Physical Sciences and Mathematics Commons^™

Patagonian Aridification At The Onset Of The Mid‐Miocene Climatic Optimum, Robin B. Trayler, Matthew J. Kohn, M. Susana Bargo, José I. Cuitiño, Richard F. Kay, Caroline A. E. Strömberg, Sergio F. Vizcaíno

Geosciences Faculty Publications and Presentations

Fossil‐rich sediments of the Santa Cruz Formation, Patagonia, Argentina, span the initiation of the Miocene Climatic Optimum (MCO), the most recent period of warm and wet conditions in the Cenozoic. These conditions drove the expansion of tropical and subtropical ecosystems to much higher latitudes, with the fossiliferous Santa Cruz Formation recording one of the southernmost examples. We collected new carbon and oxygen isotope compositions of herbivore tooth enamel from fossils ~17.4 to 16.4 Ma in age to investigate ecological and climatic changes across the initiation of the MCO. Enamel δ¹³C values are consistent with a C₃‐dominated …

Unclonable Secret Keys, Marios Georgiou

Dissertations, Theses, and Capstone Projects

We propose a novel concept of securing cryptographic keys which we call “Unclonable Secret Keys,” where any cryptographic object is modified so that its secret key is an unclonable quantum bit-string whereas all other parameters such as messages, public keys, ciphertexts, signatures, etc., remain classical. We study this model in the authentication and encryption setting giving a plethora of definitions and positive results as well as several applications that are impossible in a purely classical setting.

In the authentication setting, we define the notion of one-shot signatures, a fundamental element in building unclonable keys, where the signing key not only …

Linear And Non-Linear Elastic Constants Of Crystalline Materials From First-Principles Calculations, David Cuffari

Dissertations, Theses, and Capstone Projects

Novel methods based on the use of density functional theory (DFT) calculations are developed and applied to calculate linear and non-linear elastic constants of materials at zero and finite temperature. These methods rely on finite difference techniques and are designed to be general, numerically accurate, and suitable to investigate the thermoelastic properties of anharmonic materials. A first method was developed to compute the third-order elastic constants of crystalline materials at zero temperature, a task that is numerically challenging and is currently undertaken by using approaches typically applicable to cubic and hexagonal crystalline systems. This method relies on numerical differentiation of …

Excitons In Self-Assembled Hybrid Systems Of Molecular Aggregate Light-Harvesting Nanotubes: Charge-Transfer Substrates And Solution-Stabilized Nanocomposites, Kara Ng

Dissertations, Theses, and Capstone Projects

Delocalized Frenkel excitons-coherently-shared excitations among chromophores-are responsible for the remarkable effciency of supramolecular light-harvesting aggregates within photosynthetic organisms. Despite tremendous progress towards a deeper understanding of these photosynthetic complexes, as well as progress in the development of organic solar cells, the possibility of using bio-inspired molecular nanostructures for large-scale solar energy conversion has not been realized yet. The persistent limitations in translating natures design principles for applications in optoelectronic devices have been the supramolecular structures fragility, and the Frenkel excitons delicate nature. The structural instability, both dis-assembly and spontaneous re-assembly of aggregates. Analysis of the absorption spectrum of a model …

Control Of Molecular Energetics And Transport Via Strong Light-Matter Interaction, Rong Wu

Dissertations, Theses, and Capstone Projects

Strong light-matter coupling in excitonic systems results in the formation of half-light half-matter quasiparticles called exciton polaritons. These hybrid quasiparticles take on the best of both systems, namely, the long-range propagation and coherence arising from the photonic component and the nonlinear interaction from the excitonic component. We develop methods for making high quality factor cavities and investigate the potential applications of these strongly coupled states arising specifically in organic molecular systems.

In the first project we investigate the potential of organic dye molecules to undergo condensation in an optical cavity at room temperature. The second study involves the use of …

A Data Exploration Of Jeopardy! From 1984 To The Present, Brian S. Hamilton

Dissertations, Theses, and Capstone Projects

The gameshow Jeopardy! has been around in its current iteration—hosted by Alex Trebek—since 1984. During this time, it has accumulated data on clues, contestants, and possible strategies on how to win. Using a crowd-sourced archive called J! Archive, this project seeks to find trends in the topics that the game covers and take a deeper look into the performance of its contestants. It employs topic modeling, a text-analysis method, to organize the hundreds of thousands of archived clues and statistical analysis to rate the performance of contestants by gender. Using web-based visualization tools, the data is shown in an …

Set Operators, Xiaojin Ye

Dissertations, Theses, and Capstone Projects

My research is centered on set operators. These are universally applicable regardless of the internal structure (numeric or non-numeric) of each individual observed datum. In our research, we have developed the theory of set operators to fill holes and gaps in observed data and eliminate paper shred garbage, thereby changing the observed symbolic data set into one whose pattern is closer to the pattern in the underlying population from which the observed data set was sampled with perturbations.

