Physical Sciences and Mathematics Commons^™

Coastal Resilience At The Nexus Of Food, Energy, And Water: An Interdisciplinary Perspective For Resilience Planning, Kristin Raub

Graduate College Dissertations and Theses

Global climate change poses increased threats to coastal communities. The resilience of coastal communities relies on the protection and continued availability of essential services such as food, energy, and water (FEW) systems. However, the intersection of FEW nexus research and coastal resilience planning has not been well explored. This dissertation seeks to further the goal of operationalizing resilience planning by examining the usefulness of resilience tools and toolkits that have been developed in recent years and exploring how the FEW nexus approach has been applied to coastal resilience planning in both academic and grey literature. The first chapter provides the …

Modeling Moose Habitat Use And Fitness Consequences Of Habitat Selection In Vermont, Usa, Joshua Alexander Blouin

Graduate College Dissertations and Theses

The moose (Alces alces) population has been declining across the northeastern US largely due to the impacts of winter ticks (Dermacentor albipictus). In epizootic years, an individual moose can host a staggering number of ticks (> 60,000), affecting both survival and reproduction. Habitat management may be used to improve the status of the moose population and health of individuals, but this requires knowledge of key habitat types used by moose and their spatial distribution. We investigated 1) habitat use by moose and 2) the fitness consequences of habitat selection during two critical winter tick life stages in northeastern Vermont. To …

Small-Scale Roll Coating As A Transitional Stage In The Scaling Of Organic Electronic Device Fabrication Techniques, Jared Benson

Graduate College Dissertations and Theses

Incredible achievements have been made in the field of organic electronics in small-scale laboratory settings. A topic of increasing importance is the realization of the potential for these technologies to be applied in an industrial setting. This is a deceptively challenging process, considering that many of the procedures used to attain exceptional results in a laboratory setting are not viable for translation to larger scale fabrication efforts. Moreover, upscaling fabrication is further complicated by the enormous barrier of entry due to the expensive equipment required to fabricate organic electronics at larger scale as well as the exponentially greater quantity of …

Assessing The Impact Of Changes In Acid Deposition On Dissolved Organic Carbon Mobilization From Two Forested Headwater Catchments: A Combined Lab And Field Study, Caitlin Bristol

Graduate College Dissertations and Theses

Over the past few decades, dissolved organic carbon (DOC) concentrations in headwater streams in the northern hemisphere changed. Because these changes in DOC coincided with decreased acid deposition, a potential link was proposed early on. More recent research indicated that catchment attributes, especially soil characteristics and the presence of Ca-bearing minerals, play an important role in modulating DOC release from watersheds, but further research is necessary.

To investigate the role of catchment characteristics on DOC dynamics, I use several watersheds in the Northeastern United States with similar attributes and well-constrained differences. Sleepers River Research Watershed (SRRW) has naturally occurring Calcium …

Lcms-Based Analysis Explains The Basis Of Oxidative Resistance In Selenium-Containing Thioredoxin Reductase, Daniel Haupt

Graduate College Dissertations and Theses

Selenocysteine (Sec) is referred to as the 21st proteogenic amino acid and is found in place of the redox-sensitive amino acid cysteine (Cys) in a small number of proteins. Sec and Cys carry out similar chemistry and are structural isomers save for a single atom difference; the former contains selenium (Se), while the latter contains sulfur (S) in the identical position. Sec poses a high bioenergetic cost for its synthesis and subsequent incorporation into protein not shared by Cys. Since Sec’s discovery in 1976, scientists have debated why certain proteins express Sec while others express Cys. In recent years, it …

Distinguishing Different Styles Of Transpressional Deformation At An Obliquely Convergent Plate Margin, Fiordland, New Zealand, Emily Sarah Lincoln

Graduate College Dissertations and Theses

Fiordland, New Zealand provides one of the best-known and deepest (to 65 km) exposures of an Early Cretaceous magmatic arc root known to geologists. These exposures allow for us to study tectonic deformational processes at varying crustal depths, including the role of pre-existing structures on later reactivation. The well-preserved Grebe shear zone (GSZ) marks the boundary between major basement terranes in southern Fiordland and has undergone multiple episodes of deformation during the Cretaceous and Cenozoic time periods. The primary focus of this study is to recognize and characterize the differing phases of deformation that occurred along this shear zone. To …

