Physical Sciences and Mathematics Commons^™

Lightning-Fast And Privacy-Preserving Outsourced Computation In The Cloud, Ximeng Liu, Robert H. Deng, Pengfei Wu, Yang Yang

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud, which we refer to as LightCom. Using LightCom, a user can securely achieve the outsource data storage and fast, secure data processing in a single cloud server different from the existing multi-server outsourced computation model. Specifically, we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units (TPUs), which face the side-channel attack. Under the LightCom, we design two specified fast processing toolkits, which allow the user to achieve the commonly-used secure integer computation and …

Nearest Centroid: A Bridge Between Statistics And Machine Learning, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

In order to guide our students of machine learning in their statistical thinking, we need conceptually simple and mathematically defensible algorithms. In this paper, we present the Nearest Centroid algorithm (NC) algorithm as a pedagogical tool, combining the key concepts behind two foundational algorithms: K-Means clustering and K Nearest Neighbors (k- NN). In NC, we use the centroid (as defined in the K-Means algorithm) of the observations belonging to each class in our training data set and its distance from a new observation (similar to k-NN) for class prediction. Using this obvious extension, we will illustrate how the concepts of …

Secure And Verifiable Inference In Deep Neural Networks, Guowen Xu, Hongwei Li, Hao Ren, Jianfei Sun, Shengmin Xu, Jianting Ning, Haoming Yang, Kan Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Outsourced inference service has enormously promoted the popularity of deep learning, and helped users to customize a range of personalized applications. However, it also entails a variety of security and privacy issues brought by untrusted service providers. Particularly, a malicious adversary may violate user privacy during the inference process, or worse, return incorrect results to the client through compromising the integrity of the outsourced model. To address these problems, we propose SecureDL to protect the model’s integrity and user’s privacy in Deep Neural Networks (DNNs) inference process. In SecureDL, we first transform complicated non-linear activation functions of DNNs to low-degree …

Audee: Automated Testing For Deep Learning Frameworks, Qianyu Guo, Xiaofei Xie, Yi Li, Xiaoyu Zhang, Yang Liu, Xiaohong Li, Chao Shen

Research Collection School Of Computing and Information Systems

Deep learning (DL) has been applied widely, and the quality of DL system becomes crucial, especially for safety-critical applications. Existing work mainly focuses on the quality analysis of DL models, but lacks attention to the underlying frameworks on which all DL models depend. In this work, we propose Audee, a novel approach for testing DL frameworks and localizing bugs. Audee adopts a search-based approach and implements three different mutation strategies to generate diverse test cases by exploring combinations of model structures, parameters, weights and inputs. Audee is able to detect three types of bugs: logical bugs, crashes and Not-a-Number (NaN) …

Sadt: Syntax-Aware Differential Testing Of Certificate Validation In Ssl/Tls Implementations, Lili Quan, Qianyu Guo, Hongxu Chen, Xiaofei Xie, Xiaohong Li, Yang Liu, Jing Hu

Research Collection School Of Computing and Information Systems

The security assurance of SSL/TLS critically depends on the correct validation of X.509 certificates. Therefore, it is important to check whether a certificate is correctly validated by the SSL/TLS implementations. Although differential testing has been proven to be effective in finding semantic bugs, it still suffers from the following limitations: (1) The syntax of test cases cannot be correctly guaranteed. (2) Current test cases are not diverse enough to cover more implementation behaviours. This paper tackles these problems by introducing SADT, a novel syntax-aware differential testing framework for evaluating the certificate validation process in SSL/TLS implementations. We first propose a …

Adelaidecyc At Semeval-2020 Task 12: Ensemble Of Classifiers For Offensive Language Detection In Social Media, Mahen Herath, Thushari Atapattu, Hoang Anh Dung, Christoph Treude, Katrina Falkner

Research Collection School Of Computing and Information Systems

This paper describes the systems our team (AdelaideCyC) has developed for SemEval Task 12 (OffensEval 2020) to detect offensive language in social media. The challenge focuses on three subtasks – offensive language identification (subtask A), offense type identification (subtask B), and offense target identification (subtask C). Our team has participated in all the three subtasks. We have developed machine learning and deep learning-based ensembles of models. We have achieved F1-scores of 0.906, 0.552, and 0.623 in subtask A, B, and C respectively. While our performance scores are promising for subtask A, the results demonstrate that subtask B and C still …

The Persistence Of Acid Mine Drainage At An East Texas Coal Mine, Sarah Zagurski

Electronic Theses and Dissertations

The objective of this study was to estimate the time it will take for acid forming materials (pyrite) to be weathered to a state of equilibrium and thus cease to produce acid in ground and surface waters within Oak Hill Mine. This was accomplished using an ex-situ kinetic leaching study incorporating a humidity cell in a controlled laboratory setting. Leaching was conducted on soil cores obtained from the vadose zone at Oak Hill Mine and the humidity cell was used to accelerate oxidation of the pyrite within the cores.