We describe different set operators including increasing operators, decreasing operators, ex- pansive operators, contractive operators, union preserving operators, intersection preserving op- erators, …

Role Of Influence In Complex Networks, Nur Dean

Dissertations, Theses, and Capstone Projects

Game theory is a wide ranging research area; that has attracted researchers from various fields. Scientists have been using game theory to understand the evolution of cooperation in complex networks. However, there is limited research that considers the structure and connectivity patterns in networks, which create heterogeneity among nodes. For example, due to the complex ways most networks are formed, it is common to have some highly “social” nodes, while others are highly isolated. This heterogeneity is measured through metrics referred to as “centrality” of nodes. Thus, the more “social” nodes tend to also have higher centrality.

In this thesis, …

Small Molecule Synthetic Carbohydrate Receptors, Marcelo F. Bravo Carranco

Dissertations, Theses, and Capstone Projects

Carbohydrate – receptor interactions are often involved in the attachment of viruses to host cells, and this docking is a necessary step in the virus life cycle that precedes infection and, ultimately, replication. Despite the conserved structures of the glycans involved in docking, they are still considered “undruggable”, meaning these glycans are beyond the scope of conventional pharmacological strategies. Recent advances in the development of synthetic carbohydrate receptors (SCRs) – small molecules that bind carbohydrates – could bring carbohydrate-receptor interactions within the purview of druggable targets. Here we discuss the role of carbohydrate-receptor interactions in viral infection, the evolution of …

Assessment Of Switchgrass-Based Bioenergy Supply Using Gis-Based Fuzzy Logic And Network Optimization In Missouri (U.S.A.), Gia Nguyen, Erik Lyttek, Pankaj Lal, Taylor Wieczerak, Pralhad Burli

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Bioenergy has been globally recognized as one of the sustainable alternatives to fossil fuels. An assured supply of biomass feedstocks is a crucial bottleneck for the bioenergy industry emanating from uncertainties in land-use changes and future prices. Analytical approaches deriving from geographical information systems (GIS)-based analysis, mathematical modeling, optimization analyses, and empirical techniques have been widely used to evaluate the potential for bioenergy feedstock. In this study, we propose a three-phase methodology integrating fuzzy logic, network optimization, and ecosystem services assessment to estimate potential bioenergy supply. The fuzzy logic analysis uses multiple spatial criteria to identify suitable biomass cultivating regions. …

Robust Localized Zero-Energy Modes From Locally Embedded Pt-Symmetric Defects, Fatemeh Mostafavi, Cem Yuce, Omar S. Magana-Loaiza, Henning Schomerus, Hamidreza Ramezani

Physics and Astronomy Faculty Publications and Presentations

We demonstrate the creation of robust localized zero-energy states that are induced into topologically trivial systems by insertion of a PT-symmetric defect with local gain and loss. A pair of robust localized states induced by the defect turns into zero-energy modes when the gain-loss contrast exceeds a threshold, at which the defect states encounter an exceptional point. Our approach can be used to obtain robust lasing or perfectly absorbing modes in any part of the system.

Mapping Geographical Inequalities In Access To Drinking Water And Sanitation Facilities In Low-Income And Middle-Income Countries, 2000–17, Aniruddha Deshpande, Robert C. Reiner Jr, Veincent Christian F. Pepito, Arianna Maever L. Amit, Local Burden Of Disease Wash Collaborators, 665 Co-Authors

Ateneo School of Medicine and Public Health Publications

Background

Universal access to safe drinking water and sanitation facilities is an essential human right, recognised in the Sustainable Development Goals as crucial for preventing disease and improving human wellbeing. Comprehensive, high-resolution estimates are important to inform progress towards achieving this goal. We aimed to produce high-resolution geospatial estimates of access to drinking water and sanitation facilities.

