Physical Sciences and Mathematics Commons^™

Water And Soil Gas Sampling Near Richardton, North Dakota, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet on a 2019 Energy & Environmental Research Center (EERC) project to collect water and soil gas samples near Richardton, North Dakota, as part of the Red Trail Energy carbon capture and storage (CCS) research effort.

How Do You Define The Watershed? Individual Representations Of The Blackstone River Watershed And Their Roles In Collaborative Watershed Governance, Casey Merkle

Masters Theses

Key leaders of civic environmental stewardship organizations shape collaborative watershed governance. Individuals perceive and construct the watershed through past experiences, feeling, emotion, values, and practices. It is not well known how these individuals perceive and construct their own representations of the watershed and environmental stewardship practices. This thesis explored individuals past experiences, feelings, emotions, values, and practices in the Blackstone River watershed to a) examine the ways in which key leaders of civic environmental stewardship organizations represent the watershed b) understand how individuals think, feel, and engage in environmental stewardship practices and, c) reveal the congruences and incongruencies of individual …

Methods For Focal Plane Array Resolution Estimation Using Random Laser Speckle In Non-Paraxial Geometries, Phillip J. Plummer

Theses and Dissertations

The infrared (IR) imaging community has a need for direct IR detector evaluation due to the continued demand for small pixel pitch detectors, the emergence of strained-layer-super-lattice devices, and the associated lateral carrier diffusion issues. Conventional laser speckle-based modulation transfer function (MTF) estimation is dependent on Fresnel propagation and a wide-sense-stationary input random process, limiting the use of this approach for lambda (wavelength)-scale IR devices. This dissertation develops two alternative methodologies for speckle-based resolution evaluation of IR focal plane arrays (FPAs). Both techniques are formulated using Rayleigh-Sommerfield electric field propagation, making them valid in the non-paraxial geometries dictated for resolution …

Full Pattern Analysis And Comparison Of The Center Fed And Offset Fed Cassegrain Antennas With Large Focal Length To Diameter Ratios For High Power Microwave Transmission, Derek W. Mantzke

Theses and Dissertations

High power microwaves (HPM) have been a topic of research since the Cold War era. This paper will present a comparison between two Cassegrain-type antennas: the axially, or center fed, and the offset fed. Specifically, the 10 GHz operating frequency will be investigated with large focal length to diameter () ratios. Beam patterns which encompass the entire radiation pattern will be included for data validation and optimization. The simulations will follow a design of experiments factorial model to ensure all possible combinations of prescribed parameters are included, including an analysis of variance (ANOVA) study to find parameter influence on the …

Evaluating A Statistical-Based Assessment Tool For Stratifying Risk Among U.S. Air Force Organizations, Tiffany A. Low

Theses and Dissertations

The Air Force Inspection System is a proponent of utilizing a risk-based sampling strategy (RBSS) for conducting inspections from major command levels down to the unit level. The strategy identifies areas deemed most important or risky by commanders and prioritizes them accordingly for an independent assessment by the Inspector General. While Air Force regulation specifies the need to use a RBSS for inspection, the implementation process is delegated to individual commands and, subsequently, wings. The 23rd Wing, the sponsor for this research, directed us to analyze a RBSS tool highlighted as an example from which to adopt for those units …

Leveraging Single Cell Technologies For The Characterization And Treatment Of Refractory Pancreatic Cancer, Maria Monberg

Dissertations & Theses (Open Access)

Heterogeneity is a hallmark of cancer, and the advent of multimodal single-cell technologies has helped uncover heterogeneity in a high-throughput manner in different cancers across varied contexts at an unprecedented resolution. In an effort to improve precision medicine approaches in pancreatic ductal adenocarcinoma (PDAC), a highly lethal malignancy with a mere 11% 5-year survival rate, this dissertation focuses on first questioning the assumptions of the most basic models used to study PDAC via multimodal single-cell characterization methods at multiple levels of biological organization (scCNVseq and snATACseq for DNA assays, scRNAseq for transcriptomics, and paired protein assays such as multiplexed immunofluorescence …

