Physical Sciences and Mathematics Commons^™

Iowa Waste Reduction Center Newsletter, August 2024, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

In this issue:

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Artificial Intelligence, Work, And The Future Of Education, Daniel Brown

Presentations

No abstract provided.

Nonfactoid Question Answering As Query-Focused Summarization With Graph-Enhanced Multihop Inference, Yang Deng, Wenxuan Zhang, Weiwen Xu, Ying Shen, Wai Lam

Research Collection School Of Computing and Information Systems

Nonfactoid question answering (QA) is one of the most extensive yet challenging applications and research areas in natural language processing (NLP). Existing methods fall short of handling the long-distance and complex semantic relations between the question and the document sentences. In this work, we propose a novel query-focused summarization method, namely a graph-enhanced multihop query-focused summarizer (GMQS), to tackle the nonfactoid QA problem. Specifically, we leverage graph-enhanced reasoning techniques to elaborate the multihop inference process in nonfactoid QA. Three types of graphs with different semantic relations, namely semantic relevance, topical coherence, and coreference linking, are constructed for explicitly capturing the …

Causvsr: Causality Inspired Visual Sentiment Recognition, Xinyue Zhang, Zhaoxia Wang, Hailing Wang, Jing Xiang, Chunwei Wu, Guitao Cao

Research Collection School Of Computing and Information Systems

Visual Sentiment Recognition (VSR) is an evolving field that aims to detect emotional tendencieswithin visual content. Despite its growing significance, detecting emotions depicted in visual content,such as images, faces challenges, notably the emergence of misleading or spurious correlationsof the contextual information. In response to these challenges, we propose a causality inspired VSRapproach, called CausVSR. CausVSR is rooted in the fundamental principles of Emotional Causalitytheory, mimicking the human process from receiving emotional stimuli to deriving emotional states.CausVSR takes a deliberate stride toward conquering the VSR challenges. It harnesses the power of astructural causal model, intricately designed to encapsulate the dynamic causal …

Clamber: A Benchmark Of Identifying And Clarifying Ambiguous Information Needs In Large Language Models, Tong Zhang, Peixin Qin, Yang Deng, Chen Huang, Wenqiang Lei, Junhong Liu, Dingnan Jin, Hongru Liang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly used to meet user information needs, but their effectiveness in dealing with user queries that contain various types of ambiguity remains unknown, ultimately risking user trust and satisfaction. To this end, we introduce CLAMBER, a benchmark for evaluating LLMs using a well-organized taxonomy. Building upon the taxonomy, we construct 12K high-quality data to assess the strengths, weaknesses, and potential risks of various off-the-shelf LLMs.Our findings indicate the limited practical utility of current LLMs in identifying and clarifying ambiguous user queries, even enhanced by chain-of-thought (CoT) and few-shot prompting. These techniques may result in overconfidence …

Neural Network Semantic Backdoor Detection And Mitigation: A Causality-Based Approach, Bing Sun, Jun Sun, Wayne Koh, Jie Shi

Research Collection School Of Computing and Information Systems

Different from ordinary backdoors in neural networks which are introduced with artificial triggers (e.g., certain specific patch) and/or by tampering the samples, semantic backdoors are introduced by simply manipulating the semantic, e.g., by labeling green cars as frogs in the training set. By focusing on samples with rare semantic features (such as green cars), the accuracy of the model is often minimally affected. Since the attacker is not required to modify the input sample during training nor inference time, semantic backdoors are challenging to detect and remove. Existing backdoor detection and mitigation techniques are shown to be ineffective with respect …

Beyond Automation: Ai As A Catalyst For New Job Creation In Software Development, Jill Willard, James Hutson

Faculty Scholarship

As artificial intelligence (AI) continues to evolve, its impact on software development and programming is profound, drawing parallels to the shift from assembler to object-oriented programming. This article explores how AI is reshaping the landscape of software jobs, creating new opportunities rather than diminishing them. By simplifying complex tasks and lowering barriers to coding, AI is expanding the technology "pie," introducing new use cases, and enhancing efficiency. The transition from monolithic services to microservices has reduced risks and accelerated deployment processes, and AI is poised to further this evolution by managing the complexities of service interactions through advanced orchestration layers. …

Palynostratigraphy And Bayesian Age Stratigraphic Model Of New Ca-Id-Tims Zircon Ages From The Walloon Coal Measures, Surat Basin, Australia, K. Sobczak, J. Cooling, T. Crossingham, H. G. Holl, M. Reilly, J. Esterle, J. L. Crowley, C. Hannaford, M. T. Mohr, Z. Hamerli, S. Hurter