Methods

We used a Bayesian geostatistical model and data from 600 sources across more than 88 low-income and middle-income countries (LMICs) to estimate access to drinking water and sanitation facilities on continuous continent-wide surfaces from 2000 to 2017, and aggregated results to policy-relevant …

Pressure Driven Desalination Utilizing Nanomaterials, Fangyou Xie

Master's Theses

Nanomaterials such as graphene oxide and carbon nanotubes, have demonstrated excellent properties for membrane desalination, including decrease of maintenance, increase of flux rate, simple solution casting, and impressive chemical inertness. Here, two projects are studied to investigate nanocarbon based membrane desalination. The first project is to prepare hybrid membranes with amyloid fibrils intercalated with graphene oxide sheets. The addition of protein amyloid fibrils expands the interlayer spacing between graphene oxide nanosheets and introduces additional functional groups in the diffusion pathways, resulting in increase of flux rate and rejection rate for the organic dyes. Amyloid fibrils also provide structural assistance to …

Precision Measurement Of The Beam-Normal Single-Spin Asymmetry In Forward-Angle Elastic Electron-Proton Scattering, D. Androic, David S. Armstrong, Et Al.

Arts & Sciences Articles

A beam-normal single-spin asymmetry generated in the scattering of transversely polarized electrons from unpolarized nucleons is an observable related to the imaginary part of the two-photon exchange process. We report a 2% precision measurement of the beam-normal single-spin asymmetry in elastic electron-proton scattering with a mean scattering angle of theta_lab = 7.9 degrees and a mean energy of 1.149 GeV. The asymmetry result is B_n = -5.194 +- 0.067 (stat) +- 0.082 (syst) ppm. This is the most precise measurement of this quantity available to date and therefore provides a stringent test of two-photon exchange models at far-forward scattering angles …

Research 4.0: Research In The Age Of Automation, Rob Procter, Ben Glover, Elliot Jones

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

There is a growing consensus that we are at the start of a fourth industrial revolution, driven by developments in Artificial Intelligence, machine learning, robotics, the Internet of Things, 3-D printing, nanotechnology, biotechnology, 5G, new forms of energy storage and quantum computing. This wave of technical innovations is already having a significant impact on how research is conducted, with dramatic change across research methods in recent years within some disciplines, as this project’s interim report set out.

Whilst there are a wide range of technologies associated with the fourth industrial revolution, this report primarily seeks to understand what …

Rheological Studies Of Fully-Formulated Coatings Thickened With Heur: Effects Of Surfactants, Brandon M. Bonilla

Master's Theses

Rheology modifiers such as hydrophobically-modified ethoxylated urethane (HEUR)thickeners are included in waterborne latex coatings to optimize shear-rate dependent viscosity and other rheological properties. While these HEUR polymers are commonly used in industry, the complex chemical interactions that contribute to rheological properties are still not completely understood. Prior work in this area has focused on understanding latex-HEUR and latex-surfactant-HEUR interactions that affect rheological properties. Additionally, studies have been previously conducted to understand the relaxation mechanisms of complex interactions present in HEUR-thickened waterborne latex coatings under various dynamic conditions. The objective of this work is to extend the experimental work to fully-formulated …

Parametrically Excited Star-Shaped Patterns At The Interface Of Binary Bose-Einstein Condensates, D. K. Maity, K. Mukherjee, Simeon I. Mistakidis, S. Das, P. G. Kevrekidis, S. Majumder, P. Schmelcher

Physics Faculty Research & Creative Works

A Faraday-Wave-Like Parametric Instability Is Investigated Via Mean-Field And Floquet Analysis In Immiscible Binary Bose-Einstein Condensates. The Condensates Form A So-Called Ball-Shell Structure In A Two-Dimensional Harmonic Trap. To Trigger The Dynamics, The Scattering Length Of The Core Condensate Is Periodically Modulated In Time. We Reveal That In The Dynamics The Interface Becomes Unstable Towards The Formation Of Oscillating Patterns. The Interface Oscillates Subharmonically, Exhibiting An M-Fold Rotational Symmetry That Can Be Controlled By Maneuvering The Amplitude And The Frequency Of The Modulation. Using Floquet Analysis We Are Able To Predict The Generated Interfacial Tension Of The Mixture And Derive …

Cats Are Not Fish: Deep Learning Testing Calls For Out-Of-Distribution Awareness, David Berend, Xiaofei Xie, Lei Ma, Lingjun Zhou, Yang Liu, Chi Xu, Jianjun Zhao

