Physical Sciences and Mathematics Commons^™

Closest Pairs Search Over Data Stream, Rui Zhu Zhu, Bin Wang, Xiaochun Yang, Baihua Zheng

Research Collection School Of Computing and Information Systems

��-closest pair (KCP for short) search is a fundamental problem in database research. Given a set of��-dimensional streaming data S, KCP search aims to retrieve �� pairs with the shortest distances between them. While existing works have studied continuous 1-closest pair query (i.e., �� = 1) over dynamic data environments, which allow for object insertions/deletions, they require high computational costs and cannot easily support KCP search with �� > 1. This paper investigates the problem of KCP search over data stream, aiming to incrementally maintain as few pairs as possible to support KCP search with arbitrarily ��. To achieve this, we …

Locality-Aware Tail Node Embeddings On Homogeneous And Heterogeneous Networks, Zemin Liu, Yuan Fang, Wentao Zhang, Xinming Zhang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

While the state-of-the-art network embedding approaches often learn high-quality embeddings for high-degree nodes with abundant structural connectivity, the quality of the embeddings for low-degree or nodes is often suboptimal due to their limited structural connectivity. While many real-world networks are long-tailed, to date little effort has been devoted to tail node embeddings. In this article, we formulate the goal of learning tail node embeddings as a problem, given the few links on each tail node. In particular, since each node resides in its own local context, we personalize the regression model for each tail node. To reduce overfitting in the …

Generalized Graph Prompt: Toward A Unification Of Pre-Training And Downstream Tasks On Graphs, Xingtong Yu, Zhenghao Liu, Yuan Fang, Et Al.

Research Collection School Of Computing and Information Systems

Graphs can model complex relationships between objects, enabling a myriad of Web applications such as online page/article classification and social recommendation. While graph neural networks (GNNs) have emerged as a powerful tool for graph representation learning, in an end-to-end supervised setting, their performance heavily relies on a large amount of task-specific supervision. To reduce labeling requirement, the 'pre-train, fine-tune' and 'pre-train, prompt' paradigms have become increasingly common. In particular, prompting is a popular alternative to fine-tuning in natural language processing, which is designed to narrow the gap between pre-training and downstream objectives in a task-specific manner. However, existing study of …

Learning Transferable Negative Prompts For Out-Of-Distribution Detection, Tianqi Li, Guansong Pang, Xiao Bai, Wenjun Miao, Jin Zheng

Research Collection School Of Computing and Information Systems

Existing prompt learning methods have shown certain capabilities in Out-of-Distribution (OOD) detection, but the lack of OOD images in the target dataset in their training can lead to mismatches between OOD images and In-Distribution (ID) categories, resulting in a high false positive rate. To address this issue, we introduce a novel OOD detection method, named ‘NegPrompt’, to learn a set of negative prompts, each representing a negative connotation of a given class label, for delineating the boundaries between ID and OOD images. It learns such negative prompts with ID data only, without any reliance on external out-lier data. Further, current …

Anomaly Heterogeneity Learning For Open-Set Supervised Anomaly Detection, Jiawen Zhu, Choubo Ding, Yu Tian, Guansong Pang

Research Collection School Of Computing and Information Systems

Open-set supervised anomaly detection (OSAD) - a recently emerging anomaly detection area - aims at utilizing a few samples of anomaly classes seen during training to detect unseen anomalies (i.e., samples from open-set anomaly classes), while effectively identifying the seen anomalies. Benefiting from the prior knowledge illustrated by the seen anomalies, current OSAD methods can often largely reduce false positive errors. However, these methods are trained in a closed-set setting and treat the anomaly examples as from a homogeneous distribution, rendering them less effective in generalizing to unseen anomalies that can be drawn from any distribution. This paper proposes to …

Drag Your Noise: Interactive Point-Based Editing Via Diffusion Semantic Propagation, Haofeng Liu, Chenshu Xu, Yifei Yang, Lihua Zeng, Shengfeng He

Research Collection School Of Computing and Information Systems

Point-based interactive editing serves as an essential tool to complement the controllability of existing generative models. A concurrent work, DragDiffusion, updates the diffusion latent map in response to user inputs, causing global latent map alterations. This results in imprecise preservation of the original content and unsuccessful editing due to gradient vanishing. In contrast, we present DragNoise, offering robust and accelerated editing without retracing the latent map. The core rationale of DragNoise lies in utilizing the predicted noise output of each U-Net as a semantic editor. This approach is grounded in two critical observations: firstly, the bottleneck features of U-Net inherently …

