Digital Commons Network^™

Us Scientific Leadership Addressing Energy, Ecosystems, Climate, And Sustainable Prosperity: Report In Brief From The Berac Subcommittee On International Benchmarking, Maureen Mccann, Patrick Reed, Ana Alonso, Ludmilla Aristilde, Massie S. Ballon, Crysten Blaby, Allison A. Campbell, Kenneth James Davis, Brian H. Davison, Ben Evans, Robert F. Fischetti, Serita D. Frey, Ann M. Fridlind, Efi Foufoula-Georgiou, Ramon Gonzalez, Michael N. Gooseff, Nathan Hillson, Janet Jansson, Klaus Keller, Markus Kleber, Costas Maranas, Gerald A. Meehl, Himadri Pakrasi, Jennifer Pett-Ridge, Kristala Prather, Johannes Quaas, G. Philip Robertson, Alistair Rogers, Tim Scheibe, Thomas R. Schneider, Gary Stacey, Margaret S. Torn, Kerstin Kleese Van Dam, Detlef Vuuren, John Weyant, Stan Wullschleger, Shaocheng Xie, Seung Yon (Sue) Rhee, Huimin Zhao

Faculty Publications

This document presents the subcommittee’s overarching and domain-specific findings and recommendations for the next decade, identified by consensus across the full BERAC subcommittee and experts interviewed for this assessment.

The Effect Of Video Model Dosage And Self-Monitoring On Parent's Use Of Language-Promoting Behavior, Kacie Marie Mcgarry

Theses and Dissertations

Previous research has found a disparity between the language trajectories of children within a high, medium, or low-economic-status family. A relationship is reliably found between the language trajectory of toddlers and success throughout school. This study will evaluate a training package to teach parents to engage in behaviors that promote language and assess the training's short-term effect on the trajectories of children (i.e., growing language) within low-socioeconomic backgrounds. Specifically, experimenters will evaluate the impact of the dosage of video modeling, self-evaluation, and self-monitoring on the acquisition of the targeted skills. Data may suggest that the more accurate the individual is …

Modeling Settlement And Filtration Of The Indian River Lagoon Benthic Community, With An Emphasis On Living Dock Restoration Mats, Sandra Lisette Rech

Theses and Dissertations

The Indian River Lagoon (IRL) is one of the most biologically diverse estuaries in North America. An increase in population and anthropogenic effects have led to eutrophication, a decline in water quality, and overall degradation. The Living Docks program is a citizen science initiative started at the Florida Institute of Technology for lagoon restoration. In this program, public and private docks are volunteered to become Living Docks, where oyster mats made of plastic mesh and dead, dried oyster shells are attached to dock pilings in an effort to provide a natural substrate for benthic organism growth. The community which develops …

Representation Learning For Open Set Recognition And Novel Category Discovery, Jingyun Jia

Theses and Dissertations

As machine learning models have achieved great success in various research and industry fields, the success of these models heavily relies on the massive amount of data collection and human annotations. While the real world is an open set, the daily emerged categories and the lacking of annotations have become new challenges for machine learning models. The absence of newly emerged categories in training samples can be captured by Open Set Recognition (OSR). Then, given the newly emerged samples, the process of automatically identifying the novel categories is called Novel Category Discovery (NCD). In this dissertation, we focused on learning …

The Use Of Flexible Organic And Inorganic Building Blocks In Complex Metal- Organic Frameworks, Sahar Yahia Rajeh

Theses and Dissertations

Metal organic frameworks (MOFs) are new class of hybrid materials that draw the attention of scientists to discover new properties that help in many fields. The structural diversity of MOFs is accessible by incorporating different organic linkers to the same metal cluster. In this work, we reacted seven flexible organic linkers with different lengths varying from 4-carbons to 10-carbons to a copper-paddlewheel metal cluster. The flexibility of the linkers make the confirmation of MOFs a challenge, although we were able to prepare a new crystalline MOF from a 5-carbon organic linker with two different copper-clusters. Another MOF in powder form …

Investigating The O’Connell Effect In Kepler Eclipsing Binaries, Matthew Frederick Knote

