Physical Sciences and Mathematics Commons^™

A Lightweight Reliably Quantified Deepfake Detection Approach, Tianyi Wang, Kam Pui Chow

Annual ADFSL Conference on Digital Forensics, Security and Law

Deepfake has brought huge threats to society such that everyone can become a potential victim. Current Deepfake detection approaches have unsatisfactory performance in either accuracy or efficiency. Meanwhile, most models are only evaluated on different benchmark test datasets with different accuracies, which could not imitate the real-life Deepfake unknown population. As Deepfake cases have already been raised and brought challenges at the court, it is disappointed that no existing work has studied the model reliability and attempted to make the detection model act as the evidence at the court. We propose a lightweight Deepfake detection deep learning approach using the …

A Contentious Crop: Exploring The Regulatory Debate Of Solar Power Production Facilities In Kittitas County, Washington, Daphne Condon

All Master's Theses

Between 2010 and 2018, Kittitas County, Washington faced an influx of Solar Power Production Facility (SPPF) proposals that challenged its traditional rural land management governance. Despite state support of decarbonized energy, variegated interpretations of project permitting procedures induced heated contentions amongst stakeholders. To explore this, this research constructs a multijurisdictional legal framework for SPPF advancement. It uses these laws to divulge the permitting processes of three case study projects founded in Kittitas County’s renewable energy history: The Wild Horse Wind Facility, the Iron Horse Solar Project, and the Columbia Solar Projects. Through a mixed methodology of project archival analysis and …

Longitudinal Patterns Of Microplastic Abundance And Potential For Food Web Uptake In The Yakima River, Janell Shah

All Master's Theses

Microplastic (MP) pollutes environments worldwide, but the ecological consequences remain largely unknown. While MP research has historically focused on marine environments, recent work has increasingly investigated rivers as transporters of MP from terrestrial sources to the ocean. Some studies have documented instances of MP consumption in a river food web, but few have investigated multiple consumers at different points along a river continuum. This study enumerated the MP abundance in the water column, biofilm, and four macroinvertebrate families from different functional feeding groups across nine sites spanning 344 kilometers from the headwaters to the mouth of the Yakima River in …

Interpretable Machine Learning For Self-Service High-Risk Decision Making, Charles Recaido

All Master's Theses

This research contributes to interpretable machine learning via visual knowledge discovery in General Line Coordinates (GLC). The concepts of hyperblocks as interpretable dataset units and GLC are combined to create a visual self-service machine learning model. Two variants of GLC known as Dynamic Scaffold Coordinates (DSC) are proposed. DSC1 and DSC2 can map in a lossless manner multiple dataset attributes to a single two-dimensional (X, Y) Cartesian plane using a dynamic scaffolding graph construction algorithm.

Hyperblock analysis is used to determine visually appealing dataset attribute orders and to reduce line occlusion. It is shown that hyperblocks can generalize decision tree …

Determining The Effects Of Chemical Exposure On Hepatocyte Mitochondrial Networks And Cell Viability, Bethany Eaton

All Master's Theses

Mitochondria are cellular organelles that are becoming more recently studied. One of their main functions is the production of energy through cellular respiration, which is crucial to cell life. However, they are also associated with numerous disease states. It is hypothesized that reactive oxygen species (ROS), largely produced in mitochondria, induce oxidative stress and affect mitochondrial morphology along with cell viability. This study compares chemical exposure of menadione, an ROS producer, and phthalates (plasticizers) on two mouse hepatocyte cell lines to determine the effects they have on mitochondrial morphology and cell viability. Three experiments were performed to analyze the effects …

Establishing The Relative Composition Of Functionalized Thiols In Mixed Ligand Gold Nanoparticles By 1h-Nmr Spectroscopy, Matthias Carroll

All Master's Theses

Functionalized gold nanoparticles (AuNPs) are of interest for their optical and electrical properties, specifically the surface plasmon resonance phenomenon and potential applications for medicine and nano-circuitry. In this study, the ligand composition of small (~5 nm diameter) thiol functionalized AuNPs with mixed ligand monolayers was investigated to better understand how the molar feed ratio of ligands used during their synthesis influences the composition of ligands on the particle’s surface. The system under study was a combination of two ω-functionalized thiols, mercapto ethoxy ethoxy ethanol (MEEE) and mercapto pentyl trimethyl ammonium chloride (MPTMA). UV/Visible spectrophotometry, dynamic light scattering, and electron …

