Physical Sciences and Mathematics Commons^™

Cognitive Technologies, Tom Davenport

Asian Management Insights

AI and the revolution of work.

Professor Tom Davenport, the President’s Distinguished Professor of Information Technology and Management at Babson College, speaks about how companies can integrate generative Artificial Intelligence (GenAI) into their operations while ensuring workforce adaptation and skills development.

Water Current, Volume 56, No. 2, Summer 2024

Water Current Newsletter

No abstract provided.

Tribocorrosion And Metal Release From Austenitic Stainless Steels 304 And 201 In Simulated Cassava Food Contact, Robert Addai, Temitope E. Olowoyo, Thalia E. Standish, Jeffrey Daniel Henderson, Ubong Eduok, Yolanda Hedberg

Chemistry Publications

Cassava is the third most significant calorie source in the tropics. Its processing has changed from traditional methods to stainless steel processing machines. This study investigated the influence of cassava on metal release from two common stainless steels, ASTM 304 and 201, with and without friction, and on tribocorrosion (multianalytically) of 304. Cassava was relatively corrosive and hindered repassivation of the surface oxide of stainless steel, but it also acted as a lubricant against mechanical friction. The combined action of friction and cassava caused a significant increase in iron, chromium, nickel, and manganese release from the stainless steels (30–35- fold …

Compiler-Provenance Identification In Obfuscated Binaries Using Vision Transformers, Wasif Khan, Saed Alrabaee, Mousa Al-Kfairy, Jie Tang, Kim Kwang Raymond Choo

All Works

Extracting compiler-provenance-related information (e.g., the source of a compiler, its version, its optimization settings, and compiler-related functions) is crucial for binary-analysis tasks such as function fingerprinting, detecting code clones, and determining authorship attribution. However, the presence of obfuscation techniques has complicated the efforts to automate such extraction. In this paper, we propose an efficient and resilient approach to provenance identification in obfuscated binaries using advanced pre-trained computer-vision models. To achieve this, we transform the program binaries into images and apply a two-layer approach for compiler and optimization prediction. Extensive results from experiments performed on a large-scale dataset show that the …

Torus Surgery, Fibrations, Multisections, And Spun 4-Manifolds, Nicholas Paul Meyer

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–

A compact n-manifold X is fibered if it is a fiber bundle where the fiber F and base space B are manifolds. Fibered manifolds are particularly nice, as they are essentially classified by their monodromy maps. Two common examples of 4-dimensional fibered manifolds are surface bundles over surfaces and 3-manifold bundles over the circle.

The main focus of this dissertation is to investigate fibered 4-manifolds whose boundaries are the 3-torus and how these manifolds glue together to give new closed, fibered 4-manifolds. In particular, suppose W is diffeomorphic to S¹ × E_Y (K) where Y …

Nonlocal Frameworks For Nonlinear Conservation Laws And Advection-Diffusion Processes, Anh Thuong Vo

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–

Conservation laws are fundamental principles that play an important role in modeling various phenomena in physics, chemistry, and biology. However, their limitations, such as the development of shocks despite smooth initial conditions, are well known. The nonlocal model framework can be used to overcome these challenges. Nonlocal frameworks utilize integral operators that mimic differential operators but also incorporate long-range interactions within a finite horizon. This approach not only allows for non-smooth solutions, but also provides flexibility in modeling different phenomena. This study investigates the convergence of nonlocal divergence operators, defined with a general flux density function, to their classical counterparts. …

Exploring Producers' Willingness To Pay For Ecosystem Services: Three Essays On Soil Health, Location Preferences, And Cover Crop Adoption, Kaouter Essakkat

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–

This dissertation comprises three essays: one assessing Midwest producers' willingness-to-pay (WTP) for soil health-enhancing ecosystem services (ES), another examining the impact of policy implementation locations on WTP, and a third identifying factors influencing producers' adoption of cover crops (CC).