Geosciences Faculty Publications and Presentations

The Surat Basin hosts significant coal and coal seam gas resources. New high-precision CA-TIMS U/Pb zircon ages from tuffs and Bayesian age stratigraphic models are combined with palynology from fine-grained sedimentary rocks and zircon trace elements to provide further chronostratigraphic and biostratigraphic constrains on the Walloon Coal Measures in the eastern margin of the Surat Basin and infer the palaeoenvironment and tectonic setting. The tuff ages range from 165.88 ± 0.11 Ma to 158.84 ± 0.05 Ma, with those from the stratigraphically lower Taroom Coal Measures ranging from 165.88 ± 0.11 to 163.05 ± 0.08 Ma and Juandah Coal Measures …

Creating A Virtual Hierarchy From A Relational Database, Yucong Mo

All Graduate Theses and Dissertations, Fall 2023 to Present

In data management and modeling, the value of the hierarchical model is that it does not require expensive JOIN operations at runtime; once the hierarchy is built, the relationships among data are embedded in the tree-like hierarchical structure, and thus querying data could be much faster than using a relational database. Today most data is stored in relational databases, but if the data were stored in hierarchies, what would these hierarchies look like? And more importantly, would this transition lead to a more efficient database? This thesis explores these questions by introducing a set of algorithms to convert a relational …

Shedding Light On Past Ice-Free Intervals In Northwest Greenland: Luminescence Dating Of The Base Of The Camp Century Ice Core, Hawke Woznick

All Graduate Theses and Dissertations, Fall 2023 to Present

The goal of this thesis is to provide greater resolution on the age and character of the subglacial sediment recovered from the base of the Camp Century ice core, northwestern Greenland. Geochemical analysis indicated that the upper sub-ice sediments were geochemically different and experienced greater weathering than the basal unit underlying a one-meter silty ice lens. Analysis of feldspars within the very fine sand fraction indicates they are dominated by potassium feldspar. Sediment was dated using luminescence, which provides an age for the last time sediment was exposed to light. Luminescence analysis returned ages around 420 thousand years old, which …

Optimization Of Mass Spectrometry-Based Methods For Low-Input And Spatial Proteomics, Andikan Jones Nwosu

Theses and Dissertations

Eukaryotic cells are highly heterogeneous. These cells are arranged into different compartments, carrying out separate functions and facilitating biological processes. Proteins are the effector biomolecules targeted to subcellular locations that help fulfill specific tasks in living organisms. Spatial proteomics can help unravel molecularly how protein abundance and localization are altered in cells, which is not feasible in traditional bulk-scale proteomics. To achieve this, our lab has developed a miniaturized sample processing platform called nanoPOTS, reduced separation columns' inner diameter to increase ionization efficiency and concentrate analytes for mass spectrometers and optimized data acquisition modes for increasing proteome coverage in spatial …

Forecasting Commercial Vehicle Miles Traveled (Vmt) In Urban California Areas, Steve Chung, Jaymin Kwon, Yushin Ahn

Mineta Transportation Institute

This study investigates commercial truck vehicle miles traveled (VMT) across six diverse California counties from 2000 to 2020. The counties—Imperial, Los Angeles, Riverside, San Bernardino, San Diego, and San Francisco—represent a broad spectrum of California’s demographics, economies, and landscapes. Using a rich dataset spanning demographics, economics, and pollution variables, we aim to understand the factors influencing commercial VMT. We first visually represent the geographic distribution of the counties, highlighting their unique characteristics. Linear regression models, particularly the least absolute shrinkage and selection operator (LASSO) and elastic net regressions are employed to identify key predictors of total commercial VMT. LASSO regression …

An Analysis Of The Propagation Of Gravitational Radiation Under A Graviton Of Nonzero Mass And Its Implications For Cosmological Measurements, Margaret Johnston

UNLV Theses, Dissertations, Professional Papers, and Capstones

Under the assumptions of General Relativity (GR), gravitational waves propagate at the speed of light and their mediation can be represented as a particle through a massless graviton. We investigate the impact and observability of the presence of a massive graviton, how such a modification to GR would also modify the observed gravitational waves from astrophysical sources, and how this effect can be used as an independent measurement of cosmmological parameters, including the Hubble parameter H0. We simulate the impact of a massive graviton on compact binary coalescence observation in a near-future LIGO-Virgo-KAGRA interferometer network through a modification to the …

