.” 2014. Web. 18 Jul 2019.

Vancouver:

Ni W. Application of Clustering, Logistic Regression and Decision Tree Induction on EGM Data for Detection and Prediction of At-Risk and Problem Gamblers. [Internet] [Masters thesis]. Dalhousie University; 2014. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/10222/53596.

Council of Science Editors:

Ni W. Application of Clustering, Logistic Regression and Decision Tree Induction on EGM Data for Detection and Prediction of At-Risk and Problem Gamblers. [Masters Thesis]. Dalhousie University; 2014. Available from: http://hdl.handle.net/10222/53596

Texas A&M University

19. Li, Yehua. Topics in functional data analysis with biological applications.

Degree: 2009, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-1867

► Functional data analysis (FDA) is an active field of statistics, in which the primary subjects in the study are curves. My dissertation consists of two… (more)

▼ Functional data analysis (FDA) is an active field of statistics, in which the primary subjects in the study are curves. My dissertation consists of two innovative applications of functional data analysis in biology. The data that motivated the research broadened the scope of FDA and demanded new methodology. I develop new nonparametric methods to make various estimations, and I focus on developing large sample theories for the proposed estimators. The first project is motivated from a colon carcinogenesis study, the goal of which is to study the function of a protein (p27) in colon cancer development. In this study, a number of colonic crypts (units) were sampled from each rat (subject) at random locations along the colon, and then repeated measurements on the protein expression level were made on each cell (subunit) within the selected crypts. In this problem, measurements within each crypt can be viewed as a function, since the measurements can be indexed by the cell locations. The functions from the same subject are spatially correlated along the colon, and my goal is to estimate this correlation function using nonparametric methods. We use this data set as an motivation and propose a kernel estimator of the correlation function in a more general framework. We develop a pointwise asymptotic normal distribution for the proposed estimator when the number of subjects is fixed and the number of units within each subject goes to infinity. Based on the asymptotic theory, we propose a weighted block bootstrapping method for making inferences about the correlation function, where the weights account for the inhomogeneity of the distribution of the unit locations. Simulation studies are also provided to illustrate the numerical performance of the proposed method. My second project is on a lipoprotein profile data, where the goal is to use lipoprotein profile curves to predict the cholesterol level in human blood. Again, motivated by the data, we consider a more general problem: the functional linear models (Ramsay and Silverman, 1997) with functional predictor and scalar response. There is literature developing different methods for this model; however, there is little theory to support the methods. Therefore, we focus more on the theoretical properties of this model. There are other contemporary theoretical work on methods based on Principal Component Regression. Our work is different in the sense that we base our method on roughness penalty approach and consider a more realistic scenario that the functional predictor is observed only on discrete points. To reduce the difficulty of the theoretical derivations, we restrict the functions with a periodic boundary condition and develop an asymptotic convergence rate for this problem in Chapter III. A more general result based on splines is a future research topic that I give some discussion in Chapter IV. Advisors/Committee Members: Carroll, Raymond J. (advisor), Hsing, Tailen (advisor), Wang, Naisyin (committee member), Ward, Joe (committee member).

Subjects/Keywords: Functional Data Analysis; Nonparametric statistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Li, Y. (2009). Topics in functional data analysis with biological applications. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-1867

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Li, Yehua. “Topics in functional data analysis with biological applications.” 2009. Thesis, Texas A&M University. Accessed July 18, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-1867.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Li, Yehua. “Topics in functional data analysis with biological applications.” 2009. Web. 18 Jul 2019.

Vancouver:

Li Y. Topics in functional data analysis with biological applications. [Internet] [Thesis]. Texas A&M University; 2009. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1867.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li Y. Topics in functional data analysis with biological applications. [Thesis]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1867

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Texas A&M University

20. Almarzooq, Anas Mohammadali S. The Implications and Flow Behavior of the Hydraulically Fractured Wells in Shale Gas Formation.

