Physical Sciences and Mathematics Commons^™

Powerful Radio Sources In The Southern Sky. Iii. First Results Of The Optical Spectroscopic Campaign, A. García-Pérez, H. A. Peña-Herazo, A. Jimenez-Gallardo, V. Chavushyan, F. Massaro, S. V. White, A. Capetti, B. Balmaverde, W. R. Forman, Juan P. Madrid

Physics and Astronomy Faculty Publications and Presentations

We recently built the G4Jy-3CRE catalog of extragalactic radio sources. This catalog lists 264 powerful radio sources selected with similar criteria to those of the revised Third Cambridge Catalog, but visible from the Southern Hemisphere. A literature search revealed that 119 sources in the G4Jy-3CRE catalog (i.e., 45%) lack a firm spectroscopic redshift measurement. Here, we present a campaign aimed at acquiring optical spectra of G4Jy-3CRE sources and measuring their redshifts. We used single-slit observations obtained with the Víctor Blanco Telescope, the New Technology Telescope, the Southern Astrophysical Research Telescope, and the 2.1 m telescope of the Observatorio Astronómico Nacional …

Non-Monotonic Generation Of Knowledge Paths For Context Understanding, Pei-Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Knowledge graphs can be used to enhance text search and access by augmenting textual content with relevant background knowledge. While many large knowledge graphs are available, using them to make semantic connections between entities mentioned in the textual content remains to be a difficult task. In this work, we therefore introduce contextual path generation (CPG) which refers to the task of generating knowledge paths, contextual path, to explain the semantic connections between entities mentioned in textual documents with given knowledge graph. To perform CPG task well, one has to address its three challenges, namely path relevance, incomplete knowledge graph, and …

High-Precision U-Pb Geochronology Links Magmatism In The Southwestern Laurentia Large Igneous Province And Midcontinent Rift, M. T. Mohr, M. D. Schmitz, N. L. Swanson-Hysell, K. E. Karlstrom, F. A. Macdonald, M. E. Holland, Y. Zhang, N. S. Anderson

Geosciences Faculty Publications and Presentations

The Southwestern Laurentia large igneous province (SWLLIP) comprises voluminous, widespread ca 1.1 Ga magmatism in the southwestern United States and northern Mexico. The timing and tempo of SWLLIP magmatism and its relationship to other late Mesoproterozoic igneous provinces have been unclear due to difficulties in dating mafic rocks at high precision. New precise U-Pb zircon dates for comagmatic felsic segregations within mafic rocks reveal distinct magmatic episodes at ca. 1098 Ma (represented by massive sills in Death Valley, California, the Grand Canyon, and central Arizona) and ca. 1083 Ma (represented by the Cardenas Basalts in the Grand Canyon and a …

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 …

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 …

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 …

Supply Is Not Limulus: Research Review Of Horseshoe Crab Conservation In The Face Of Intense Pharmaceutical Demand, Zoya Galeev

University Honors Theses

Horseshoe crabs are being used by the pharmaceutical industry to conduct endotoxin tests using LAL derived from the organism’s blood to ensure safe medical practice. Their annual collection and bleeding, while not always leading to mortality, affects horseshoe crab behavior and health. This research seeks to understand how the American horseshoe crab, L. polyphemus, is being used by pharmaceutical agencies and the implications that their harvesting has on the industry and the conservation of the species. Studies were collected from the past decade across two databases, Web of Science (WOS) and PubMed, to assess present conservation techniques to reduce …

Future-Proofing The Past: Artificial Intelligence In The Restoration Of Andalusian Architectural Heritage: A Case Study Of The Alhambra Palace, Granada, Spain, Kholoud Bader Hasan Ghaith

Theses

This thesis explains the contribution of artificial intelligence in heritage restoration as an icon of Andalusian architecture by using the Alhambra as an example. The task of sustaining heritage is increasing dramatically due to the accumulation of heritage assets and the need for modern and innovative operations to cope with preservation tasks. Therefore, this thesis reviews the role of artificial intelligence in improving the restoration operation to improve accuracy and efficiency. I applied the case study as a scientific methodology to explain this work to overcome scientific and subjective obstacles, such as scarce data and software integration while explaining the …

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 …

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.

Screening Through A Broad Pool: Towards Better Diversity For Lexically Constrained Text Generation, Changsen Yuan, Heyan Huang, Yixin Cao, Qianwen Cao

Research Collection School Of Computing and Information Systems

Lexically constrained text generation (CTG) is to generate text that contains given constrained keywords. However, the text diversity of existing models is still unsatisfactory. In this paper, we propose a lightweight dynamic refinement strategy that aims at increasing the randomness of inference to improve generation richness and diversity while maintaining a high level of fluidity and integrity. Our basic idea is to enlarge the number and length of candidate sentences in each iteration, and choose the best for subsequent refinement. On the one hand, different from previous works, which carefully insert one token between two words per action, we insert …

Navigating Sustainable Futures, Franziska Zimmermann

Asian Management Insights

A leadership imperative.

Hello, Jarvis, Archan Misra

Asian Management Insights

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

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.

