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Joint Estimation Of Multiple Graphical Models From High Dimensional Time Series, Huitong Qiu, Fang Han, Han Liu, Brian Caffo 2013 Johns Hopkins University

Joint Estimation Of Multiple Graphical Models From High Dimensional Time Series, Huitong Qiu, Fang Han, Han Liu, Brian Caffo

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this manuscript the problem of jointly estimating multiple graphical models in high dimensions is considered. It is assumed that the data are collected from n subjects, each of which consists of m non-independent observations. The graphical models of subjects vary, but are assumed to change smoothly corresponding to a measure of the closeness between subjects. A kernel based method for jointly estimating all graphical models is proposed. Theoretically, under a double asymptotic framework, where both (m,n) and the dimension d can increase, the explicit rate of convergence in parameter estimation is provided, thus characterizing the strength one can borrow …


A Study On The Correlation Of Bivariate And Trivariate Normal Models, Maria del Pilar Orjuela 2013 Florida International University

A Study On The Correlation Of Bivariate And Trivariate Normal Models, Maria Del Pilar Orjuela

FIU Electronic Theses and Dissertations

Suppose two or more variables are jointly normally distributed. If there is a common relationship between these variables it would be very important to quantify this relationship by a parameter called the correlation coefficient which measures its strength, and the use of it can develop an equation for predicting, and ultimately draw testable conclusion about the parent population.

This research focused on the correlation coefficient ρ for the bivariate and trivariate normal distribution when equal variances and equal covariances are considered. Particularly, we derived the maximum Likelihood Estimators (MLE) of the distribution parameters assuming all of them are unknown, and …


Sparse Median Graphs Estimation In A High Dimensional Semiparametric Model, Fang Han, Han Liu, Brian Caffo 2013 Johns Hopkins University

Sparse Median Graphs Estimation In A High Dimensional Semiparametric Model, Fang Han, Han Liu, Brian Caffo

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this manuscript a unified framework for conducting inference on complex aggregated data in high dimensional settings is proposed. The data are assumed to be a collection of multiple non-Gaussian realizations with underlying undirected graphical structures. Utilizing the concept of median graphs in summarizing the commonality across these graphical structures, a novel semiparametric approach to modeling such complex aggregated data is provided along with robust estimation of the median graph, which is assumed to be sparse. The estimator is proved to be consistent in graph recovery and an upper bound on the rate of convergence is given. Experiments on both …


Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito 2013 Carnegie Mellon University

Towards Real-Time, On-Board, Hardware-Supported Sensor And Software Health Management For Unmanned Aerial Systems, Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Ole J. Mengshoel, Timmy Mbaya, Corey Ippolito

Ole J Mengshoel

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. In this paper, we design a real-time, on-board system health management (SHM) capability to continuously monitor sensors, software, and hardware components for detection and diagnosis of failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and/or software signals; (2) signal analysis, preprocessing, and …


Perceived Attitudes And Staff Roles Of Community Based Outpatient Clinics In Disaster Management, Pauline Antoinette Hodge-Hilton 2013 Loma Linda University

Perceived Attitudes And Staff Roles Of Community Based Outpatient Clinics In Disaster Management, Pauline Antoinette Hodge-Hilton

Loma Linda University Electronic Theses, Dissertations & Projects

Objective: Natural and manmade disasters have claimed the lives of thousands of individuals in the US and caused billions of dollars in property damage. First responders carry the responsibility of disaster management, leaving other health care professionals such as medical clinic staff underutilized to support the clinic staff. We explored how medical and support staff in Community-based Outpatient VHA Clinics (CBOC) perceive their roles in disaster response, their attitudes about clinic readiness and continuity of care during disasters, and their ability to function in a post disaster environment.