Degree: 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8626

► Shale gas formations are known to have low permeability. This low permeability can be as low as 100 nano darcies. Without stimulating wells drilled in… (more)

▼ Shale gas formations are known to have low permeability. This low permeability can be as low as 100 nano darcies. Without stimulating wells drilled in the shale gas formations, it is hard to produce them at an economic rate. One of the stimulating approaches is by drilling horizontal wells and hydraulically fracturing the formation. Once the formation is fractured, different flow patterns will occur. The dominant flow regime observed in the shale gas formation is the linear flow or the transient drainage from the formation matrix toward the hydraulic fracture. This flow could extend up to years of production and it can be identified by half slop on the log-log plot of the gas rate against time. It could be utilized to evaluate the hydraulic fracture surface area and eventually evaluate the effectiveness of the completion job. Different models from the literature can be used to evaluate the completion job. One of the models used in this work assumes a rectangular reservoir with a slab shaped matrix between each two hydraulic fractures. From this model, there are at least five flow regions and the two regions discussed are the Region 2 in which bilinear flow occurs as a result of simultaneous drainage form the matrix and hydraulic fracture. The other is Region 4 which results from transient matrix drainage which could extend up to many years. The Barnett shale production data will be utilized throughout this work to show sample of the calculations. This first part of this work will evaluate the field data used in this study following a systematic procedure explained in Chapter III. This part reviews the historical production, reservoir and fluid data and well completion records available for the wells being analyzed. It will also check for data correlations from the data available and explain abnormal flow behaviors that might occur utilizing the field production data. It will explain why some wells might not fit into each model. This will be followed by a preliminary diagnosis, in which flow regimes will be identified, unclear data will be filtered, and interference and liquid loading data will be pointed. After completing the data evaluation, this work will evaluate and compare the different methods available in the literature in order to decide which method will best fit to analyze the production data from the Barnett shale. Formation properties and the original gas in place will be evaluated and compared for different methods. Advisors/Committee Members: Wattenbarger, Robert A. (advisor), Sun, Yuefeng (committee member), Maggard, Bryan (committee member).

Subjects/Keywords: Shale gas; production data analysis

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APA (6^th Edition):

Almarzooq, A. M. S. (2012). The Implications and Flow Behavior of the Hydraulically Fractured Wells in Shale Gas Formation. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8626

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Almarzooq, Anas Mohammadali S. “The Implications and Flow Behavior of the Hydraulically Fractured Wells in Shale Gas Formation.” 2012. Thesis, Texas A&M University. Accessed July 18, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8626.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Almarzooq, Anas Mohammadali S. “The Implications and Flow Behavior of the Hydraulically Fractured Wells in Shale Gas Formation.” 2012. Web. 18 Jul 2019.

Vancouver:

Almarzooq AMS. The Implications and Flow Behavior of the Hydraulically Fractured Wells in Shale Gas Formation. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8626.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Almarzooq AMS. The Implications and Flow Behavior of the Hydraulically Fractured Wells in Shale Gas Formation. [Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8626

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Victoria University of Wellington

21. Li, Xiaomei. Approaches to Modelling Heterogeneity in Longitudinal Studies.

Degree: 2011, Victoria University of Wellington

URL: http://hdl.handle.net/10063/1695

► This thesis is about estimation bias of longitudinal data when there is correlation between the explanatory variable and the individual effect. In our study, we… (more)

Subjects/Keywords: Longitudinal data analysis; Estimation bias

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APA (6^th Edition):

Li, X. (2011). Approaches to Modelling Heterogeneity in Longitudinal Studies. (Masters Thesis). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/1695

Chicago Manual of Style (16^th Edition):

Li, Xiaomei. “Approaches to Modelling Heterogeneity in Longitudinal Studies.” 2011. Masters Thesis, Victoria University of Wellington. Accessed July 18, 2019. http://hdl.handle.net/10063/1695.

MLA Handbook (7^th Edition):

Li, Xiaomei. “Approaches to Modelling Heterogeneity in Longitudinal Studies.” 2011. Web. 18 Jul 2019.

Vancouver:

Li X. Approaches to Modelling Heterogeneity in Longitudinal Studies. [Internet] [Masters thesis]. Victoria University of Wellington; 2011. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/10063/1695.

