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Articles 1 - 30 of 79
Full-Text Articles in Physical Sciences and Mathematics
Enhancing Search Engine Results: A Comparative Study Of Graph And Timeline Visualizations For Semantic And Temporal Relationship Discovery, Muhammad Shahiq Qureshi
Enhancing Search Engine Results: A Comparative Study Of Graph And Timeline Visualizations For Semantic And Temporal Relationship Discovery, Muhammad Shahiq Qureshi
Electronic Theses and Dissertations
In today’s digital age, search engines have become indispensable tools for finding information among the corpus of billions of webpages. The standard that most search engines follow is to display search results in a list-based format arranged according to a ranking algorithm. Although this format is good for presenting the most relevant results to users, it fails to represent the underlying relations between different results. These relations, among others, can generally be of either a temporal or semantic nature. A user who wants to explore the results that are connected by those relations would have to make a manual effort …
Digital Twins Of The Living Knee: From Measurements To Model, Thor Erik Andreassen
Digital Twins Of The Living Knee: From Measurements To Model, Thor Erik Andreassen
Electronic Theses and Dissertations
Modern medicine has dramatically improved the lives of many. In orthopaedics, robotic surgery has given clinicians superior accuracy when performing interventions over conventional methods. Nevertheless, while these and many other methods are available to ensure treatments are performed successfully, far fewer methods exist to predict the proper treatment option for a given person. Clinicians are forced to categorize individuals, choosing the best treatment on “average.” However, many individuals differ significantly from the “average” person, for which many of these treatments are designed. Going forward, a method of testing, evaluating, and predicting different treatment options' short- and long-term effects on an …
Controllable Language Generation Using Deep Learning, Rohola Zandie
Controllable Language Generation Using Deep Learning, Rohola Zandie
Electronic Theses and Dissertations
The advent of deep neural networks has sparked a revolution in Artificial Intelligence (AI), notably with the creation of Transformer models like GPT-X and ChatGPT. These models have surpassed previous methods in various Natural Language Processing (NLP) tasks. As the NLP field evolves, there is a need to further understand and question the capabilities of these models. Text generation, a crucial part of NLP, remains an area where our comprehension is limited while being critical in research.
This dissertation focuses on the challenging problem of controlling the general behaviors of language models such as sentiment, topical focus, and logical reasoning. …
An Investigation Into Machine Learning Techniques For Designing Dynamic Difficulty Agents In Real-Time Games, Ryan Adare Dunagan
An Investigation Into Machine Learning Techniques For Designing Dynamic Difficulty Agents In Real-Time Games, Ryan Adare Dunagan
Electronic Theses and Dissertations
Video games are an incredibly popular pastime enjoyed by people of all ages world wide. Many different kinds of games exist, but most games feature some elements of the player overcoming some challenge, usually through gameplay. These challenges are insurmountable for some people and may turn them off to video games as a pastime. Games can be made more accessible to players of little skill and/or experience through the use of Dynamic Difficulty Adjustment (DDA) systems that adjust the difficulty of the game in response to the player’s performance. This research seeks to establish the effectiveness of machine learning techniques …
Patient Movement Monitoring Based On Imu And Deep Learning, Mohsen Sharifi Renani
Patient Movement Monitoring Based On Imu And Deep Learning, Mohsen Sharifi Renani
Electronic Theses and Dissertations
Osteoarthritis (OA) is the leading cause of disability among the aging population in the United States and is frequently treated by replacing deteriorated joints with metal and plastic components. Developing better quantitative measures of movement quality to track patients longitudinally in their own homes would enable personalized treatment plans and hasten the advancement of promising new interventions. Wearable sensors and machine learning used to quantify patient movement could revolutionize the diagnosis and treatment of movement disorders. The purpose of this dissertation was to overcome technical challenges associated with the use of wearable sensors, specifically Inertial Measurement Units (IMUs), as a …
Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young
Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young
Electronic Theses and Dissertations
While marker-based motion capture remains the gold standard in measuring human movement, accuracy is influenced by soft-tissue artifacts, particularly for subjects with high body mass index (BMI) where markers are not placed close to the underlying bone. Obesity influences joint loads and motion patterns, and BMI may not be sufficient to capture the distribution of a subject’s weight or to differentiate differences between subjects. Subjects in need of a joint replacement are more likely to have mobility issues or pain, which prevents exercise. Obesity also increases the likelihood of needing a total joint replacement. Accurate movement data for subjects with …
A Unified Approach To Regression Testing For Mobile Apps, Zeinab Saad Abdalla
A Unified Approach To Regression Testing For Mobile Apps, Zeinab Saad Abdalla
Electronic Theses and Dissertations
Mobile Applications have been widely used in recent years daily all over the world and are essential in our personal lives and at work. Because Mobile Applications update frequently, it is important that developers perform regression testing to ensure their quality. In addition, the Mobile Applications market has been growing rapidly, allowing anyone to write and publish an application without appropriate validation. A need for regression testing has arisen with the growth of different Mobile Apps and the added functionalities and complexities. In this dissertation, we adapted the FSMWeb [14] approach for selective regression testing to allow for selective regression …
Reference Frames In Human Sensory, Motor, And Cognitive Processing, Dongcheng He
Reference Frames In Human Sensory, Motor, And Cognitive Processing, Dongcheng He
Electronic Theses and Dissertations
Reference-frames, or coordinate systems, are used to express properties and relationships of objects in the environment. While the use of reference-frames is well understood in physical sciences, how the brain uses reference-frames remains a fundamental question. The goal of this dissertation is to reach a better understanding of reference-frames in human perceptual, motor, and cognitive processing. In the first project, we study reference-frames in perception and develop a model to explain the transition from egocentric (based on the observer) to exocentric (based outside the observer) reference-frames to account for the perception of relative motion. In a second project, we focus …
Terrain Cost Learning From Human Preferences For Robot Path Planning Using A Visual User Interface, Kaivalya Velagapudi
Terrain Cost Learning From Human Preferences For Robot Path Planning Using A Visual User Interface, Kaivalya Velagapudi
Electronic Theses and Dissertations
Robot navigation in terrains with limited exploration and limited knowledge has been a problem of interest in robotics due to the potential dangers that may arise during traversal. Due to the large number of path permutations within a complex and feature-rich real-world environment, and in the interest of saving time and ensuring safety, the robot should learn the optimal path without repeated exploration of the terrain. This can be accomplished by leveraging the path preferences of a human operator so that, with selective inputs, the agent can effectively learn a terrain-cost mapping in order to determine the optimal route, thereby …
Artificial Emotional Intelligence In Socially Assistive Robots, Hojjat Abdollahi
Artificial Emotional Intelligence In Socially Assistive Robots, Hojjat Abdollahi
Electronic Theses and Dissertations
Artificial Emotional Intelligence (AEI) bridges the gap between humans and machines by demonstrating empathy and affection towards each other. This is achieved by evaluating the emotional state of human users, adapting the machine’s behavior to them, and hence giving an appropriate response to those emotions. AEI is part of a larger field of studies called Affective Computing. Affective computing is the integration of artificial intelligence, psychology, robotics, biometrics, and many more fields of study. The main component in AEI and affective computing is emotion, and how we can utilize emotion to create a more natural and productive relationship between humans …
Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan
Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan
Electronic Theses and Dissertations