Application Of Machine Learning Algorithms In Healthcare, Dwaipayan Mukhopadhyay

UNLV Theses, Dissertations, Professional Papers, and Capstones

Machine Learning (ML) is a subset of artificial intelligence that has made substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, amongst a few fields of healthcare. Here we provide a brief overview of machine learning-based approaches and learning algorithms. Second, we discuss a general procedure of ML and review some studies presented in ML application for several healthcare fields. We also briefly discuss the risks and challenges of ML application to healthcare.This dissertation also consists of four different cases in healthcare where we have applied ML techniques on real life data sets. …

Mining Gambling Data For Modeling Gambling Behavior Patterns, Piyush Aniruddha Puranik

UNLV Theses, Dissertations, Professional Papers, and Capstones

Understanding player behavior for responsible gambling research is a difficult task due to the lack of data on players’ activities. Past studies in this area are largely limited to publicly available behavioral data or aggregated players data. Problem gambling in gamblers is typically identified only after they have already been addicted or have already been engaging in problematic gambling behavior. Furthermore, “risky” gambling behavior has historically been difficult to define due to the varying patterns of gambling activity that could potentially be attributed to it.In this dissertation we illustrate the methodology and algorithms used to engineer financial data for further …

Canine Parasites In Southern Nevada Urban Dog Parks: Paravec Study, Miklo Azrael A. Alcala

UNLV Theses, Dissertations, Professional Papers, and Capstones

While dogs are one of humans’ greatest companions, they also serve as hosts for a multitude of parasites. Urban dog parks serve as environments where the transmission of diseases is likely to occur. Exposure to infective agents, contained within the soil, intermediate hosts (e.g., rodents, rabbits), and feces, can directly affect the health of dogs and their owners. Other factors that can further influence canine health include age, previous diagnoses of parasites/diseases, and migration. Many dog owners visit dog parks to encourage socialization and exercise. Such activities are meant to improve health, but unawareness of microbiological organisms can lead to …

Magnetization And Age Of Ca. 544 Ma Syenite, Eastern Canada: Evidence For Renewal Of The Geodynamo, Tinghong Zhou, Mauricio Ibañez-Mejia, Richard K. Bono, Rory D. Cottrell, Wouter Bleeker, Kenneth P. Kodama, Wentao Huang, Eric G. Blackman, Francis Nimmo, Aleksey Smirnov, John A. Tarduno

Michigan Tech Publications, Part 2

The ca. 565 Ma Ediacaran geodynamo was highly unusual, producing an ultralow field 10 times weaker than present-day value of 8 x 1022 A m2. A ∼5 times rise in field strength is seen in time-averaged single crystal paleointensity data of ca. 532 Ma Early Cambrian anorthosites of Oklahoma (USA). The field increase could record the onset of inner core nucleation predicted by thermal evolution and numerical dynamo models. Here, we examine the renewal of the geodynamo through zircon U-Pb geochronology and single crystal paleointensity studies of plagioclase from the Chatham-Grenville syenite intrusion in the Grenville Province (Canada). U-Pb data …

Evidence For Rapid Variability At High Energies In Grbs, E. Casey Aldrich, Robert J. Nemiroff

Michigan Tech Publications, Part 2

Intrinsic variability was searched for in arrival times of six gamma-ray bursts (GRBs) at high energies – between 30 MeV and 2 GeV – detected by the Fermi satellite’s Large Area Telescope (LAT). The GRBs were selected from the Fermi LAT catalogue with preference for events with numerous photons, a strong initial pulse, and measured redshifts. Three long GRBs and three short GRBs were selected and tested. Two different variability-detection algorithms were deployed, one counting photons in pairs, and the other multiplying time gaps between photons. In both tests, a real GRB was compared to 1000 Monte Carlo versions of …

Accretion Of Warm Chondrules In Weakly Metamorphosed Ordinary Chondrites And Their Subsequent Reprocessing, Alex M. Ruzicka, Richard C. Hugo, Jon M. Friedrich, Michael T. Ream

Geology Faculty Publications and Presentations

To better understand chondrite accretion and subsequent processes, the textures, crystallography, deformation, and compositions of some chondrite constituents in ten lithologies of different cluster texture strength were studied in seven weakly metamorphosed (Type 3) and variably shocked ordinary chondrites (Ragland—LL3 S1, Tieschitz—H/L3 S1, NWA 5421—LL3 S2, NWA 5205—LL3 S2, NWA 11905—LL3-5 S3, NWA 5781—LL3 S3, NWA 11351—LL3-6 S4) using optical and electron microscopy and microtomography techniques.