Council of Science Editors:

Li X. Approaches to Modelling Heterogeneity in Longitudinal Studies. [Masters Thesis]. Victoria University of Wellington; 2011. Available from: http://hdl.handle.net/10063/1695

Texas A&M University

22. Ding, Weihao. Experiment of Mapper Algorithm on High-Dimensional Data in Microseismic Monitoring.

Degree: MS, Petroleum Engineering, 2017, Texas A&M University

URL: http://hdl.handle.net/1969.1/166077

► The objective of this research to utilize data driven methods to analyze microseismic monitoring, especially using Topological data analysis (TDA) with limited physically based approaches.… (more)

▼ The objective of this research to utilize data driven methods to analyze microseismic monitoring, especially using Topological data analysis (TDA) with limited physically based approaches. Python Mapper (PM) is the tool of TDA for this study. Microseismic data has great characteristics of big data. Previous studies suggesting stage-by-stage microseismic analysis also avoid the limitation of current software, which can only process slightly over 10,000 data points. During this study, more TDA packages are constantly evolving to handle larger and more complex data such as Betti Mapper by Spark. PM is a tool by combining topology principles and machine learning methods into an integrated data analytic implementation. The high-dimensionality of microseismic data practically limits what classical statistical analyses can achieve. Machine learning techniques such as dimensionality reduction are required for such datasets. Where PM stands out is its ability to retain the raw feature of data set when machine-learning algorithm is applied. The first portion of the study is to observe the data point relation of microseismic data entirely and stage-by-stage. Dividing attributes into location and signal data reveals the relation within and between two different data types. The main discovery from location data of network is the high density areas are tend to be earlier events and could locate where high pressure start to build up, or the origins of the fracture networks. Origins that are far apart in the beginning grow into each other to result in one (most of the time) or more (rarely more than two) networks. The fracture growth with complex directions of extensions can be represented with a much simpler, single-directional network. Signal data reveals location-specific data quality trends. These trends are hardly visible if attributes are investigated in pairs but obvious when mapped altogether. Locational and geological characteristics may be an explanation, but this needs further information to prove the observations. In fracture growth softwares, these trends will allow researchers to ignore the location of the wellbore and focuses at the actual origins of the fracture network. An override including discontinuity of the network and confidence of stimulated reservoir volume could be manually added to improve the accuracy of the fracture simulation. A sensitivity analysis to PM parameters is carried out to test the robustness of the method and comparing raw data clustering method to prove the effectiveness and benefits of using TDA. TDA is a great method for data preprocesses, analyses, and has virtually infinite possibility, but should never be the end of a project. The results from PM could be used as input for many other studies. Advisors/Committee Members: Killough, John (advisor), Gildin, Eduardo (committee member), Barrufet, Maria (committee member).

Subjects/Keywords: Data Analysis; Microseismic; Topological; Mapper

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APA (6^th Edition):

Ding, W. (2017). Experiment of Mapper Algorithm on High-Dimensional Data in Microseismic Monitoring. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/166077

Chicago Manual of Style (16^th Edition):

Ding, Weihao. “Experiment of Mapper Algorithm on High-Dimensional Data in Microseismic Monitoring.” 2017. Masters Thesis, Texas A&M University. Accessed July 18, 2019. http://hdl.handle.net/1969.1/166077.

MLA Handbook (7^th Edition):

Ding, Weihao. “Experiment of Mapper Algorithm on High-Dimensional Data in Microseismic Monitoring.” 2017. Web. 18 Jul 2019.

Vancouver:

Ding W. Experiment of Mapper Algorithm on High-Dimensional Data in Microseismic Monitoring. [Internet] [Masters thesis]. Texas A&M University; 2017. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/1969.1/166077.

Council of Science Editors:

Ding W. Experiment of Mapper Algorithm on High-Dimensional Data in Microseismic Monitoring. [Masters Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/166077

California State University – Sacramento

23. Khosla, Charu. YouTube data analysis using Hadoop.

Degree: MS, Computer Science, 2016, California State University – Sacramento

URL: http://hdl.handle.net/10211.3/182685

► Analysis of structured data has seen tremendous success in the past. However, analysis of large scale unstructured data in the form of video format remains… (more)

Subjects/Keywords: Hadoop; Data analysis; Hive

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APA (6^th Edition):

Khosla, C. (2016). YouTube data analysis using Hadoop. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.3/182685

Chicago Manual of Style (16^th Edition):

Khosla, Charu. “YouTube data analysis using Hadoop.” 2016. Masters Thesis, California State University – Sacramento. Accessed July 18, 2019. http://hdl.handle.net/10211.3/182685.