The first essay pioneers the understanding of agricultural producers’ valuation of soil health-associated ES amid growing concerns of soil degradation due to agricultural intensification. Using a discrete choice experiment, this study assesses producers’ WTP for a policy that incentivizes ES provision, specifically improved water quality, carbon sequestration, and enhanced crop yield. Surveying producers across Iowa, Kansas, and Nebraska, our results show …

A Study Of Electron- And Photon-Induced Dissociative Electron Attachment To Molecules And Within Anion-Molecule Clusters, Mahmudul Hasan

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–

Dissociative electron attachment (DEA) is a resonant process in which a molecule captures a low-energy electron, forming a transient negative ion (TNI). Subsequently, this unstable TNI fragments into a stable anion and one or more neutral fragments. DEA is crucial in various phenomena, ranging from atmospheric and radiation chemistry to processes occurring in plasmas, and is particularly significant in the context of radiation-induced damage to biological molecules. This study uses different experimental methods to better understand the fragmentation in molecular anions forming through dissociative photoexcitation and electron attachment. We have developed an experimental apparatus for dissociative photoexcitation studies. This apparatus …

Stochastic Dominance: Cases Of Interval And P-Box Uncertainty, Kittawit Autchariyapanikul, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditional decision theory recommendation about making a decision assume that we know both the probabilities of different outcomes of each possible decision, and we know the utility function -- that describes the decision maker's preferences. Sometimes, we can make a recommendation even when we only have partial information about utility. Such cases are known as cases of stochastic dominance. In other cases, in addition to not knowing the utility function, we also only have partial information about the probabilities of different outcomes. For example, we may only known bounds on the outcomes (case of interval uncertainty) or bounds on the …

If Subsequent Results Are Too Easy To Obtain, The Proof Most Probably Has Errors: Explanation Of The Empirical Observation, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Many modern mathematical proofs are very complex, checking them is difficult; as a result, errors sneak into published proofs, even into proofs published in highly reputable journals. Sometimes, the errors are repairable, but sometimes, it turns out that the supposedly proven result is actually wrong. When the error is not noticed for some time, the published result is used to prove many other results -- and when the error is eventually found, all these new results are invalidated. This happened several times. Since it is not realistic to more thoroughly check all the proofs, and we want to minimize the …

For 2 X N Cases, Proportional Fitting Problem Reduces To A Single Equation, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, for each of two classifications, we know the probabilities that a randomly selected object belong to different categories. For example, we know what proportion of people are below 20 years old, what proportion is between 20 and 30, etc., and we also know what proportion of people earns less than 10K, between 10K and 20K, etc. In such situations, we are often interested in proportion of people who are classified by two classifications into two given categories. For example, we are interested in the proportion of people whose age is between 20 and 30 and whose …

Is Alaska Negative-Tax Arrangement Fair? Almost: Mathematical Analysis, Chon Van Le, Vladik Kreinovich

Departmental Technical Reports (CS)

In the State of Alaska there is no state income tax. Instead, there is a negative tex: every year every resident gets some money from the state. At present, every resident -- from the poorest to the richest -- gets the exact same amount of money: in 2024, it is expected to be around $1500. A natural question is: Is this fair? Maybe poor people should get more since their needs are greater? Maybe the rich people should get proportionally more, since fairness means equal added happiness for all, and for rich people, extra $1500 is barely noticeable? There have …

Why Angles Between Galactic Center Filaments And Galactic Plane Follow A Bimodal Distribution: A Symmetry-Based Explanation, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

Recent observations have shown that the angles between the Galaxy Center filaments and the Galactic plane follow a bimodal distribution: a large number of filaments are approximately orthogonal to the Galactic plane, a large number of filaments are approximately parallel to the Galactic plane, and much fewer filaments have other orientations. In this paper, we show this bimodal distribution can be explained by natural geometric symmetries.