Wilderness And The Geotag: Exploring The Claim That "Geotagging Ruins Nature" In The Alpine Lakes Wilderness, Wa, Mara Gans

All Master's Theses

This research explores the claim that “geotagging ruins nature” by quantifying and qualifying patterns in geotag use and visitors’ experiences in the Alpine Lakes Wilderness, in Washington, United States. Many have raised concerns that geotags increase recreational visitation to public lands, which subsequently contributes to negative resource impacts. Others, however, claim that geotagging has made the outdoors more accessible to less privileged communities and raise concerns that condemning geotags will perpetuate the exclusion of certain groups from outdoor recreation. This debate is studied within federally designated Wilderness, which is legally defined as “untrammeled by man,” a definition rooted in problematic …

Geomorphic History And Preservation Of Archaeologically Significant Areas In The Hanford Reach Of The Columbia River, Washington State, Benjamin Deans

All Master's Theses

Archaeological sites near rivers may be preserved through burial, altered by exposure, or destroyed through erosion. Preserved because of the unusual needs of the Manhattan Project, the Hanford Reach is the only remaining free-flowing reach of the Columbia River and ideal for research into the geomorphic settings of archaeological sites along this river. The 1894 (742,000 cfs [20,900 m³/s]) and 1948 (690,000 cfs [19,000 m³/s]) floods were the largest in the historical record through the reach, but their relationship with geomorphic change and site preservation are less understood. To understand how floods have preserved and destroyed …

Binding Interactions Between Mixed-Monlayer Functionalized Gold Nanoparticles (Aunps) And The Serum Protein Albumin, Jennifer Hanigan-Diebel

All Master's Theses

This study investigated the protein adsorption interactions of bovine serum albumin (BSA) with three different functionalized 5 nm gold nanoparticles (AuNPs) in order to determine the binding affinity and total amount of protein adsorbed to each AuNP surface chemistry. AuNPs were synthesized using two different capping agents to display three different surface chemistries: a neutral ω-functionalized thiol ligand (mercapto-ethoxy-ethoxy-ethanol, MEEE), a thiol ligand that is negatively charged at pH 7.4 (mercaptohexanoic acid, MHA), and a mixture of the two ligands (mixed-ligand AuNPs). The interactions of this library of AuNPs with bovine serum albumin (BSA) were investigated using UV-visible absorbance spectroscopy, …

The Effects Of Channel Incision And Land Use On Surface-Water/Groundwater Interactions In The Teanaway River Basin, Washington, Usa, Joseph Petralia

All Master's Theses

The Teanaway River basin, a major tributary to the Yakima River, is host to several restoration projects with the intention of returning the river channel to a more natural state and improving riparian habitat. These projects may also increase aquifer storage and potentially increase summertime streamflows. This study of the Teanaway Valley Family Farm, an 88-hectare parcel on the main-stem Teanaway River that was recently purchased by Washington Department of Fish and Wildlife, provides hydrogeologic data that will inform these restoration projects. Following the purchase of this land, ten wells were installed within and slightly above the floodplain in order …

Decadal-Scale Effects Of Large Wood Restoration On Channel Morphology And Groundwater Connectivity, Taneum Creek, Wa, Samuel Fixler

All Master's Theses

The importance of large wood (LW) in creating channel complexity is widely recognized; however, few LW projects have been in place long enough to track meaningful channel changes on a decadal timescale. Taneum Creek, located in central Washington, is one of the earliest LW restoration areas (2008) in the Yakima River Basin and the central Cascade Mountains. The flood in 2011, with an estimated discharge of 69 m³/s (2,400-2,800 cfs), provided further channel change by mobilizing LW and channel sediments. Three reaches with similar channel characteristics and LW additions were compared with a control reach without LW additions …

Assessing The Mechanics Of Two Earthquake Clusters In The Basin And Range Province, Jamie Hansen

All Master's Theses

The seismicity in the Basin and Range Province of the western United States often manifests as clusters of earthquakes occurring over brief windows of time, lasting from months to years. Two different earthquake clusters occurring between 2014 and 2018, near Challis, Idaho and northwestern Nevada, were assessed in this study. The seismic activity in the southeastern section of the Challis cluster began with a M5.2 earthquake that was likely the main-shock earthquake in an aftershock sequence. The northwestern section of the Challis cluster does have several potential candidates for a main-shock earthquake, but none have been identified as a start …