MLA Handbook (7^th Edition):

Khosla, Charu. “YouTube data analysis using Hadoop.” 2016. Web. 18 Jul 2019.

Vancouver:

Khosla C. YouTube data analysis using Hadoop. [Internet] [Masters thesis]. California State University – Sacramento; 2016. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/10211.3/182685.

Council of Science Editors:

Khosla C. YouTube data analysis using Hadoop. [Masters Thesis]. California State University – Sacramento; 2016. Available from: http://hdl.handle.net/10211.3/182685

University of Hong Kong

24. Lai, Yiu-ming. Automatic identification of hot topics and user clusters from online discussion forums.

Degree: M. Phil., 2011, University of Hong Kong

URL: Lai, Y. [黎耀明]. (2011). Automatic identification of hot topics and user clusters from online discussion forums. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784995 ; http://dx.doi.org/10.5353/th_b4784995 ; http://hdl.handle.net/10722/174553

►

With the advancement of Internet technology and the changes in the mode of communications, it is found that much first-hand news have been discussed in… (more)

Subjects/Keywords: Cluster analysis.; Data mining.

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APA (6^th Edition):

Lai, Y. (2011). Automatic identification of hot topics and user clusters from online discussion forums. (Masters Thesis). University of Hong Kong. Retrieved from Lai, Y. [黎耀明]. (2011). Automatic identification of hot topics and user clusters from online discussion forums. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784995 ; http://dx.doi.org/10.5353/th_b4784995 ; http://hdl.handle.net/10722/174553

Chicago Manual of Style (16^th Edition):

Lai, Yiu-ming. “Automatic identification of hot topics and user clusters from online discussion forums.” 2011. Masters Thesis, University of Hong Kong. Accessed July 18, 2019. Lai, Y. [黎耀明]. (2011). Automatic identification of hot topics and user clusters from online discussion forums. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784995 ; http://dx.doi.org/10.5353/th_b4784995 ; http://hdl.handle.net/10722/174553.

MLA Handbook (7^th Edition):

Lai, Yiu-ming. “Automatic identification of hot topics and user clusters from online discussion forums.” 2011. Web. 18 Jul 2019.

Vancouver:

Lai Y. Automatic identification of hot topics and user clusters from online discussion forums. [Internet] [Masters thesis]. University of Hong Kong; 2011. [cited 2019 Jul 18]. Available from: Lai, Y. [黎耀明]. (2011). Automatic identification of hot topics and user clusters from online discussion forums. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784995 ; http://dx.doi.org/10.5353/th_b4784995 ; http://hdl.handle.net/10722/174553.

Council of Science Editors:

Lai Y. Automatic identification of hot topics and user clusters from online discussion forums. [Masters Thesis]. University of Hong Kong; 2011. Available from: Lai, Y. [黎耀明]. (2011). Automatic identification of hot topics and user clusters from online discussion forums. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4784995 ; http://dx.doi.org/10.5353/th_b4784995 ; http://hdl.handle.net/10722/174553

University of Hawaii – Manoa

25. Abrishamkar, Alireza. License plate survey for traffic analysis : improving accuracy with correction algorithms.

Degree: 2016, University of Hawaii – Manoa

URL: http://hdl.handle.net/10125/101281

►

M.S. University of Hawaii at Manoa 2012.

Vehicle tracking methods are widely used for a variety of purposes including collection of travel time and duration… (more)

Subjects/Keywords: traffic analysis; data collection

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APA (6^th Edition):

Abrishamkar, A. (2016). License plate survey for traffic analysis : improving accuracy with correction algorithms. (Thesis). University of Hawaii – Manoa. Retrieved from http://hdl.handle.net/10125/101281

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Abrishamkar, Alireza. “License plate survey for traffic analysis : improving accuracy with correction algorithms.” 2016. Thesis, University of Hawaii – Manoa. Accessed July 18, 2019. http://hdl.handle.net/10125/101281.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Abrishamkar, Alireza. “License plate survey for traffic analysis : improving accuracy with correction algorithms.” 2016. Web. 18 Jul 2019.

