Physical Sciences and Mathematics Commons^™

Fed-Ltd: Towards Cross-Platform Ride Hailing Via Federated Learning To Dispatch, Yansheng Wang, Yongxin Tong, Zimu Zhou, Ziyao Ren, Yi Xu, Guobin Wu, Weifeng Lv

Research Collection School Of Computing and Information Systems

Learning based order dispatching has witnessed tremendous success in ride hailing. However, the success halts within individual ride hailing platforms because sharing raw order dispatching data across platforms may leak user privacy and business secrets. Such data isolation not only impairs user experience but also decreases the potential revenues of the platforms. In this paper, we advocate federated order dispatching for cross-platform ride hailing, where multiple platforms collaboratively make dispatching decisions without sharing their local data. Realizing this concept calls for new federated learning strategies that tackle the unique challenges on effectiveness, privacy and efficiency in the context of order …

Finding Meta Winning Ticket To Train Your Maml, Dawei Gao, Yuexiang Xie, Zimu Zhou, Zhen Wang, Yaliang Li, Bolin. Ding

Research Collection School Of Computing and Information Systems

The lottery ticket hypothesis (LTH) states that a randomly initialized dense network contains sub-networks that can be trained in isolation to the performance of the dense network. In this paper, to achieve rapid learning with less computational cost, we explore LTH in the context of meta learning. First, we experimentally show that there are sparse sub-networks, known as meta winning tickets, which can be meta-trained to few-shot classification accuracy to the original backbone. The application of LTH in meta learning enables the adaptation of meta-trained networks on various IoT devices with fewer computation. However, the status quo to identify winning …

Variational Graph Author Topic Modeling, Ce Zhang, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

While Variational Graph Auto-Encoder (VGAE) has presented promising ability to learn representations for documents, most existing VGAE methods do not model a latent topic structure and therefore lack semantic interpretability. Exploring hidden topics within documents and discovering key words associated with each topic allow us to develop a semantic interpretation of the corpus. Moreover, documents are usually associated with authors. For example, news reports have journalists specializing in writing certain type of events, academic papers have authors with expertise in certain research topics, etc. Modeling authorship information could benefit topic modeling, since documents by the same authors tend to reveal …

Integrated Assessment Of Urban Overheating Impacts On Human Life, N. Nazarian, E. S. Krayenhoff, B. Bechtel, D. M. Hondula, R. Paolini, J. Vanos, T. Cheung, Winston T. L. Chow, Et Al

Research Collection College of Integrative Studies

Urban overheating, driven by global climate change and urban development, is a major contemporary challenge that substantially impacts urban livability and sustainability. Overheating represents a multifaceted threat to the well-being, performance, and health of individuals as well as the energy efficiency and economy of cities, and it is influenced by complex interactions between building, city, and global scale climates. In recent decades, extensive discipline-specific research has characterized urban heat and assessed its implications on human life, including ongoing efforts to bridge neighboring disciplines. The research horizon now encompasses complex problems involving a wide range of disciplines, and therefore comprehensive and …

Multimodal Private Signatures, Khoa Nguyen, Fuchun Guo, Willy Susilo, Guomin Yang

Research Collection School Of Computing and Information Systems

We introduce Multimodal Private Signature (MPS) - an anonymous signature system that offers a novel accountability feature: it allows a designated opening authority to learn some partial information op about the signer’s identity id, and nothing beyond. Such partial information can flexibly be defined as op = id (as in group signatures), or as op = 0 (like in ring signatures), or more generally, as op = Gj (id), where Gj (·) is a certain disclosing function. Importantly, the value of op is known in advance by the signer, and hence, the latter can decide whether she/he wants to disclose …

Self-Checking Deep Neural Networks For Anomalies And Adversaries In Deployment, Yan Xiao, Ivan Beschastnikh, Yun Lin, Rajdeep Singh Hundal, Xiaofei Xie, David S. Rosenblum, Jin Song Dong

Research Collection School Of Computing and Information Systems

Deep Neural Networks (DNNs) have been widely adopted, yet DNN models are surprisingly unreliable, which raises significant concerns about their use in critical domains. In this work, we propose that runtime DNN mistakes can be quickly detected and properly dealt with in deployment, especially in settings like self-driving vehicles. Just as software engineering (SE) community has developed effective mechanisms and techniques to monitor and check programmed components, our previous work, SelfChecker, is designed to monitor and correct DNN predictions given unintended abnormal test data. SelfChecker triggers an alarm if the decisions given by the internal layer features of the model …

Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang

Information Technology & Decision Sciences Faculty Publications

(First paragraph) Smart manufacturing (SM) distinguishes itself from other system paradigms by introducing ‘smartness’ as a measure to a manufacturing system; however, researchers in different domains have different expectations of system smartness from their own perspectives. In this Special Issue (SI), SM refers to a system paradigm where digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the internet to expand system capabilities, (3) supporting data-driven decision making at all domains and levels of businesses, or (4) reconfiguring systems to adapt changes and uncertainties in dynamic environments. …

A Climate Resilience Research Renewal Agenda: Learning Lessons From The Covid-19 Pandemic For Urban Climate Resilience, Mark Pelling, Winston T. L. Chow, Eric Chu, Richard Dawson, David Dodman, Arabella Fraser, Bronwyn Hayward, Luna Khirfan, Timon Mcphearson, Anjal Prakash, Gina Ziervogel

Research Collection School of Social Sciences

Learning lessons from the COVID-19 pandemic opens an opportunity for enhanced research and action on inclusive urban resilience to climate change. Lessons and their implications are used to describe a climate resilience research renewal agenda. Three key lessons are identified. The first lesson is generic, that climate change risk coexists and interacts with other risks through overlapping social processes, conditions and decision-making contexts. Two further lessons are urban specific: that networks of connectivity bring risk as well as resilience and that overcrowding is a key indicator of the multiple determinants of vulnerability to both COVID-19 and climate change impacts. From …

Destress: Computation-Optimal And Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization, Boyue Li, Zhize Li, Yuejie Chi

Research Collection School Of Computing and Information Systems

Emerging applications in multiagent environments such as internet-of-things, networked sensing, autonomous systems, and federated learning, call for decentralized algorithms for finite-sum optimizations that are resource efficient in terms of both computation and communication. In this paper, we consider the prototypical setting where the agents work collaboratively to minimize the sum of local loss functions by only communicating with their neighbors over a predetermined network topology. We develop a new algorithm, called DEcentralized STochastic REcurSive gradient methodS (DESTRESS) for nonconvex finite-sum optimization, which matches the optimal incremental first-order oracle complexity of centralized algorithms for finding first-order stationary points, while maintaining communication …

Resumable Zero-Knowledge For Circuits From Symmetric Key Primitives, Handong Zhang, Puwen Wei, Haiyang Xue, Yi Deng, Jinsong Li, Wei Wang, Guoxiao Liu

Research Collection School Of Computing and Information Systems

Consider the scenario that the prover and the verifier perform the zero-knowledge (ZK) proof protocol for the same statement multiple times sequentially, where each proof is modeled as a session. We focus on the problem of how to resume a ZK proof efficiently in such scenario. We introduce a new primitive called resumable honest verifier zero-knowledge proof of knowledge (resumable HVZKPoK) and propose a general construction of the resumable HVZKPoK for circuits based on the “MPC-in-the-head" paradigm, where the complexity of the resumed session is less than that of the original ZK proofs. To ensure the knowledge soundness for the …

Revised Draft Final Solid Media Management Program Plan, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Butte Reclaimed Areas Maintenance And Monitoring (M&M) Plan In Accordance With Butte Reclamation Evaluation System (Bres), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Symmetric Generations And An Algorithm To Prove Relations, Diddier Andrade

Electronic Theses, Projects, and Dissertations

In this thesis we have discovered homomorphic images of several progenitors such as 3^(*56):(23:(3:7), 3^(*14):(23:(3:7)), 5^(∗24) : S5, 2^(∗10) : (10 : 2), 56^(∗24) : (A5 : 2), and 11^(∗12) :m L2(11). We give isomorphism types of each image that we have found.
We then create a monomial representation of L2(11) by lifting 5:11 onto it.
We manually perform Double Coset Enumeration of 3:(2×S5) over D12
to create its Cayley graph. This is achieved by solving many word problems. The
Cayley graph is used to find a permutation representation of 3:(2×S5). We also
perform Double Coset Enumeration S3 × A5 …

Ultrashort Pulse Laser Filamentation Electrical And Optical Diagnostic Comparison, James E. Wymer

Optical Science and Engineering ETDs

Results presented here examine the effect of changing gas pressure on the radio frequency (RF) emissions of an ultrashort pulse laser filament plasma and how those emissions vary longitudinally in the laser focal region. We use a WR284 rectangular waveguide with a 1.5 cm hole that allows the beam through. A 3.2 GHz microwave signal is emitted in the waveguide, and signals are received through a waveguide-to-coax antenna connected to an HP8470B Schottky diode. By enabling and disabling the 3.2 GHz signal, we measure both the self-emitted RF from a USPL filament and subsequently the degree of attenuation a filament …

Understanding Water Security In Portland, Oregon: Using Newspapers As Tools For Science Communication And Education, Julian Roth