Parkinson’s disease (PD) is a neurodegenerative movement disorder that progresses gradually over time. The onset of symptoms in people who are suffering from PD can vary from case to case, and it depends on the progression of the disease in each patient. The PD symptoms gradually develop and exacerbate the patient’s movements throughout time. An early diagnosis of PD could improve the outcomes of treatments and could potentially delay the progression of this disorder and that makes discovering a new diagnostic method valuable. In this study, I investigate the feasibility of using a machine learning (ML) approach to classify PD …
Frequency Analysis Of Trabecular Bone Structure, Daniel Parada San Martin
Frequency Analysis Of Trabecular Bone Structure, Daniel Parada San Martin
Electronic Theses and Dissertations
Medical data is hard to obtain due to privacy laws making research difficult. Many databases of medical data have been compiled over the years and are available to the scientific community. These databases are not comprehensive and lack many clinical conditions. Certain type of medical conditions are rare, making them harder to obtain, or are not present at all in the aforementioned databases. Due to the sparsity or complete lack of data regarding certain conditions, research has stifled. Recent developments in machine learning and generative neural networks have made it possible to generate realistic data that can overcome the lack …
Model-Based Testing Of Smart Home Systems Using Efsm, Cefsm, And Fsmapp, Afnan Mohammed Albahli
Model-Based Testing Of Smart Home Systems Using Efsm, Cefsm, And Fsmapp, Afnan Mohammed Albahli
Electronic Theses and Dissertations
Smart Home Systems (SHS) are some of the most popular Internet of Things (IoT) applications. In 2021, there were 52.22 million smart homes in the United States and they are expected to grow to 77.1 million in 2025 [71]. According to MediaPost [74], 69 percent of American households have at least one smart home device. The number of smart home systems poses a challenge for software testers to find the right approach to test these systems. This dissertation employs Extended Finite State Machines (EFSMs) [6, 24, 105], Communicating Extended Finite State Machines (EFSMs) [68] and FSMApp [10] to generate reusable …
Humanizing Computational Literature Analysis Through Art-Based Visualizations, Alexandria Leto
Humanizing Computational Literature Analysis Through Art-Based Visualizations, Alexandria Leto
Electronic Theses and Dissertations
Inequalities in gender representation and characterization in fictional works are issues that have long been discussed by social scientists. This work addresses these inequalities with two interrelated components. First, it contributes a sentiment and word frequency analysis task focused on gender-specific nouns and pronouns in 15,000 fictional works taken from the online library, Project Gutenberg. This analysis allows for both quantifying and offering further insight on the nature of this disparity in gender representation. Then, the outcomes of the analysis are harnessed to explore novel data visualization formats using computational and studio art techniques. Our results call attention to the …
Multi-Agent Pathfinding In Mixed Discrete-Continuous Time And Space, Thayne T. Walker
Multi-Agent Pathfinding In Mixed Discrete-Continuous Time And Space, Thayne T. Walker
Electronic Theses and Dissertations
In the multi-agent pathfinding (MAPF) problem, agents must move from their current locations to their individual destinations while avoiding collisions. Ideally, agents move to their destinations as quickly and efficiently as possible. MAPF has many real-world applications such as navigation, warehouse automation, package delivery and games. Coordination of agents is necessary in order to avoid conflicts, however, it can be very computationally expensive to find mutually conflict-free paths for multiple agents – especially as the number of agents is increased. Existing state-ofthe- art algorithms have been focused on simplified problems on grids where agents have no shape or volume, and …
Change Request Prediction And Effort Estimation In An Evolving Software System, Lamees Abdullah Alhazzaa
Change Request Prediction And Effort Estimation In An Evolving Software System, Lamees Abdullah Alhazzaa
Electronic Theses and Dissertations
Prediction of software defects has been the focus of many researchers in empirical software engineering and software maintenance because of its significance in providing quality estimates from the project management perspective for an evolving legacy system. Software Reliability Growth Models (SRGM) have been used to predict future defects in a software release. Modern software engineering databases contain Change Requests (CR), which include both defects and other maintenance requests. Our goal is to use defect prediction methods to help predict CRs in an evolving legacy system.
