Physical Sciences and Mathematics Commons^™

Hu-Fu: Efficient And Secure Spatial Queries Over Data Federation, Yongxin Tong, Xuchen Pan, Yuxiang Zeng, Yexuan Shi, Chunbo Xue, Zimu Zhou, Xiaofei Zhang, Lei Chen, Yi Xu, Ke Xu, Weifeng Lv

Research Collection School Of Computing and Information Systems

Data isolation has become an obstacle to scale up query processing over big data, since sharing raw data among data owners is often prohibitive due to security concerns. A promising solution is to perform secure queries over a federation of multiple data owners leveraging secure multi-party computation (SMC) techniques, as evidenced by recent federation work over relational data. However, existing solutions are highly inefficient on spatial queries due to excessive secure distance operations for query processing and their usage of general-purpose SMC libraries for secure operation implementation. In this paper, we propose Hu-Fu, the first system for efficient and secure …

Mems Ultrasonic Transducers For Safe, Low-Power And Portable Eye-Blinking Monitoring, Sheng Sun, Jianyuan Wang, Menglun Zhang, Yuan Ning, Dong Ma, Yi Yuan, Pengfei Niu, Zhicong Rong, Zhuochen Wang, Wei Pang

Research Collection School Of Computing and Information Systems

Eye blinking is closely related to human physiology and psychology. It is an effective method of communication among people and can be used in human–machine interactions. Existing blink monitoring methods include video-oculography, electro-oculograms and infrared oculography. However, these methods suffer from uncomfortable use, safety risks, limited reliability in strong light or dark environments, and infringed informational security. In this paper, we propose an ultrasound-based portable approach for eye-blinking activity monitoring. Low-power pulse-echo ultrasound featuring biosafety is transmitted and received by microelectromechanical system (MEMS) ultrasonic transducers seamlessly integrated on glasses. The size, weight and power consumption of the transducers are 2.5 …

Imagining New Futures Beyond Predictive Systems In Child Welfare: A Qualitative Study With Impacted Stakeholders, Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alexandra Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi Zhu

Research Collection School Of Computing and Information Systems

Child welfare agencies across the United States are turning to datadriven predictive technologies (commonly called predictive analytics) which use government administrative data to assist workers’ decision-making. While some prior work has explored impacted stakeholders’ concerns with current uses of data-driven predictive risk models (PRMs), less work has asked stakeholders whether such tools ought to be used in the first place. In this work, we conducted a set of seven design workshops with 35 stakeholders who have been impacted by the child welfare system or who work in it to understand their beliefs and concerns around PRMs, and to engage them …

Information Sources, Perceived Personal Experience, And Climate Change Beliefs, Sonny Rosenthal

Research Collection College of Integrative Studies

This study proposes and tests a model of serial mediation based on the norm activation model and value-belief-norm theory. It argues that beliefs about climate change are related to perceived personal experience, which is related to the use of different information sources. Structural equation modeling of survey data from 1084 adult residents of Singapore found mixed support for three hypotheses. Results showed that perceived personal experience of climate change was related to the use of traditional media (β = 0.20), social media (β = 0.16), and interpersonal sources (β = 0.13), but not institutional sources. Perceived personal experience of climate …

Challenges For Inclusion In Software Engineering: The Case Of The Emerging Papua New Guinean Society, Raula Kula, Christoph Treude, Hideaki Hata, Sebastian Baltes, Igor Steinmacher, Marco Gerosa, Winifred Kula Amini

Research Collection School Of Computing and Information Systems

Software plays a central role in modern societies, with its high economic value and potential for advancing societal change. In this paper, we characterise challenges and opportunities for a country progressing towards entering the global software industry, focusing on Papua New Guinea (PNG). By hosting a Software Engineering workshop, we conducted a qualitative study by recording talks (n=3), employing a questionnaire (n=52), and administering an in-depth focus group session with local actors (n=5). Based on a thematic analysis, we identified challenges as barriers and opportunities for the PNG software engineering community. We also discuss the state of practices and how …