An Effective And Efficient Graph Representation Learning Approach For Big Graphs, Edoardo Serra, Mikel Joaristi, Alfredo Cuzzocrea, Selim Soufargi, Carson K. Leung

Computer Science Faculty Publications and Presentations

In the Big Data era, large graph datasets are becoming increasingly popular due to their capability to integrate and interconnect large sources of data in many fields, e.g., social media, biology, communication networks, etc. Graph representation learning is a flexible tool that automatically extracts features from a graph node. These features can be directly used for machine learning tasks. Graph representation learning approaches producing features preserving the structural information of the graphs are still an open problem, especially in the context of large-scale graphs. In this paper, we propose a new fast and scalable structural representation learning approach called SparseStruct. …

Enriching Language Models With Visually-Grounded Word Vectors And The Lancaster Sensorimotor Norms, Casey Kennington

Computer Science Faculty Publications and Presentations

Language models are trained only on text despite the fact that humans learn their first language in a highly interactive and multimodal environment where the first set of learned words are largely concrete, denoting physical entities and embodied states. To enrich language models with some of this missing experience, we leverage two sources of information: (1) the Lancaster Sensorimotor norms, which provide ratings (means and standard deviations) for over 40,000 English words along several dimensions of embodiment, and which capture the extent to which something is experienced across 11 different sensory modalities, and (2) vectors from coefficients of binary classifiers …

An Analysis On Pixel Redundancy Structure In Equirectangular Images, I. Vazquez, S. Cutchin

Computer Science Faculty Publications and Presentations

360° photogrammetry captures the surrounding light from a central point. To process and transmit these types of images over the network to the end user, the most common approach is to project them onto a 2D image using the equirectangular projection to generate a 360° image. However, this projection introduces redundancy into the image, increasing storage and transmission requirements. To address this problem, the standard approach is to use compression algorithms, such as JPEG or PNG, but they do not take full advantage of the visual redundancy produced by the equirectangular projection. In this study of the 360SP dataset (a …

Optimal Claim Settlement Strategies Under Constraint Of Cap On Claim Loss, Hong Mao, Krzysztof Ostaszewski

Faculty Publications – Mathematics

In this paper, we examine the question of how to devise an optimal insurance claim settlement scheme under the constraint of a cap on the amount of the claim payment. We establish objective functions to maximize the net benefit due to exaggerated claims while at the same time maximizing the total expected wealth of the insured. Then, we establish a dual objective function to minimize the total expected loss, including the perspective of the insurer. Finally, we illustrate applications of our work and provide numerical analysis of it along with an example.

The Potential For Remote Sensing Measurement Of Dissolved Organic Carbon As A Tool For Metal Risk Assessments, Mickey Nielsen

Theses and Dissertations (Comprehensive)

The biotic ligand model (BLM) is a tool used to quantitatively evaluate how receiving water chemistry affects the bioavailability of metals. Sensitivity testing can be used to understand how the model outputs vary in response to systematic changes in water chemistry inputs. This will allow users of such models to understand how accurate their input parameters must be for a specified level of confidence in the output. Our focus was on dissolved organic carbon (DOC), which is often the most limiting data for application of BLM approaches to metals risk management. To potentially address DOC data limitations remote sensing can …

Classification Of Holomorphic Functions As Pólya Vector Fields Via Differential Geometry, Lucian-Miti Ionescu, Cristina-Liliana Pripoae, Gabriel-Teodor Pripoae

Faculty Publications – Mathematics

We review Pólya vector fields associated to holomorphic functions as an important pedagogical tool for making the complex integral understandable to the students, briefly mentioning its use in other dimensions. Techniques of differential geometry are then used to refine the study of holomorphic functions from a metric (Riemannian), affine differential or differential viewpoint. We prove that the only nontrivial holomorphic functions, whose Pólya vector field is torse-forming in the cannonical geometry of the plane, are the special Möbius transformations of the form f(z)=b(z+d)−1" role="presentation">𝑓(𝑧)=𝑏(𝑧+𝑑)−1. We define and characterize several types of affine connections, related to the parallelism of Pólya …

Biotrade: A Key To Climate, Social, And Economic Despair, Sustainable Measures Applied To Myanmar Businesses Show Hope For The Future, Sydney Rosensaft

The Synapse: Intercollegiate science magazine

No abstract provided.