Extensive Thiol Profiling For Assessment Of Intracellular Redox Status In Cultured Cells By Hplc-Ms/Ms, Jiandong Wu, Anna Chernatynskaya, Annalise Pfaff, Huari Kou, Nan Cen, Nuran Ercal, Honglan Shi

Computer Science Faculty Research & Creative Works

Oxidative stress may contribute to the pathology of many diseases, and endogenous thiols, especially glutathione (GSH) and its metabolites, play essential roles in the maintenance of normal redox status. Understanding how these metabolites change in response to oxidative insult can provide key insights into potential methods of prevention and treatment. Most existing methodologies focus only on the GSH/GSH disulfide (GSSG) redox couple, but GSH regulation is highly complex and depends on several pathways with multiple redox-active sulfur-containing species. In order to more fully characterize thiol redox status in response to oxidative insult, a high-performance liquid chromatography with tandem mass spectrometry …

An Icn-Based Secure Task Cooperation Scheme In Challenging Wireless Edge Networks, Ningchun Liu, Shuai Gao, Teng Liang, Xindi Hou, Sajal K. Das

Computer Science Faculty Research & Creative Works

Task cooperation is an effective way to execute a complex task in challenging wireless edge networks. Existing TCP/IP-based solutions encounter the problem of low network resource utilization and the heavy dependency of infrastructure connections. Information-centric networking (ICN) is a promising architecture to address these issues. In existing ICN-based task cooperation schemes, the data reuse feature of ICN improves the utilization of network resources, which also brings potential security threats to the reused data. To guarantee the security of data reuse in task cooperation without affecting the data reuse feature, we propose an ICN-based secure task cooperation scheme. In our scheme, …

Mdz: An Efficient Error-Bounded Lossy Compressor For Molecular Dynamics, Kai Zhao, Sheng Di, Danny Perez, Xin Liang, Zizhong Chen, Franck Cappello

Computer Science Faculty Research & Creative Works

Molecular dynamics (MD) has been widely used in today's scientific research across multiple domains including materials science, biochemistry, biophysics, and structural biology. MD simulations can produce extremely large amounts of data in that each simulation could involve a large number of atoms (up to trillions) for a large number of timesteps (up to hundreds of millions). In this paper, we perform an in-depth analysis of a number of MD simulation datasets and then develop an efficient error-bounded lossy compressor that can significantly improve the compression ratios. The contributions are fourfold. (1) We characterize a number of MD datasets and summarize …

Locality-Aware Qubit Routing For The Grid Architecture, Avah Banerjee, Xin Liang, R. Tohid

Computer Science Faculty Research & Creative Works

Due to the short decohorence time of qubits available in the NISQ-era, it is essential to pack (minimize the size and or the depth of) a logical quantum circuit as efficiently as possible given a sparsely coupled physical architecture. In this work we introduce a locality-aware qubit routing algorithm based on a graph theoretic framework. Our algorithm is designed for the grid and certain 'grid-like' architectures. We experimentally show the competitiveness of algorithm by comparing it against the approximate token swapping algorithm, which is used as a primitive in many state-of-the-art quantum trans pilers. Our algorithm produces circuits of comparable …

Privacy-Preserving Data Falsification Detection In Smart Grids Using Elliptic Curve Cryptography And Homomorphic Encryption, Sanskruti Joshi, Ruixiao Li, Shameek Bhattacharjee, Sajal K. Das, Hayato Yamana

Computer Science Faculty Research & Creative Works

In an advanced metering infrastructure (AMI), the electric utility collects power consumption data from smart meters to improve energy optimization and provides detailed information on power consumption to electric utility customers. However, AMI is vulnerable to data falsification attacks, which organized adversaries can launch. Such attacks can be detected by analyzing customers' fine-grained power consumption data; however, analyzing customers' private data violates the customers' privacy. Although homomorphic encryption-based schemes have been proposed to tackle the problem, the disadvantage is a long execution time. This paper proposes a new privacy-preserving data falsification detection scheme to shorten the execution time. We adopt …