An in-situ field study was also conducted that monitored groundwater conditions …

Transfer-To-Transfer Learning Approach For Computer Aided Detection Of Covid-19 In Chest Radiographs, Barath Narayanan Narayanan, Russell C. Hardie, Vignesh Krishnaraja, Christina Karam, Venkata Salini Priyamvada Davuluru

Electrical and Computer Engineering Faculty Publications

The coronavirus disease 2019 (COVID-19) global pandemic has severely impacted lives across the globe. Respiratory disorders in COVID-19 patients are caused by lung opacities similar to viral pneumonia. A Computer-Aided Detection (CAD) system for the detection of COVID-19 using chest radiographs would provide a second opinion for radiologists. For this research, we utilize publicly available datasets that have been marked by radiologists into two-classes (COVID-19 and non-COVID-19). We address the class imbalance problem associated with the training dataset by proposing a novel transfer-to-transfer learning approach, where we break a highly imbalanced training dataset into a group of balanced mini-sets and …

Walls Have Ears: Eavesdropping User Behaviors Via Graphics-Interrupt-Based Side Channel, Haoyu Ma, Jianwen Tian, Debin Gao, Jia Chunfu

Research Collection School Of Computing and Information Systems

Graphics Processing Units (GPUs) are now playing a vital role in many devices and systems including computing devices, data centers, and clouds, making them the next target of side-channel attacks. Unlike those targeting CPUs, existing side-channel attacks on GPUs exploited vulnerabilities exposed by application interfaces like OpenGL and CUDA, which can be easily mitigated with software patches. In this paper, we investigate the lower-level and native interface between GPUs and CPUs, i.e., the graphics interrupts, and evaluate the side channel they expose. Being an intrinsic profile in the communication between a GPU and a CPU, the pattern of graphics interrupts …

Secure Answer Book And Automatic Grading, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

In response to the growing need to perform assessments online, we have developed a secure answer book, as well as a tool for automatically grading it for our course on spread- sheet modeling. We applied these techniques to a cohort of about 160 students who took the course last term. In this paper, we describe the design, implementation and the techniques employed to enhance both the security of the answer book and the ease, accuracy and consistency of grading. In addition, we summarize the experience and takeaways, both from the instructor and the student perspectives. Although the answer book and …

Puerto Rico’S Electric Power System: An Analysis Of Contemporary Failures And The Opportunity To Rebuild A More Resilient Grid, Including The Development Of A Utility-Scale Solar Farm On The Island Municipality Of Culebra, Federico Sotomayor

Sustainability and Social Justice

Puerto Rico’s grid was decimated in 2017 after experiencing back-to-back hurricanes – Maria and Irma. Although the hurricanes caused tremendous damage and hardship to the island, it also created the right circumstances for the local energy landscape to transition toward a more resilient and sustainable model. Through an analysis of recent challenges by the local electric utility PREPA, and subsequent fallout from the hurricanes, we see that they now hold a unique opportunity to redeem themselves by taking advantage of catalyzed resources to rebuild a better system. One region that could greatly benefit from an improved and reimagined grid are …

Optimizing Raman Spectral Collection For Quartz And Zircon Crystals For Elastic Geothermobarometry, Mayara F. Cizina

Boise State University Theses and Dissertations

Raman microspectroscopy is widely used to identify and characterize organic and inorganic compounds. In the geosciences, Raman microspectroscopy has been used to identify mineral and fluid inclusions in host crystals, as well as to calculate pressure-temperature (P-T) conditions using mineral inclusions in host crystals, such as quartz-in-garnet barometry (QuiG). For thermobarometric applications, the reproducibility of Raman peak position measurements is crucial to obtain accurate P-T estimates. In this study, we explored how to optimize Raman spectral collection of quartz and zircon inclusions and reference crystals by monitoring machine stability and by varying spectral parameters. We also monitored a reference Hg …