Torsh: Obfuscating Consumer Internet-Of-Things Traffic With A Collaborative Smart-Home Router Network, Adam Vandenbussche

Dartmouth College Undergraduate Theses

When consumers install Internet-connected "smart devices" in their homes, metadata arising from the communications between these devices and their cloud-based service providers enables adversaries privy to this traffic to profile users, even when adequate encryption is used. Internet service providers (ISPs) are one potential adversary privy to users’ incom- ing and outgoing Internet traffic and either currently use this insight to assemble and sell consumer advertising profiles or may in the future do so. With existing defenses against such profiling falling short of meeting user preferences and abilities, there is a need for a novel solution that empowers consumers to …

Understanding Coastal And Inland Hydrometeorological Hazards Produced By Extratropical And Tropical Cyclones Along The East Coast Of The United States, Katherine Towey

Dissertations, Theses, and Capstone Projects

As global temperatures continue to rise, the effects of anthropogenic climate change will impact the magnitude and frequency of pluvial, fluvial, and coastal flooding events. If we want to accurately predict changes in these flooding events, we need to fully understand them in the current climate. As such, this research examines the relationship between hydrometeorological hazards and the characteristics of the storm types, such as extratropical cyclones (ETCs) and tropical cyclones (TCs), that produce such hazards. Through the use of observational and reanalysis data, the work herein utilizes a cyclone-hazard association algorithm and extreme value analysis to assess the extent, …

An Overview Of Technologies Deployed In Gcc Countries To Combat Covid-19, Samia Loucif, Murad Al-Rajab, Reem Salem, Nadine Akkila

All Works

Since December 2019, COVID-19 and all of its variants continue to ravage the planet with consequent negative impact that has completely changed our lives within a short period of time after the outbreak of the Virus. On March 11, 2020, COVID-19 was declared a global pandemic by the World Health Organization. Since then, a group of new COVID-19 variants has emerged posing a greater danger to humanity. By the start of August 2021, the reported COVID-19 related death toll across the globe has rocketed to 4,233,139. To deal with the COVID-19 pandemic, countries across the world have rushed to develop …

Collective Behavior Of Dissipatively-Coupled Photonic Oscillator Networks, Jiajie Ding

Dissertations, Theses, and Capstone Projects

This thesis discusses the collective behavior of networks formed by photonic oscillators. The key motivations for doing this research are the interest in developing high power laser arrays on photonic chips and performing optical computing.

Symmetries, Zero Modes And Light Transport In Non-Hermitian Photonics, Jose David Hernandez Rivero

Dissertations, Theses, and Capstone Projects

We approach some fundamental aspects of photonic dissipative systems treated by a non-Hermitian theory. Inspired by the possibilities provided by some major non-Hermitian symmetries, we study systematically the properties of the novel pseudochirality, pseudo-anti-Hermiticity, and supersymmetry. We analyze other aspect of photonics, the zero mode, which has a profound connection to non-Hermitian physics. We propose a scheme to realize a zero mode that exists even in the absence of symmetries. Finally, we approach light transport in non-Hermitian photonic systems, where the introduction of gain and loss can modify drastically the propagation speed of wavepackets.

Two-Current Transition Amplitudes With Two-Body Final States, Keegan H. Sherman, Feliipe G. Ortega-Gama, Raúl A. Briceño, Andrew W. Jackura

Physics Faculty Publications

We derive the on-shell form of amplitudes containing two external currents with a single hadron in the initial state and two hadrons in the final state, denoted as 1 + J → 2 + J . This class of amplitude is relevant in precision tests of the Standard Model as well as for exploring the structure of excited states in the QCD spectrum. We present a model-independent description of the amplitudes where we sum to all orders in the strong interaction. From this analytic form we are able to extract transition and elastic resonance form factors consistent with previous work …

Machine Learning And The Network Analysis Of Ethereum Trading Data, Santosh Sivakumar

