Computer Sciences Commons^™

Take The Lead: Toward A Virtual Video Dance Partner, Ty Farris

Master's Theses

My work focuses on taking a single person as input and predicting the intentional movement of one dance partner based on the other dance partner's movement. Human pose estimation has been applied to dance and computer vision, but many existing applications focus on a single individual or multiple individuals performing. Currently there are very few works that focus specifically on dance couples combined with pose prediction. This thesis is applicable to the entertainment and gaming industry by training people to dance with a virtual dance partner.

Many existing interactive or virtual dance partners require a motion capture system, multiple cameras …

Verification Of Piecewise Deep Neural Networks: A Star Set Approach With Zonotope Pre-Filter, Hoang-Dung Tran, Neelanjana Pal, Diego Manzanas Lopez, Patrick Musau, Xiaodong Yang, Luan Viet Nguyen, Weiming Xiang, Stanley Bak, Taylor T. Johnson

Computer Science Faculty Publications

Verification has emerged as a means to provide formal guarantees on learning-based systems incorporating neural network before using them in safety-critical applications. This paper proposes a new verification approach for deep neural networks (DNNs) with piecewise linear activation functions using reachability analysis. The core of our approach is a collection of reachability algorithms using star sets (or shortly, stars), an effective symbolic representation of high-dimensional polytopes. The star-based reachability algorithms compute the output reachable sets of a network with a given input set before using them for verification. For a neural network with piecewise linear activation functions, our approach can …

Innovative Computational Methods For Pharmaceutical Problem Solving A Review Part Ii: Serious Gaming, Heather R. Campbell, Robert A. Lodder

Pharmaceutical Sciences Faculty Publications

Serious gaming has begun to take a foothold in pharmaceutical problem-solving. Companies such as Akili's Interactive are seeing success in the form of positive clinical trial results and FDA approval of digital therapeutics. Academic researchers have begun exploring novel uses for serious gaming in the way of protein design and more with promising results. This paper provides a review of such topics in addition to topics of game repurposing- repurposing a game originally intended for entertainment into a serious game-such as Minecraft and America's Army. Reviewing these topics this paper shows the utility of serious gaming as a tool for …

Innovative Computational Methods For Pharmaceutical Problem Solving A Review Part I: The Drug Development Process, Heather R. Campbell, Robert A. Lodder

Pharmaceutical Sciences Faculty Publications

Computational methods have provided pharmaceutical scientists and engineers a means to go beyond what's possible with experimental testing alone. Providing a means to study active pharmaceutical ingredients (API), excipients, and drug interactions at or near-atomic levels. This paper provides a review of this and other innovative computational methods used for solving pharmaceutical problems throughout the drug development process. Part one of two this paper will emphasize the role of computational methods and game theory in solving pharmaceutical challenges.

Hardware For Quantized Mixed-Precision Deep Neural Networks, Andres Rios

Open Access Theses & Dissertations

Recently, there has been a push to perform deep learning (DL) computations on the edge rather than the cloud due to latency, network connectivity, energy consumption, and privacy issues. However, state-of-the-art deep neural networks (DNNs) require vast amounts of computational power, data, and energyâ??resources that are limited on edge devices. This limitation has brought the need to design domain-specific architectures (DSAs) that implement DL-specific hardware optimizations. Traditionally DNNs have run on 32-bit floating-point numbers; however, a body of research has shown that DNNs are surprisingly robust and do not require all 32 bits. Instead, using quantization, networks can run on …

A Real-World, Hybrid Event Sequence Generation Framework For Android Apps, Jun Sun

School of Computing: Dissertations, Theses, and Student Research

Generating meaningful inputs for Android apps is still a challenging issue that needs more research. Past research efforts have shown that random test generation is still an effective means to exercise User-Interface (UI) events to achieve high code coverage. At the same time, heuristic search approaches can effectively reach specified code targets. Our investigation shows that these approaches alone are insufficient to generate inputs that can exercise specific code locations in complex Android applications.