Results support a four-stage model for chondrite formation. This includes 1) limited annealing following collisions during chondrule crystallization and rapid cooling in space prior to accretion, as evidenced by olivine microstructures consistent with dislocation …

Phthalocyanine-Enabled Technologies For Water Treatment And Disinfection Strategies, Hooralain Bushnaq, Catherine Munro, Sisi Pu, Amir Razmjou, Masoumeh Zargar, Giovanni Palmisano, Srinivas Mettu, Ludovic F. Dumée

Research outputs 2022 to 2026

Water treatment and disinfection are critical factors in ensuring a safe and sustainable water supply. Phthalocyanines (Pcs), a class of versatile and robust organic compounds, have garnered significant attention for their application in various water treatment processes. This review paper offers a groundbreaking investigation of Pc-enabled technologies within the domain of water treatment applications. The core aim of this review is to meticulously analyze the chemical and optical properties of Pcs, elucidate their photosensitization mechanism and establish the crucial connection between their chemical structure and photodynamic efficacy. The various modes of Pcs application in water treatment processes - whether in …

Variation In Zero Plane Displacement And Roughness Length For Momentum Revisited, Ashvath Singh Kunadi, Richard P. Silberstein, Sally E. Thompson

Research outputs 2022 to 2026

Zero plane displacement height (d0) and momentum roughness length (z0m), describe the aerodynamic characteristics of a vegetated surface. Usually, d0 and z0m are assumed to be constant functions of the physical characteristics of the surface. Prior evidence collected from the literature and our examination of flux tower data show that d0 and z0m vary in time at sites with tree and shrub canopies, but not grasslands. The conventional explanations of these variations are based on linear functions of wind velocity and friction velocity, with little theoretical basis. This study explains the variation in aerodynamic parameters by matching four analytical canopy …

Upscaling Relative Permeability And Capillary Pressure From Digital Core Analysis In Otway Formation: Considering The Order And Size Effects Of Facies, Masoud Aslannezhad, Mohammad Sayyafzadeh, David Tang, Zhenjiang You, Stefan Iglauer, Alireza Keshavarz

Research outputs 2022 to 2026

Digital Core Analysis (DCA) has emerged as a crucial instrument in reservoir characterization in recent times. With the advent of high-resolution micro-CT imaging, it is now possible to visualize the three-dimensional microstructures of in-situ pores and flow patterns within rocks. DCA offers several notable benefits over traditional techniques, such as a higher density of measurements, faster processing times, and the preservation of rock samples. It also demonstrates considerable flexibility with challenging core conditions and can derive numerous parameters from each individual sample. The objective of this work is to utilise DCA data from Otway formation to enhance reservoir characterisation and …

Predicting Personality Or Prejudice? Facial Inference In The Age Of Artificial Intelligence, Shilpa Madan, Gayoung Park

Research Collection Lee Kong Chian School Of Business

Facial inference, a cornerstone of person perception, has traditionally been studied through human judgments about personality traits and abilities based on people's faces. Recent advances in artificial intelligence (AI) have introduced new dimensions to this field, employing machine learning algorithms to reveal people's character, capabilities, and social outcomes based just on their faces. This review examines recent research on human and AI-based facial inference across psychology, business, computer science, legal, and policy studies to highlight the need for scientific consensus on whether or not people's faces can reveal their inner traits, and urges researchers to address the critical concerns …

On The Multi-Turn Instruction Following For Conversational Web Agents, Yang Deng, Xuan Zhang, Wenxuan Zhang, Yifei Yuan, See-Kiong Ng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Web agents powered by Large Language Models (LLMs) have demonstrated remarkable abilities in planning and executing multi-step interactions within complex web-based environments, fulfilling a wide range of web navigation tasks. Despite these advancements, the potential for LLM-powered agents to effectively engage with sequential user instructions in real-world scenarios has not been fully explored. In this work, we introduce a new task of Conversational Web Navigation, which necessitates sophisticated interactions that span multiple turns with both the users and the environment, supported by a specially developed dataset named Multi-Turn Mind2Web (MT-Mind2Web). To tackle the limited context length of LLMs and the …