Dartmouth College Undergraduate Theses

Since their conception, cryptocurrencies have captured the public interest, motivating a growing body of research aimed at exploring blockchain-based transactions. This said, little work has been done to draw conclusions from transaction patterns, particularly in the realm of predicting cryptocurrency price movements. Moreover, research in the cryptocurrency sphere largely focuses on Bitcoin, paying little attention to Ethereum, Bitcoin's second-in-line with respect to market capitalization. In this paper, we construct hourly networks for a year of Ethereum transactions, using computed graph metrics as features in a series of machine learning models. We find that regression-based approaches to predicting Ether prices/price deltas …

Magnetism Of Novel Rare-Earth-Free Intermetallic Compounds, Haohan Wang

Department of Physics and Astronomy: Dissertations, Theses, and Student Research

Rare-earth-free magnets have drawn lots of interest because of their low cost, and the production is not limited by the shortage of rare-earth elements. This dissertation focuses on three rare-earth-free materials, Fe-Co-Ti alloys, Fe-Ni-B alloys, and Co-Si. All of them are synthesized by arc melting followed by melt-spinning. Fe_3+xCo_3−xTi₂ (x = 0, 2, 3) alloys exhibit hexagonal crystal structures and show non-collinear spin structures according to neutron diffraction. The magnetic moments have projections on both the c-axis and basal plane, and the corresponding misalignment angle exhibits a nonlinear decrease with …

2022 June - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

The Hyperporphyrin Concept: A Contemporary Perspective, Carl C. Wamser, Abhik Ghosh

Chemistry Faculty Publications and Presentations

The Gouterman four-orbital model conceptualizes porphyrin UV–visible spectra as dominated by four frontier molecular orbitals─two nearly degenerate HOMOs and two exactly degenerate LUMOS under D4h symmetry. These are well separated from all the other molecular orbitals, and normal spectra involve transitions among these MOs. Unusual spectra occur when additional orbitals appear in this energy range, typically as a consequence of the central coordinated atom. For example, metals with empty d orbitals in a suitable energy range may lead to charge transfer from porphyrin (ligand) to metal, that is, so-called LMCT transitions. Metals with filled p or d orbitals may …

Emissions Baseline Report For The Agriculture Sector In Western Australia, Mandy Curnow, Christophe D'Abbadie, Robert French, Jackie Bucat, Dario Stefanelli, Neil Lantzke, Valeria Almeida Lima, Jess Austen, Lee Chester, Kate Pritchett, Millie Brady, Dylan Bennett

Climate Science Published Reports

The Intergovernmental Panel on Climate Change Sixth Assessment Report found that climate impacts are appearing earlier and are more severe than expected. The world faces multiple unavoidable climate hazards over the next two decades with global warming of 1.5ºC and accelerated action is required to avoid mortality and loss of biodiversity and infrastructure.

Achieving Climate Resilience requires both climate adaptation and mitigation of Greenhouse Gases which are accelerating climate change. Western Australia is committed to building resilience of the agriculture industry and as part of that is focussed on reducing greenhouse gas (GHG) emissions at both an industry and government …

Cross-Lingual Adaptation For Recipe Retrieval With Mixup, Bin Zhu, Chong-Wah Ngo, Jingjing Chen, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Cross-modal recipe retrieval has attracted research attention in recent years, thanks to the availability of large-scale paired data for training. Nevertheless, obtaining adequate recipe-image pairs covering the majority of cuisines for supervised learning is difficult if not impossible. By transferring knowledge learnt from a data-rich cuisine to a data-scarce cuisine, domain adaptation sheds light on this practical problem. Nevertheless, existing works assume recipes in source and target domains are mostly originated from the same cuisine and written in the same language. This paper studies unsupervised domain adaptation for image-to-recipe retrieval, where recipes in source and target domains are in different …