Research Collection School Of Computing and Information Systems

As Deep Learning (DL) is continuously adopted in many industrial applications, its quality and reliability start to raise concerns. Similar to the traditional software development process, testing the DL software to uncover its defects at an early stage is an effective way to reduce risks after deployment. According to the fundamental assumption of deep learning, the DL software does not provide statistical guarantee and has limited capability in handling data that falls outside of its learned distribution, i.e., out-of-distribution (OOD) data. Although recent progress has been made in designing novel testing techniques for DL software, which can detect thousands of …

The Gap Of Semantic Parsing: A Survey On Automatic Math Word Problem Solvers, Dongxiang Zhang, Lei Wang, Luming Zhang, Bing Tian Dai, Heng Tao Shen

Research Collection School Of Computing and Information Systems

Solving mathematical word problems (MWPs) automatically is challenging, primarily due to the semantic gap between human-readable words and machine-understandable logics. Despite the long history dated back to the 1960s, MWPs have regained intensive attention in the past few years with the advancement of Artificial Intelligence (AI). Solving MWPs successfully is considered as a milestone towards general AI. Many systems have claimed promising results in self-crafted and small-scale datasets. However, when applied on large and diverse datasets, none of the proposed methods in the literature achieves high precision, revealing that current MWP solvers still have much room for improvement. This motivated …

Efficient Fine-Grained Data Sharing Mechanism For Electronic Medical Record Systems With Mobile Devices, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Zong, Kai He, Yuting Xiao

Research Collection School Of Computing and Information Systems

Sharing digital medical records on public cloud storage via mobile devices facilitates patients (doctors) to get (offer) medical treatment of high quality and efficiency. However, challenges such as data privacy protection, flexible data sharing, efficient authority delegation, computation efficiency optimization, are remaining toward achieving practical fine-grained access control in the Electronic Medical Record (EMR) system. In this work, we propose an innovative access control model and a fine-grained data sharing mechanism for EMR, which simultaneously achieves the above-mentioned features and is suitable for resource-constrained mobile devices. In the model, complex computation is outsourced to public cloud servers, leaving almost no …

Social Influence Attentive Neural Network For Friend-Enhanced Recommendation, Yuanfu Lu, Ruobing Xie, Chuan Shi, Yuan Fang, Wei Wang, Xu Zhang, Leyu Lin

Research Collection School Of Computing and Information Systems

With the thriving of online social networks, there emerges a new recommendation scenario in many social apps, called FriendEnhanced Recommendation (FER) in this paper. In FER, a user is recommended with items liked/shared by his/her friends (called a friend referral circle). These friend referrals are explicitly shown to users. Different from conventional social recommendation, the unique friend referral circle in FER may significantly change the recommendation paradigm, making users to pay more attention to enhanced social factors. In this paper, we first formulate the FER problem, and propose a novel Social Influence Attentive Neural network (SIAN) solution. In order to …

Privacy-Preserving Outsourced Calculation Toolkit In The Cloud, Ximeng Liu, Robert H. Deng, Kim-Kwang Raymond Choo, Yang Yang, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

In this paper, we propose a privacy-preserving outsourced calculation toolkit, Pockit, designed to allow data owners to securely outsource their data to the cloud for storage. The outsourced encrypted data can be processed by the cloud server to achieve commonly-used plaintext arithmetic operations without involving additional servers. Specifically, we design both signed and unsigned integer circuits using a fully homomorphic encryption (FHE) scheme, construct a new packing technique (hereafter referred to as integer packing), and extend the secure circuits to its packed version. This achieves significant improvements in performance compared with the original secure signed/unsigned integer circuit. The secure integer …

Fasts: A Satisfaction-Boosting Bus Scheduling Assistant (Demo), Momo Song, Zhifeng Bao, Baihua Zheng, Zhiyong Peng

Research Collection School Of Computing and Information Systems

In this paper, we demonstrate a satisfaction-boosting bus scheduling assistant called FASTS, which assists users to find an optimal bus schedule. FASTS performs bus scheduling based on the constraints specified by the user in either a coarse-grained or a fine-grained manner, supports different explorations with a varying number of constraints, and provides analysis to quantify the performance of bus schedules and presents the results in a visually pleasing way. We demonstrate FASTS using real-world bus routes (396 routes) and one-week bus touch-on/touch-off records (28 million trip records) in Singapore.