Do-Gan: A Double Oracle Framework For Generative Adversarial Networks, Aye Phyu Phye Aung, Xinrun Wang, Runsheng Yu, Bo An, Senthilnath Jayavelu, Xiaoli Li

Research Collection School Of Computing and Information Systems

In this paper, we propose a new approach to train Gen-erative Adversarial Networks (GANs) where we deploy a double-oracle framework using the generator and discrim-inator oracles. GAN is essentially a two-player zero-sum game between the generator and the discriminator. Training GANs is challenging as a pure Nash equilibrium may not exist and even finding the mixed Nash equilibrium is difficult as GANs have a large-scale strategy space. In DO-GAN, we extend the double oracle framework to GANs. We first generalize the players' strategies as the trained models of generator and discriminator from the best response or-acles. We then compute the …

Differential Cost Analysis With Simultaneous Potentials And Anti-Potentials, Dorde Zikelic, Bor-Yuh Evan Chang, Pauline Bolignano, Franco Raimondi

Research Collection School Of Computing and Information Systems

We present a novel approach to differential cost analysis that, given a program revision, attempts to statically bound the difference in resource usage, or cost, between the two program versions. Differential cost analysis is particularly interesting because of the many compelling applications for it, such as detecting resource-use regressions at code-review time or proving the absence of certain side-channel vulnerabilities. One prior approach to differential cost analysis is to apply relational reasoning that conceptually constructs a product program on which one can over-approximate the difference in costs between the two program versions. However, a significant challenge in any relational approach …

Draft Final Blacktail Creek Remediation And Contaminated Groundwater Hydraulic Control Site Piezometer Installation And Monitoring Well Repair Plan, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Bpsou Draft Final Residential Metals Abatement Program (Rmap) Qapp (Non-Residential Parcels) (5/12/22), Nikia Greene, Butte Silver Bow, Atlantic Richfield Company

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

2022 - Draft Final - Butte Reduction Works (Brw) Smelter Area Mine Waste Remediation And Contaminated Groundwater Hydraulic Control Site Phase Iii Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Scheduling For Space Tracking And Heterogeneous Sensor Environments, Gabriel H. Greve

Theses and Dissertations

This dissertation draws on the fields of heuristic and meta-heuristic algorithm development, resource allocation problems, and scheduling to address key Air Force problems. The world runs on many schedules. People depend upon them and expect these schedules to be accurate. A process is needed where schedules can be dynamically adjusted to allow tasks to be completed efficiently. For example, the Space Surveillance Network relies on a schedule to track objects in space. The schedule must use sensor resources to track as many high-priority satellites as possible to obtain orbit paths and to warn of collision paths. Any collisions that occurred …

Innovative Heuristics To Improve The Latent Dirichlet Allocation Methodology For Textual Analysis And A New Modernized Topic Modeling Approach, Jamie T. Zimmerman

Theses and Dissertations

Natural Language Processing is a complex method of data mining the vast trove of documents created and made available every day. Topic modeling seeks to identify the topics within textual corpora with limited human input into the process to speed analysis. Current topic modeling techniques used in Natural Language Processing have limitations in the pre-processing steps. This dissertation studies topic modeling techniques, those limitations in the pre-processing, and introduces new algorithms to gain improvements from existing topic modeling techniques while being competitive with computational complexity. This research introduces four contributions to the field of Natural Language Processing and topic modeling. …

A Unified View Of A Human Digital Twin, Michael Miller, Emily Spatz

Faculty Publications

The term human digital twin has recently been applied in many domains, including medical and manufacturing. This term extends the digital twin concept, which has been illustrated to provide enhanced system performance as it combines system models and analyses with real-time measurements for an individual system to improve system maintenance. Human digital twins have the potential to change the practice of human system integration as these systems employ real-time sensing and feedback to tightly couple measurements of human performance, behavior, and environmental influences throughout a product’s life cycle to human models to improve system design and performance. However, as this …

