Digital Commons Network^™

Learning Mixed Sparse Factor Networks Structure: A Latent Variable Approach, Ruofeng Wen

Stony Brook Theses and Dissertations Collection, 2006-2020 (closed to submissions)

Learning and visualizing complex causal or dependence structure among various variables is of great interest in applied science. Probabilistic Graphical Models, including Bayesian Networks and Markov Random Field, are well-developed tools for such problems, particularly when variables are either all categorical or continuous. In the first and major part of this text, we proposed a novel graphical structure learning approach, the MIxed Sparse FActor Network (MISFAN), to accommodate categorical and continuous variables seamlessly in one sparse Probit latent factor model. Such a network bridges the gap among latent variable models, traditional multivariate analysis and graphical models, can visualize the underlying …

Identification Of Differential Gene Pathways In Microarray Data, Qiao Zhang

Stony Brook Theses and Dissertations Collection, 2006-2020 (closed to submissions)

A gene pathway typically refers to a group of genes and small molecules that work together to control one or more cell functions. In systems biology, pathway analysis is of paramount biological importance, and recent studies revealed that malfunction of gene pathways could induce disease manifestations, such as cancer. Usually, a gene pathway consists of two components: the upstream factors, which are signaling molecules transmitting stimulus from cell surface to nucleus, and the downstream factors, which respond to cell signaling through changes of their expression levels. Although several methods have been reported for analysis of gene pathways, almost all of …

On Using Risk-Benefit Analysis To Assess And Manage Controversial Research, Daniel Rozell

Stony Brook Theses and Dissertations Collection, 2006-2020 (closed to submissions)

Science research in the twenty-first century increasingly results in powerful and rapidly disseminated technologies that raise concerns over technological risk and public safety. A common recommendation for assessing and managing controversial research is to perform a quantitative risk-benefit analysis (RBA) in order to help determine an appropriate course of action. However, these recommendations lack guidelines on how to perform such an assessment. This dissertation lays out a detailed argument why a quantitative RBA should not be used as a basis for making complex policy decisions. Rather, RBA should be regarded as a tool for exploring the impacts of technology on …

Fused Convolutional Neural Network Accelerators, Manoj Alwani

Stony Brook Theses and Dissertations Collection, 2006-2020 (closed to submissions)

Deep convolutional neural networks (CNNs) are rapidly becoming the domi-nant approach to computer vision and a major component of many other pervasivemachine learning tasks, such as speech recognition, natural language processing,and fraud detection. As research and development of CNNs progresses, the size ofthe networks grows, leading to large increases in the computation and bandwidthrequired to evaluate these networks. Typical CNNs in use today already exceedthe capabilities of general-purpose CPUs, resulting in rapid adoption and activeresearch of CNN hardware accelerators such as GPUs, FPGAs, and ASICs. Inthis work, we develop a novel CNN accelerator architecture and design method-ology that breaks away …

Review: A Short Introduction To De Branges-Rovnyak Spaces, Stephan Ramon Garcia

Pomona Faculty Publications and Research

No abstract provided.

Eeg-Controlling Robotic Car And Alphabetic Display By Support Vector Machine For Aiding Amyotrophic Lateral Sclerosis Patients, Quang M. Le

Electrical Engineering Undergraduate Honors Theses

This thesis presents the design and experiment of a system that can detect the human thinking such as driving directions and letters using the brainwave signals known as electroencephalogram (EEG) and a machine learning algorithm called support vector machine (SVM). This research is motivated by amyotrophic lateral sclerosis (ALS) disease which makes patients seriously lose mobility and speaking capabilities. The developed system in this thesis has three main steps. First, wearing EPOC headset from Emotiv Company, a user can record the EEG signals when he/she is thinking a direction or a letter, and also save the data in a personal …

Umphlett Qci 2015, Natalie A. Umphlett

High Plains Regional Climate Center: Staff Publications

Highlights for the Basin

Temperature and Precipitation Anomalies

Late Hard Freeze

Late Freezes Extended Growing Season

Warm Fall Delays Bird Migrations

Monitoring Water Resources Across the Basin

3-Month Precipitation and Temperature Outlooks

Estimating The Water Quality Condition Of River And Lake Water In The Midwestern United States From Its Spectral Characteristics, Jing Tan

Open Access Dissertations

This study focuses on developing/calibrating remote sensing algorithms for water quality retrieval in Midwestern rivers and lakes. In the first part of this study, the spectral measurements collected using a hand-held spectrometer as well as water quality observations for the Wabash River and its tributary the Tippecanoe River in Indiana were used to develop empirical models for the retrieval of chlorophyll (chl) and total suspended solids (TSS). A method for removing sky and sun glint from field spectra for turbid inland waters was developed and tested. Empirical models were then developed using a subset of the field measurements with the …

Ole Miss Engineer 2015-2016

Ole Miss Engineer

No abstract provided.