Can We Trust Your Explanations? Sanity Checks For Interpreters In Android Malware Analysis, Min Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu

Research Collection School Of Computing and Information Systems

With the rapid growth of Android malware, many machine learning-based malware analysis approaches are proposed to mitigate the severe phenomenon. However, such classifiers are opaque, non-intuitive, and difficult for analysts to understand the inner decision reason. For this reason, a variety of explanation approaches are proposed to interpret predictions by providing important features. Unfortunately, the explanation results obtained in the malware analysis domain cannot achieve a consensus in general, which makes the analysts confused about whether they can trust such results. In this work, we propose principled guidelines to assess the quality of five explanation approaches by designing three critical …

Rapid Transition Of A Technical Course From Face-To-Face To Online, Swapna Gottipatti, Venky Shankaraman

Research Collection School Of Computing and Information Systems

Just like most universities around the world, the senior management at Singapore Management University decided to move all courses to a virtual, online, synchronous mode, giving instructors a very short notice period—one week—to make this transition. In this paper, we describe the challenges, practical solutions adopted, and the lessons learnt in rapidly transitioning a face-to-face Master’s degree course in Text Analytics and Applications into a virtual, online, course format that could deliver a quality learning experience.

Privattnet: Predicting Privacy Risks In Images Using Visual Attention, Zhang Chen, Thivya Kandappu, Vigneshwaran Subbaraju

Research Collection School Of Computing and Information Systems

Visual privacy concerns associated with image sharing is a critical issue that need to be addressed to enable safe and lawful use of online social platforms. Users of social media platforms often suffer from no guidance in sharing sensitive images in public, and often face with social and legal consequences. Given the recent success of visual attention based deep learning methods in measuring abstract phenomena like image memorability, we are motivated to investigate whether visual attention based methods could be useful in measuring psychophysical phenomena like “privacy sensitivity”. In this paper we propose PrivAttNet – a visual attention based approach, …

Partial Adversarial Behavior Deception In Security Games, Thanh H. Nguyen, Arunesh Sinha, He He

Research Collection School Of Computing and Information Systems

Learning attacker behavior is an important research topic in security games as security agencies are often uncertain about attackers’ decision making. Previous work has focused on developing various behavioral models of attackers based on historical attack data. However, a clever attacker can manipulate its attacks to fail such attack-driven learning, leading to ineffective defense strategies. We study attacker behavior deception with three main contributions. First, we propose a new model, named partial behavior deception model, in which there is a deceptive attacker (among multiple attackers) who controls a portion of attacks. Our model captures real-world security scenarios such as wildlife …

Analysis Of Subtelomeric Rextal Assemblies Using Quast, Tunazzina Islam, Desh Ranjan, Mohammad Zubair, Eleanor Young, Ming Xiao, Harold Riethman

Computer Science Faculty Publications

Genomic regions of high segmental duplication content and/or structural variation have led to gaps and misassemblies in the human reference sequence, and are refractory to assembly from whole-genome short-read datasets. Human subtelomere regions are highly enriched in both segmental duplication content and structural variations, and as a consequence are both impossible to assemble accurately and highly variable from individual to individual. Recently, we developed a pipeline for improved region-specific assembly called Regional Extension of Assemblies Using Linked-Reads (REXTAL). In this study, we evaluate REXTAL and genome-wide assembly (Supernova) approaches on 10X Genomics linked-reads data sets partitioned and barcoded using the …

Recognizing Figure Labels In Patents, Ming Gong, Xin Wei, Diane Oyen, Jian Wu, Martin Gryder

Computer Science Faculty Publications

Scientific documents often contain significant information in figures. The United States Patent and Trademark Office (USPTO) awards thousands of patents each week, with each patent containing on the order of a dozen figures. The information conveyed by these figures typically include a drawing or diagram, a label, caption and reference text within the document. Yet associating the short bits of text to the figure is challenging when labels are embedded within the figure, as they typically are in patents. Using patents as a testbench, this paper highlights an open challenge in analyzing all of the information presented in scientific/technical documents …