Rethinking Multi-View Representation Learning Via Distilled Disentangling, Guanzhou Ke, Bo Wang, Xiaoli Wang, Shengfeng He

Research Collection School Of Computing and Information Systems

Multi-view representation learning aims to derive robust representations that are both view-consistent and view-specific from diverse data sources. This paper presents an in-depth analysis of existing approaches in this domain, highlighting a commonly overlooked aspect: the redundancy between view-consistent and view-specific representations. To this end, we propose an innovative framework for multi-view representation learning, which incorporates a technique we term 'distilled disentangling'. Our method introduces the concept of masked cross-view prediction, enabling the extraction of compact, high-quality view-consistent representations from various sources without incurring extra computational overhead. Additionally, we develop a distilled disentangling module that efficiently filters out consistency-related information …

Zero-Shot Out-Of-Distribution Detection With Outlier Label Exposure, Choubo Ding, Guansong Pang

Research Collection School Of Computing and Information Systems

As vision-language models like CLIP are widely applied to zero-shot tasks and gain remarkable performance on in-distribution (ID) data, detecting and rejecting out-of-distribution (OOD) inputs in the zero-shot setting have become crucial for ensuring the safety of using such models on the fly. Most existing zero-shot OOD detectors rely on ID class label-based prompts to guide CLIP in classifying ID images and rejecting OOD images. In this work we instead propose to leverage a large set of diverse auxiliary outlier class labels as pseudo OOD class text prompts to CLIP for enhancing zero-shot OOD detection, an approach we called Outlier …

Analyzing Swimming Performance Using Drone Captured Aerial Videos, Ngoc Doan Thu Tran, Kenny Tsu Wei Choo, Shaohui Foong, Hitesh Bhardwaj, Shane Kyi Hla Win, Wei Jun Ang, Kenneth T. Goh, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Monitoring swimmer performance is crucial for improving training and enhancing athletic techniques. Traditional methods for tracking swimmers, such as above-water and underwater cameras, face limitations due to the need for multiple cameras and obstructions from water splashes. This paper presents a novel approach for tracking swimmers using a moving UAV. The proposed system employs a UAV equipped with a high-resolution camera to capture aerial footage of the swimmers. The footage is then processed using computer vision algorithms to extract the swimmers' positions and movements. This approach offers several advantages, including single camera use and comprehensive coverage. The system's accuracy is …

Assessing Impact Of Urban Densification On Outdoor Microclimate And Thermal Comfort Using Envi-Met Simulations For Combined Spatial-Climatic Design (Cscd) Approach, Shreya Banerjee, Rachel X.Y. Pek, Sin Kang Yik, Graces N. Ching, Xiang Tian Ho, Dzyuban Yuliya, Peter J. Crank, Juan A. Acero, Winston T. L. Chow

Research Collection College of Integrative Studies

Future urban planning requires context-specific integration of spatial design and microclimate especially for tropical cities with extreme weather conditions. Thus, we propose a Combined Spatial-Climatic Design approach to assess impact of urban densification on annual outdoor thermal comfort performance employing ENVI-met simulations for Singapore. We first consider building bylaws and residential site guidelines to develop eight urban-density site options for a target population range. We further classify annual weather data into seven weather-types and use them as boundary conditions for the simulations. Comparing such fifty-six combined spatial-climatic simulation outputs by analyzing Outdoor Thermal Comfort Autonomy, we report the influence of …

Physician-Patient Interactions In Online Healthcare Communities: The Effects Of Preconsultation On Service Delivery And Patient Satisfaction, Qian Tang, Anqi Zhao

Research Collection School Of Computing and Information Systems

Preconsultation by medical professionals is a common practice in offline healthcare services to improve consultation efficiency but is rarely adopted for online healthcare services. In a noteworthy departure from this trend, a Chinese online healthcare community (OHC) has instituted preconsultation by assistant physicians prior to online consultations. Using comprehensive service data from this OHC, this study scrutinizes the effects of preconsultation on online healthcare services from both the physician and patient perspectives. The findings reveal that preconsultation by the assistant physician can significantly increase the attending physician’s response speed, length, and provision of informational support, while maintaining a consistent level …