Theses and Dissertations

The O’Connell effect – the presence of unequal maxima in eclipsing binaries – remains an unsolved riddle in the study of close binary systems. The Kepler space telescope produced high precision photometry of nearly 3,000 eclipsing binary systems, providing a unique opportunity to study the O’Connell effect in a large sample and in greater detail than in previous studies. I have characterized the observational properties – including temperature, luminosity, and eclipse depth – of a set of 212 systems (7.3% of Kepler eclipsing binaries) that display a maxima flux difference of at least 1%, representing the largest sample of O’Connell …

Deep Learning Approach To Speech Recognition: A Signal Extractor & Producer For Artificial General Intelligence, Ahmad Zuhair S. Hasanain

Theses and Dissertations

The efficient use of a communication bandwidth starts with the data source. The features of the speech signals can be extracted and reconstructed to lower the Internet traffic of the acoustic artificial agents and to increase the quality of the automatic speech recognition systems. The Speech Quefrency Transform (SQT) is hereby introduced in the work to enrich the communication space between the artificial agents and mankind. We describe the motivation, methodology, and deep learning approach in detail as we apply the SQT technology to several applications: sharp pitch track extraction, real-time speech communications, and emotion recognition. The results were excellent. …

Towards Orchestration In The Cloud-Fog Continuum, Xavier Jesus Merino Aguilera

Theses and Dissertations

The proliferation of the Internet-of-Things has raised demand for computing, storage, and network resources. The cloud model is ill-equipped to handle the volume and variety of data travelling to and from the cloud’s core as more data is generated and consumed at the network’s edge. Some applications necessitate low-latency connectivity and geographical awareness, highlighting the cloud’s centralization shortcomings. By localizing resources, minimizing bandwidth utilization, and lowering latency, the fog and edge layers are proposed to circumvent these limitations. At these layers, resource orchestration is crucial because poor resource management has an impact on service delivery. The aim of this study …

Identifying Properties Of Blockchain Making It Relevant To Iot Applications, Ashwaq Alaklabi

Theses and Dissertations

Blockchain is a distributed ledger system that enables machine-to-machine interactions combined with the Internet of Things (IoT). It employs a series of transactions stored in a database, confirmed by numerous sources, and written into a shared ledger distributed across all nodes. The marriage of IoT with blockchain has several potential benefits, including the ability for a smart device to act autonomously without the need for a centralized authority. It can also monitor how devices communicate with one another. A blockchain network can track and sell almost anything of value, lowering risk and costs for everyone involved. Numerous applications from diverse …

Non-Negative Matrix Factorization In The Identification Of Co-Mutations, Michael Robert Kolar

Theses and Dissertations

One of the difficulties of genetic research is the asymmetrical relationship between data collection techniques and data analysis techniques. The goal of this research was to test a novel application of non-negative matrix factorization, which would allow researchers to more easily identify co-mutations. Those co-mutations then can then be further verified by frequency analysis. This pruning process allows researchers to identify more fruitful research opportunities, saving time, energy, and funding. Past research has utilized non-negative matrix factorization to extract factors which meaningfully express underlying data features. This study extends the depth of non-negative matrix factorization knowledge in various ways. First, …

On Clinical Use Of Infrared Cameras For Video-Based Estimation Of 3d Facial Kinematics, William Mackenzie Harrington

Theses and Dissertations

Neurological and neurodegenerative disorders such as Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and stroke can cause speech and orofacial motor impairments with devastating effects on quality of life. Analysis of orofacial movement provides vital information for early diagnosis and tracking disease progression, but current clinical practice relies on perceptual assessments performed by clinicians, which are unreliable and insensitive to early symptoms. New methods in machine learning have enabled automatic and objective assessment of orofacial kinematics from color and depth videos, hence we introduce MEADepthCamera, a mobile application for RGB-D video and audio recording and automatic estimation of 3D facial …

Cloud Image Classification Using Machine Learning, Marcus Peter Cote

Theses and Dissertations

Machine learning is a rapidly expanding technology that has proven to be highly useful for image classification. Ground-based camera networks are an emerging resource for aviation weather information with near real-time imagery available online for public viewing and download. While raw web camera imagery can be analyzed by aviators, high pilot workload motivates the use of machine learning to autonomously interpret cloud type information from images that is relevant to aviation weather hazards. In particular, transfer learning is a machine learning approach by which elements of a pre-trained machine learning model are refitted for new tasks. By employing transfer learning …