Vancouver:

Abrishamkar A. License plate survey for traffic analysis : improving accuracy with correction algorithms. [Internet] [Thesis]. University of Hawaii – Manoa; 2016. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/10125/101281.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Abrishamkar A. License plate survey for traffic analysis : improving accuracy with correction algorithms. [Thesis]. University of Hawaii – Manoa; 2016. Available from: http://hdl.handle.net/10125/101281

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Tampere University

26. Lin, Jake. Metagenomic tools and applications toward Type 1 Diabetes .

Degree: 2018, Tampere University

URL: http://tampub.uta.fi/handle/10024/103701

► Laskennallinen mikrobipopulaatioiden havaitseminen tyypin 1 diabeteksen ulosteetäytteillä Ihmisen autoimmuunisairauksien puhkeamiseen vaikuttavat hyvin monenlaiset häiriöt solujen toiminnassa ja autoimmuunisairauksien kirjo on hyvin laaja. Esimerkiksi ykköstyypin diabetes… (more)

▼ Laskennallinen mikrobipopulaatioiden havaitseminen tyypin 1 diabeteksen ulosteetäytteillä Ihmisen autoimmuunisairauksien puhkeamiseen vaikuttavat hyvin monenlaiset häiriöt solujen toiminnassa ja autoimmuunisairauksien kirjo on hyvin laaja. Esimerkiksi ykköstyypin diabetes puhkeaa tyypillisesti lapsuuden aikana. Ykköstyypin diabetekseen sairastuneella henkilöllä immuunijärjestelmä tuhoaa insuliinia tuottavia haimasoluja, ja insuliinin määrä laskee haitallisen alas. Yksityiskohtaista tietoa ykköstyypin diabeteksen puhkeamismekanismeista ei ole, mutta useissa tutkimuksissa sairauden puhkeaminen on yhdistetty erilaisiin mikrobialtistuksiin ja erityisesti tietyn tyyppisiin virusinfektioihin. Nykyaikaisten sekvensointiteknologioiden kehityksen myötä on mahdollista tuottaa laajoja metagenomiikka-aineistoja, joiden avulla saadaan yksityiskohtaista tietoa esimerkiksi vesi-, maaperä- tai ulostenäytteiden geneettisestä materiaalista. Metagenomiikkatutkimuksen avulla on myös mahdollista selvittää erilaisten mikrobiaalisten ja viruspohjaisten altistusten sekä populaatiodynamiikan vaikutusta ihmisen autoimmuunisairauksiin. Tässä työssä metagenomiikkatutkimusta sovelletaan viruspohjaisten ja mikrobiaalisten tekijöiden tutkimiseen ykköstyypin diabeteksen yhteydessä. Erityisesti työssä kehitettiin uusia menetelmiä lasten ja nuorten ulostenäytteistä saatujen metagenomiikka-aineistojen tilastolliseen ja laskennalliseen analyysiin. Väitöskirjatyössä on kehitetty bioinformatiikkatyökalu Vipie, joka mahdollistaa metagenomiikkanäytteiden analysoinnin ja visualisoinnin helppokäyttöisessä web-pohjaisessa laskentaympäristössä. Bioinformatiikkatyökalu Vipie sekä kehitetyt menetelmät perustuvat avoimeen lähdekoodiin ja menetelmät ovat tällä hetkellä aktiivisessa käytössä useissa tutkimusryhmissä. Lisäksi väitöskirjatyön soveltavassa osiossa on raportoitu uusia biologisia löydöksiä ykköstyypin diabetekseen sairastuneiden lasten ja nuorten ulostenäytteiden virus- ja bakteerikannoista. Ykköstyypin diabetesta sairastavien henkilöiden suolistossa todettiin esimerkiksi olevan vahvempia bakteerien välisiä riippuvuuksia kuin terveellä henkilöllä.; Computational detection of environmental microbial populations with assessment in Type 1 Diabetes stool samples Human autoimmune diseases stem from abnormal responses towards normal cells. Relatively common, there are many types of autoimmune diseases. For example, Type 1 diabetes impacting children and teenagers, is caused by gradual immune targeting and subsequent destruction of pancreatic beta cells. The exact reasons, or triggers for the initial targeting of the beta cells are not known but there have been multiple reports citing microbes, particularly certain virus infections and gut bacteria population shifts as possible culprits. The introduction of metagenomics together with advances in next generation sequencing technologies have enabled detection of genetic material directly from the environmental samples such as soil, water and human stool. Prior to metagenomics, most bacterial…