More Human-Likeness, Less Self-Disclosure? Avatars' Form Realism And Job Applicants' Self-Disclosure In Ai Interviews, Yamin Xu, Keng Siau, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The rise of AI in recruitment promises to revolutionize how organizations evaluate job candidates. The quality of AI evaluations is determined by the input data, which depends on job applicants' self-disclosure. However, little is known about how the design elements of AI interview systems, particularly avatar interviewers, influence job applicants' self-disclosure during these interactions. This study aims to address this gap by specifically focusing on how the form realism of avatar interviewers affects job applicants' self-disclosure through their perceptions. In addition, the study will examine the effects of job type as a moderator. Drawing on the Stimulus-Organism-Response (S-O-R) model, this …

On Efficient Object-Detection Nas For Adas On Edge Devices, Diksha Gupta, Rhui Dih Lee, Laura Wynter

Research Collection School Of Computing and Information Systems

Object detection is a crucial building block for Advanced Driving Assistance Systems (ADAS). These systems require real-time accurate detection on resource-constrained edge devices. Deep learning models are emerging as popular techniques over traditional methods with superior performance. A hurdle in deploying these models is the inference time and computational cost of these models, in addition to training challenges for specialized tasks.We address this using supernet training-based neural architecture search (NAS) to obtain a variety of object detection models at a scale specific to the ADAS application. To this end, we consider a convolutional neural network-based object detection model. We produce …

D-Hacking, Emily Black, Talia B. Gillis, Zara Hall

Faculty Scholarship

Recent regulatory efforts, including Executive Order 14110 and the AI Bill of Rights, have focused on mitigating discrimination in AI systems through novel and traditional application of anti-discrimination laws. While these initiatives rightly emphasize fairness testing and mitigation, we argue that they pay insufficient attention to robust bias measurement and mitigation — and that without doing so, the frameworks cannot effectively achieve the goal of reducing discrimination in deployed AI models. This oversight is particularly concerning given the instability and brittleness of current algorithmic bias mitigation and fairness optimization methods, as highlighted by growing evidence in the algorithmic fairness literature. …

Aromatic-Carbonyl Interactions As An Emerging Type Of Non-Covalent Interactions, Chaowei Yin, Hebo Ye, Yu Hai, Hanxun Zou, Lei You

Faculty, Staff and Student Publications

Aromatic-carbonyl (Ar···C═O) interactions, attractive interactions between the arene plane and the carbon atom of carbonyl, are in the infancy as one type of new supramolecular bonding forces. Here the study and functionalization of aromatic-carbonyl interactions in solution is reported. A combination of aromatic-carbonyl interactions and dynamic covalent chemistry provided a versatile avenue. The stabilizing role and mechanism of arene-aldehyde/imine interactions are elucidated through crystal structures, NMR studies, and computational evidence. The movement of imine exchange equilibria further allowed the quantification of the interplay between arene-aldehyde/imine interactions and dynamic imine chemistry, with solvent effects offering another handle and matching the electrostatic …

Trace Element Contamination In Urban Soils: Testing And Management, Melissa Chilinski, Melanie Stock, Paul R. Grossl, Eli Oliver

All Current Publications

Trace elements, often referred to as heavy metals, naturally occur in the soil at low levels. Certain land use histories can elevate the concentrations of trace elements to levels that present health risks. Understanding which elements and soil test values may impact human or crop health is an important aspect of gardening and micro-farming, particularly in urban environments that are at increased risk of soil contamination. This fact sheet provides instructions on interpreting soil test results for trace elements through the Total Element Composition EPA 3050B Soil Test (#S19) at Utah State University Analytical Laboratory.

Settingsorder Article Reprints Open Accesseditor’S Choicearticle Exploring The Impact Of Spray Process Parameters On Graphite Coatings: Morphology, Thickness, And Tribological Properties, Adedoyin Abe, Josue A. Goss, Min Zou

Mechanical Engineering Faculty Publications and Presentations

This study explores, through a full factorial experimental design, the effects of graphite concentration and spray flow rate on the morphology, thickness, and tribological performance of graphite coatings for potential tribological applications. Coatings were applied to rough substrates using varying concentrations and flow rates, followed by analysis of their morphological characteristics, roughness, thickness, coefficient of friction (COF), and wear behavior. The results revealed distinct differences in the coating morphology based on flow rate, with low-flow-rate coatings exhibiting a porous structure and higher roughness, while high-flow-rate coatings displayed denser structures with lower roughness. A COF as low as 0.09 was achieved, …

