Physical Sciences and Mathematics Commons^™

Editorial: Innovating A New Knowledge Base For Water Justice Studies: Hydrosocial, Sociohydrology, And Beyond, Melissa Haeffner, Jenia Mukherjee, Rebecca Lave, Jamie Linton, John Ndiritu, Raul Pacheco-Vega, Maria Ruska, Margreet Zwarteveen

Environmental Science and Management Faculty Publications and Presentations

Creating a new knowledge base that centers water justice (Zwarteveen and Boelens, 2014; Sultana, 2018; Wölfle-Hazard, 2022) in hydrosocial and sociohydrology studies involves a broader discussion about why justice matters, how to work toward this goal, and what the implications for research praxis are. The articles in this Research Topic approach different angles of water justice: as law (Fernández and Alba), a social movement (Dame et al.), practice (Pool et al.; Reeves and Bonney), cases of injustice (Caretta et al.), and theory (Krueger and Alba). From this Research Topic, we find that the interrelated concepts of naturecultures and care can …

Navigating Sustainable Futures, Franziska Zimmermann

Asian Management Insights

A leadership imperative.

Maximizing The Ai Revolution In Southeast Asia, Shoeb Kagda

Asian Management Insights

For that, the region must narrow the digital divide.

Superminds At Work: The Promise Of Human-Ai Collaboration, Thomas W. Malone

Asian Management Insights

Massachusetts Institute of Technology (MIT) Center for Collective Intelligence Director Professor Thomas W. Malone’s scholarship offers deep insights into the promise afforded by the synergies between human intelligence and technology. According to Professor Malone, the boundaries between human intellect and technological prowess are becoming increasingly blurred, but this may not be a bad thing for humankind. In Asian Management Insights’ inaugural Pulse Point interview, we get to learn more about the concept of ‘collective intelligence’, which explores how a partnership between humans and Artificial Intelligence (AI) can be catalysed to make ground-breaking advancements in addressing the wicked problems of our …

Hello, Jarvis, Archan Misra

Asian Management Insights

How AI-enabled interactive agents will reshape our workforce of today and tomorrow.

Reconnecting A Stream Channel To Its Floodplain: Implications For Benthic Diatoms And Macroinvertebrate Trophic Structure, Patrick M. Edwards, Nicole C. Popp, Yangdong Pan, Christine L. Weilhoefer, Aspen Peterman, Lauren Mork, Matthew F. Johnson, Megan Colley, Multiple Additional Authors

Environmental Science and Management Faculty Publications and Presentations

Streams systems draining upland landscapes provide valuable ecosystem services, but they are vulnerable to incision and channelization caused by anthropogenic disturbance. Restoring a degraded stream to its pre-disturbance condition by reconnecting the channel to its historical floodplain aims to recover lost hydro-morphological processes and functions. Seeking evidence to indicate whether that aim is met in practice, we examined diatoms and the stream macroinvertebrate trophic structures in three reaches of Whychus Creek, Oregon, United States. Two reaches were reconnected to their pre-disturbance floodplains in 2012 and 2016. The third, control reach, was not restored and was selected to represent the degraded …

Where The Rubber Meets The Road: Emerging Environmental Impacts Of Tire Wear Particles And Their Chemical Cocktails, Paul M. Mayer, Kelly D. Moran, Susanne Brander, Stacey L. Harper, Manuel Garcia-Jaramillo, Elise F. Granek, Multiple Additional Authors

Environmental Science and Management Faculty Publications and Presentations

About 3 billion new tires are produced each year and about 800 million tires become waste annually. Global dependence upon tires produced from natural rubber and petroleum-based compounds represents a persistent and complex environmental problem with only partial and often-times, ineffective solutions. Tire emissions may be in the form of whole tires, tire particles, and chemical compounds, each of which is transported through various atmospheric, terrestrial, and aquatic routes in the natural and built environments. Production and use of tires generates multiple heavy metals, plastics, PAH's, and other compounds that can be toxic alone or as chemical cocktails. Used tires …

Why Do We Not Stand Up To Misinformation? Factors Influencing The Likelihood Of Challenging Misinformation On Social Media And The Role Of Demographics, Selin Gurgun, Deniz Cemiloglu, Emily Arden Close, Keith Phalp, Preslav Nakov, Raian Ali

Natural Language Processing Faculty Publications

This study investigates the barriers to challenging others who post misinformation on social media platforms. We conducted a survey amongst U.K. Facebook users (143 (57.2 %) women, 104 (41.6 %) men) to assess the extent to which the barriers to correcting others, as identified in literature across disciplines, apply to correcting misinformation on social media. We also group the barriers into factors and explore demographic differences amongst them. It has been suggested that users are generally hesitant to challenge misinformation. We found that most of our participants (58.8 %) were reluctant to challenge misinformation. We also identified moderating roles of …