Subjects/Keywords: Metagenomics; Sequencing; Data Analysis; T1D

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Lin, J. (2018). Metagenomic tools and applications toward Type 1 Diabetes . (Doctoral Dissertation). Tampere University. Retrieved from http://tampub.uta.fi/handle/10024/103701

Chicago Manual of Style (16^th Edition):

Lin, Jake. “Metagenomic tools and applications toward Type 1 Diabetes .” 2018. Doctoral Dissertation, Tampere University. Accessed July 18, 2019. http://tampub.uta.fi/handle/10024/103701.

MLA Handbook (7^th Edition):

Lin, Jake. “Metagenomic tools and applications toward Type 1 Diabetes .” 2018. Web. 18 Jul 2019.

Vancouver:

Lin J. Metagenomic tools and applications toward Type 1 Diabetes . [Internet] [Doctoral dissertation]. Tampere University; 2018. [cited 2019 Jul 18]. Available from: http://tampub.uta.fi/handle/10024/103701.

Council of Science Editors:

Lin J. Metagenomic tools and applications toward Type 1 Diabetes . [Doctoral Dissertation]. Tampere University; 2018. Available from: http://tampub.uta.fi/handle/10024/103701

Penn State University

27. Lin, Chun-yu. AN EXPLORATION ON THE USE OF DATA ENVELOPMENT ANALYSIS IN THE PRODUCT DESIGN DOMAIN.

Degree: MS, Industrial Engineering, 2009, Penn State University

URL: https://etda.libraries.psu.edu/catalog/9666

► In engineering design domain, product design process is a major focus. In this process, products are realized by several consecutive stages, and decision making is… (more)

Subjects/Keywords: product design; Data envelopment analysis

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APA (6^th Edition):

Lin, C. (2009). AN EXPLORATION ON THE USE OF DATA ENVELOPMENT ANALYSIS IN THE PRODUCT DESIGN DOMAIN. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9666

Chicago Manual of Style (16^th Edition):

Lin, Chun-yu. “AN EXPLORATION ON THE USE OF DATA ENVELOPMENT ANALYSIS IN THE PRODUCT DESIGN DOMAIN.” 2009. Masters Thesis, Penn State University. Accessed July 18, 2019. https://etda.libraries.psu.edu/catalog/9666.

MLA Handbook (7^th Edition):

Lin, Chun-yu. “AN EXPLORATION ON THE USE OF DATA ENVELOPMENT ANALYSIS IN THE PRODUCT DESIGN DOMAIN.” 2009. Web. 18 Jul 2019.

Vancouver:

Lin C. AN EXPLORATION ON THE USE OF DATA ENVELOPMENT ANALYSIS IN THE PRODUCT DESIGN DOMAIN. [Internet] [Masters thesis]. Penn State University; 2009. [cited 2019 Jul 18]. Available from: https://etda.libraries.psu.edu/catalog/9666.

Council of Science Editors:

Lin C. AN EXPLORATION ON THE USE OF DATA ENVELOPMENT ANALYSIS IN THE PRODUCT DESIGN DOMAIN. [Masters Thesis]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9666

Penn State University

28. Hu, Xiaocheng. DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH.

Degree: MS, Industrial Engineering, 2015, Penn State University

URL: https://etda.libraries.psu.edu/catalog/25731

► Most of the researches on corporate filling mainly focus on qualitative analysis. This thesis used quantitative method-Bayesian Learning Machine in analyzing the information content of… (more)

Subjects/Keywords: data mining; text analysis; Perl

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APA (6^th Edition):

Hu, X. (2015). DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/25731

Chicago Manual of Style (16^th Edition):

Hu, Xiaocheng. “DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH.” 2015. Masters Thesis, Penn State University. Accessed July 18, 2019. https://etda.libraries.psu.edu/catalog/25731.