Divergent Serpentoviruses In Free-Ranging Invasive Pythons And Native Colubrids In Southern Florida, United States, Steven B. Tillis, Jillian M. Josimovich, Melissa A. Miller, Laura L. Hoon-Hanks, Arik M. Hartmann, Natalie M. Claunch, Marley E. Iredale, Tracey D. Logan, Amy A. Yackel Adams, Ian A. Bartoszek, John S. Humphrey, Bryan M. Kluever, Mark D. Stenglein, Robert N. Reed, Christina M. Romagosa, James F.X. Wellehan, Robert J. Ossiboff

United States Department of Agriculture Wildlife Services: Staff Publications

Burmese python (Python bivittatus) is an invasive snake that has significantly affected ecosystems in southern Florida, United States. Aside from direct predation and competition, invasive species can also introduce nonnative pathogens that can adversely affect native species. The subfamily Serpentovirinae (order Nidovirales) is composed of positive-sense RNA viruses primarily found in reptiles. Some serpentoviruses, such as shingleback nidovirus, are associated with mortalities in wild populations, while others, including ball python nidovirus and green tree python nidovirus can be a major cause of disease and mortality in captive animals. To determine if serpentoviruses were present in invasive Burmese …

Rainwater Catchment System Designed For California Polytechnic State University Building 34, Jonah S. Aere

Construction Management

California Polytechnic State University currently receives its water supply from either Whale Rock Reservoir, for distilled water, or pumped from six ground wells, for agricultural use. Although the university’s Agricultural College requires a certain amount of water to grow crops, these demands are often not met due to the lack of water within these underground wells. A rainwater capture system could be constructed to ease the water supply burden which is already depleting, reduce wasted drainage, and maintain a sustainable agricultural water source without being dependent on other locations. This would benefit the institution by reducing imported water thereby saving …

Objective Evaluation Of The Somatogravic Illusion From Flight Data Of An Airplane Accident, Eric L. Groen, Torin K. Clark, Mark M.J. Houben, Jelte E. Bos, Randall J. Mumaw

Faculty Research, Scholarly, and Creative Activity

(1) Background: It is difficult for accident investigators to objectively determine whether spatial disorientation may have contributed to a fatal airplane accident. In this paper, we evaluate three methods to reconstruct the possible occurrence of the somatogravic illusion based on flight data recordings from an airplane accident. (2) Methods: The outputs of two vestibular models were compared with the “standard” method, which uses the unprocessed gravito-inertial acceleration (GIA). (3) Results: All three methods predicted that the changing orientation of the GIA would lead to a somatogravic illusion when no visual references were available. However, the methods were not able to …

Traffic Restrictions During The 2008 Olympic Games Reduced Urban Heat Intensity And Extent In Beijing, Bo Yang, Hongxing Liu, Emily L. Kang, Timothy L. Hawthorne, Susanna T.Y. Tong, Song Shu, Min Xu

Faculty Research, Scholarly, and Creative Activity

Satellite thermal remote sensing has been utilized to examine the urban heat dynamics in relation to the urban traffic restriction policy. During the 2008 Olympic Games in Beijing, the traffic volume was approximately cut off by half through the road space rationing. Based on daily MODIS satellite thermal observations on the surface temperature, statistical models were developed to analyze the contribution of traffic volume reduction to the urban heat intensity and spatial extent. Our analyses show that cutting off half of the traffic volume has led to a marked decrease in the mean surface temperature by 1.5–2.4 °C and shrinkage …

Supporting Inclusive Learning Using Chatbots? A Chatbot-Led Interview Study, Sambhav Gupta, Yu Chen

Faculty Research, Scholarly, and Creative Activity

Supporting student academic success has been one of the major goals for higher education. However, low teacher-to-student ratio makes it difficult for students to receive sufficient and personalized support that they might want to. The advancement of artificial intelligence (AI) and conversational agents, such as chatbots, has provided opportunities for assisting learning for different types of students. This research aims at investigating the opportunities and requirements of chatbots as an intelligent helper to facilitate equity in learning. We developed a chatbot as an experimental platform to investigate the design opportunities of using chatbots to support inclusive learning. Through a chatbot-led …

Recuerdos De Mi Niñez, Noel Barsenas

Theses and Dissertations

This thesis contains an original work for orchestra that features programmatic elements and musical gestures referencing previous generations of composers as well as other influential relatives of the author that are then recombined into a personal style. The document also contains commentary about the piece’s personal, historic, and cultural contexts, as well as a theoretical analysis addressing the form, structure, and harmonic content of the work.