On Modeling Labor Markets For Fine-Grained Insights, Hendrik Santoso Sugiarto, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

The labor market consists of job seekers looking for jobs, and job openings waiting for applications. Classical labor market models assume that salary is the primary factor explaining why job-seekers select certain jobs. In practice, job seeker behavior is much more complex and there are other factors that should be considered. In this paper, we therefore propose the Probabilistic Labor Model (PLM) which considers salary satisfaction, topic preference matching, and accessibility as important criteria for job seekers to decide when they apply for jobs. We also determine the user and job latent variables for each criterion and define a graphical …

Urban Scale Trade Area Characterization For Commercial Districts With Cellular Footprints, Yi Zhao, Zimu Zhou, Xu Wang, Tongtong Liu, Zheng Yang

Research Collection School Of Computing and Information Systems

Understanding customer mobility patterns to commercial districts is crucial for urban planning, facility management, and business strategies. Trade areas are a widely applied measure to quantify where the visitors are from. Traditional trade area analysis is limited to small-scale or store-level studies, because information such as visits to competitor commercial entities and place of residence is collected by labour-intensive questionnaires or heavily biased location-based social media data. In this article, we propose CellTradeMap, a novel district-level trade area analysis framework using mobile flow records (MFRs), a type of fine-grained cellular network data. We show that compared to traditional cellular data …

Persona Perception Scale: Development And Exploratory Validation Of An Instrument For Evaluating Individuals' Perceptions Of Personas, Joni Salminen, Joao M. Santos, Haewoon Kwak, Jisun An, Soon-Gyo Jung

Research Collection School Of Computing and Information Systems

Although used in many domains, the evaluation of personas is difficult due to the lack of validated measurement instruments. To tackle this challenge, we propose the Persona Perception Scale (PPS), a survey instrument for evaluating how individuals perceive personas. We develop the scale by reviewing relevant literature from social psychology, persona studies, and Human-Computer Interaction to find relevant constructs and items for measuring persona perceptions. Following initial pilot testing, we conduct an exploratory validation of the scale with 412 respondents and find that the constructs and items of the scale perform satisfactorily for deployment. The research has implications for both …

A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Electric Vehicles (EVs) and charging infrastructure are starting to become commonplace in major cities around the world. For logistics providers to adopt an EV fleet, there are many factors up for consideration, such as route planning for EVs with limited travel range as well as long-term planning of fleet size. In this paper, we present a genetic algorithm to perform route planning that minimises the number of vehicles required. Specifically, we discuss the challenges on the violations of constraints in the EV routing problem (EVRP) arising from applying genetic algorithm operators. To overcome the challenges, techniques specific to addressing the …

An Empirical Study Of The Dependency Networks Of Deep Learning Libraries, Junxiao Han, Shuiguang Deng, David Lo, Chen Zhi, Jianwei Yin, Xin Xia

Research Collection School Of Computing and Information Systems

Deep Learning techniques have been prevalent in various domains, and more and more open source projects in GitHub rely on deep learning libraries to implement their algorithms. To that end, they should always keep pace with the latest versions of deep learning libraries to make the best use of deep learning libraries. Aptly managing the versions of deep learning libraries can help projects avoid crashes or security issues caused by deep learning libraries. Unfortunately, very few studies have been done on the dependency networks of deep learning libraries. In this paper, we take the first step to perform an exploratory …

Visualization Research Lab At Hkust, Yong Wang

Research Collection School Of Computing and Information Systems

HKUST VisLab (http://vis.cse.ust.hk/) is one of the leading research labs in the field of data visualization and human-computer interaction worldwide. The lab is dedicated to conducting cutting-edge research on data visualization and human-computer interaction to facilitate data exploration and analytics in various application domains, including E-learning, urban computing, social media and industry 4.0. Starting from its foundation by Prof. Huamin Qu in August 2004, the mission of HKUST VisLab is to build an excellent visualization research center and foster data visualization research and talent cultivation in Asia, as there were very few visualization researchers in Asia around 2004.

Accelerating All-Sat Computation With Short Blocking Clauses, Yueling Zhang, Geguang Pu, Jun Sun

Research Collection School Of Computing and Information Systems

The All-SAT (All-SATisfiable) problem focuses on finding all satisfiable assignments of a given propositional formula, whose applications include model checking, automata construction, and logic minimization. A typical ALL-SAT solver is normally based on iteratively computing satisfiable assignments of the given formula. In this work, we introduce BASOLVER, a backbone-based All-SAT solver for propositional formulas. Compared to the existing approaches, BASOLVER generates shorter blocking clauses by removing backbone variables from the partial assignments and the blocking clauses. We compare BASOLVER with 4 existing ALL-SAT solvers, namely MBLOCKING, BC, BDD, and NBC. Experimental results indicate that although finding all the backbone variables …