MLA Handbook (7^th Edition):

Hu, Xiaocheng. “DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH.” 2015. Web. 18 Jul 2019.

Vancouver:

Hu X. DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH. [Internet] [Masters thesis]. Penn State University; 2015. [cited 2019 Jul 18]. Available from: https://etda.libraries.psu.edu/catalog/25731.

Council of Science Editors:

Hu X. DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH. [Masters Thesis]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/25731

Penn State University

29. Narayanan, Savitri. INTRODUCTION TO DATA ENVELOPMENT ANALYSIS AND A CASE STUDY IN HEALTH CARE PROVIDERS.

Degree: MS, Industrial Engineering, 2009, Penn State University

URL: https://etda.libraries.psu.edu/catalog/9053

► Data Envelopment Analysis is a methodology which is used to determine relative efficiencies between decision making units (DMU). It can be used in various industries… (more)

Subjects/Keywords: data envelopment analysis; methods

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APA (6^th Edition):

Narayanan, S. (2009). INTRODUCTION TO DATA ENVELOPMENT ANALYSIS AND A CASE STUDY IN HEALTH CARE PROVIDERS. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9053

Chicago Manual of Style (16^th Edition):

Narayanan, Savitri. “INTRODUCTION TO DATA ENVELOPMENT ANALYSIS AND A CASE STUDY IN HEALTH CARE PROVIDERS.” 2009. Masters Thesis, Penn State University. Accessed July 18, 2019. https://etda.libraries.psu.edu/catalog/9053.

MLA Handbook (7^th Edition):

Narayanan, Savitri. “INTRODUCTION TO DATA ENVELOPMENT ANALYSIS AND A CASE STUDY IN HEALTH CARE PROVIDERS.” 2009. Web. 18 Jul 2019.

Vancouver:

Narayanan S. INTRODUCTION TO DATA ENVELOPMENT ANALYSIS AND A CASE STUDY IN HEALTH CARE PROVIDERS. [Internet] [Masters thesis]. Penn State University; 2009. [cited 2019 Jul 18]. Available from: https://etda.libraries.psu.edu/catalog/9053.

Council of Science Editors:

Narayanan S. INTRODUCTION TO DATA ENVELOPMENT ANALYSIS AND A CASE STUDY IN HEALTH CARE PROVIDERS. [Masters Thesis]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9053

Louisiana State University

30. Jose, Neha Clare. Social Media Network Data Mining and Optimization.

Degree: MS, Computer Sciences, 2016, Louisiana State University

URL: etd-05252016-161222 ; https://digitalcommons.lsu.edu/gradschool_theses/3024

► Many small social aid organizations could benefit from collaborating with other organizations on common causes, but may not have the necessary social relationships. We present… (more)

Subjects/Keywords: Graph Analysis; Centrality; Data Mining

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APA (6^th Edition):

Jose, N. C. (2016). Social Media Network Data Mining and Optimization. (Masters Thesis). Louisiana State University. Retrieved from etd-05252016-161222 ; https://digitalcommons.lsu.edu/gradschool_theses/3024

Chicago Manual of Style (16^th Edition):

Jose, Neha Clare. “Social Media Network Data Mining and Optimization.” 2016. Masters Thesis, Louisiana State University. Accessed July 18, 2019. etd-05252016-161222 ; https://digitalcommons.lsu.edu/gradschool_theses/3024.

MLA Handbook (7^th Edition):

Jose, Neha Clare. “Social Media Network Data Mining and Optimization.” 2016. Web. 18 Jul 2019.

Vancouver:

Jose NC. Social Media Network Data Mining and Optimization. [Internet] [Masters thesis]. Louisiana State University; 2016. [cited 2019 Jul 18]. Available from: etd-05252016-161222 ; https://digitalcommons.lsu.edu/gradschool_theses/3024.

Council of Science Editors:

Jose NC. Social Media Network Data Mining and Optimization. [Masters Thesis]. Louisiana State University; 2016. Available from: etd-05252016-161222 ; https://digitalcommons.lsu.edu/gradschool_theses/3024

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Open Access Theses and Dissertations