My Journey As An Elementary Science Teacher: From Linear To Authentic, Johanna Lynn Esparza

Theses and Dissertations

The purpose of this dissertation is to provide a personalized narrative of one science teacher’s use of reflexive teaching as an agent of change. This dissertation is about a journey of change in instruction fostered by a change of identity as a science teacher, using the butterfly cycle as a metaphor. This dissertation narrates the identity evolution of the teacher. This study has relevance because the process utilized by the teacher provides a method of self-examination and identity construction for other elementary science classroom teachers who want to improve their science practices. This study also has relevance because it describes …

Search For Gravitational Waves From Core Collapse Supernovae In Ligo's Observation Runs Using A Network Of Detectors, Shahrear Khan Faisal

Theses and Dissertations

Core-Collapse Supernova (CCSN) is one of the most anticipated sources of Gravitational Waves (GW) in the fourth observation run (O4) of LIGO and other network of GW detectors. A very low rate of galactic CCSN, coupled with the fact that the CCSN waveforms are unmodeled, make detection of these signals extremely challenging. Mukherjee et. al. have developed a new burst search pipeline, the Multi-Layer Signal Enhancement with cWB and CNN or MuLaSEcC, that integrates a non-parametric signal estimation and Machine Learning. MuLaSEcC operates on GW data from a network of detectors and enhances the detection probability while reducing the false …

The Impacts Of Supporting Productive Struggle Teaching Practice On Students’ Conceptual Understanding, Procedural Fluency, And Strategic Competence: The Case Of Quadratic Functions, Sumeyra Karatas

Theses and Dissertations

This quasi-experimental design study aimed to examine how exposure to supporting productive struggle teaching practice impacts students’ conceptual understanding, procedural fluency, and strategic competence when solving high-demanding quadratic functions problem solving tasks. Results suggested that students in the supporting productive struggle teaching practice group performed significantly better than students who received facilitated instruction in every three strands of mathematical proficiency (i.e., conceptual understanding, procedural fluency, and strategic competence). By examining the effectiveness of supporting productive struggle teaching practice, this study offers insight into the conceptions and strategies teachers can implement in their classrooms to improve students’ mathematical proficiency.

Influence Of Pretreatments On Physiological Status And Post-Planting Survival Of Thornforest Seedlings In A Restoration Context, Douglas E. Mainhart

Theses and Dissertations

Semi-arid ecosystems across the globe have faced land conversion posing a threat to the important ecosystem services they provide. Revegetation-centered restoration efforts in arid regions have low success due to limited water availability and higher temperatures. Typically, practitioners utilize methods that modify field conditions around seedlings to mitigate these stressors. I evaluated the efficacy of in-nursery treatments to improve plant water status. Three pretreatments were applied: elevated CO2, drought hardening, and an antitranspirant foliar spray. My goal was to understand how these pretreatments would impact survival and growth in the field and what physiological traits they altered. Elevated CO2 and …

Incorporating Native Plants In Insectary Strips To Promote Insect Diversity And Below-Ground Beneficial Microbes In South Texas, Lindsey N. Richards

Theses and Dissertations

Farm edges are generally the most undisturbed areas in a farm with diverse vegetation and can enhance agrobiodiversity and provide crucial food and shelter for wildlife, insects, and soil biota. Planting native wildflowers with the ability to reseed and withstand local climatic conditions for semi-permanent vegetation around farm edges or in between crops has potential to biologically control pests. To test this, we ran a two-year study and installed three different flowering insectary strips on a certified organic vegetable farm in South Texas during the winter season. The treatments were: 1) a commercially sourced 17-species native wildflower seed mix; 2) …

Learnfca: A Fuzzy Fca And Probability Based Approach For Learning And Classification, Suraj Ketan Samal

School of Computing: Dissertations, Theses, and Student Research

Formal concept analysis(FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. Over the past several years, many of its extensions have been proposed and applied in several domains including data mining, machine learning, knowledge management, semantic web, software development, chemistry ,biology, medicine, data analytics, biology and ontology engineering.