Buried Soil Carbon Vulnerability To Decomposition With Landscape Disturbance, Abby Mcmurtry

Boise State University Theses and Dissertations

Buried layers of ancient soil organic carbon (SOC) can store significant amounts carbon (C). Persistence of this C is favored by burial, which disconnects the soil from atmospheric conditions and limits plant derived C inputs, thus reducing microbial activity. However, erosion exposes buried paleosols to modern surface conditions and results in influx of root-derived C through the processes of root exudation and root turnover. These C inputs stimulate microbial activity and leave paleosol C vulnerable to decomposition. Understanding turnover of ancient soil C is critical for predicting the response of this large C reservoir to environmental change and feedbacks to …

Analytic Solutions For Diffusion On Path Graphs And Its Application To The Modeling Of The Evolution Of Electrically Indiscernible Conformational States Of Lysenin, K. Summer Ware

Boise State University Theses and Dissertations

Memory is traditionally thought of as a biological function of the brain. In recent years, however, researchers have found that some stimuli-responsive molecules exhibit memory-like behavior manifested as history-dependent hysteresis in response to external excitations. One example is lysenin, a pore-forming toxin found naturally in the coelomic fluid of the common earthworm Eisenia fetida. When reconstituted into a bilayer lipid membrane, this unassuming toxin undergoes conformational changes in response to applied voltages. However, lysenin is able to "remember" past history by adjusting its conformational state based not only on the amplitude of the stimulus but also on its previous …

Unsupervised Structural Graph Node Representation Learning, Mikel Joaristi

Boise State University Theses and Dissertations

Unsupervised Graph Representation Learning methods learn a numerical representation of the nodes in a graph. The generated representations encode meaningful information about the nodes' properties, making them a powerful tool for tasks in many areas of study, such as social sciences, biology or communication networks. These methods are particularly interesting because they facilitate the direct use of standard Machine Learning models on graphs. Graph representation learning methods can be divided into two main categories depending on the information they encode, methods preserving the nodes connectivity information, and methods preserving nodes' structural information. Connectivity-based methods focus on encoding relationships between nodes, …

The Signal Of Modern To Holocene Drivers Of Complex Channel Response Of A Small Alluvial Stream, Scott D. Ducar

Boise State University Theses and Dissertations

Small alluvial streams (~100km² drainage area) are important for water resources and aquatic habitat. Small streams throughout the Western United States are impacted by anthropogenic land-use including urban development, mining, logging, beaver trapping, grazing, and farming. Land-use change can trigger a complex series of channel response (such as stream channel incision or channel migration) that vary spatially and temporally in the watershed. However, streams also respond to other external forcings, such as tectonically or climatically-driven changes in discharge or base-level, which make disentangling the drivers of channel response complicated. Therefore, it is important to place modern channel changes into …

Useable Coarse-Grained Models For Semiconducting Polymers And Thermosets, Michael Montgomery Henry

Boise State University Theses and Dissertations

This work aims to inform the formulation and processing of polymer mixtures through the use of models that have minimally sufficient complexity. Models with minimal complexity are easier to develop, understand, explain, and extend, all of which underpin model validation, verification, and reproducibility.

We develop simplified models for two different material systems, semiconducting polymers and thermosets. With the relatively low cost of predicting morphologies enabled by these models, we investigate structure-property-processing relationships in record system sizes and combinatorial parameter spaces. The insight from these models lays the foundation for improving the efficiency of organic solar cells and air travel.

The …

A Collection Of Fast Algorithms For Scalar And Vector-Valued Data On Irregular Domains: Spherical Harmonic Analysis, Divergence-Free/Curl-Free Radial Basis Functions, And Implicit Surface Reconstruction, Kathryn Primrose Drake

Boise State University Theses and Dissertations

This dissertation addresses problems that arise in a diverse group of fields including cosmology, electromagnetism, and graphic design. While these topics may seem disparate, they share a commonality in their need for fast and accurate algorithms which can handle large datasets collected on irregular domains. An important issue in cosmology is the calculation of the angular power spectrum of the cosmic microwave background (CMB) radiation. CMB photons offer a direct insight into the early stages of the universe's development and give the strongest evidence for the Big Bang theory to date. The Hierarchical Equal Area isoLatitude Pixelation (HEALPix) grid is …

Observed Defects Of Swiss Cheese Based On The Microbiome Contribution To The Production Of Organic Acids, Vannessa D. Campfield