Automatic Metadata Extraction Incorporating Visual Features From Scanned Electronic Theses And Dissertations, Muntabir Hasan Choudhury, Himarsha R. Jayanetti, Jian Wu, William A. Ingram, Edward A. Fox

Computer Science Faculty Publications

Electronic Theses and Dissertations (ETDs) contain domain knowledge that can be used for many digital library tasks, such as analyzing citation networks and predicting research trends. Automatic metadata extraction is important to build scalable digital library search engines. Most existing methods are designed for born-digital documents, so they often fail to extract metadata from scanned documents such as ETDs. Traditional sequence tagging methods mainly rely on text-based features. In this paper, we propose a conditional random field (CRF) model that combines text-based and visual features. To verify the robustness of our model, we extended an existing corpus and created a …

Extractive Research Slide Generation Using Windowed Labeling Ranking, Athar Sefid, Prasenjit Mitra, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

Presentation slides generated from original research papers provide an efficient form to present research innovations. Manually generating presentation slides is labor-intensive. We propose a method to automatically generates slides for scientific articles based on a corpus of 5000 paper-slide pairs compiled from conference proceedings websites. The sentence labeling module of our method is based on SummaRuNNer, a neural sequence model for extractive summarization. Instead of ranking sentences based on semantic similarities in the whole document, our algorithm measures the importance and novelty of sentences by combining semantic and lexical features within a sentence window. Our method outperforms several baseline methods …

Em Estimation For Zero- And K-Inflated Poisson Regression Model, Monika Arora, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

Count data with excessive zeros are ubiquitous in healthcare, medical, and scientific studies. There are numerous articles that show how to fit Poisson and other models which account for the excessive zeros. However, in many situations, besides zero, the frequency of another count k tends to be higher in the data. The zero- and k-inflated Poisson distribution model (ZkIP) is appropriate in such situations The ZkIP distribution essentially is a mixture distribution of Poisson and degenerate distributions at points zero and k. In this article, we study the fundamental properties of this mixture distribution. Using stochastic representation, we …

Lidar-Based Riparian Forest Assessment Of The Nooksack River, Washington, Julia Tatum

WWU Graduate School Collection

This paper addresses two applications of lidar remote sensing: an area-based watershed-scale analysis of forest structure used to prioritize riparian restoration projects for salmon, and an individual-tree-based analysis for tree species classification. Salmon conservation is extremely important in the Pacific Northwest, but restoration efforts have been hampered by insufficient data on riparian stand conditions. I used lidar to map riparian stand structure and composition along the Nooksack River, Washington, and developed a restoration priority model based on six factors: riparian stand conditions, shade potential, cause of riparian impairment, susceptibility to climate change, position in the watershed, and proximity to intact …

Organic Crystal Nucleation In Ultrathin Liquid Films: Applications Of Computational And Experimental Methods For The Exploration Of Dynamic Spatial Relationships And Controlled Growth, Haley Doran

WWU Graduate School Collection

The advancement of semiconducting materials is paramount to the future of electronics. Organic semiconducting materials are of particular interest due to their significantly lower processing cost compared to traditional inorganic semiconducting materials, such as silicon. However, the present toolkit for solution-based controlled growth of polycrystalline thin films is lacking. Therefore, the purpose of this research is to build such a toolkit, wherein tunable parameter relationships of organic thin-film growth are evaluated and compared both experimentally and computationally. A multi-scale model has been developed, which combines mean field rate equations with a self-consistent treatment of the critical stable monomer cluster size, …

Martian Spectroscopy: Laboratory Calibration Of The Perseverance Rover’S Mastcam-Z And Photometric Investigation Of Mars-Analog Ferric-Coated Sand, Kristiana Lapo