This thesis reviews the state-of-the-art of theory of Formal Concept Analysis(FCA) and its various extensions that have been developed and well-studied in the past several years. We discuss their historical roots, reproduce the original definitions and derivations with illustrative examples. Further, we provide …

Bevers: A General, Simple, And Performant Framework For Automatic Fact Verification, Mitchell Dehaven

School of Computing: Dissertations, Theses, and Student Research

Fact verification has become an important process, primarily done manually by humans, to verify the authenticity of claims and statements made online. Increasingly, social media companies have utilized human effort to debunk false claims on their platforms, opting to either tag the content as misleading or false, or removing it entirely to combat misinformation on their sites. In tandem, the field of automatic fact verification has become a subject of focus among the natural language processing (NLP) community, spawning new datasets and research. The most popular dataset is the Fact Extraction and VERification (FEVER) dataset. In this thesis an end-to-end …

Attention In The Faithful Self-Explanatory Nlp Models, Mostafa Rafaiejokandan

School of Computing: Dissertations, Theses, and Student Research

Deep neural networks (DNNs) can perform impressively in many natural language processing (NLP) tasks, but their black-box nature makes them inherently challenging to explain or interpret. Self-Explanatory models are a new approach to overcoming this challenge, generating explanations in human-readable languages besides task objectives like answering questions. The main focus of this thesis is the explainability of NLP tasks, as well as how attention methods can help enhance performance. Three different attention modules are proposed, SimpleAttention, CrossSelfAttention, and CrossModality. It also includes a new dataset transformation method called Two-Documents that converts every dataset into two separate documents required by the …

Identification Of Factors Contributing To Traffic Crashes By Analysis Of Text Narratives, Cristian D. Arteaga-Sanchez

UNLV Theses, Dissertations, Professional Papers, and Capstones

The fatalities, injuries, and property damage that result from traffic crashes impose a significant burden on society. Current research and practice in traffic safety rely on analysis of quantitative data from crash reports to understand crash severity contributors and develop countermeasures. Despite advances from this effort, quantitative crash data suffers from drawbacks, such as the limited ability to capture all the information relevant to the crashes and the potential errors introduced during data collection. Crash narratives can help address these limitations, as they contain detailed descriptions of the context and sequence of events of the crash. However, the unstructured nature …

Beyond The Numbers: A Deeper Dive Into The Dearth Of Girls And Women In Stem, Jennifer John Buck

UNLV Theses, Dissertations, Professional Papers, and Capstones

Despite decades of research attempting to better understand the dearth of girls and women in science, technology, engineering, and math (STEM), gender imbalances persist in many STEM fields. This is particularly the case in math-intensive STEM fields. The current program of research used mixed-methods research to better understand these inequities. The first paper identified gender and ethnic variation in how undergraduates reason about STEM inequities. The second paper found that how emerging adults narrate “turning points” in their relationship with math was associated with their current math outcomes and future plans to pursue math. The final paper demonstrated that how …

Age And Genesis Of W-Mo-Cu Mineralization, Gold Hill, Utah, Nathan J. Carey

UNLV Theses, Dissertations, Professional Papers, and Capstones

Utah's Gold Hill mining district hosts a Jurassic felsic pluton (~80 km^2) that was emplaced into a Mississippian to Pennsylvanian carbonate-dominated sedimentary sequence and is spatially associated with numerous polymetallic mineral deposits. This study focuses on W-Mo-Cu mineralization at the Lucy L., Doctor, Yellow Hammer, Reaper, and Rustler deposits within the district. The new, detailed petrographic observations, mineral chemistry (on scheelite, molybdenite, chalcopyrite, magnetite, garnet, and pyroxene), and Re-Os molybdenite geochronological data presented here allows for the determination of key mineral associations and paragenesis, the characterization of deposit types and their evolution, and the constraining of the relative and absolute …

Payment Profiles: Using Payment Transaction Data To Identify And Characterize Gamblers, Kasra Ghaharian

UNLV Theses, Dissertations, Professional Papers, and Capstones

Payment providers in the gambling industry facilitate transactions, allowing customers to transfer money to and from wagering accounts. Payments transaction data is information that is captured from these transactions, including, for example, the type, amount, time, and location. How this data may be used for gambling harm minimization and prevention has garnered significant interest, particularly due to accelerated payments modernization in the wake of the COVID-19 pandemic. With this study, I explored the utility of payments transaction data to categorize subgroups of gamblers in order to identify individuals who may be at-risk of harm. I benchmarked six cluster analysis methods …