This thesis introduces a hybrid approach that combines two different input generation techniques--heuristic search based on genetic algorithm and random instigation of UI events, to reach …

Using Contextual Bandits To Improve Traffic Performance In Edge Network, Aziza Al Zadjali

School of Computing: Dissertations, Theses, and Student Research

Edge computing network is a great candidate to reduce latency and enhance performance of the Internet. The flexibility afforded by Edge computing to handle data creates exciting range of possibilities. However, Edge servers have some limitations since Edge computing process and analyze partial sets of information. It is challenging to allocate computing and network resources rationally to satisfy the requirement of mobile devices under uncertain wireless network, and meet the constraints of datacenter servers too. To combat these issues, this dissertation proposes smart multi armed bandit algorithms that decide the appropriate connection setup for multiple network access technologies on the …

Towards Machine Learning-Based Demand Response Forecasting Using Smart Grid Data, Matthew S. Johnson

Theses, Dissertations and Culminating Projects

Demand response is a valuable tool for improving the reliability, stability, and financial efficiency of smart grids. With the intention of altering customer power consumption patterns, utility companies often implement strategies such as time-of-use (TOU) programs. Although effective in some situations, TOU programs struggle to perform in highly developed countries due to the complexity of human behavior. In this study, we analyze power consumption readings from smart meters from 5567 households in London, UK from November 2011 to February 2014 to measure the success of the TOU program. We additionally consider the variability of weather conditions and customer demographics when …

Theoretical And Observational Analysis Of Ice Particles For Improvement Of Ice Microphysical Models, Vanessa Przybylo

Legacy Theses & Dissertations (2009 - 2024)

Frozen hydrometeors can grow to acquire a multitude of shapes and sizes, which influence the distribution of mass within cloud systems. Aggregates have a variety of formations based on initial ice particle size, shape, falling orientation, and the number of particles that collect. This work employs the theoretical Ice Particle and Aggregate Simulator (IPAS) as a statistical tool to repetitively collect ice crystals to derive bulk aggregate characteristics.

The Foundations Of Inference And Its Application To Fundamental Physics, Nicholas Matthew Carrara

Legacy Theses & Dissertations (2009 - 2024)

This thesis concerns the foundations of inference – probability theory,entropic inference, information geometry, etc. – and its application to the Entropic Dynamics (ED) approach to Quantum Mechanics (QM) [21, 22, 41, 53, 56–61, 150–153, 165, 195, 196, 268]. The first half of this thesis, chapters 2-6, concern the development of the inference framework. We begin in chapter 2 by discussing de- ductive inference, which involves formal logic and it’s role in access- ing the truth of propositions. We eventually discover that deductive inference is incomplete, in that it can’t address situations in which we have incomplete information. This necessitates a …

Understanding Complex Human Activities In Videos : The Study Of Concurrent Activity Detection And Group Activity Recognition, Yi Wei

Legacy Theses & Dissertations (2009 - 2024)

Human activity understanding, as one of the most important task in video analysis, has been studied for decades. Great efforts have been made to push the activity recognition models towards effective and efficient representation learning. However, it is difficult to define an explicit semantic organization of activities, even for human. Current activity recognition benchmarks only organize the activity labels with shallow hierarchies, which hinders the development of activity recognition system.

Fast Magnetic Resonance Image Reconstruction With Deep Learning Using An Efficientnet Encoder, Tahsin Rahman

Open Access Theses & Dissertations

This thesis aims to develop an efficient, deep network based method for Magnetic Resonance Imaging (MRI) acceleration through undersampled MR image reconstruction. Deep Neural Networks, particularly Deep Convolutional Networks, have been demonstrated to be highly effective in a wide variety of computer vision tasks, including MRI reconstruction. However, modern highly efficient encoder structures, such as the EfficientNet can potentially reduce reconstruction times further while improving reconstruction quality. To that end, we have developed a multi-channel U-Net MRI reconstruction network which uses an EfficientNet encoder and a custom asymmetric. The network was trained and tested using 5x undersampled multi-channel brain MR …