Improved Bias Correction Techniques For Hydrological Simulations Of Climate Change, David W. Pierce, Daniel R. Cayan, Edwin P. Maurer, John T. Abatzoglou, Katherine C. Hegewisch

Civil, Environmental and Sustainable Engineering

Global climate model (GCM) output typically needs to be bias corrected before it can be used for climate change impact studies. Three existing bias correction methods, and a new one developed here, are applied to daily maximum temperature and precipitation from 21 GCMs to investigate how different methods alter the climate change signal of the GCM. The quantile mapping (QM) and cumulative distribution function transform (CDF-t) bias correction methods can significantly alter the GCM’s mean climate change signal, with differences of up to 2°C and 30% points for monthly mean temperature and precipitation, respectively. Equidistant quantile matching (EDCDFm) bias correction …

Iowa Waste Reduction Center Newsletter, December 2015, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Contents:

--- Happy Holidays
--- 2016-2017 Recordkeeping Compliance Calendar for Dry Cleaners
--- 2016-2017 Compliance Calendar/Logbook for Bulk Gasoline Plants
--- Food Waste Reduction Assistance Available
--- Industry News

Sports Broadcasting News Analysis [Career Paper], Jefferson Sanders

Undergraduate Research Award

No abstract provided.

How To Start A Movement: Ted Talk Annotated Resource List, Daulton Cowan

Undergraduate Research Award

No abstract provided.

Prospective Testing And Redesign Of A Temporal Biomarker Based Risk Model For Patients With Septic Shock: Implications For Septic Shock Biology, Hector R. Wong, Natalie R. Cvijanovich, Nick Anas, Geoffrey L. Allen, Neal J. Thomas, Robert J. Freishtat, +17 Additional Authors

Pediatrics Faculty Publications

The temporal version of the pediatric sepsis biomarker risk model (tPERSEVERE) estimates the risk of a complicated course in children with septic shock based on biomarker changes from days 1 to 3 of septic shock. We validated tPERSEVERE performance in a prospective cohort, with an a priori plan to redesign tPERSEVERE if it did not perform well. Biomarkers were measured in the validation cohort (n = 168) and study subjects were classified according to tPERSEVERE. To redesign tPERSEVERE, the validation cohort and the original derivation cohort (n = 299) were combined and randomly allocated to training (n = 374) and …

Battle Bot Ai – Patriot Bot, James Johnston

Computer Engineering

An entry in the the 'Battle Block AI' competition hosted by 'The AI Games'.

Large-Eddy Simulation Of The Transient And Near-Equilibrium Behavior Of Precipitating Shallow Convection, Axel Seifert, Thijs Heus, Robert Pincus, Bjorn Stevens

Physics Faculty Publications

Large-eddy simulation is used to study the sensitivity of trade wind cumulus clouds to perturbations in cloud droplet number concentrations. We find that the trade wind cumulus system approaches a radiative-convective equilibrium state, modified by net warming and drying from imposed large-scale advective forcing. The system requires several days to reach equilibrium when cooling rates are specified but much less time, and with less sensitivity to cloud droplet number density, when radiation depends realistically on the vertical distribution of water vapor. The transient behavior and the properties of the near-equilibrium cloud field depend on the microphysical state and therefore on …

How To Predict Nesting Sites?, Stephen Escarzaga, Craig Tweedie, Vladik Kreinovich

Departmental Technical Reports (CS)

How to predict nesting sites? Usually, all we know is the past nesting sites, and the fact that the birds select a site which is optimal for them (in some reasonable sense), but we do not know the exact objective function describing this optimality. In this paper, we propose a way to make predictions in such a situation.