University Honors Theses

Water insecurity is faced by a large percentage of the global population, particularly in urban areas, which face greater and more complex needs for water resources. Better tools are needed to be able to recognize and communicate water security issues in a way that reinforces water systems, engages all stakeholders, and recognizes early warnings of environmental injustice. This research examines utilizing public newspaper articles to produce these tools. Using a case-study approach, this thesis explores newspaper articles about water from 2014-2020 in the urban center of Portland, Oregon, to understand local water security issues and to build a system of …

Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt

Electronic Theses and Dissertations

Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag …

Characteristic Sets Of Matroids, Dony Varghese

Doctoral Dissertations

Matroids are combinatorial structures that generalize the properties of linear independence. But not all matroids have linear representations. Furthermore, the existence of linear representations depends on the characteristic of the fields, and the linear characteristic set is the set of characteristics of fields over which a matroid has a linear representation. The algebraic independence in a field extension also defines a matroid, and also depends on the characteristic of the fields. The algebraic characteristic set is defined in the similar way as the linear characteristic set.

The linear representations and characteristic sets are well studied. But the algebraic representations and …

Rotational Spectroscopy Of Nonafluoro-Tert-Butyl Alcohol, Zayra Leticia Gonzalez

Theses and Dissertations

Nonafluoro-tert-butyl alcohol (NFTBA) is an alcohol being used in medicine and for the analysis of physiochemical and biological properties. Quantum chemical calculations on NFTBA were carried out using cluster computers from the Texas Advanced Computing Center (TACC) at Austin, TX. We scanned the C–C–O–H dihedral angle for 36 steps with each step at 10 degrees at the B3LYP/aug-cc-pVTZ level in order to identify the stable conformations and the energy barriers. The geometry of nonafluoro-tert-butyl was studied using MP2 and B3LYP Density Functional Theory (DFT) with an aug-cc- pVTZ basis set. The calculated rotational constants and dipole moments were used to …

Growth And Reproduction In Gulf Of Mexico Black Corals (Antipatharians) In Field And Laboratory Studies, Victoria E. Salinas

Theses and Dissertations

Black corals provide an important ecosystem of marine life and are found throughout all the oceans of the world at depths between 2 and 8,600 m. However, little is understood about their life history and the factors that control the distribution of black corals, particularly in the Gulf of Mexico (GoM). Given the impacts of the Deepwater Horizon oil spill on soft corals (e.g., black corals and octocorals) in the GoM, studies of their growth and reproductive biology in both natural and aquaculture environments are crucial for restoration efforts. The objectives of this study were to examine reproductive processes, compare …

Monte Carlo Simulation Of Thallium-Bromide Semiconductor Detector For Range Verification Of A Carbon Ion Radiotherapy Beam Through Prompt Gamma-Ray Detection, Peter Dimpfl

UNLV Theses, Dissertations, Professional Papers, and Capstones

Thallium-Bromide is a semiconductor material which is well suited for photon detection. Composed of high atomic number elements and a high mass density of 7.56 g/cm3, TlBr has superb photon stopping power. External beam radiation therapy is an ever-changing environment with technology rapidly improving. With proton therapy facilities becoming more widely available, and carbon ion facilities showcasing the benefits of carbon ion radiation therapy, there is an industry need toprovide accurate dosimetric treatment plans to verify patients are receiving proper care. Current clinical practices apply safety margins to clinical target volumes to safe treatment. Through research to improve detection techniques, …

Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche

Electronic Theses and Dissertations

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …

The On-Line Width Of Various Classes Of Posets., Israel R. Curbelo

Electronic Theses and Dissertations

An on-line chain partitioning algorithm receives a poset, one element at a time, and irrevocably assigns the element to one of the chains. Over 30 years ago, Szemer\'edi proved that any on-line algorithm could be forced to use $\binom{w+1}{2}$ chains to partition a poset of width $w$. The maximum number of chains that can be forced on any on-line algorithm remains unknown. In the survey paper by Bosek et al., variants of the problem were studied where the class is restricted to posets of bounded dimension or where the poset is presented via a realizer of size $d$. We prove …

Classifying The 2022 Status Of Tsuga Canadensis (Eastern Hemlock) Along The Kentucky Portion Of The Pine Mountain Wildlands Corridor., Grace M. Embree

Electronic Theses and Dissertations

The invasion of the Hemlock Woolly Adelgid (HWA) (Adelges tsugae) has posed a continual threat in the United States to the Eastern Hemlock (Tsuga canadensis) trees since the 1950s. HWA feed on eastern hemlock needles, reducing the amount of healthy photosynthesizing vegetative area. The use of satellite imagery has been instrumental in identifying areas of eastern hemlock presence. Satellite platforms like Landsat and AVIRIS are commonly used for identification, classification, and mapping of eastern hemlock. Sentinel-2 imagery was released in 2015 for free access. It has a finer spatial grain of with the majority of the …