Why Seismicity In Ireland Is Low: A Possible Geometric Explanation, Julio C. Urenda, Aaron Velasco, Vladik Kreinovich

Departmental Technical Reports (CS)

For each geographic location, its seismicity level is usually determined by how close this location is to the boundaries of tectonic plates. However, there is one notable exception: while Ireland and Britain are at approximately the same distance from such boundaries, the seismicity level in Ireland is much lower than in Britain. A recent paper provided a partial explanation for this phenomenon: namely, it turns out that the lithosphere under Ireland is unusually thick, and this can potentially lead to lower seismicity. However, the current explanation of the relation between the lithosphere thickness and seismicity level strongly depends on the …

Green Finance Growth Prediction Model Based On Time-Series Conditional Generative Adversarial Networks, Aya Salama Abdelhady, Nadia Dahmani, Lobna M. Abouel-Magd, Ashraf Darwish, Aboul Ella Hassanien

All Works

Climate change mitigation necessitates increased investment in green sectors. This study proposes a methodology to predict green finance growth across various countries, aiming to encourage such investments. Our approach leverages time-series Conditional Generative Adversarial Networks (CT-GANs) for data augmentation and Nonlinear Autoregressive Neural Networks (NARNNs) for prediction. The green finance growth predicting model was applied to datasets collected from forty countries across five continents. The Augmented Dickey-Fuller (ADF) test confirmed the non-stationary nature of the data, supporting the use of Nonlinear Autoregressive Neural Networks (NARNNs). CT-GANs were then employed to augment the data for improved prediction accuracy. Results demonstrate the …

Generalized Optimal Transport And Mean Field Control Problems For Reaction-Diffusion Systems With High-Order Finite Element Computation, Guosheng Fu, Stanley Osher, Will Pazner, Wuchen Li

Mathematics and Statistics Faculty Publications and Presentations

We design and compute a class of optimal control problems for reaction-diffusion systems. They form mean field control problems related to multi-density reaction-diffusion systems. To solve proposed optimal control problems numerically, we first apply high-order finite element methods to discretize the space-time domain and then solve the optimal control problem using augmented Lagrangian methods (ALG2). Numerical examples, including generalized optimal transport and mean field control problems between Gaussian distributions and image densities, demonstrate the effectiveness of the proposed modeling and computational methods for mean field control problems involving reaction-diffusion equations/systems.

Quasi – Monte Carlo Estimation For Functional Generalized Linear Mixed Models, Ruvini Jayamaha

Waldo Library Student Exhibits

Functional Data Analysis (FDA) is a topic of growing interest in the Statistics community. The data in FDA are smooth curves or surfaces in time or space which can be conceptualized as functions.

We propose a Functional Generalized Linear Mixed Model (FGLMM) to fit EEG data and estimate the parameters using Quasi-Monte Carlo Method.

This proposed model deals with non-Gaussian scalar response, functional predictor, and random effects. We relax the assumption of link and variance functions.

The Analysis Of Artificially Flavored Coffees, Hannah Knights

Longwood Senior Thesis Proposal

This project aims to determine the molecular components that give artificially flavored coffees their advertised flavor. Much work has been conducted to determine various characteristics such as antioxidant properties, phenolic compounds, flavors, and aromas found in natural coffees. In addition, there is ample literature on the results of sensory tests for a variety of commercial coffees. However, not much work has been conducted to determine the compounds found in artificially flavored coffees that give rise to their distinctive aroma and flavor. This is, perhaps, due to the proprietary nature of the flavoring process employed by commercial producers. The goal of …

Contextualizing Interpersonal Data Sharing In Smart Homes, Weijia He, Nathan Reitinger, Atheer Almogbil, Yi-Shyuan Chiang, Timothy J. Pierson, David Kotz

Dartmouth Scholarship

A key feature of smart home devices is monitoring the environment and recording data. These devices provide security via motion-detection video alerts, cost-savings via thermostat usage history, and peace of mind via functions like auto-locking doors or water leak detectors. At the same time, the sharing of this information in interpersonal relationships---though necessary---is currently accomplished on an all-or-nothing basis. This can easily lead to oversharing in a multi-user environment. Although prior work has studied people's perceptions of information sharing with vendors or ISPs, the sharing of household data among users who interact personally is less well understood. Interpersonal situations make …