Why It Is Healthy To Regularly Challenge Authority: An Algorithmic Explanation, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

One way to make group decisions is to select the best decision maker(s) in the group as the authority, and to follow his or her decisions. At first glance, it seems that if the selected authority is indeed the best decision maker, it is beneficial for everyone to obey his or her authority. However, history shows that in many cases, challenges to the authority (even to the authority of the best decision maker) were beneficial to the group. In this paper, we provide an algorithmic explanation for this phenomenon. The main idea behind this explanation is that most practical general …

Geosciences Newsletter - 2015, Department Of Geosciences

Geological and Environmental Sciences News

Vol. 8, No. 1

The department of Geosciences 50th anniversary issue.

Libsbolj 2.0: A Java Library To Support Sbol 2.0, Zhen Zhang, Tramy Nguyen, Nicholas Roehner, Goksel Misirli, Matthew Pocock, Ernst Oberortner, Meher Samineni, Zach Zundel, Jacob Beal, Kevin Clancy, Anil Wipat, Chris J. Myers

Electrical and Computer Engineering Faculty Publications

The Synthetic Biology Open Language (SBOL) is an emerging data standard for representing synthetic biology designs. The goal of SBOL is to improve the reproducibility of these designs and their electronic exchange between researchers and/or genetic design

Using Protoplanetary Disks To Weigh The Youngest Stars And Constrain The Earliest Stages Of Stellar Evolution, I. Czekala, S. Andrews, Eric L. N. Jensen, K. Stassun, D. W. Latham, D. Wilner, G. Torres

Physics & Astronomy Faculty Works

Mass is the fundamental property that determines the fate of a star. In particular, the masses of young stars are of great relevance to many astrophysical problems, including star and planet formation. We have developed a novel approach that combines spatially resolved sub-millimeter spectral line imaging and optical/near-infrared high resolution spectroscopy to derive the fundamental properties of a young star: mass, temperature, and radius. By applying our technique to a sample of pre-main sequence stars, we are mapping out a dynamically-calibrated Hertzsprung-Russell diagram for the express purpose of evaluating pre-main sequence evolutionary models. Looking forward, ALMA is poised to deliver …

Factors Impacting Transgender Patients’ Discomfort With Their Family Physicians: A Respondent-Driven Sampling Survey, Greta R. Bauer, Xuchen Zong, Ayden I. Scheim, Rebecca Hammond, Amardeep Thind

Epidemiology and Biostatistics Publications

BACKGROUND: Representing approximately 0.5% of the population, transgender (trans) persons in Canada depend on family physicians for both general and transition-related care. However, physicians receive little to no training on this patient population, and trans patients are often profoundly uncomfortable and may avoid health care. This study examined factors associated with patient discomfort discussing trans health issues with a family physician in Ontario, Canada.

METHODS: 433 trans people age 16 and over were surveyed using respondent-driven sampling for the Trans PULSE Project; 356 had a family physician. Weighted logistic regression models were fit to produce prevalence risk ratios (PRRs) via …

Energy Forecasting For Event Venues: Big Data And Prediction Accuracy, Katarina Grolinger, Alexandra L'Heureux, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Advances in sensor technologies and the proliferation of smart meters have resulted in an explosion of energy-related data sets. These Big Data have created opportunities for development of new energy services and a promise of better energy management and conservation. Sensor-based energy forecasting has been researched in the context of office buildings, schools, and residential buildings. This paper investigates sensor-based forecasting in the context of event-organizing venues, which present an especially difficult scenario due to large variations in consumption caused by the hosted events. Moreover, the significance of the data set size, specifically the impact of temporal granularity, on energy …

Students' Perspectives Of Mobile Learning Platforms: An Empirical Study, Muasaad Alrasheedi, Luiz Fernando Capretz, Arif Raza

Electrical and Computer Engineering Publications

Educational institutions are becoming involved in adopting technological innovations like th e mobile learning (m-Learning) platform for education. Mobile technologies are the next frontier as infrast ructure for m-Learning because they can provide high-quality learning capab ilities to satisfy the rising student demand for mobility and flexibility due to the ubiquitous nature of mobile tec hnology (smartphones) and the va st opportunities it offers, there ar e indications that smartphones could lead the next generation for learning platforms. Researchers have examin ed the idea from several angles and produced a copious amount of literature devoted to explaining the interrelationships of …