Hydrothermal Synthesis Of (C5h14n2)[Cocl4]⸳0.5h2o: Crystal Structure, Spectroscopic Characterization, Thermal Behavior, Magnetic Properties And Biological Evaluation, Sandra Walha, Noureddine Mhadhbi, Basem F. Ali, Abdellah Kaiba, Ahlem Guesmi, Wesam Abd El-Fattah, Naoufel Ben Hamadi, Mark M. Turnbull, Ferdinando Costantino, Houcine Naïli

Chemistry

The organic-inorganic compound (C₅H₁₄N₂)[CoCl₄]⸳0.5H₂O, I, was characterized by various physicochemical techniques. The X-ray diffraction analysis revealed that the compound crystallizes in the centrosymmetric space group C2/c of the monoclinic system. The atomic arrangement the Co(II) complex is built from isolated [CoCl₄]^2– anions, 1-methylpiperazine-1,4-diium [C₅H₁₄N₂]²⁺ cations and free water molecules. The crystal structure study showed that the cohesion of I is assured through N–H···Cl and N–H···O hydrogen bonds giving birth to a 3-D architecture. Hirshfeld surface analysis revealed that Cl···H/H···Cl and …

Advances In Computational And Statistical Inverse Problems, Dylan Green

Dartmouth College Ph.D Dissertations

Inverse problems are prevalent in many fields of science and engineering, such as signal processing and medical imaging. In such problems, indirect data are used to recover information regarding some unknown parameters of interest. When these problems fail to be well-posed, the original problems must be modified to include additional constraints or optimization terms, giving rise to so-called regularization techniques. Classical methods for solving inverse problems are often deterministic and focus on finding point estimates for the unknowns. Some newer methods approach the solving of inverse problems by instead casting them in a statistical framework, allowing for novel point estimate …

Development And Applications Of Flexible Piezoelectric Nanogenerators Using Batio3, Pdms, And Mwcnts For Energy Harvesting And Sensory Integration In Smart Systems, Islam Uddin Shipu, Dipasree Bhowmick, Nondon Lal Dey

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

Mechanical energy is a versatile and accessible green energy source, increasingly harnessed to power small-scale devices via innovative flexible piezoelectric nanogenerators (F- PNGs). These devices convert mechanical energy into electricity using lightweight materials such as Barium Titanate (BaTiO3), poly dimethyl siloxane (PDMS), and multi-walled carbon nanotubes (MWCNTs). In this design, BaTiO3 nanoparticles were embedded in a composite film with PDMS and MWCNTs, sandwiched between two copper electrodes. The BaTiO3/PDMS/MWCNT composite PENGs, synthesized for this study, produce an output voltage of ∼8 V through periodic cyclic beating. This represents an increase of about 16% compared to the PENGs without MWCNT doping. …

A Sentiment Analysis Approach For Understanding Users’ Perception Of Metaverse Marketplace, Ahmed Al-Adaileh, Mousa Al-Kfairy, Mohammad Tubishat, Omar Alfandi

All Works

This research explores the user perceptions of the Metaverse Marketplace, analyzing a substantial dataset of over 860,000 Twitter posts through sentiment analysis and topic modeling techniques. The study aims to uncover the driving factors behind user engagement and sentiment in this novel digital trading space. Key findings highlight a predominantly positive user sentiment, with significant enthusiasm for the marketplace's revenue generation and entertainment potential, particularly within the gaming sector. Users express appreciation for the innovative opportunities the Metaverse Marketplace offers for artists, designers, and traders in handling and trading digital assets. This positive outlook is tempered by notable concerns regarding …

Parabolic And Non-Parabolic Surfaces With Small Or Large End Spaces Via Fenchel-Nielsen Parameters, Michael Antony Pandazis

Dissertations, Theses, and Capstone Projects

We consider conditions on the Fenchel-Nielsen parameters of a Riemann surface X that determine whether or not a surface X is parabolic. Fix a geodesic pants decomposition of a surface and call the boundary geodesics in the decomposition cuffs. For a zero or half-twist flute surface, we prove that parabolicity is equivalent to the surface having a covering group of the first kind. Using that result, we give necessary and sufficient conditions on the Fenchel-Nielsen parameters of a half-twist flute surface X with increasing cuff lengths such that X is parabolic. As an application, we determine whether or not each …

Bifurcations And Resultants For Rational Maps And Dynatomic Modular Curves In Positive Characteristic, Colette Lapointe

Dissertations, Theses, and Capstone Projects

No abstract provided.