Methods: A mixed method study was conducted to answer questions related to …


Optimizing Parallel Belief Propagation In Junction Trees Using Regression, Lu Zheng, Ole J. Mengshoel 2013 Carnegie Mellon University

Optimizing Parallel Belief Propagation In Junction Trees Using Regression, Lu Zheng, Ole J. Mengshoel

Ole J Mengshoel

The junction tree approach, with applications in artificial intelligence, computer vision, machine learning, and statistics, is often used for computing posterior distributions in probabilistic graphical models. One of the key challenges associated with junction trees is computational, and several parallel computing technologies - including many-core processors - have been investigated to meet this challenge. Many-core processors (including GPUs) are now programmable, unfortunately their complexities make it hard to manually tune their parameters in order to optimize software performance. In this paper, we investigate a machine learning approach to minimize the execution time of parallel junction tree algorithms implemented on a …


Exploring Multiple Dimensions Of Parallelism In Junction Tree Message Passing, Lu Zheng, Ole J. Mengshoel 2013 Carnegie Mellon University

Exploring Multiple Dimensions Of Parallelism In Junction Tree Message Passing, Lu Zheng, Ole J. Mengshoel

Ole J Mengshoel

Belief propagation over junction trees is known to be computationally challenging in the general case. One way of addressing this computational challenge is to use node-level parallel computing, and parallelize the computation associated with each separator potential table cell. However, this approach is not efficient for junction trees that mainly contain small separators. In this paper, we analyze this problem, and address it by studying a new dimension of node-level parallelism, namely arithmetic parallelism. In addition, on the graph level, we use a clique merging technique to further adapt junction trees to parallel computing platforms. We apply our parallel approach …


Latent Topic Analysis For Predicting Group Purchasing Behavior On The Social Web, Feng-Tso Sun, Martin Griss, Ole J. Mengshoel, Yi-Ting Yeh 2013 Carnegie Mellon University

Latent Topic Analysis For Predicting Group Purchasing Behavior On The Social Web, Feng-Tso Sun, Martin Griss, Ole J. Mengshoel, Yi-Ting Yeh

Ole J Mengshoel

Group-deal websites, where customers purchase products or services in groups, are an interesting phenomenon on the Web. Each purchase is kicked o#11;ff by a group initiator, and other customers can join in. Customers form communities with people with similar interests and preferences (as in a social network), and this drives bulk purchasing (similar to online stores, but in larger quantities per order, thus customers get a better deal). In this work, we aim to better understand what factors in influence customers' purchasing behavior for such social group-deal websites. We propose two probabilistic graphical models, i.e., a product-centric inference model (PCIM) …


Mobile Computing: Challenges And Opportunities For Autonomy And Feedback, Ole J. Mengshoel, Bob Iannucci, Abe Ishihara 2013 Carnegie Mellon University

Mobile Computing: Challenges And Opportunities For Autonomy And Feedback, Ole J. Mengshoel, Bob Iannucci, Abe Ishihara

Ole J Mengshoel

Mobile devices have evolved to become computing platforms more similar to desktops and workstations than the cell phones and handsets of yesteryear. Unfortunately, today’s mobile infrastructures are mirrors of the wired past. Devices, apps, and networks impact one another, but a systematic approach for allowing them to cooperate is currently missing. We propose an approach that seeks to open key interfaces and to apply feedback and autonomic computing to improve both user experience and mobile system dynamics.


Software Health Management With Bayesian Networks, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, Adnan Darwiche 2013 Carnegie Mellon University

Software Health Management With Bayesian Networks, Johann Schumann, Timmy Mbaya, Ole J. Mengshoel, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, Adnan Darwiche

Ole J Mengshoel

Software Health Management (SWHM) is an emerging field which addresses the critical need to detect, diagnose, predict, and mitigate adverse events due to software faults and failures. These faults could arise for numerous reasons including coding errors, unanticipated faults or failures in hardware, or problematic interactions with the external environment. This paper demonstrates a novel approach to software health management based on a rigorous Bayesian formulation that monitors the behavior of software and operating system, performs probabilistic diagnosis, and provides information about the most likely root causes of a failure or software problem. Translation of the Bayesian network model into …


Automating Large-Scale Simulation Calibration To Real-World Sensor Data, Richard Everett Edwards 2013 University of Tennessee, Knoxville

Automating Large-Scale Simulation Calibration To Real-World Sensor Data, Richard Everett Edwards