Management's Perspective On Critical Success Factors Affecting Mobile Learning In Higher Education Institutions - An Empirical Study, Muasaad Alrasheedi, Luiz Fernando Capretz, Arif Raza

Electrical and Computer Engineering Publications

Mobile learning (m-Learning) is considered to be one of the fastest growing learning platforms. The immense interest in m-Learning is attributed to the incredible rate of growth of mobile technology and its proliferation into every aspect of modern life. Despite this, m-Learning has not experienced a similar adoption rate in the education sector, chiefly higher education. Researchers have attempted to explain this anomaly by conducting several studies in the area. However, mostly the research in m-Learning is examined from the perspective of the students and educators. In this research, it is contended that there is a third important stakeholder group …

The Role Of Information And Reflection In Reducing The Bias Blind Spot: A Cross-Cultural Study, Wejdan Shukri Felmban

Dissertations

The current study examined whether two types of intervention reduced the "bias blind spot" (i.e., perceptions of others being more biased than one’s self) and whether the bias blind spot was related to culture, reasoning performance, and motivation. The design was a 2 (information: reading or not reading about the bias blind spot) x 2 (reflection reflecting on the effects of biases on other or non-relevant reflection) x 2 (priming: reasoning tasks completed before or after the interventions). Students (N = 193) from Western and Middle Eastern cultures participated online or in a class. In each condition, participants responded to …

Positive Influence Dominating Set Generation In Social Networks, Akshaye Dhawan, Matthew Rink

Mathematics, Computer Science & Statistics Faculty Publications

Current algorithms in the Positive Influence Dominating Set (PIDS) problem domain are focused on a specific type of PIDS, the Total Positive Influence Dominating Set (TPIDS). We have developed an algorithm specifically targeted towards the non-total type of PIDS. In addition to our new algorithm, we adapted two existing TPIDS algorithms to generate PIDS. We ran simulations for all three algorithms, and our new algorithm consistently generates smaller PIDS than both existing algorithms, with our algorithm generating PIDS approximately 5% smaller than the better of the two existing algorithms.

Randomized Algorithms For Approximating A Connected Dominating Set In Wireless Sensor Networks, Akshaye Dhawan, Michelle Tanco, Aaron Yeiser

Mathematics, Computer Science & Statistics Faculty Publications

A Connected Dominating Set (CDS) of a graph representing a Wireless Sensor Network can be used as a virtual backbone for routing through the network. Since the sensors in the network are constrained by limited battery life, we desire a minimal CDS for the network, a known NP-hard problem. In this paper we present three randomized algorithms for constructing a CDS. We evaluate our algorithms using simulations and compare them to the two-hop K2 algorithm and two other greedy algorithms from the literature. After pruning, the randomized algorithms construct a CDS that are generally equivalent in size to those constructed …

Contact Resistance To Srruo3 And La0.67Sr0.33Mno3 Epitaxial Films, Mohammad Abuwasib, Hyungwoo Lee, Alexei Gruverman, Chang-Beom Eom, Uttam Singisetti

Alexei Gruverman Publications

Contact resistance to the metallic oxide electrodes, SrRuO₃ (SRO) and La_0.67Sr_0.33MnO₃ (LSMO), is an important parameter that affects the ferroelectric tunnel junction (FTJ) device performance. We have systematically studied the contact resistance between metallic oxide electrodes (SRO, LSMO) and contact metal overlayers (Ti, Pt) after exposure to various processing environments. Specific contact resistivity (ρ_c) for Ti and Pt contact metals and the sheet resistance (R_sh) of the metallic oxides are measured after exposure to different reactive ion plasma process steps. Sheet resistance degradation was observed for both SRO and …

Comparative Aquatic Toxicity Of A Commercial Naphthenic Acid And Processes For Mitigating Risks, Ciera Kinley

All Theses

Comparative toxicity data can inform predictions of relative risk, and can be used to implement strategies for altering exposures to mitigate risk. Naphthenic acids (NAs) are a complex group of carboxylic acids that naturally occur in petroleum sources and energy-derived process waters (e.g. refinery effluents and oil sands process affected waters). These compounds are relatively persistent in water and can be a source of toxicity to aquatic organisms. In the first experiment of this thesis, responses of sentinel aquatic organisms to 7-d exposures of commercial (Fluka) NAs were measured (in terms of acute toxicity) to discern relative sensitivities. In terms …