Modeling Of Argon Bombardment And Densification Of Low Temperature Organic Precursors Using Reactive Md Simulations And Machine Learning, Kwabena Asante-Boahen

Graduate Theses/Dissertations

In this study, an important aspect of the synthesis process for a-BxC:Hy was systematically modeled by utilizing the Reactive Molecular Dynamics (MD) in modeling the argon bombardment from the orthocarborane molecules as the precursor. The MD simulations are used to assess the dynamics associated with the free radicals that result from the ion bombardment. By applying the Data Mining/Machine Learning analysis into the datasets generated from the large reactive MD simulations, I was able to identify and quality the kinetics of these radicals. Overall, this approach allows for a better understanding of the overall mechanism at the atomistic level of …

Aerial Flight Paths For Communication, Alisha Bevins

School of Computing: Dissertations, Theses, and Student Research

This body of work presents an iterative process of refinement to understand naive perception of communication using the motion of an unmanned aerial vehicle (UAV). This includes what people believe the UAV is trying to communicate, and how they expect to respond through physical action or emotional response. Previous work in this area sought to communicate without clear definitions of the states attempting to be conveyed. In an attempt to present more concrete states and better understand specific motion perception, this work goes through multiple iterations of state elicitation and label assignment. The lessons learned in this work will be …

Lightweight Mutual Authentication And Privacy Preservation Schemes For Iot Systems., Samah Mansour

Electronic Theses and Dissertations

Internet of Things (IoT) presents a holistic and transformative approach for providing services in different domains. IoT creates an atmosphere of interaction between humans and the surrounding physical world through various technologies such as sensors, actuators, and the cloud. Theoretically, when everything is connected, everything is at risk. The rapid growth of IoT with the heterogeneous devices that are connected to the Internet generates new challenges in protecting and preserving user’s privacy and ensuring the security of our lives. IoT systems face considerable challenges in deploying robust authentication protocols because some of the IoT devices are resource-constrained with limited computation …

High-Density Parking For Autonomous Vehicles., Parag J. Siddique

Electronic Theses and Dissertations

In a common parking lot, much of the space is devoted to lanes. Lanes must not be blocked for one simple reason: a blocked car might need to leave before the car that blocks it. However, the advent of autonomous vehicles gives us an opportunity to overcome this constraint, and to achieve a higher storage capacity of cars. Taking advantage of self-parking and intelligent communication systems of autonomous vehicles, we propose puzzle-based parking, a high-density design for a parking lot. We introduce a novel method of vehicle parking, which leads to maximum parking density. We then propose a heuristic method …

Signal Fingerprinting And Machine Learning Framework For Uav Detection And Identification., Olusiji Oloruntobi Medaiyese

Electronic Theses and Dissertations

Advancement in technology has led to creative and innovative inventions. One such invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now an intrinsic part of our society because their application is becoming ubiquitous in every industry ranging from transportation and logistics to environmental monitoring among others. With the numerous benign applications of UAVs, their emergence has added a new dimension to privacy and security issues. There are little or no strict regulations on the people that can purchase or own a UAV. For this reason, nefarious actors can take advantage of these aircraft to intrude into …

Multilateration Index., Chip Lynch

Electronic Theses and Dissertations

We present an alternative method for pre-processing and storing point data, particularly for Geospatial points, by storing multilateration distances to fixed points rather than coordinates such as Latitude and Longitude. We explore the use of this data to improve query performance for some distance related queries such as nearest neighbor and query-within-radius (i.e. “find all points in a set P within distance d of query point q”). Further, we discuss the problem of “Network Adequacy” common to medical and communications businesses, to analyze questions such as “are at least 90% of patients living within 50 miles of a covered emergency …

Modeling The Spatiotemporal Dynamics Of Active Regions On The Sun Using Deep Neural Networks, Godwill Amankwa

Open Access Theses & Dissertations

Solar active regions are areas on the Sun's surface that have especially strong magnetic fields. Several phenomena that can have significant negative effects on technology and subsequently on human life, such as solar flares and coronal mass ejections (CMEs), are often associated with active regions.Since the physical phenomena underlying the evolution of active regions are still poorly understood, the accurate prediction of solar flares and coronal mass ejections remains an open problem.