A Thesis, Or Digressions On Sculptural Practice: In Which, Concepts & Influences Thereof Are Explained, Set Forth, Catalogued, Or Divulged By Way Of Commentaries To A Poem, First Conceived By The Artist, Fed Through Chatg.P.T., And Re-Edited By The Artist, To Which Are Added, Annotated References, Impressions And Ruminations Thereof, Also Including Private Thoughts & Personal Accounts Of The Artist, Jaimie An

Masters Theses

This thesis is an exercise in, perhaps a futile, attempt to trace just some of the ideas, stories, and musings I might meander through in my process. It’s not quite a map, nor is it a neat catalogue; it is a haphazard collection of tickets and receipts from a travel abroad, carelessly tossed in a carry-on, only to be stashed upon returning home. These ideas are derived from much greater thinkers and authors than myself; I am a mere collector or a translator, if that, and not a very good one, for much is lost. I do not claim comprehensive …

Searching For The Hyperobject: Crystals As Transscalar Vehicles, Jay Costello

Masters Theses

When I touch the street outside my house, I'm touching Los Angeles—a contiguous vector of material bisecting a continent. A slab, a stone, dust and oil, a googolplex of tightly packed anisotropic particles... At nightfall, I sneak to the edge of the highway and break off a piece. 'What does it mean for a worm to be aware of the scale of the planet?' Bruno Latour's evocative questioning of scalar jumps prompts an existentialism that places me somewhere between the hyperlocal and the massively distributed. Like a cosmic traveler floating through the universe, I feel adrift. I look around, grasping …

Fluid Futures: The Revitalization Of Yangzhou Through Its Historical Waterways, Feiyang Wu

Masters Theses

In China, cities such as Yangzhou, which in pre-modern times played central roles in the political, cultural, and economic functioning of the country based on their geographic location, proximity to water-based trade routes, and connections to the imperial court, are today facing uncertain futures due to waterways no longer being critical to trade, and government-driven development being focused on first-tier cities such as Beijing, Shanghai, Shenzhen, and Guangzhou. With this, the working-age population migrates from smaller cities toward these urban giants, leaving behind aging relatives, a less robust and diversified economic base, and few attributes other than cultural tourism that …

On Near-Linear Cellular Automata Over Near Spaces, Abdul-Rahman M. Nasser

Dissertations

Cellular Automata can be considered as examples of massively parallel machines. They are computational mathematical objects consisting of a grid of cells, each of which can exist in a finite number of states. These cells evolve over discrete time steps according to a set of predefined rules based on the states of neighboring cells. The notion of cellular automata was first introduced by Ulam and von Neumann and then popularized by John H. Conway in the 1970s with one of the most famous examples being The Game of Life.

This research builds on and generalizes the work of Tullio Ceccherini-Silberstein …

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

Tennessee Climate Office Monthly Reports

No abstract provided.

The Impact Of Video Assistant Referee (Var) On The English Premier League, Jack Kenyon Brown

Master's Theses

The aim of this study is to examine how the introduction of the Video Assisted Referee (VAR) system influenced the English Premier League (EPL). Since its implementation in the English Premier League in 2019, VAR has been a constant source of debate and controversy. Many studies have been done on the immediate impact of VAR on other elite professional soccer leagues, but the scope of results is very limited and due to be updated. The data for the ensuing analysis consists of 3800 matches played in the English Premier League during the five seasons before (14/15, 15/16, 16/17, 17/18, and …

Performance Interference Detection For Cloud-Native Applications Using Unsupervised Machine Learning Models, Eli Bakshi

Master's Theses

Contemporary cloud-native applications frequently adopt the microservice architecture, where applications are deployed within multiple containers that run on cloud virtual machines (VMs). These applications are typically hosted on public cloud platforms, where VMs from multiple cloud subscribers compete for the same physical resources on a cloud server. When a cloud subscriber application running on a VM competes for shared physical resources from other applications running on the same VM or from other VMs co-located on the same cloud server, performance interference may occur when the performance of an application degrades due to shared resource contention. Detecting such interference is crucial …