Limited research has been done in defect prediction using curve-fitting methods evolving software systems, with …
Deep Learning Methods For Fingerprint-Based Indoor And Outdoor Positioning, Fahad Alhomayani
Deep Learning Methods For Fingerprint-Based Indoor And Outdoor Positioning, Fahad Alhomayani
Electronic Theses and Dissertations
Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance. In the past, shallow learning algorithms were traditionally used in location fingerprinting. Recently, the research community started utilizing deep learning methods for fingerprinting after witnessing the great success and superiority these methods have over traditional/shallow machine learning algorithms. The contribution of this dissertation is fourfold:
First, a Convolutional Neural Network (CNN)-based method for …
Wind Turbine Parameter Calibration Using Deep Learning Approaches, Rebecca Mccubbin
Wind Turbine Parameter Calibration Using Deep Learning Approaches, Rebecca Mccubbin
Electronic Theses and Dissertations
The inertia and damping coefficients are critical to understanding the workings of a wind turbine, especially when it is in a transient state. However, many manufacturers do not provide this information about their turbines, requiring people to estimate these values themselves. This research seeks to design a multilayer perceptron (MLP) that can accurately predict the inertia and damping coefficients using the power data from a turbine during a transient state. To do this, a model of a wind turbine was built in Matlab, and a simulation of a three-phase fault was used to collect realistic fault data to input into …
Observation Of New Particle Formation In The Northern Hemisphere At Altitude From 4 To 20 Km, Mohamed Saad
Observation Of New Particle Formation In The Northern Hemisphere At Altitude From 4 To 20 Km, Mohamed Saad
Electronic Theses and Dissertations
New particle formation (NPF) is investigated using measurements of aerosol size distributions and meteorological variables made in two continents, including USA and Europe. Despite the considerably different aerosol particle abundances among the sites, a common relationship was found between the characteristics of NPF events and the air mass convective and/or advective transport. CO and O3 act as tracers of tropospheric and stratospheric air, respectively, their statistical relationship can be used to quantify air mass characteristics and origins. The mixing ratio values of CO increased within the upper troposphere layer before/during NPF events, which may serve as an indicator of occurring …
The Design, Development, And Determination Of A Virtual Reality Classroom, Victoria Alexxis Reddington
The Design, Development, And Determination Of A Virtual Reality Classroom, Victoria Alexxis Reddington
Electronic Theses and Dissertations
The COVID-19 pandemic has radically changed the way students learn and engage with their peers and instructors. Likewise, instructors have had to quickly transform their course materials to suit the online classroom format. Results from a survey of students and instructors at the University of Denver revealed that perceived levels of learning and collaboration were lessened with the transition to online learning. Moreover, the sense of presence in an educational atmosphere with other individuals was reported to be significantly stronger in a real physical classroom, as compared to an online classroom. This thesis therefore seeks to provide a new, alternative …
Investigating New Methods To Develop Perovskite Solar Cells, Amani Hussain Alfaifi
Investigating New Methods To Develop Perovskite Solar Cells, Amani Hussain Alfaifi
Electronic Theses and Dissertations
Discovering the potential of organic-inorganic metal halide perovskites (MHP) as a harvesting material in solar cells has strongly affected the research direction in solar energy. The fascinating optical and electronic properties offered by MHP combined with tremendous effort from scientists around the world have improved the efficiency to about 25% in a decade.
In the first part of the dissertation, we studied the lamination process as a new fabrication method for producing self-encapsulated perovskite solar cells based on laminating half stacks,as opposed to the conventional layer-by-layer method. Our work focused on optimizing the lamination process of complex triple cations perovskite …
Automated Change Detection In Privacy Policies, Andrick Adhikari
Automated Change Detection In Privacy Policies, Andrick Adhikari
Electronic Theses and Dissertations
Privacy policies notify Internet users about the privacy practices of websites, mobile apps, and other products and services. However, users rarely read them and struggle to understand their contents. Also, the entities that provide these policies are sometimes unmotivated to make them comprehensible. Due to the complicated nature of these documents, it gets even harder for users to understand and take note of any changes of interest or concern when these policies are changed or revised.
With recent development of machine learning and natural language processing, tools that can automatically annotate sentences of policies have been developed. These annotations can …
Using Natural Language Processing To Categorize Fictional Literature In An Unsupervised Manner, Dalton J. Crutchfield
Using Natural Language Processing To Categorize Fictional Literature In An Unsupervised Manner, Dalton J. Crutchfield
Electronic Theses and Dissertations
When following a plot in a story, categorization is something that humans do without even thinking; whether this is simple classification like “This is science fiction” or more complex trope recognition like recognizing a Chekhov's gun or a rags to riches storyline, humans group stories with other similar stories. Research has been done to categorize basic plots and acknowledge common story tropes on the literary side, however, there is not a formula or set way to determine these plots in a story line automatically. This paper explores multiple natural language processing techniques in an attempt to automatically compare and cluster …