Understanding Rapid Intercalation Materials One Parameter At A Time, Wessel Van Den Bergh, Morgan Stefik

Faculty Publications

Demand for fast, energy-dense storage drives the research into nanoscale intercalation materials. Nanomaterials accelerate kinetics and can modify reaction path thermodynamics, intercalant solubility, and reversibility. The discovery of intercalation pseudocapacitance has opened questions about their fundamental operating principles. For example, are their capacitor-like current responses caused by storing energy in special near-surface regions or rather is this response due to normal intercalation limited by a slower faradaic surface-reaction? This review highlights emerging methods combining tailored nanomaterials with the process of elimination to disambiguate cause-and-effect at the nanoscale. This method is applied to multiple intercalation pseudocapacitive materials showing that the timescales …

Diagnostics Of Dementia From Structural And Functional Markers Of Brain Atrophy With Machine Learning, Tetiana Habuza

Dissertations

Dementia is a condition in which higher mental functions are disrupted. It currently affects an estimated 57 million people throughout the world. A dementia diagnosis is difficult since neither anatomical indicators nor functional testing is currently sufficiently sensitive or specific. There remains a long list of outstanding issues that must be addressed. First, multimodal diagnosis has yet to be introduced into the early stages of dementia screening. Second, there is no accurate instrument for predicting the progression of pre-dementia. Third, non-invasive testing cannot be used to provide differential diagnoses. By creating ML models of normal and accelerated brain aging, we …

Symplectically Integrated Symbolic Regression Of Hamiltonian Dynamical Systems, Daniel Dipietro

Computer Science Senior Theses

Here we present Symplectically Integrated Symbolic Regression (SISR), a novel technique for learning physical governing equations from data. SISR employs a deep symbolic regression approach, using a multi-layer LSTMRNN with mutation to probabilistically sample Hamiltonian symbolic expressions. Using symplectic neural networks, we develop a model-agnostic approach for extracting meaningful physical priors from the data that can be imposed on-the-fly into the RNN output, limiting its search space. Hamiltonians generated by the RNN are optimized and assessed using a fourth-order symplectic integration scheme; prediction performance is used to train the LSTM-RNN to generate increasingly better functions via a risk-seeking policy gradients …

Silverrush. Xii. Intensity Mapping For Ly Α Emission Extending Over 100-1000 Comoving Kpc Around Z ∼2-7 Laes With Subaru Hsc-Ssp And Chorus Data, Shotaro Kikuchihara, Yuichi Harikane, Masami Ouchi, Yoshiaki Ono, Takatoshi Shibuya, Ryohei Itoh, Ryota Kakuma, Akio K. Inoue, Haruka Kusakabe, Kazuhiro Shimasaku, Rieko Momose, Yuma Sugahara, Satoshi Kikuta, Shun Saito

Physics Faculty Research & Creative Works

We conduct intensity mapping to probe for extended diffuse Lyα emission around Lyα emitters (LAEs) at z ∼2-7, exploiting very deep (∼26 mag at 5σ) and large-area (∼4.5 deg2) Subaru/Hyper Suprime-Cam narrowband (NB) images and large LAE catalogs consisting of a total of 1540 LAEs at z = 2.2, 3.3, 5.7, and 6.6 obtained by the HSC-SSP and CHORUS projects. We calculate the spatial correlations of these LAEs with ∼1-2-billion-pixel flux values of the NB images, deriving the average Lyα surface brightness (SBLyα ) radial profiles around the LAEs. By carefully estimating systematics such as fluctuations of sky background and …

The Application Of Electron Backscatter Diffraction To The Forensic Analysis Of Minerals, Tiffany J. Millett

Dissertations, Theses, and Capstone Projects

Electron Backscatter Diffraction has been largely used in the metallurgic and material sciences and until now, has found few applications in the forensic sciences. One of the few utilizations of this technique in forensic science is in firearm serial number restoration as a complementary technique to the time-consuming and tedious chemical etching methods. This research aims to expand the uses of Electron Backscatter Diffraction in the forensic sciences as it applies to other types of samples, specifically as it pertains to forensic mineral analysis.