Doctoral Dissertations

Many key decisions and design policies are made using sophisticated computer simulations. However, these sophisticated computer simulations have several major problems. The two main issues are 1) gaps between the simulation model and the actual structure, and 2) limitations of the modeling engine's capabilities. This dissertation's goal is to address these simulation deficiencies by presenting a general automated process for tuning simulation inputs such that simulation output matches real world measured data. The automated process involves the following key components -- 1) Identify a model that accurately estimates the real world simulation calibration target from measured sensor data; 2) Identify …


Integrative Biomarker Identification And Classification Using High Throughput Assays, Pan Tong 2013 The University of Texas Graduate School of Biomedical Sciences at Houston

Integrative Biomarker Identification And Classification Using High Throughput Assays, Pan Tong

Dissertations & Theses (Open Access)

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays …


A Bayesian Regression Tree Approach To Identify The Effect Of Nanoparticles Properties On Toxicity Profiles, Cecile Low-Kam, Haiyuan Zhang, Zhaoxia Ji, Tian Xia, Jeffrey I. Zinc, Andre Nel, Donatello Telesca 2013 UCLA Biostatistics - CNSI

A Bayesian Regression Tree Approach To Identify The Effect Of Nanoparticles Properties On Toxicity Profiles, Cecile Low-Kam, Haiyuan Zhang, Zhaoxia Ji, Tian Xia, Jeffrey I. Zinc, Andre Nel, Donatello Telesca

COBRA Preprint Series

We introduce a Bayesian multiple regression tree model to characterize relationships between physico-chemical properties of nanoparticles and their in-vitro toxicity over multiple doses and times of exposure. Unlike conventional models that rely on data summaries, our model solves the low sample size issue and avoids arbitrary loss of information by combining all measurements from a general exposure experiment across doses, times of exposure, and replicates. The proposed technique integrates Bayesian trees for modeling threshold effects and interactions, and penalized B-splines for dose and time-response surfaces smoothing. The resulting posterior distribution is sampled via a Markov Chain Monte Carlo algorithm. This …


“Seeing” The Elephant: Assessing The Impact Of Library-Composition Program Collaboration On First-Year Student Learning, Erin E. Rinto 2013 University of Nevada, Las Vegas

“Seeing” The Elephant: Assessing The Impact Of Library-Composition Program Collaboration On First-Year Student Learning, Erin E. Rinto

Library Faculty Presentations

Though university libraries and composition programs have historically collaborative relationships, these partnerships can take a variety of formats, including single course period library sessions, teaching-the-teachers, and librarian-driven assignment models. A hybrid of these collaborative approaches was implemented Fall 2012 at UNLV in an effort to provide first-year composition students with a more systematic information literacy experience in the required ENG 102 course. A two-pronged assessment method was used to evaluate the impact of the collaboration for both first-year student learning as well as to implement programmatic change.


Global Quantitative Assessment Of The Colorectal Polyp Burden In Familial Adenomatous Polyposis Using A Web-Based Tool, Patrick M. Lynch, Jeffrey S. Morris, William A. Ross, Miguel A. Rodriguez-Bigas, Juan Posadas, Rossa Khalaf, Diane M. Weber, Valerie O. Sepeda, Bernard Levin, Imad Shureiqi 2013 The University of Texas M.D. Anderson Cancer Center

Global Quantitative Assessment Of The Colorectal Polyp Burden In Familial Adenomatous Polyposis Using A Web-Based Tool, Patrick M. Lynch, Jeffrey S. Morris, William A. Ross, Miguel A. Rodriguez-Bigas, Juan Posadas, Rossa Khalaf, Diane M. Weber, Valerie O. Sepeda, Bernard Levin, Imad Shureiqi

Jeffrey S. Morris

Background: Accurate measures of the total polyp burden in familial adenomatous polyposis (FAP) are lacking. Current assessment tools include polyp quantitation in limited-field photographs and qualitative total colorectal polyp burden by video.

Objective: To develop global quantitative tools of the FAP colorectal adenoma burden.

Design: A single-arm, phase II trial.

Patients: Twenty-seven patients with FAP.

Intervention: Treatment with celecoxib for 6 months, with before-treatment and after-treatment videos posted to an intranet with an interactive site for scoring.