Extracting insights from the available datasets of solar activity that can lead to a better understanding of solar active regions has been an important research goal at the …

An Approach To Predicting Performance Of Sparse Computations On Nvidia Gpus, Rogelio Long

Open Access Theses & Dissertations

Sparse problems arise from a variety of applications, from scientific simulations to graph analytics. Traditional HPC systems have failed to effectively provide high bandwidth for sparse problems. This limitation is primarily because of the nature of sparse computations and their irregular memory access patterns.We predict the performance of sparse computations given an input matrix and GPU hardware characteristics. This prediction is done by identifying hardware bottlenecks in modern NVIDIA GPUs using roofline trajectory models. Roofline trajectory models give us insight into the performance by simultaneously showing us the effects of strong and weak scaling. We then create regression models for …

Non-Invasive In-Vitro Glucose Monitoring Using Optical Sensor And Machine Learning Techniques For Diabetes Applications, Maryamsadat Shokrekhodaei

Open Access Theses & Dissertations

Diabetes is a major public health challenge affecting more than 451 million people. Physiological and experimental factors influence the accuracy of non-invasive glucose monitoring, and these need to be addressed before replacing the finger prick method with a non-invasive glucose measurement technique. Also, the suitable employment of machine learning techniques on experimental data can significantly improve the accuracy of glucose predictions.

This work includes the design, development, testing and data analysis of an optical based sensor for glucose measurements. The feasibility of non-invasive measurement of glucose within aqueous solutions that assimilate the composition of human blood plasma is investigated. The …

Selecting Robust Strategies When Players Do Not Know Exactly What Game They Are Playing, Oscar Samuel Veliz

Open Access Theses & Dissertations

Game theory is a tool for modeling multi-agent decision problems and has been used to great success in modeling and simulating problems such as poker, security, and trading agents. However, many real games are extremely large and complex with multiple agent interactions. One approach for solving these games is to use abstraction techniques to shrink the game to a form that can be solved by removing details and translating a solution back to the original.However, abstraction introduces error into the model. This research studies ways to analyze games, abstractions, and strategies that are robust to noise in the game.

Gaining …

Effects Of Saltatory Rewards And Generalized Advantage Estimation On Reference-Based Deep Reinforcement Learning Of Humanlike Motions, Md Rysul Kabir

Theses and Dissertations

In the application of learning physics-based character skills, deep reinforcement learning (DRL) can lead to slow convergence and local optimum solutions during the training process of a reinforcement learning (RL) agent. With the presence of an environment with reward saltation, we can easily plan to magnify those saltatory rewards with the perspective of sample usage to increase the experience pool of an agent during this training process. In our work, we have proposed two modified algorithms. The first one is the addition of a parameter based reward optimization process to magnify the saltatory rewards and thus increasing an agent’s utilization …

Outsourcing Service Fair Payment Based On Blockchain And Its Applications In Cloud Computing, Yinghui Zhang, Robert H. Deng, Ximeng Liu, Dong Zheng

Research Collection School Of Computing and Information Systems

As a milestone in the development of outsourcing services, cloud computing enables an increasing number of individuals and enterprises to enjoy the most advanced services from outsourcing service providers. Because online payment and data security issues are involved in outsourcing services, the mutual distrust between users and service providers may severely impede the wide adoption of cloud computing. Nevertheless, most existing solutions only consider a specific type of services and rely on a trusted third-party to realize fair payment. In this paper, to realize secure and fair payment of outsourcing services in general without relying on any third-party, trusted or …