Rssafe: Personalized Driver Behavior Prediction For Safe Driving, Bhumika, Debasis Das, Sajal K. Das

Computer Science Faculty Research & Creative Works

While the increased demand for taxi services like Uber, Lyft, Hailo, Ola, Grab, Cabify etc. provides livelihood to many drivers, the desire to raise income forces the drivers to work very hard without rest. However, continuous journeys not only affect their health, but also lead to abnormal driving behavior such as rash driving, swerving, sideslipping, sudden brakes, or weaving, leading to accidents in the worst cases. Motivated by the severity of rising accidents and health issues among drivers, this paper proposes a recommendation system, called RsSafe, for the safety of drivers. Aiming to improve the driving quality and the driver's …

Anomaly Based Incident Detection In Large Scale Smart Transportation Systems, Jaminur Islam, Jose Paolo Talusan, Shameek Bhattacharjee, Francis Tiausas, Sayyed Mohsen Vazirizade, Abhishek Dubey, Keiichi Yasumoto, Sajal K. Das

Computer Science Faculty Research & Creative Works

Modern smart cities are focusing on smart transportation solutions to detect and mitigate the effects of various traffic incidents in the city. To materialize this, roadside units and ambient trans-portation sensors are being deployed to collect vehicular data that provides real-time traffic monitoring. In this paper, we first propose a real-time data-driven anomaly-based traffic incident detection framework for a city-scale smart transportation system. Specifically, we propose an incremental region growing approximation algorithm for optimal Spatio-temporal clustering of road segments and their data; such that road segments are strategically divided into highly correlated clusters. The highly correlated clusters enable identifying a …

Leveraging Spanning Tree To Detect Colluding Attackers In Federated Learning, Priyesh Ranjan, Federico Coro, Ashish Gupta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated learning distributes model training among multiple clients who, driven by privacy concerns, perform training using their local data and only share model weights for iterative aggregation on the server. In this work, we explore the threat of collusion attacks from multiple malicious clients who pose targeted attacks (e.g., label flipping) in a federated learning configuration. By leveraging client weights and the correlation among them, we develop a graph-based algorithm to detect malicious clients. Finally, we validate the effectiveness of our algorithm in presence of varying number of attackers on a classification task using a well-known Fashion-MNIST dataset.

Mathematics For Liberal Arts (Ma301), Lecture Notes, Lyubomir I. Boyadzhiev

Open Educational Resources

These lecture notes are designed to provide the students majoring in the liberal arts with an understanding and appreciation of mathematics as a lively, interesting, and surprisingly rich human activity with many fascinating applications. The text, emphasizing strongly intuitive thinking and visualization, is a collection of topics chosen to show the open-minded readers that:

• The connection between the mathematics presented in the course and down-to-earth, concrete real-life problems is transparent and immediate.
• Modern mathematical discoveries do not have to be the exclusive province of professional mathematicians.
• There is an important aesthetic component in mathematics, and just as in art and …

A Contraction Based Approach To Tensor Isomorphism, Anh Kieu

Honors Theses

Tensor isomorphism is a hard problem in computational complexity theory. Tensor isomorphism arises not just in mathematics, but also in other applied fields like Machine Learning, Cryptography, and Quantum Information Theory (QIT). In this thesis, we develop a new approach to testing (non)-isomorphism of tensors that uses local information from "contractions" of a tensor to detect differences in global structures. Specifically, we use projective geometry and tensor contractions to create a labelling data structure for a given tensor, which can be used to compare and distinguish tensors. This contraction labelling isomorphism test is quite general, and its practical potential remains …

Environmental Racism In Baltimore: A Geographical Study Into The Connections Between Environmental Toxins And Public Health, Genevieve Block

Honors Theses

An investigation into the relationship between environmental toxins and environmental racism in Baltimore City, Maryland.

Evaluating The Relationship Between Floodplain Topography And Channel Avulsion: Evidence From The Devonian Catskill Formation, North-Central Pennsylvania, Usa, Molly O'Halloran

Honors Theses

Topographic complexity on floodplains can route flow, control sediment dispersal, and influence channel behavior, but studying floodplain-channel interactions in modern rivers is challenging because of human modifications and the short timescales of observable data. This project assesses the link between different types of floodplain microtopography and avulsion style in the Devonian Catskill Formation, north-central Pennsylvania, where thick stacks of fluvial strata provide a lengthy record of channel-floodplain interaction. Using a combination of field observations and computer modeling, this study identifies sedimentary features indicative of floodplain complexity and analyzes their impact on avulsion style at fourteen Catskill Formation outcrops.