Boise State University Theses and Dissertations

The United States Department of Agriculture downgrades on the order of 17% of all Swiss cheese produced in the United States due to defects. Many of these defects are related to improper eye formation, number, distribution, or size; leading to an industry loss of over $69 million per annum. The microbiome in Swiss-type cheeses plays a significant role in eye development due to production of organic acids and gaseous emissions contingent on bacterial abundance and phenotype. The relationship between bacteria and the organic acids they produce leading to Swiss cheese defects can be correlated using Next-generation sequencing and high-performance liquid …

Approaches To Studying Bacterial Biofilms In The Bioeconomy With Nanofabrication Techniques And Engineered Platforms., Michelle Caroline Halsted

Doctoral Dissertations

Studies that estimate more than 90% of bacteria subsist in a biofilm state to survive environmental stressors. These biofilms persist on man-made and natural surfaces, and examples of the rich biofilm diversity extends from the roots of bioenergy crops to electroactive biofilms in bioelectrochemical reactors. Efforts to optimize microbial systems in the bioeconomy will benefit from an improved fundamental understanding of bacterial biofilms. An understanding of these microbial systems shows promise to increase crop yields with precision agriculture (e.g. biosynthetic fertilizer, microbial pesticides, and soil remediation) and increase commodity production yields in bioreactors. Yet conventional laboratory methods investigate these micron-scale …

Framework Grain Composition And Texture Of The Wedington Sandstone Member, Fayetteville Shale, As A Provenance And Sediment Dispersal Indicator For Clastic Depositional Systems Across The Northern Arkansas Structural Platform During The Late Mississippian, Tanner Wayne Corbin

Graduate Theses and Dissertations

The Wedington Sandstone Member of the Fayetteville Shale is a constructive delta complex in the Chesterian section of the Late Mississippian record in Northwest Arkansas. A comparative analysis of framework grain composition between the Wedington and two other stratigraphically proximal Carboniferous sandstones: the Batesville Sandstone (older) and the Basal Atoka-Spiro Sandstone (younger) has addressed three questions: 1) Is there similarity in sediment provenance for the three sandstones? 2) Do these three sandstone units have a similar sediment dispersal vector? 3) What are likely sediment source terrains for the Wedington Sandstone? Wedington samples overwhelmingly plot as quartzarenites with fewer samples plotting …

Otolith Age Validation And Microchemical Investigation Of The Northern Stock F Atlantic Black Sea Bass (Centropristis Striata), Elise R. Koob

Graduate Masters Theses

Black sea bass (Centropristis striata) is a demersal marine species that supports extensive commercial and recreational fisheries along the Atlantic coast. A recent expansion into the Gulf of Maine raises questions about this species’ movement and population dynamics in the region. Additionally, the 2016 catch-at-age stock assessment model for the northern stock incorporated a population split at the Hudson Canyon. Though this model better accounts for differences in populations, several issues remain. First, validation of the otolith ageing technique for this stock is incomplete; and, second, the origin of fish that moved into the northern ranges of the Gulf of …

Assessing The Recalibration Interval For Nearshore Sediment Assemblages After Hurricane Irma: Implications For Developing Long-Term Records Of Overwash Deposits, Stephen Mitchell

Master's Theses

Surface distributions are commonly collected to assist with overwash interpretation; however, many of these are first established immediately after a major overwash event as part of a post-event field survey. This study documents the impacts of Hurricane Irma, a Category 5 storm, on nearshore sediments off the coast of Anegada (British Virgin Islands) using distributions of Homotrema rubra, an encrusting foraminifer with a defined provenance in coral reef ecosystems. Over four sampling intervals spanning 2 years, from six months pre-Hurricane Irma to 18 months post-Hurricane Irma, surface sediment was collected from three shore-perpendicular transects on both the northern and …

Random Search Plus: A More Effective Random Search For Machine Learning Hyperparameters Optimization, Bohan Li

Masters Theses

Machine learning hyperparameter optimization has always been the key to improve model performance. There are many methods of hyperparameter optimization. The popular methods include grid search, random search, manual search, Bayesian optimization, population-based optimization, etc. Random search occupies less computations than the grid search, but at the same time there is a penalty for accuracy. However, this paper proposes a more effective random search method based on the traditional random search and hyperparameter space separation. This method is named random search plus. This thesis empirically proves that random search plus is more effective than random search. There are some case …