Certification-Driven Testing Of Safety-Critical Systems, Aiman S. Gannous
Certification-Driven Testing Of Safety-Critical Systems, Aiman S. Gannous
Electronic Theses and Dissertations
Safety-critical systems are those systems that when they fail they could cause loss of life or significant physical damages. Since software now is an essential component of these types of systems, failures caused by software faults could come from flaws in the software development life-cycle. As a result, challenges unfold in two directions. First, in verifying that the software will not put the system in an unsafe state, and identifying external failures and mitigate them properly. Second, in providing sufficient evidence for an efficient safety certification process. In this study, we propose an approach for testing safety-critical systems called Model-Combinatorial …
Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale
Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale
Electronic Theses and Dissertations
The variation of facial images in the wild conditions due to head pose, face illumination, and occlusion can significantly affect the Facial Expression Recognition (FER) performance. Moreover, between subject variation introduced by age, gender, ethnic backgrounds, and identity can also influence the FER performance. This Ph.D. dissertation presents a novel algorithm for end-to-end facial expression recognition, valence and arousal estimation, and visual object matching based on deep Siamese Neural Networks to handle the extreme variation that exists in a facial dataset. In our main Siamese Neural Networks for facial expression recognition, the first network represents the classification framework, where we …
Automated Recognition Of Facial Affect Using Deep Neural Networks, Behzad Hasani
Automated Recognition Of Facial Affect Using Deep Neural Networks, Behzad Hasani
Electronic Theses and Dissertations
Automated Facial Expression Recognition (FER) has been a topic of study in the field of computer vision and machine learning for decades. In spite of efforts made to improve the accuracy of FER systems, existing methods still are not generalizable and accurate enough for use in real-world applications. Many of the traditional methods use hand-crafted (a.k.a. engineered) features for representation of facial images. However, these methods often require rigorous hyper-parameter tuning to achieve favorable results.
Recently, Deep Neural Networks (DNNs) have shown to outperform traditional methods in visual object recognition. DNNs require huge data as well as powerful computing units …
Deep Reinforcement Learning For The Optimization Of Building Energy Control And Management, Jun Hao
Deep Reinforcement Learning For The Optimization Of Building Energy Control And Management, Jun Hao
Electronic Theses and Dissertations
Most of the current game-theoretic demand-side management methods focus primarily on the scheduling of home appliances, and the related numerical experiments are analyzed under various scenarios to achieve the corresponding Nash-equilibrium (NE) and optimal results. However, not much work is conducted for academic or commercial buildings. The methods for optimizing academic-buildings are distinct from the optimal methods for home appliances. In my study, we address a novel methodology to control the operation of heating, ventilation, and air conditioning system (HVAC).
We assume that each building in our campus is equipped with smart meter and communication system which is envisioned in …
Renewable Energy Integration In Distribution System With Artificial Intelligence, Yi Gu
Renewable Energy Integration In Distribution System With Artificial Intelligence, Yi Gu
Electronic Theses and Dissertations
With the increasing attention of renewable energy development in distribution power system, artificial intelligence (AI) can play an indispensiable role. In this thesis, a series of artificial intelligence based methods are studied and implemented to further enhance the performance of power system operation and control.
Due to the large volume of heterogeneous data provided by both the customer and the grid side, a big data visualization platform is built to feature out the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. An open source cluster calculation framework with Apache Spark is used to discover big data …
Satellite Constellation Deployment And Management, Joseph Ryan Kopacz
Satellite Constellation Deployment And Management, Joseph Ryan Kopacz
Electronic Theses and Dissertations
This paper will review results and discuss a new method to address the deployment and management of a satellite constellation. The first two chapters will explorer the use of small satellites, and some of the advances in technology that have enabled small spacecraft to maintain modern performance requirements in incredibly small packages.
The third chapter will address the multiple-objective optimization problem for a global persistent coverage constellation of communications spacecraft in Low Earth Orbit. A genetic algorithm was implemented in MATLAB to explore the design space – 288 trillion possibilities – utilizing the Satellite Tool Kit (STK) software developers kit. …
Real-Time Detection Of Demand Manipulation Attacks On A Power Grid, Srinidhi Madabhushi
Real-Time Detection Of Demand Manipulation Attacks On A Power Grid, Srinidhi Madabhushi
Electronic Theses and Dissertations
An increased usage in IoT devices across the globe has posed a threat to the power grid. When an attacker has access to multiple IoT devices within the same geographical location, they can possibly disrupt the power grid by regulating a botnet of high-wattage IoT devices. Based on the time and situation of the attack, an adversary needs access to a fixed number of IoT devices to synchronously switch on/off all of them, resulting in an imbalance between the supply and demand. When the frequency of the power generators drops below a threshold value, it can lead to the generators …