Mathematical Modeling And Numerical Approximations Of Combustion Instability Frequencies And Growth Rates, Harvey B. Ring Iii

Doctoral Dissertations

This dissertation presents a mathematical model and numerical simulations to determine the resonant frequencies and their associated growth rates for longitudinal modes in a combustion system similar to that found in a rocket engine. The mathematical model, which is applicable to a two-duct system with a thin flame between the two ducts, each of which having constant area and properties, considers the case of axial mean velocity and uses a vibrating wall at the inlet to select the frequency so that all modes may be found. The model is applied to the acoustics equations describing pressure and velocity fluctuations, derived …

Prompt Tuning On Graph-Augmented Low-Resource Text Classification, Zhihao Wen, Yuan Fang

Research Collection School Of Computing and Information Systems

Text classification is a fundamental problem in information retrieval with many real-world applications, such as predicting the topics of online articles and the categories of e-commerce product descriptions. However, low-resource text classification, with no or few labeled samples, presents a serious concern for supervised learning. Meanwhile, many text data are inherently grounded on a network structure, such as a hyperlink/citation network for online articles, and a user-item purchase network for e-commerce products. These graph structures capture rich semantic relationships, which can potentially augment low-resource text classification. In this paper, we propose a novel model called Graph-Grounded Pre-training and Prompting (G2P2) …

Cross-Problem Learning For Solving Vehicle Routing Problems, Zhuoyi Lin, Yaoxin Wu, Bangjian Zhou, Zhiguang Cao, Wen Song, Yingqian Zhang, Senthilnath Jayavelu

Research Collection School Of Computing and Information Systems

Existing neural heuristics often train a deep architecture from scratch for each specific vehicle routing problem (VRP), ignoring the transferable knowledge across different VRP variants. This paper proposes the cross-problem learning to assist heuristics training for different downstream VRP variants. Particularly, we modularize neural architectures for complex VRPs into 1) the backbone Transformer for tackling the travelling salesman problem (TSP), and 2) the additional lightweight modules for processing problem-specific features in complex VRPs. Accordingly, we propose to pre-train the backbone Transformer for TSP, and then apply it in the process of fine-tuning the Transformer models for each target VRP variant. …

Hierarchical Neural Constructive Solver For Real-World Tsp Scenarios, Yong Liang Goh, Zhiguang Cao, Yining Ma, Yanfei Dong, Mohammed Haroon Dupty, Wee Sun Lee

Research Collection School Of Computing and Information Systems

Existing neural constructive solvers for routing problems have predominantly employed transformer architectures, conceptualizing the route construction as a set-to-sequence learning task. However, their efficacy has primarily been demonstrated on entirely random problem instances that inadequately capture real-world scenarios. In this paper, we introduce realistic Traveling Salesman Problem (TSP) scenarios relevant to industrial settings and derive the following insights: (1) The optimal next node (or city) to visit often lies within proximity to the current node, suggesting the potential benefits of biasing choices based on current locations. (2) Effectively solving the TSP requires robust tracking of unvisited nodes and warrants succinct …

Investigations Of Sulfurized Polymers For Their Use In Lithium-Sulfur Cells, Alan M. Rowland

All Theses

With the invention of the Lithium-Ion cell in the latter half of the 20th century, there has been a continued endeavor for innovation in compact energy-storage. Combined with the ever-growing need to move away from fossil fuels, electrochemical energy storage has seen a myriad of research projects in the pursuit of finding the ‘beyond-lithium’ cell. One of these projects that I personally assisted with was lithium-sulfur cells, which allow for a significantly greater energy storage capacity when compared to lithium-ion cells. In investigating a popular cathode in lithium-sulfur cells, sulfurized polyacrylonitrile (SPAN), it was hinted that there may be more …

Cohen-Macaulay Type Of Open Neighborhood Ideals Of Unmixed Trees, Jounglag Lim

All Theses

Given a tree T and a field k, we define the open neighborhood ideal N(T) of T in k[V] to be the ideal generated by the open neighborhoods of all vertices in the graph. If T is unmixed with respect to the total domination problem, then it is known that N(T) is Cohen-Macaulay. Our goal is to compute the (Cohen-Macaulay) type of k[V]/N(T) using graph theoretical properties of T. We achieve this by using homological algebra and properties of monomial ideals. Along the way, we also provide a different characterization of unmixed trees and a generalization of the total dominating …