Fast Neutron Assay Of Elemental Content Of Bulk Samples, Calder Emerson Lane

UNLV Theses, Dissertations, Professional Papers, and Capstones

The purpose of this research was to analyze the capabilities of fast neutrons in the detection and analysis of various isotopes in bulk samples. The deuterium-tritium (DT) fusion reaction generates highly penetrating, high-energy (14.1-MeV) neutrons which induce nuclear reactions in irradiated targets. Neutrons and gamma rays are generated in these reactions. Emitted gamma rays are characteristic of the emitter; the gamma spectrum enables stoichiometric identification of the assayed samples. Neutron backscattering can also be used for identification of the elemental composition of the sample.

This work had three objectives. The first objective was to develop a computational technique to model …

A Fortified Extension Of The Aes And Its Implementation, Ashby Mullin

UNLV Theses, Dissertations, Professional Papers, and Capstones

With the advancement of quantum computing (QC), the integrity of cryptography has been called into question. For example, two QC algorithms have been developed that can break asymmetric encryption (i.e., Grover’s, Shor’s), which also poses a threat to symmetric encryption. Asymmetric encryption efforts addressing this threat include lattice-based cryptography, which uses lattice problems to reduce efficiency of cryptanalysis. Symmetric encryption security can be bolstered by increasing the key length, allowing for additional permutations a key could have; known as keyspace. This thesis seeks to expand the keyspace of symmetric encryption in order to create more possibilities. This fortification to the …

Initial Measurements On The Effect Of Stress On P- And S-Wave Velocities In Olivine, Taryn Traylor

UNLV Theses, Dissertations, Professional Papers, and Capstones

It is well known that elasticity is a key physical property in the determination of the structure and composition of the Earth and provides critical information for the interpretation of seismic data. This study investigates the stress-induced variation in elastic wave velocities, known as the acoustoelastic effect, in San Carlos olivine. A recently developed experimental ultrasonic acoustic system, the Directly Integrated Acoustic System Combined with Pressure Experiments (DIASCoPE), was used with the D-DIA multi-anvil apparatus to transmit ultrasonic sound waves and collect the reflections. We use the DIASCoPE to obtain longitudinal (P) and shear (S) elastic wave velocities from the …

Microbe-Mineral Interactions During Exceptional Fossil Preservation, Stromatolite Formation, And Desert Varnish Growth, Michael Strange

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Ediacaran to Cambrian Deep Spring Formation consists of mixed carbonate-siliciclastic strata which contain an increasingly complex and biogeographically important biota. Past investigations of the Deep Spring Formation at Mt. Dunfee, Nevada, explored the highly diverse microbialite reefs consisting of a wide range of stromatolite morphologies which exerted significant control on local sedimentation and topography. Early investigations also documented the biomineralizing metazoan Cloudina (an Ediacaran index fossil). However, recent exploration of the area has resulted in the discovery of several new metazoan fossil communities consisting of a diverse assemblage of Ediacaran soft-tissue tubicolous vermiforms (tube fossils) similar to Cloudina. The …

The Processj C++ Runtime System And Code Generator, Alexander Christian Thomason

UNLV Theses, Dissertations, Professional Papers, and Capstones

ProcessJ is a modern Process-Oriented language that builds on previous work from other languages like occam and occam-pi. However, the only readily-available runtime system is built on top of the Java Virtual Machine (JVM). This is not a choice made intentionally, but simply out of a lack of other implementations -- until now. This thesis introduces the new C++-based runtime system for ProcessJ, coupled with a new C++ code generator for the ProcessJ compiler. This thesis later examines the implementation details of the runtime system, including the components that make it up. We also examine the ability to cooperatively schedule …

Developments Of Machine Learning Potentials For Atomistic Simulations, Howard Yanxon

UNLV Theses, Dissertations, Professional Papers, and Capstones

Atomistic modeling methods such as molecular dynamics play important roles in investigating time-dependent physical and chemical processes at the microscopic level. In the simulations, energy and forces, sometimes including stress tensor, need to be recalculated iteratively as the atomic configuration evolves. Consequently, atomistic simulations crucially depend on the accuracy of the underlying potential energy surface. Modern quantum mechanical modeling based on density functional theory can consistently generate an accurate description of the potential energy surface. In most cases, molecular dynamics simulations based on density functional theory suffer from highly demanding computational costs. On the other hand, atomistic simulations based on …