Mega-Influencers And Brand Dynamics: Shaping Attitudes Toward Leading And Challenger Brandsthrough Electronic Word Of Mouth, Riccardo Rialto, Lamberto Zollo, Kacy Kim, Sukki Yoon

Mathematics and Economics Faculty Journal Articles

The aim of this paper is to explore how mega‐influencers' electronic word of mouth (eWOM) messages on social media influence consumers' brand attitudes in duopolistic markets. Through three experimental studies, we observe that when mega‐ influencers send positive (vs. negative) eWOM messages about a leading brand, followers form positive (vs. negative) brand attitudes, but these effects fail to occur when influencers back challenger brands. The findings are consistent across three duopolistic market rivals (Apple vs. Samsung; UPS vs. FedEx; Nike vs. Adidas), three social media platforms (Facebook, Instagram, and X), and four mega‐influencers (Marques Brownlee, Gary Vaynerchuk, Kanye West, and …

Search For Gravitational-Lensing Signatures In The Full Third Observing Run Of The Ligo–Virgo Network, R. Abbott, H. Abe, F. Acernese, Teviet Creighton, Mario C. Diaz, Francisco Llamas, Soma Mukherjee, Gaukhar Nurbek, Volker Quetschke, Wenhui Wang

Physics and Astronomy Faculty Publications and Presentations

Gravitational lensing by massive objects along the line of sight to the source causes distortions to gravitational wave (GW) signals; such distortions may reveal information about fundamental physics, cosmology, and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO-Virgo network. We search for repeated signals from strong lensing by (1) performing targeted searches for subthreshold signals, (2) calculating the degree of overlap among the intrinsic parameters and sky location of pairs of signals, (3) comparing the similarities of the spectrograms among pairs of …

2024 July - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

Ocular Gene Transfer In The Spotlight: Implications Of Newspaper Content For Clinical Communications, Shelly Benjaminy, Tania M. Bubela

Office of the Provost

Background: Ocular gene transfer clinical trials are raising hopes for blindness treatments and attracting media attention. News media provide an accessible health information source for patients and the public, but are often criticized for overemphasizing benefits and underplaying risks of novel biomedical interventions. Overly optimistic portrayals of unproven interventions may influence public and patient expectations; the latter may cause patients to downplay risks and over-emphasize benefits, with implications for informed consent for clinical trials. We analyze the news media communications landscape about ocular gene transfer and make recommendations for improving communications between clinicians and potential trial participants in light of …

A Class Of Stable Nonlinear Non-Hermitian Skin Modes, Hamed Ghaemi-Dizicheh

Physics and Astronomy Faculty Publications and Presentations

The non-Hermitian skin effect (NHSE) is a well-known phenomenon in open topological systems that causes a large number of eigenstates to become localized at the boundary. Although many aspects of its theory have been investigated in linear systems, this phenomenon remains novel in nonlinear models. In the first step of this paper, we look at the conditions for the presence of quasi-skin modes in a semi-infinite, one-dimensional, nonlinear, nonreciprocal lattice. In the following phase, we explore the survival time of the quasi-skin mode in a finite nonlinear lattice with open edges. We study the dependency of the survival time on …

Unveiling The Dynamics Of Crisis Events: Sentiment And Emotion Analysis Via Multi-Task Learning With Attention Mechanism And Subject-Based Intent Prediction, Phyo Yi Win Myint, Siaw Ling Lo, Yuhao Zhang

Research Collection School Of Computing and Information Systems

In the age of rapid internet expansion, social media platforms like Twitter have become crucial for sharing information, expressing emotions, and revealing intentions during crisis situations. They offer crisis responders a means to assess public sentiment, attitudes, intentions, and emotional shifts by monitoring crisis-related tweets. To enhance sentiment and emotion classification, we adopt a transformer-based multi-task learning (MTL) approach with attention mechanism, enabling simultaneous handling of both tasks, and capitalizing on task interdependencies. Incorporating attention mechanism allows the model to concentrate on important words that strongly convey sentiment and emotion. We compare three baseline models, and our findings show that …