Main Outcome Measurements: Global adenoma counts and sizes (grouped into categories: less than 2 mm, 2-4 mm, and greater than 4 mm) were …


Epistemology And Synthesis: Instrumental Neutron Activation Analysis And The Caddo Tradition, Robert Z. Selden Jr. 2013 Heritage Research Center, Stephen F. Austin State University

Epistemology And Synthesis: Instrumental Neutron Activation Analysis And The Caddo Tradition, Robert Z. Selden Jr.

CRHR: Archaeology

The statistical groupings illustrated herein represent the current iteration of Caddo INAA compositional groups based upon the chemical composition of archaeologically-recovered ceramics. For some time, a number of Caddo archaeologists have thought these results to be lacking. This poster symbolizes the first step toward a new interpretation of chemical composition groups, and the initial instancce within which GIS has been employed as an analytical tool.


Consilience: Radiocarbon, Instrumental Neutron Activation Analysis, And Litigation In The Ancestral Caddo Region, Robert Z. Selden Jr. 2013 Heritage Research Center, Stephen F. Austin State University

Consilience: Radiocarbon, Instrumental Neutron Activation Analysis, And Litigation In The Ancestral Caddo Region, Robert Z. Selden Jr.

CRHR: Archaeology

Through the creation and analysis of databases for radiocarbon, instrumental neutron activation analysis (INAA), and law, macro-level trends are exposed that form the framework of a broader research program aimed at advancing ideas of craft specialization and archaeological theory in the ancestral Caddo region of Southwest Arkansas, Northwest Louisiana, Northeast Texas, and Southeast Oklahoma. The findings of this investigation illustrate the research potential that remains buried within the context of cultural resource management (CRM) reports and legal databases (Westlaw and LexisNexis) that is awaiting consumption within regional research designs aimed at exploring the nuances and trends that appear through synthetic …


Sas Macro: Kappa Statistic For Clustered Matched-Pair Data, Zhao Yang 2013 Quintiles Inc

Sas Macro: Kappa Statistic For Clustered Matched-Pair Data, Zhao Yang

Zhao (Tony) Yang, Ph.D.

The SAS macro was developed to calculate the kappa statistic for the clustered matched-pair data.


Multiscale Analysis Of Factors That Affect The Distribution Of Sharks Throughout The Northern Gulf Of Mexico, J. Marcus Drymon, Laure Carassou, Sean P. Powers, Mark Grace, John Dindo, Brian Dzwonkowski 2013 University of South Alabama

Multiscale Analysis Of Factors That Affect The Distribution Of Sharks Throughout The Northern Gulf Of Mexico, J. Marcus Drymon, Laure Carassou, Sean P. Powers, Mark Grace, John Dindo, Brian Dzwonkowski

University Faculty and Staff Publications

Identification of the spatial scale at which marine communities are organized is critical to proper management, yet this is particularly difficult to determine for highly migratory species like sharks. We used shark catch data collected during 2006–09 from fishery- independent bottom-longline surveys, as well as biotic and abiotic explanatory data to identify the factors that affect the distribution of coastal sharks at 2 spatial scales in the northern Gulf of Mexico. Centered principal component analyses (PCAs) were used to visualize the patterns that characterize shark distributions at small (Alabama and Mississippi coast) and large (northern Gulf of Mexico) spatial scales. …


Mapping And Decomposing Scale-Dependent Soil Moisture Variability Within An Inner Bluegrass Landscape, Carla Landrum 2013 University of Kentucky

Mapping And Decomposing Scale-Dependent Soil Moisture Variability Within An Inner Bluegrass Landscape, Carla Landrum

Theses and Dissertations--Plant and Soil Sciences

There is a shared desire among public and private sectors to make more reliable predictions, accurate mapping, and appropriate scaling of soil moisture and associated parameters across landscapes. A discrepancy often exists between the scale at which soil hydrologic properties are measured and the scale at which they are modeled for management purposes. Moreover, little is known about the relative importance of hydrologic modeling parameters as soil moisture fluctuates with time. More research is needed to establish which observation scales in space and time are optimal for managing soil moisture variation over large spatial extents and how these scales are …


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