Why Two Fish Follow Each Other But Three Fish Form A School: A Symmetry-Based Explanation, Shahnaz Shahbazova, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Recent experiments with fish has shown an unexpected strange behavior: when two fish of the same species are placed in an aquarium, they start following each other, while when three fish are placed there, they form (approximately) an equilateral triangle, and move in the direction (approximately) orthogonal to this triangle. In this paper, we use natural symmetries -- such as rotations, shifts, and permutation of fish -- to show that this observed behavior is actually optimal. This behavior is not just optimal with respect to one specific optimality criterion, it is optimal with respect to any optimality criterion -- as …

Identifying Rural Health Clinics Within The Transformed Medicaid Statistical Information System (T-Msis) Analytic Files, Katherine Ahrens Mph, Phd, Zachariah Croll, Yvonne Jonk Phd, John Gale Ms, Heidi O'Connor Ms

Rural Health Clinics

Researchers at the Maine Rural Health Research Center describe a methodology for identifying Rural Health Clinic encounters within the Medicaid claims data using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files.

Background: There is limited information on the extent to which Rural Health Clinics (RHC) provide pediatric and pregnancy-related services to individuals enrolled in state Medicaid/CHIP programs. In part this is because methods to identify RHC encounters within Medicaid claims data are outdated.

Methods: We used a 100% sample of the 2018 Medicaid Demographic and Eligibility and Other Services Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files for 20 states …

The Effect Of Internet Firms’ Data Analytics Capability On Their Innovation Speed And Innovation Quality: A Dynamic Capability Perspective, Yeyu Hua

Dissertations and Theses Collection (Open Access)

With the advent of big data era, data plays a pivotal role in sustainingfirms’ competitive advantages. Although a few studies have shown that data analytics capability contributes to firms’ innovative performance, these studies either focus on general innovative performance or specific types of innovation, such as incremental innovation, radical innovation, and supply chaininnovation. In this thesis, I enrich this stream of literature by conducting twostudies to further examine the relationship between data analytics capabilityand innovation speed as well as innovation quality. This thesis consists of twostudies. Study 1 is a survey study, in which I investigate the relationshipbetween data analytics …

Stage And Discharge Prediction From Documentary Time-Lapse Imagery, Kenneth W. Chapman, Troy E. Gilmore, Mehrube Mehrubeoglu, Christian D. Chapman, Aaron R. Mittelstet, John E. Stranzl Jr.

Conservation and Survey Division

Imagery from fixed, ground-based cameras is rich in qualitative and quantitative information that can improve stream discharge monitoring. For instance, time-lapse imagery may be valuable for filling data gaps when sensors fail and/or during lapses in funding for monitoring programs. In this study, we used a large image archive (>40,000 images from 2012 to 2019) from a fixed, ground-based camera that is part of a documentary watershed imaging project (https://plattebasintimelapse.com/). Scalar image features were extracted from daylight images taken at one-hour intervals. The image features were fused with United States Geological Survey stage and discharge data as response variables …

Marketing Video Games To Aging Demographics: A Generational Profile Analysis, Brinna Louise Ball

Theses

Marketing video games to aging demographics like Baby Boomers, Generation X, and Millennials requires a unique approach by video game studios and consumer products divisions alike. The strategies employed for younger generations such as Generation Z and Generation Alpha differ from conventional methods, requiring a fresh outlook and a need for more innovative and inventive approaches. To comprehend the current aging audience more effectively, it's essential to examine four crucial factors: accessibility, exposure, media habits, and motivations to play video games. Examining these factors by generation, we can better grasp how to effectively market video games to these demographics. It's …

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – First Quarter 2022, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Errata: Water Main Break Rates In The Usa And Canada: A Comprehensive Study, Steven Barfuss

Reports

Page 5 – Major Finding 6 (change also made in text on Page 18):

Added “in the reported pipe inventory” to better clarify the percentage reduction

Page 6 – Major Finding 14 (change also made in text on Page 31):

Changed “six” to “five” years to explain the time elapsed between the 2018 and 2023 studies

Page 7 – Major Finding 28 (change also made in text on Page 46):

Added “percentage” to better clarify the percentage of acceptance

Page 8 – Section 1.1:

Updated “(WRF, 2017)” to “(Grigg, 2007)” and “(US Conference of Mayors, 2018)” to “(Anderson, 2018)”

Page …

Math Word Problem Generation Via Disentangled Memory Retrieval, Wei Qin, Xiaowei Wang, Zhenzhen Hu, Lei Wang, Yunshi Lan, Richang Hong