Electron Backscatter Diffraction offers the analyst information regarding crystal structure of a material, so long as …

Fractional Bernstein Operational Matrices For Solving Integro-Differential Equations Involved By Caputo Fractional Derivative, M.H.T. Alshbool, Mutaz Mohammad, Osman Isik, Ishak Hashim

All Works

The present work is devoted to developing two numerical techniques based on fractional Bernstein polynomials, namely fractional Bernstein operational matrix method, to numerically solving a class of fractional integro-differential equations (FIDEs). The first scheme is introduced based on the idea of operational matrices generated using integration, whereas the second one is based on operational matrices of differentiation using the collocation technique. We apply the Riemann–Liouville and fractional derivative in Caputo’s sense on Bernstein polynomials, to obtain the approximate solutions of the proposed FIDEs. We also provide the residual correction procedure for both methods to estimate the absolute errors. Some results …

Recreating Nasa Images Using Hubble Data: Two Populations Of Stars In Messier 5, Adam N. Looper

Physics

This project seeks to recreate a color photo from NASA using Hubble data that shows the two distinct populations of stars in the cluster. Although the colored image displays the two types of stars, scientists often recolor astronomical pictures for two reasons: in order to clearly define objects, or to convert an image taken outside the visible spectrum into color. Thus, overlapping Hubble images colored according to filter should verify that there are two populations of stars in Messier 5, and the colored NASA photograph is valid in highlighting the unusual distribution of stars.

A Comparison Of Exotic And Pyraf In Analyzing Exoplanet Transits, Kailei A. Gallup

Physics

In this paper we discuss the data analysis processes using PyRaf, a Python-based version of IRAF, which is one of the most commonly used coding softwares in the astronomy community, as well as the analysis process using EXOTIC. Additionally, we will compare the outcomes from each process to determine if either has significant benefits over the other.

Solid Thermal Storage As An Energy Storage Device In Insulated Solar Electric Cookers: Thermal Modeling And Experiment, Michael Antonio Fernandez

Physics

The use of solid thermal storage (STS) as an energy storage device in insulated solar electric cookers (ISEC) was explored using a thermal simulation before retrofitting an existing cooker without energy storage and testing it under several conditions. STS sizing, material selection, and geometry were examined from both theoretical and practical perspectives and re-examined following experimental results. Characterization of the system’s thermal interfaces and methods to improve their thermal conductivities were investigated resulting in several performance enhancements to the system.

Quantum Key Distribution Simulation Using Entangled Bell States, Nayana Tiwari

Physics

To communicate information securely, the sender and recipient of the information need to have a shared, secret key. Quantum key distribution (QKD) is a proposed method for this and takes advantage of the laws of quantum mechanics. The users, Alice and Bob, exchange quantum information in the form of entangled qubits over a quantum channel as well as exchanging measurement information over a classical channel. A successful QKD algorithm will ensure that when an eavesdropper has access to both the quantum and classical information channels, they cannot deduce the key, and they will be detected by the key generators. This …

Developing A Data Acquisition System For Use In Cold Neutral Atom Traps, Jonathan E. Fuzaro Alencar

Physics

The rising interest in quantum computing has led to new quantum systems being developed and researched. Among these are trapped neutral atoms which have several desirable features and may be configured and operated on using lasers in an optical lattice. This work describes the development of a new data acquisition system for use in tuning lasers near the precise hyperfine transition frequencies of Rb 87 atoms, a crucial step in the functionality of a neutral atom trap. This improves on previous implementations that were deprecated and limited in laser frequency sweep range. Integration into the experiment was accomplished using an …

Data-Driven Analysis Of Drug And Substance Abuse Rates Across The Varying Regions In The United States Of America, Reem Saleh