WWU Graduate School Collection

The Mars 2020 rover Perseverance will search for signs of past habitability and biosignatures after landing in Jezero Crater in February 2021. Spectroscopy is a vital tool for planetary remote sensing and Perseverance is equipped with Mastcam-Z, a stereoscopic, zoom-enabled, multispectral imager that can acquire true color images with red, green, and blue (RGB) color filters, and visible- to near-infrared images with 12 narrowband science filters between 400 and 1100 nm. Mastcam-Z will provide operational support for the rover as well as directly contribute to Perseverance’s geologic investigations. Given the integral role of Mastcam-Z in the Mars 2020 mission, calibration …

Synthesis And Reactions Of Medium-Ring Silyl Ethers, Inna A. Fomina

WWU Graduate School Collection

Olefin metathesis is a reaction that creates new carbon-carbon double bonds by rearranging two alkenes. The reaction has undergone significant development since its discovery in the 1950s, from first reports to new catalysts and industrial uses, culminating in the 2005 Nobel Prize in chemistry. Grubbs ruthenium-based catalysts are widely used for such reactions, including ring closing metathesis (RCM) that involves the rearrangement of two alkenes on a single molecule to form a ring. During the course of investigating RCM reactions to produce eight-membered ring silyl ethers, we observed double bond isomerization when using the second-generation Grubbs catalyst and the Hoveyda-Grubbs …

Exploring Biochemical Mechanisms With Hybrid Quantum Mechanics/Molecular Mechanics And Enhanced Sampling Methods, Edwin Enciso

WWU Graduate School Collection

In the field of molecular dynamics (MD), a long-standing issue is the time frame required in order to fully observe a chemical reaction. Enhanced sampling methods have been the primary way of overcoming this issue for the past 40 years. In this experiment our goal was to combine new and existing sampling methods in order to create an efficient and accurate way of retrieving kinetics data from simulations. In order to do this, we examined two test cases: the enzymes chorismate mutase and cytosine deaminase. We did this using hybrid quantum mechanics/molecular mechanics simulations coupled with enhanced sampling methods. The …

Systematizing Confidence In Open Research And Evidence (Score), Nazanin Alipourfard, Beatrix Arendt, Daniel M. Benjamin, Noam Benkler, Michael Bishop, Mark Burstein, Martin Bush, James Caverlee, Yiling Chen, Chae Clark, Anna Dreber Almenberg, Timothy M. Errington, Fiona Fidler, Nicholas Fox, Aaron Frank, Hannah Fraser, Scott Friedman, Ben Gelman, James Gentile, Jian Wu, Et Al., Score Collaboration

Computer Science Faculty Publications

Assessing the credibility of research claims is a central, continuous, and laborious part of the scientific process. Credibility assessment strategies range from expert judgment to aggregating existing evidence to systematic replication efforts. Such assessments can require substantial time and effort. Research progress could be accelerated if there were rapid, scalable, accurate credibility indicators to guide attention and resource allocation for further assessment. The SCORE program is creating and validating algorithms to provide confidence scores for research claims at scale. To investigate the viability of scalable tools, teams are creating: a database of claims from papers in the social and behavioral …

Extraction And Evaluation Of Statistical Information From Social And Behavioral Science Papers, Sree Sai Teja Lanka, Sarah Rajtmajer, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

With substantial and continuing increases in the number of published papers across the scientific literature, development of reliable approaches for automated discovery and assessment of published findings is increasingly urgent. Tools which can extract critical information from scientific papers and metadata can support representation and reasoning over existing findings, and offer insights into replicability, robustness and generalizability of specific claims. In this work, we present a pipeline for the extraction of statistical information (p-values, sample size, number of hypotheses tested) from full-text scientific documents. We validate our approach on 300 papers selected from the social and behavioral science literatures, and …

A Simple Background Elimination Method For Miniaturized Fiber-Optic Raman Probe, Bohong Zhang

Masters Theses

"Raman scattering is called a photonic - molecular interaction based on the kinetic model of the analytic. Due to the uniqueness of the Raman scattering technique, it can provide a unique fingerprint signal for molecular recognition. However, a serious challenge often encountered in Raman measurement comes from the requirements of fast, real-time remote sensing, background fluorescence suppression, and micro-environmental detection.

A new Miniaturized Fiber-Optic Raman Probe (MFORP) for Raman spectroscopy, used especially for eliminating background fluorescence and enhancing sampling, is presented. Its main purpose is to provide an overview of excellent research on the detection of very small substances and …