Research Collection Lee Kong Chian School Of Business

The task of math word problem (MWP) generation, which generates an MWP given an equation and relevant topic words, has increasingly attracted researchers’ attention. In this work, we introduce a simple memory retrieval module to search related training MWPs, which are used to augment the generation. To retrieve more relevant training data, we also propose a disentangled memory retrieval module based on the simple memory retrieval module. To this end, we first disentangle the training MWPs into logical description and scenario description and then record them in respective memory modules. Later, we use the given equation and topic words as …

A Study On Ethical Hacking In Cybersecurity Education Within The United States, Jordan Chew

Master's Theses

As the field of computer security continues to grow, it becomes increasingly important to educate the next generation of security professionals. However, much of the current education landscape primarily focuses on teaching defensive skills. Teaching offensive security, otherwise known as ethical hacking, is an important component in the education of all students who hope to contribute to the field of cybersecurity. Doing so requires a careful consideration of what ethical, legal, and practical issues arise from teaching students skills that can be used to cause harm. In this thesis, we first examine the current state of cybersecurity education in the …

Procedures For Rangeland Condition Assessment In The Kimberley 2022, Department Of Primary Industries And Regional Development

Natural resources published reports

This report defines the procedures used in 2022 by the Department of Primary Industries and Regional Development (DPIRD) to complete rangeland condition assessment (RCA) in the Kimberley region which has grass-based pastures. For the rest of the pastoral estate, DPIRD uses the Procedures for RCA in the Pilbara and southern rangelands which have predominantly shrub pastures.

RCA is the process DPIRD uses to make systematic, lease-level assessment of rangeland. Rangeland condition considers both the condition of pastures (as defined in the Pasture condition guide for the Kimberley, Ryan et al. 2013) and soils as determined by erosion, using the …

Navigating Through Chaos, Hoong Chuin Lau

Asian Management Insights

How AI and optimisation models can strengthen supply chain resilience.

Eyris: From The Lab To The Market, Steven Miller, David Gomulya, Mahima Rao-Kachroo

Asian Management Insights

Singapore’s trailblazer AI algorithm for detecting diabetes-related eye diseases. Can you imagine getting the results of your eye disease screening within minutes rather than days? This capability is what EyRIS, a Singapore-based start-up that uses the AI (Artificial Intelligence)-driven Singapore Eye LEsion Analyzer (SELENA+) algorithm to screen for diabetes-related eye diseases, set out to productise and commercialise.

Developing Singapore As A Smart Nation, Josephine Teo

Asian Management Insights

Mrs Josephine Teo, Singapore’s Minister for Communications and Information, and Minister-in-charge of Smart Nation and Cybersecurity, speaks about leading the country’s Smart Nation drive.

Quantum Computing And U.S. Cybersecurity: A Case Study Of The Breaking Of Rsa And Plan For Cryptographic Algorithm Transition, Helena Holland

Honors Theses

The invention of a cryptographically relevant quantum computer would revolutionize computing power, transforming industry and national security. While a theoretical possibility at the time of this writing, the ability of quantum algorithms to solve the factoring and discrete logarithm problems, upon which all currently employed public-key cryptography depends, presents a serious threat to digital communications. This research examines both the mathematics and government policy behind these risks and their implications for cybersecurity. Specifically, a case study of RSA, Shor’s algorithm, and the American Intelligence Community’s plan to transition toward quantum-resistant algorithms is presented to analyze quantum threats and opportunities and …

Predictive Understanding Of Lake Water Temperature And Dissolved Oxygen Profiles Across The Red River Basin Through Interpretable Machine Learning, Isabela Suaza Sierra

Open Access Theses & Dissertations

Accurately predicting lake water temperature (LWT) and dissolved oxygen (DO) is crucial for determining threshold values of fish survivability under warmer global conditions, with recreational fishing in reservoirs significantly contributing to regional economies, such as $779 million and $1,891 million annually to the economies of Oklahoma and Texas, respectively. Current mathematical models for temperature and oxygen profiles, which incorporate multi-layer and turbulent mixing equations, are complex and challenging to parameterize, particularly due to uncertainties in acquiring sufficient data for training and validation. Leveraging the flexibility and information extraction power of machine learning (ML) methods, this master thesis aimed to set …

Field Research Report: Results From The Enreec Vri Field For The 2021, 2022, And 2023 Crop Seasons, Derek M. Heeren, Ali T. Mohammed, Eric Wilkening, Christopher M. U. Neale, Alan L. Boldt, Ankit Chandra, Precious Nneka Amori, Ivo Z. Goncalves, Yeyin Shi, Guillermo R. Balboa