University Honors Theses

Drugs and substance abuse is one of the leading causes of death for adolescents in the United States. The consequences of using these drugs are profound and can cause both damage to one's physical and psychological health. The rates of drug abuse in the United States continue to increase over the years. This paper analyzes the trends in rates of drug abuse in the four regions in the United States. It looks at the rates in cocaine, cigarettes, marijuana, and tobacco. A preliminary analysis was done to look at the trend in rates followed by an ARIMA time series model …

A Bidirectional Formulation For Walk On Spheres, Yang Qi

Dartmouth College Master’s Theses

Poisson’s equations and Laplace’s equations are important linear partial differential equations (PDEs)
widely used in many applications. Conventional methods for solving PDEs numerically often need to
discretize the space first, making them less efficient for complex shapes. The random walk on spheres
method (WoS) is a grid-free Monte-Carlo method for solving PDEs that does not need to discrete the
space. We draw analogies between WoS and classical rendering algorithms, and find that the WoS
algorithm is conceptually identical to forward path tracing.
We show that solving the Poisson’s equation is equivalent to solving the Green’s function for every
pair of …

Biomimetic And Medical Applications Of Hollow Nanoscale Structures, Justin Fang

Dissertations, Theses, and Capstone Projects

Materials whose structure incorporates nanoscale void spaces have multiple possible uses, whether in a bulk form or as individual particles, due to the combination of high surface area ratios and nanoscale material properties. This thesis will explore a few of these possibilities, concentrating on potential biomimetic and biomedical applications, for two materials: metal- organic frameworks and superparamagnetic iron oxide nanocages.

Metal-organic frameworks consist of metal ions such as Cu2+ which have highly porous lattice structures allowing them to absorb and release guest molecules such as peptides like diphenylalanine; this stored chemical energy can be turned into kinetic energy and used …

The Zariski-Riemann Space As A Universal Model For The Birational Geometry Of A Function Field, Giovan Battista Pignatti Morano Di Custoza

Dissertations, Theses, and Capstone Projects

Given a function field $K$ over an algebraically closed field $k$, we propose to use the Zariski-Riemann space $\ZR (K/k)$ of valuation rings as a universal model that governs the birational geometry of the field extension $K/k$. More specifically, we find an exact correspondence between ad-hoc collections of open subsets of $\ZR (K/k)$ ordered by quasi-refinements and the category of normal models of $K/k$ with morphisms the birational maps. We then introduce suitable Grothendieck topologies and we develop a sheaf theory on $\ZR (K/k)$ which induces, locally at once, the sheaf theory of each normal model. Conversely, given a sheaf …

Symmetry-Inspired Analysis Of Biological Networks, Ian Leifer

Dissertations, Theses, and Capstone Projects

The description of a complex system like gene regulation of a cell or a brain of an animal in terms of the dynamics of each individual element is an insurmountable task due to the complexity of interactions and the scores of associated parameters. Recent decades brought about the description of these systems that employs network models. In such models the entire system is represented by a graph encapsulating a set of independently functioning objects and their interactions. This creates a level of abstraction that makes the analysis of such large scale system possible. Common practice is to draw conclusions about …

A Simple Data Mixing Prior For Improving Self-Supervised Learning, Sucheng Ren, Huiyu Wang, Zhengqi Gao, Shengfeng He, Alan Yuille, Yuyin Zhou, Cihang Xie

Research Collection School Of Computing and Information Systems

Data mixing (e.g., Mixup, Cutmix, ResizeMix) is an essential component for advancing recognition models. In this paper, we focus on studying its effectiveness in the self-supervised setting. By noticing the mixed images that share the same source images are intrinsically related to each other, we hereby propose SDMP, short for Simple Data Mixing Prior, to capture this straightforward yet essential prior, and position such mixed images as additional positive pairs to facilitate self-supervised representation learning. Our experiments verify that the proposed SDMP enables data mixing to help a set of self-supervised learning frameworks (e.g., MoCo) achieve better accuracy and out-of-distribution …