Desktop Application For The Puzzle Board Game “Rush Hour”, Huanqing Nong

Electronic Theses, Projects, and Dissertations

Rush Hour is a sliding block puzzle board game. This game comes with a board of 6 x 6 grid simulating a parking lot with an exit at the right end of the third row and some vehicle models of size 1 x 2 or 1 x 3 which can slide along the grooves of the grid forward or backward. The goal of the game is to clear the path by moving the vehicles on the board in a certain way for the target car, which lies on the third row of the grid, to merge out the “parking lot” …

Cybersecurity: Creating A Cybersecurity Culture, Steven Edward Ogden

Electronic Theses, Projects, and Dissertations

Human error has been identified as one of the highest contributing factors to successful cyber-attacks and security incidents that result in data leaks and theft of sensitive information. Human error has been caused by employees not behaving securely when interacting with information systems. This culminating experience project investigated how a cybersecurity culture can be developed to address the human error problem. The research was based on several key questions that focus on influencing factors of human behavior and best practices that have been used to develop a cybersecurity culture so that employees engage in secure behaviors. Social Cognitive Theory was …

Spatial Analyses Of Gray Fossil Site Vertebrate Remains: Implications For Depositional Setting And Site Formation Processes, David Carney

Electronic Theses and Dissertations

This project uses exploratory 3D geospatial analyses to assess the taphonomy of the Gray Fossil Site (GFS). During the Pliocene, the GFS was a forested, inundated sinkhole that accumulated biological materials between 4.9-4.5 mya. This deposit contains fossils exhibiting different preservation modes: from low energy lacustrine settings to high energy colluvial deposits. All macro-paleontological materials have been mapped in situ using survey-grade instrumentation. Vertebrate skeletal material from the site is well-preserved, but the degree of skeletal articulation varies spatially within the deposit. This analysis uses geographic information systems (GIS) to analyze the distribution of mapped specimens at different spatial scales. …

Application Of Artificial Intelligence And Machine Learning In Libraries: A Systematic Review, Rajesh Kumar Das, Mohammad Sharif Ul Islam

Library Philosophy and Practice (e-journal)

As the concept and implementation of cutting-edge technologies like artificial intelligence and machine learning has become relevant, academics, researchers and information professionals involve research in this area. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring application of artificial intelligence and machine learning in libraries. To achieve the objectives of the study, a systematic literature review was conducted based on the original guidelines proposed by Kitchenham et al. (2009). Data was collected from Web of Science, Scopus, LISA and LISTA databases. Following the rigorous/ established selection process, a total of thirty-two articles were …

Node-Wise Localization Of Graph Neural Networks, Zemin Liu, Yuan Fang, Chenghao Liu, Steven C.H. Hoi

Research Collection School Of Computing and Information Systems

Graph neural networks (GNNs) emerge as a powerful family of representation learning models on graphs. To derive node representations, they utilize a global model that recursively aggregates information from the neighboring nodes. However, different nodes reside at different parts of the graph in different local contexts, making their distributions vary across the graph. Ideally, how a node receives its neighborhood information should be a function of its local context, to diverge from the global GNN model shared by all nodes. To utilize node locality without overfitting, we propose a node-wise localization of GNNs by accounting for both global and local …

Calculation And Optimization Of Correlation Function In Distillation Method Of Lattice Quantum Chromodynamcis, Ren-Qiang Zhang, Xiang-Yu Jiang, Jiongchi Yu, Chong Zeng, Ming Gong, Shun Xu

Research Collection School Of Computing and Information Systems

Lattice quantum chromodynamics (lattice QCD) is a theory based on quantum chromodynamics, which is widely used in strong interaction related calculations. As a research method that can give accurate and reliable theoretical results, with the improvement of computer ability, Lattice QCD is playing an increasingly important role in recent years. Distillation method is an important numerical method to calculate hadron correlation function in lattice QCD, and can improve the signal-to-noise ratio of calculated physical quantities. Distillation is a method to approximately compute full propagator via replace the laplacian operator with it's outerproduct of laplace eigenvectors. In this way, the construction …