Investigating Communication Of Findings In Environmental Impact Assessment And Developing A Research Agenda For Improvement, Alan Bond, Francois Retief, Angus Morrison-Saunders, Jenny Pope, Reece C. Alberts, Claudine Roos, Dirk Cilliers

Research outputs 2022 to 2026

Environmental Impact Assessment (EIA) aims to embed consideration of the significance of predicted environmental consequences (the findings) of proposed developments into approval decision making. Achieving this aim relies on adequate communication of the findings of the EIA to the stakeholders, especially the decision makers responsible for the approval decision. However, the naïve assumption that this communication of findings can be effectively achieved through the publication of a written report pervades legislation worldwide, despite decades of evidence to the contrary. As a first step towards improving such communication, this research identifies the contingent conditions associated with effectively transferring EIA findings from …

Conditional Neural Heuristic For Multiobjective Vehicle Routing Problems, Mingfeng Fan, Yaoxin Wu, Zhiguang Cao, Wen Song, Guillaume Sartoretti, Huan Liu, Guohua Wu

Research Collection School Of Computing and Information Systems

Existing neural heuristics for multiobjective vehicle routing problems (MOVRPs) are primarily conditioned on instance context, which failed to appropriately exploit preference and problem size, thus holding back the performance. To thoroughly unleash the potential, we propose a novel conditional neural heuristic (CNH) that fully leverages the instance context, preference, and size with an encoder–decoder structured policy network. Particularly, in our CNH, we design a dual-attention-based encoder to relate preferences and instance contexts, so as to better capture their joint effect on approximating the exact Pareto front (PF). We also design a size-aware decoder based on the sinusoidal encoding to explicitly …

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 …

Hypergraphs With Attention On Reviews For Explainable Recommendation, Theis E. Jendal, Trung Hoang Le, Hady Wirawan Lauw, Matteo Lissandrini, Peter Dolog, Katja Hose

Research Collection School Of Computing and Information Systems

Given a recommender system based on reviews, the challenges are how to effectively represent the review data and how to explain the produced recommendations. We propose a novel review-specific Hypergraph (HG) model, and further introduce a model-agnostic explainability module. The HG model captures high-order connections between users, items, aspects, and opinions while maintaining information about the review. The explainability module can use the HG model to explain a prediction generated by any model. We propose a path-restricted review-selection method biased by the user preference for item reviews and propose a novel explanation method based on a review graph. Experiments on …

Community Similarity Based On User Profile Joins, Konstantinos Theocharidis, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Similarity joins on multidimensional data are crucial operators for recommendation purposes. The classic ��-join problem finds all pairs of points within �� distance to each other among two ��-dimensional datasets. In this paper, we consider a novel and alternative version of ��-join named community similarity based on user profile joins (CSJ). The aim of CSJ problem is, given two communities having a set of ��-dimensional users, to find how similar are the communities by matching every single pair of users (a user can be matched with at most one other user) having an absolute difference of at most �� per …

Revisiting The Markov Property For Machine Translation, Cunxiao Du, Hao Zhou, Zhaopeng Tu, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper, we re-examine the Markov property in the context of neural machine translation. We design a Markov Autoregressive Transformer (MAT) and undertake a comprehensive assessment of its performance across four WMT benchmarks. Our findings indicate that MAT with an order larger than 4 can generate translations with quality on par with that of conventional autoregressive transformers. In addition, counter-intuitively, we also find that the advantages of utilizing a higher-order MAT do not specifically contribute to the translation of longer sentences.

On The Effects Of Information Asymmetry In Digital Currency Trading, Kwansoo Kim, Robert John Kauffman

Research Collection School Of Computing and Information Systems

We report on two studies that examine how social sentiment influences information asymmetry in digital currency markets. We also assess whether cryptocurrency can be an investment vehicle, as opposed to only an instrument for asset speculation. Using a dataset on transactions from an exchange in South Korea and sentiment from Korean social media in 2018, we conducted a study of different trading behavior under two cryptocurrency trading market microstructures: a bid-ask spread dealer's market and a continuous trading buy-sell, immediate trade execution market. Our results highlight the impacts of positive and negative trader social sentiment valences on the effects of …

Monocular Bev Perception Of Road Scenes Via Front-To-Top View Projection, Wenxi Liu, Qi Li, Weixiang Yang, Jiaxin Cai, Yuanhong Yu, Yuexin Ma, Shengfeng He, Jia Pan

Research Collection School Of Computing and Information Systems

HD map reconstruction is crucial for autonomous driving. LiDAR-based methods are limited due to expensive sensors and time-consuming computation. Camera-based methods usually need to perform road segmentation and view transformation separately, which often causes distortion and missing content. To push the limits of the technology, we present a novel framework that reconstructs a local map formed by road layout and vehicle occupancy in the bird's-eye view given a front-view monocular image only. We propose a front-to-top view projection (FTVP) module, which takes the constraint of cycle consistency between views into account and makes full use of their correlation to strengthen …

Stopguess: A Framework For Public-Key Authenticated Encryption With Keyword Search, Tao Xiang, Zhongming Wang, Biwen Chen, Xiaoguo Li, Peng Wang, Fei Chen