Effective Sequence Models And Graph Neural Networks For Molecular Data Analysis, Chaochao Yan

Computer Science and Engineering Dissertations

Drug discovery is the process of discovering new candidate medications. New drugs are continually developed by pharmaceutical industries to address increasing medical needs. Drug discovery involves a series of processes including target identification and validation, hit identification, lead generation and optimization, and finally the identification of a candidate for further development. The development further includes optimization of chemical synthesis and its formulation, toxicological studies in animals, clinical trials, and eventually regulatory approval. Both of these processes are time-consuming and cost-expensive. Computer-aided drug discovery mainly relies on modern computers to model drug molecules, which can speed up the process of drug …

Towards High Performance Cancer Staging From Histology Images, Ashwin Raju

Computer Science and Engineering Dissertations

Digital Pathology (DP) has been recently used in replacement to traditional microscopy samples as it easy to navigate and can be analysed, processed and saved. With the invention of Digital pathology, there has been exponential increase of automated process to make the life of Doctors easier. One such automated process is Artificial Intelligence (AI) where the AI is used as an assistant to Humans and to make the analysis and guide the experts. With the advent of AI and in particular Deep Learning, research has been divided and focused to solve multiple problems in Digital Pathology. One such important application …

Hand Analysis From Depth Images, Mohammad Rezaei

Computer Science and Engineering Dissertations

Hand analysis using vision systems is necessary for interaction between people and digital devices and thus is crucial in many applications relating to computer vision and human computer interaction (HCI). The proposed dissertation will explore hand analysis from depth images along two lines: hand part segmentation and 3D hand pose estimation. First, we investigate hand part segmentation from depth images, which is formulated as a semantic segmentation task. We explore a method aimed at determining for every pixel what hand part it belongs to. This method attempts to perform this task without requiring the ground-truth segmentation labels for training. It …

Diverse Effects Of Ev Charging Infrastructure On Electric Power Distribution Systems, Travis Michael Moore Newbolt

Open Access Theses & Dissertations

The advanced technology of today has allowed for an avenue into cleaner forms of energy that will not only protect our environment but also continue to advance our society. Among the many forms of clean energy, electric vehicles (EV) have the potential to mitigate our consumption of fossil fuels in vehicle transportation industries. In the U.S. for 2021, EVs account for approximately 700,000 registrations. That number is projected to increase to 2 million by 2030. Although EVs do reduce the number of emissions when compared to an internal combustion engine, they do however shift the responsibility to utility companies to …

A Computational Model Of The Line-1 Retrotransposon Life Cycle And Visualization Of Metabolic Networks In 3-Dimensions., Michael D. Martin

Electronic Theses and Dissertations

Computational modeling of metabolic reactions and cellular systems is evolving as a tool for quantitative prediction of metabolic parameters and reaction pathway analysis. In this work, the basics of computational cell biology are presented as well as a summary of physical processes within the cell, and the algorithmic methods used to find time dependent solutions. Protein-protein and enzyme-substrate interactions are mathematically represented via mass action kinetics to construct sets of linear differential equations that describe reaction rates and formation of protein complexes. Using mass action methods, examples of reaction networks and their solutions are presented within the Virtual Cell simulation …

Role Of Deep Learning Techniques In Non-Invasive Diagnosis Of Human Diseases., Hisham Abouelseoud Elsayem Abdeltawab

Electronic Theses and Dissertations

Machine learning, a sub-discipline in the domain of artificial intelligence, concentrates on algorithms able to learn and/or adapt their structure (e.g., parameters) based on a set of observed data. The adaptation is performed by optimizing over a cost function. Machine learning obtained a great attention in the biomedical community because it offers a promise for improving sensitivity and/or specificity of detection and diagnosis of diseases. It also can increase objectivity of the decision making, decrease the time and effort on health care professionals during the process of disease detection and diagnosis. The potential impact of machine learning is greater than …

Dimension And Ramsey Results In Partially Ordered Sets., Sida Wan

Electronic Theses and Dissertations

In this dissertation, there are two major parts. One is the dimension results on different classes of partially ordered sets. We developed new tools and theorems to solve the bounds on interval orders using different number of lengths. We also discussed the dimension of interval orders that have a representation with interval lengths in a certain range. We further discussed the interval dimension and semi dimension for posets. In the second part, we discussed several related results on the Ramsey theory of grids, the results involve the application of Product Ramsey Theorem and Partition Ramsey Theorem