Based on …

Fidget Spinner Generator System For Mi-Star Unit 7.1, Douglas Oppliger

Mi-STAR

This simple system is an integral and important part of this unit. It allows students to see, feel, and experience how kinetic energy can be transformed to another kind of energy. It is an effective learning tool in the unit because it is reasonably easy to make, has just a few simple and visible components, and reliably transforms enough energy to light an LED (light emitting diode). The LED provides a satisfying light output which is easy to observe.

Meltpondnet: A Swin Transformer U-Net For Detection Of Melt Ponds On Arctic Sea Ice, Ivan Sudakow, Vijayan K. Asari, Ruixu Liu, Denis Demchev

Electrical and Computer Engineering Faculty Publications

High-resolution aerial photographs of Arctic region are a great source for different sea ice feature recognition, which are crucial to validate, tune, and improve climate models. Melt ponds on the surface of melting Arctic sea ice are of particular interest as they are sensitive and valuable indicators and are proxy to the processes in the Arctic climate system. Manual analysis of this remote sensing data is extremely difficult and time-consuming due to the complex shapes and unpredictable boundaries of the melt ponds, and that leads to the necessity for automatizing the processes. In this study, we propose a robust and …

Circuit Optimization Techniques For Efficient Ex-Situ Training Of Robust Memristor Based Liquid State Machine, Alex Henderson, Christopher Yakopcic, Cory Merkel, Steven Harbour, Tarek M. Taha, Hananel Hazan

Electrical and Computer Engineering Faculty Publications

Spiking neural network hardware offers a high performance, power-efficient and robust platform for the processing of complex data. Many of these systems require supervised learning, which poses a challenge when using gradient-based algorithms due to the discontinuous properties of SNNs. Memristor based hardware can offer gains in portability, power reduction, and throughput efficiency when compared to pure CMOS. This paper proposes a memristor-based spiking liquid state machine (LSM). The inherent dynamics of the LSM permit the use of supervised learning without backpropagation for weight updates. To carry out the design space evaluation of the LSM for optimal hardware performance, several …

Deep Learning Anomaly Detection Using Edge Ai, William Holdren

Electronic Theses and Dissertations, 2020-2023

Deep learning anomaly detection is an evolving field with many real-world applications. As more and more devices continue to be added to the Internet of Things (IoT), there is an increasing desire to make use of the additional computational capacity to run demanding tasks. The increase in devices and amounts of data flooding in have led to a greater need for security and outlier detection. Motivated by those facts, this thesis studies the potential of creating a distributed anomaly detection framework. While there have been vast amounts of research into deep anomaly detection, there has been no research into building …

Studying The Robustness Of Machine Learning-Based Malware Detection Models: Analysis, Design, And Implementation, Ahmed Abusnaina

Electronic Theses and Dissertations, 2020-2023

With the rise of the popularity of machine learning (ML), it has been shown that ML-based classifiers are susceptible to adversarial examples and concept drifting, where a small modification in the input space may result in misclassification. The ever-evolving nature of the data, the behavioral and pattern shifting over time not only lessened the trust in the machine learning output but also created a barrier for its usage in critical applications. This dissertation builds toward analyzing machine learning-based malware detection systems, including the detection and mitigation of adversarial malware examples. In particular, we first introduce two black-box adversarial attacks on …

Angler Catch Rates, Opinions, And Abiotic Variable Relationships In The Lower Logan River, Utah, Tyler Coleman, Jim Derito, Chris Penne, Gary Thiede, Phaedra Budy

Watershed Sciences Student Research

Summer base flows for rivers are critical for maintaining water quality, healthy fish populations, and a functional aquatic ecosystem. Low summer base flows can increase water temperatures and lower dissolved oxygen levels. These conditions can cause Brown Trout (Salmo trutta) energetic stress and result in lower angler catch. The goal of this study was to determine if low river flows and higher water temperatures influence angler catch rates of Brown Trout on the lower Logan River, Utah and to better understand angler use of the lower river. We performed a creel survey on approximately 6.4 km of the …