Reinforcement Learning-Based Interactive Video Search, Zhixin Ma, Jiaxin Wu, Zhijian Hou, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Despite the rapid progress in text-to-video search due to the advancement of cross-modal representation learning, the existing techniques still fall short in helping users to rapidly identify the search targets. Particularly, in the situation that a system suggests a long list of similar candidates, the user needs to painstakingly inspect every search result. The experience is frustrated with repeated watching of similar clips, and more frustratingly, the search targets may be overlooked due to mental tiredness. This paper explores reinforcement learning-based (RL) searching to relieve the user from the burden of brute force inspection. Specifically, the system maintains a graph …

Group Contextualization For Video Recognition, Yanbin Hao, Hao Zhang, Chong-Wah Ngo, Xiangnan He

Research Collection School Of Computing and Information Systems

Learning discriminative representation from the complex spatio-temporal dynamic space is essential for video recognition. On top of those stylized spatio-temporal computational units, further refining the learnt feature with axial contexts is demonstrated to be promising in achieving this goal. However, previous works generally focus on utilizing a single kind of contexts to calibrate entire feature channels and could hardly apply to deal with diverse video activities. The problem can be tackled by using pair-wise spatio-temporal attentions to recompute feature response with cross-axis contexts at the expense of heavy computations. In this paper, we propose an efficient feature refinement method that …

Mlp-3d: A Mlp-Like 3d Architecture With Grouped Time Mixing, Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

Convolutional Neural Networks (CNNs) have been re-garded as the go-to models for visual recognition. More re-cently, convolution-free networks, based on multi-head self-attention (MSA) or multi-layer perceptrons (MLPs), become more and more popular. Nevertheless, it is not trivial when utilizing these newly-minted networks for video recognition due to the large variations and complexities in video data. In this paper, we present MLP-3D networks, a novel MLP-like 3D architecture for video recognition. Specifically, the architecture consists of MLP-3D blocks, where each block contains one MLP applied across tokens (i.e., token-mixing MLP) and one MLP applied independently to each token (i.e., channel MLP). …

Learnings From A Pilot Hybrid Question Answering System: Cqas: Case Study Based On A Singapore Government Agency's Customer Service Centre, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

The Singapore Government first released their digital government blueprint in 2018 with the key message for all their agencies to be "digital to the core and served with heart". With this push, agencies are moving towards human-centric digital services, especially for individual citizens. During COVID-19, Singapore government agencies introduced many COVID-19 digital initiatives resulting in more incoming inquiries from citizens to respective agencies. This surge in inquiries created the challenge on the agencies' end to meet service level agreements. One widely adopted solution is the use of chatbot technology that directly interfaces with the customer. However, several organisations have faced …

Reinforcement Learning Approach To Solve Dynamic Bi-Objective Police Patrol Dispatching And Rescheduling Problem, Waldy Joe, Hoong Chuin Lau, Jonathan Pan

Research Collection School Of Computing and Information Systems

Police patrol aims to fulfill two main objectives namely to project presence and to respond to incidents in a timely manner. Incidents happen dynamically and can disrupt the initially-planned patrol schedules. The key decisions to be made will be which patrol agent to be dispatched to respond to an incident and subsequently how to adapt the patrol schedules in response to such dynamically-occurring incidents whilst still fulfilling both objectives; which sometimes can be conflicting. In this paper, we define this real-world problem as a Dynamic Bi-Objective Police Patrol Dispatching and Rescheduling Problem and propose a solution approach that combines Deep …

Transportation-Enabled Urban Services: A Brief Discussion, Hai Wang

Research Collection School Of Computing and Information Systems

Nearly 55% of the world's population lives in urban areas or cities, and is expected to rise above 70% over the coming decades. Rapid urbanization brings steadily more residents and a growing freelancing workforce into cities. The developments of city infrastructure and technologies—for instance, mobile location tracking and computing, autonomous and connected vehicles, wearable devices, robotics and robots, smart appliances, biometric authentication, various internet-of-things devices, and smart monitoring systems—are creating numerous opportunities and inspiring innovative and emerging urban services. Among these innovations, complex systems of urban transportation and logistics have embraced advances in technologies and, consequently, been significantly reshaped (Agatz …