Hierarchical Damage Correlations For Old Photo Restoration, Weiwei Cai, Xuemiao Xu, Jiajia Xu, Huaidong Zhang, Haoxin Yang, Kun Zhang, Shengfeng He

Research Collection School Of Computing and Information Systems

Restoring old photographs can preserve cherished memories. Previous methods handled diverse damages within the same network structure, which proved impractical. In addition, these methods cannot exploit correlations among artifacts, especially in scratches versus patch-misses issues. Hence, a tailored network is particularly crucial. In light of this, we propose a unified framework consisting of two key components: ScratchNet and PatchNet. In detail, ScratchNet employs the parallel Multi-scale Partial Convolution Module to effectively repair scratches, learning from multi-scale local receptive fields. In contrast, the patch-misses necessitate the network to emphasize global information. To this end, we incorporate a transformer-based encoder and decoder …

Comparative Analysis Of Hate Speech Detection: Traditional Vs. Deep Learning Approaches, Haibo Pen, Nicole Anne Huiying Teo, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Detecting hate speech on social media poses a significant challenge, especially in distinguishing it from offensive language, as learning-based models often struggle due to nuanced differences between them, which leads to frequent misclassifications of hate speech instances, with most research focusing on refining hate speech detection methods. Thus, this paper seeks to know if traditional learning-based methods should still be used, considering the perceived advantages of deep learning in this domain. This is done by investigating advancements in hate speech detection. It involves the utilization of deep learning-based models for detailed hate speech detection tasks and compares the results with …

Performance Analysis Of Llama 2 Among Other Llms, Donghao Huang, Zhenda Hu, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Llama 2, an open-source large language model developed by Meta, offers a versatile and high-performance solution for natural language processing, boasting a broad scale, competitive dialogue capabilities, and open accessibility for research and development, thus driving innovation in AI applications. Despite these advancements, there remains a limited understanding of the underlying principles and performance of Llama 2 compared with other LLMs. To address this gap, this paper presents a comprehensive evaluation of Llama 2, focusing on its application in in-context learning — an AI design pattern that harnesses pre-trained LLMs for processing confidential and sensitive data. Through a rigorous comparative …

Generative Ai For Pull Request Descriptions: Adoption, Impact, And Developer Interventions, Tao Xiao, Hideaki Hata, Christoph Treude, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

GitHub's Copilot for Pull Requests (PRs) is a promising service aiming to automate various developer tasks related to PRs, such as generating summaries of changes or providing complete walkthroughs with links to the relevant code. As this innovative technology gains traction in the Open Source Software (OSS) community, it is crucial to examine its early adoption and its impact on the development process. Additionally, it offers a unique opportunity to observe how developers respond when they disagree with the generated content. In our study, we employ a mixed-methods approach, blending quantitative analysis with qualitative insights, to examine 18,256 PRs in …

A Bottom-Up Multi-Disciplinary Approach For Sustainability Education: Un-Sdg 13.3, Benjamin Gan, Thomas Menkhoff, Eng Lieh Ouh, Kevin Cheong

Research Collection School Of Computing and Information Systems

Teaching both information systems and business undergraduates to break the current inertia in sustainability action requires innovative teaching & learning approaches as well as inter-disciplinary knowledge inputs. This study presents a bottom-up T&L approach delivered by a group of educators from different disciplines aimed at addressing UN-SDG Goal 13 ‘Climate Action’ with a novel approach. Integrating a problem-centric community project assignment into existing courses, our students worked on different disciplinary elements such as persuasive technologies and awareness campaigns to help to address local sustainability initiatives by community partners. We collected data to measure how students’ motivation, engagement, teamwork, and community …