Research Collection School Of Computing and Information Systems

Public key encryption with keyword search (PEKS) allows users to search on encrypted data without leaking the keyword information from the ciphertexts. But it does not preserve keyword privacy within the trapdoors, because an adversary (e.g., untrusted server) might launch inside keyword-guessing attacks (IKGA) to guess keywords from the trapdoors. In recent years, public key authenticated encryption with keyword search (PAEKS) has become a promising primitive to counter the IKGA. However, existing PAEKS schemes focus on the concrete construction of PAEKS, making them unable to support modular construction, intuitive proof, or flexible extension. In this paper, our proposal called “StopGuess” …

Transiam: Aggregating Multi-Modal Visual Features With Locality For Medical Image Segmentation, Xuejian Li, Shiqiang Ma, Junhai Xu, Jijun Tang, Shengfeng He, Fei Guo

Research Collection School Of Computing and Information Systems

Automatic segmentation of medical images plays an important role in the diagnosis of diseases. On single-modal data, convolutional neural networks have demonstrated satisfactory performance. However, multi-modal data encompasses a greater amount of information rather than single-modal data. Multi-modal data can be effectively used to improve the segmentation accuracy of regions of interest by analyzing both spatial and temporal information. In this study, we propose a dual-path segmentation model for multi-modal medical images, named TranSiam. Taking into account that there is a significant diversity between the different modalities, TranSiam employs two parallel CNNs to extract the features which are specific to …

Simulated Annealing With Reinforcement Learning For The Set Team Orienteering Problem With Time Windows, Vincent F. Yu, Nabila Y. Salsabila, Shih-W Lin, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This research investigates the Set Team Orienteering Problem with Time Windows (STOPTW), a new variant of the well-known Team Orienteering Problem with Time Windows and Set Orienteering Problem. In the STOPTW, customers are grouped into clusters. Each cluster is associated with a profit attainable when a customer in the cluster is visited within the customer's time window. A Mixed Integer Linear Programming model is formulated for STOPTW to maximizing total profit while adhering to time window constraints. Since STOPTW is an NP-hard problem, a Simulated Annealing with Reinforcement Learning (SARL) algorithm is developed. The proposed SARL incorporates the core concepts …

Fixing Your Own Smells: Adding A Mistake-Based Familiarization Step When Teaching Code Refactoring, Ivan Wei Han Tan, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

Programming problems can be solved in a multitude of functionally correct ways, but the quality of these solutions (e.g. readability, maintainability) can vary immensely. When code quality is poor, symptoms emerge in the form of 'code smells', which are specific negative characteristics (e.g. duplicate code) that can be resolved by applying refactoring patterns. Many undergraduate computing curricula train students on this software engineering practice, often doing so via exercises on unfamiliar instructor-provided code. Our observation, however, is that this makes it harder for novices to internalise refactoring as part of their own development practices. In this paper, we propose a …

Ditmos: Delving Into Diverse Tiny-Model Selection On Microcontrollers, Xiao Ma, Shengfeng He, Hezhe Qiao, Dong Ma

Research Collection School Of Computing and Information Systems

Enabling efficient and accurate deep neural network (DNN) inference on microcontrollers is non-trivial due to the constrained on-chip resources. Current methodologies primarily focus on compressing larger models yet at the expense of model accuracy. In this paper, we rethink the problem from the inverse perspective by constructing small/weak models directly and improving their accuracy. Thus, we introduce DiTMoS, a novel DNN training and inference framework with a selectorclassifiers architecture, where the selector routes each input sample to the appropriate classifier for classification. DiTMoS is grounded on a key insight: a composition of weak models can exhibit high diversity and the …

T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng

Research Collection School Of Computing and Information Systems

Taxi drivers often take much time to navigate the streets to look for passengers, which leads to high vacancy rates and wasted resources. Empty taxi cruising remains a big concern for taxi companies. Analyzing the pick-up point selection behavior can solve this problem effectively, providing suggestions for taxi management and dispatch. Many studies have been devoted to analyzing and recommending hotspot regions of pick-up points, which can make it easier for drivers to pick-up passengers. However, the selection of pick-up points is complex and affected by multiple factors, such as convenience and traffic management. Most existing approaches cannot produce satisfactory …

Ionization Cross Sections Of Hydrogen Molecule By Electron And Positron Impact, Károly Tőkési, Robert D. Dubois

Physics Faculty Research & Creative Works

We Present Ionization Cross Sections of Hydrogen Molecules by Electron and Positron Impact for Impact Energies between 20 and 1000 EV. a Three-Body Classical Trajectory Monte Carlo Approximation is Applied to Mimic the Collision System. in This Approach, the H2 Molecule is Modeled by a Hydrogen-Type Atom with One Active Electron Bound to a Central Core of Effective Charge with an Effective Binding Energy. Although This Model is Crude for Describing a Hydrogen Molecule, We Found that the Total Cross Sections for Positron Impact Agree Reasonably Well with the Experimental Data. for the Electron Impact, Our Calculated Cross Sections Are …