Department of Biological Systems Engineering: Conference Presentations and White Papers

Long-term irrigation management research has been conducted from 2014 to 2023 for corn and soybean at the Eastern Nebraska Research, Extension, and Education Center (ENREEC) Variable Rate Irrigation (VRI) Field located in subhumid east-central Nebraska (in the Lower Platte North Natural Resources District). The objective of this report was to present the overall results from the VRI Field for 2021 to 2023. Across the three growing seasons, there were the following irrigation treatments: Best Management Practice (BMP), 50% BMP, 125% BMP, rainfed, Spatial ET Modeling Interface (SETMI), SDD1, SDD2, machine-learning-based Cyber-Physical System (CPS), a student team recommended rate, and industry …

Soil Nitrate Prediction Using Ftir-Atr, Vis-Nir, And Raman Spectroscopy, Sabiha Ferdous

Department of Biological Systems Engineering: Dissertations and Theses

Fourier transform infrared spectroscopy (FTIR) combined with Attenuated total reflectance (ATR), Visible-Near Infrared spectroscopy (Vis-NIR), and Raman spectroscopy (RS) are non-destructive techniques for rapid determination of nitrogen compounds in soil. Leveraging FTIR-ATR and Vis-NIR spectra using partial least squares regression (PLSR) modeling, the study aims to predict soil nitrate content and explored the feasibility of Raman spectroscopy to detect nitrate (NO₃^-), nitrite (NO₂^-), and ammonium (NH₄⁺) in soil. Soil samples were collected from four different fields, dried, sieved (2mm), and then used for collecting spectra (FTIR-ATR and Vis-NIR). Laboratory analysis was …

Why Linear And Sigmoid Last Layers Work Better In Classification, Lehel Dénes-Fazakas, Lásló Szilágyi, Vladik Kreinovich

Departmental Technical Reports (CS)

Usually, when a deep neural network is used to classify objects, its last layer computes the softmax. Our empirical results show we can improve the classification results if instead, we have linear or sigmoid last layer. In this paper, we provide an explanation for this empirical phenomenon.

Basecol2023 Scientific Content, Dmitri Babikov

Chemistry Faculty Research and Publications

Context. The global context of making numerous data produced by researchers available requires collecting and organising the data, assigning meaningful metadata, and presenting the data in a meaningful and homogeneous way. The BASECOL database, which collects inelastic rate coefficients for application to the interstellar medium and to circumstellar and cometary atmospheres, meets those requirements.

Aims. We aim to present the scientific content of the BASECOL2023 edition.

Methods. While the previous versions relied on finding rate coefficients in the literature, the current version is populated with published results sent by the producers of data. The paper presents the …

Knowledge Generation For Zero-Shot Knowledge-Based Vqa, Rui Cao, Jing Jiang

Research Collection School Of Computing and Information Systems

Previous solutions to knowledge-based visual question answering (K-VQA) retrieve knowledge from external knowledge bases and use supervised learning to train the K-VQA model. Recently pre-trained LLMs have been used as both a knowledge source and a zero-shot QA model for K-VQA and demonstrated promising results. However, these recent methods do not explicitly show the knowledge needed to answer the questions and thus lack interpretability. Inspired by recent work on knowledge generation from LLMs for text-based QA, in this work we propose and test a similar knowledge-generation-based K-VQA method, which first generates knowledge from an LLM and then incorporates the generated …

A Social-Aware Gaussian Pre-Trained Model For Effective Cold-Start Recommendation, Siwei Liu, Xi Wang, Craig Macdonald, Iadh Ounis

Machine Learning Faculty Publications

The use of pre-training is an emerging technique to enhance a neural model's performance, which has been shown to be effective for many neural language models such as BERT. This technique has also been used to enhance the performance of recommender systems. In such recommender systems, pre-training models are used to learn a better initialisation for both users and items. However, recent existing pre-trained recommender systems tend to only incorporate the user interaction data at the pre-training stage, making it difficult to deliver good recommendations, especially when the interaction data is sparse. To alleviate this rcommon data sparsity issue, we …

Artificial Intelligence And/Or Machine Learning (Ai &| Ml), George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

These slides are from an invited panel presentation at my home institution, Loyola University Chicago, organized by the Loyola University Chicago Retiree Association (LUCRA). I was asked to give a broad historical overview of AI and ML and speak about its societal impacts.

"The Loyola University Chicago Retiree Association embraces the Vision of Loyola University Chicago and will assist students, faculty, and administrators as they strive to serve humanity. The group values freedom of inquiry, the pursuit of truth, and care of others and embraces a commitment to excellence, service that promotes social justice, values based leadership, and global awareness."