Flavor-Videos: Enhancing The Flavor Perception Of Food While Eating With Videos, Meetha Nesam James, Nimesha Ranasinghe, Anthony Tang, Lora Oehlberg

Research Collection School Of Computing and Information Systems

People are typically involved in different activities while eating, particularly when eating alone, such as watching television or playing games on their phones. Previous research in Human-Food Interaction (HFI) has primarily focused on studying people’s motivation and analyzing of the media content watched while eating. However, their impact on human behavioral and cognitive processes, particularly flavor perception and its attributes, remains underexplored. We present a user study to investigate the influence of six types of videos, including mukbang – a new food video genre, on flavor perceptions (taste sensations, liking, and emotions) while eating plain white rice. Our findings revealed …

Deep Learning For Person Re-Identification: A Survey And Outlook, Mang Ye, Jianbing Shen, Gaojie Lin, Tao Xiang, Ling Shao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks and increasing demand of intelligent video surveillance, it has gained significantly increased interest in the computer vision community. By dissecting the involved components in developing a person Re-ID system, we categorize it into the closed-world and open-world settings. We first conduct a comprehensive overview with in-depth analysis for closed-world person Re-ID from three different perspectives, including deep feature representation learning, deep metric learning and ranking optimization. With the performance saturation under closed-world setting, the research focus for person Re-ID …

Decomposing Generation Networks With Structure Prediction For Recipe Generation, Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Research Collection School Of Computing and Information Systems

Recipe generation from food images and ingredients is a challenging task, which requires the interpretation of the information from another modality. Different from the image captioning task, where the captions usually have one sentence, cooking instructions contain multiple sentences and have obvious structures. To help the model capture the recipe structure and avoid missing some cooking details, we propose a novel framework: Decomposing Generation Networks (DGN) with structure prediction, to get more structured and complete recipe generation outputs. Specifically, we split each cooking instruction into several phases, and assign different sub-generators to each phase. Our approach includes two novel ideas: …

Simultaneous Energy Harvesting And Gait Recognition Using Piezoelectric Energy Harvester, Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

Piezoelectric energy harvester, which generates electricity from stress or vibrations, is gaining increasing attention as a viable solution to extend battery life in wearables. Recent research further reveals that, besides generating energy, PEH can also serve as a passive sensor to detect human gait power-efficiently because its stress or vibration patterns are significantly influenced by the gait. However, as PEHs are not designed for precise measurement of motion, achievable gait recognition accuracy remains low with conventional classification algorithms. The accuracy deteriorates further when the generated electricity is stored simultaneously. To classify gait reliably while simultaneously storing generated energy, we make …

Deep Learning For Anomaly Detection, Guansong Pang, Charu Aggarwal, Chunhua Shen, Nicu Sebe

Research Collection School Of Computing and Information Systems

A nomaly detection aims at identifying data points which are rare or significantly different from the majority of data points. Many techniques are explored to build highly efficient and effective anomaly detection systems, but they are confronted with many difficulties when dealing with complex data, such as failing to capture intricate feature interactions or extract good feature representations. Deep-learning techniques have shown very promising performance in tackling different types of complex data in a broad range of tasks/problems, including anomaly detection. To address this new trend, we organized this Special Issue on Deep Learning for Anomaly Detection to cover the …

Consensus Formation On Heterogeneous Networks, Edoardo Fadda, Junda He, Claudia J. Tessone, Paolo Barucca

Research Collection School Of Computing and Information Systems

Reaching consensus-a macroscopic state where the system constituents display the same microscopic state-is a necessity in multiple complex socio-technical and techno-economic systems: their correct functioning ultimately depends on it. In many distributed systems-of which blockchain-based applications are a paradigmatic example-the process of consensus formation is crucial not only for the emergence of a leading majority but for the very functioning of the system. We build a minimalistic network model of consensus formation on blockchain systems for quantifying how central nodes-with respect to their average distance to others-can leverage on their position to obtain competitive advantage in the consensus process. We …