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City Goers: An Exploration Into Creating Seemingly Intelligent A.I. Systems, Matthew Brooke 2021 University of Arkansas, Fayetteville

City Goers: An Exploration Into Creating Seemingly Intelligent A.I. Systems, Matthew Brooke

Computer Science and Computer Engineering Undergraduate Honors Theses

Artificial Intelligence systems have come a long way over the years. One particular application of A.I. is its incorporation in video games. A key goal of creating an A.I. system in a video game is to convey a level of intellect to the player. During playtests for Halo: Combat Evolved, the developers at Bungie noticed that players deemed tougher enemies as more intelligent than weaker ones, despite the fact that there were no differences in behavior in the enemies. The tougher enemies provided a greater illusion of intelligence to the players. Inspired by this, I set out to ...


Improving Bayesian Graph Convolutional Networks Using Markov Chain Monte Carlo Graph Sampling, Aneesh Komanduri 2021 University of Arkansas, Fayetteville

Improving Bayesian Graph Convolutional Networks Using Markov Chain Monte Carlo Graph Sampling, Aneesh Komanduri

Computer Science and Computer Engineering Undergraduate Honors Theses

In the modern age of social media and networks, graph representations of real-world phenomena have become incredibly crucial. Often, we are interested in understanding how entities in a graph are interconnected. Graph Neural Networks (GNNs) have proven to be a very useful tool in a variety of graph learning tasks including node classification, link prediction, and edge classification. However, in most of these tasks, the graph data we are working with may be noisy and may contain spurious edges. That is, there is a lot of uncertainty associated with the underlying graph structure. Recent approaches to modeling uncertainty have been ...


Security Fatigue And Its Effects On Perceived Password Strength Among University Students, Chase Carroll 2021 University of Tennessee at Chattanooga

Security Fatigue And Its Effects On Perceived Password Strength Among University Students, Chase Carroll

Honors Theses

This study was performed with the goal of observing the effect, if any, that security fatigue has on students’ perceived strength of passwords. In doing so, it was hoped to find some correlation between the two that would help in establishing a measurable effect of the phenomenon in students. This could potentially aid organizational decision-makers, such as security policy writers and system admins, to make more informed decisions about implementing security measures. To achieve the goal of observing this fatigue and attempting to measure it, a survey was distributed to numerous students on the University of Tennessee at Chattanooga campus ...


Dynamic Task Allocation In Partially Defined Environments Using A* With Bounded Costs, James Hendrickson 2021 Embry-Riddle Aeronautical University

Dynamic Task Allocation In Partially Defined Environments Using A* With Bounded Costs, James Hendrickson

PhD Dissertations and Master's Theses

The sector of maritime robotics has seen a boom in operations in areas such as surveying and mapping, clean-up, inspections, search and rescue, law enforcement, and national defense. As this sector has continued to grow, there has been an increased need for single unmanned systems to be able to undertake more complex and greater numbers of tasks. As the maritime domain can be particularly difficult for autonomous vehicles to operate in due to the partially defined nature of the environment, it is crucial that a method exists which is capable of dynamically accomplishing tasks within this operational domain. By considering ...


Deep Learning And Optimization In Visual Target Tracking, Mohammadreza Javanmardi 2021 Utah State University

Deep Learning And Optimization In Visual Target Tracking, Mohammadreza Javanmardi

All Graduate Theses and Dissertations

Visual tracking is the process of estimating states of a moving object in a dynamic frame sequence. It has been considered as one of the most paramount and challenging topics in computer vision. Although numerous tracking methods have been introduced, developing a robust algorithm that can handle different challenges still remains unsolved. In this dissertation, we introduce four different trackers and evaluate their performance in terms of tracking accuracy on challenging frame sequences. Each of these trackers aims to address the drawbacks of their peers. The first developed method is called a structured multi-task multi-view tracking (SMTMVT) method, which exploits ...


Simplifying The Creation Of Virtual Topologies Using Mpi Sessions, Tom Herschberg 2021 University of Tennessee at Chattanooga

Simplifying The Creation Of Virtual Topologies Using Mpi Sessions, Tom Herschberg

Honors Theses

As supercomputers have approached exascale performance, several scalability issues have emerged within MPI. These issues arise because MPI includes all processes in the World model, which consumes unacceptable amounts of time and resources at large scale. The Sessions model was developed to combat these issues by removing the requirement of MPI_COMM_WORLD, which provides a more scalable method of creating communication groups in large jobs. Additionally, the Sessions model enables the creation of virtual topologies directly from sets of processes allocated to the execution of a parallel application rather than building virtual topologies from an existing communication group such as MPI_COMM_WORLD ...


Attendio: Attendance Tracking Made Simple, Benjamin L. Greenberg, Spencer L. Howell, Tucker R. Miles, Vicki Tang, Daniel N. Troutman 2021 University of Tennessee, Knoxville

Attendio: Attendance Tracking Made Simple, Benjamin L. Greenberg, Spencer L. Howell, Tucker R. Miles, Vicki Tang, Daniel N. Troutman

Chancellor’s Honors Program Projects

No abstract provided.


An In-Depth Look At Learning Computer Language Syntax In A High-Repetition Practice Environment, Stephanie Gonzales 2021 Utah State University

An In-Depth Look At Learning Computer Language Syntax In A High-Repetition Practice Environment, Stephanie Gonzales

All Graduate Theses and Dissertations

Students in an introductory computer science course generally have difficulty producing code that follows the arrangement rules known as syntax. Phanon was created to help students practice writing correct code that follows the rules of syntax. Previous research suggests this tool has helped students improve their exam scores and strengthen effectiveness in the course. A study was conducted to observe students while they complete the syntax exercises to find meaningful patterns in the steps the students take to complete an exercise.

Evidence to support high intrinsic load was found throughout the study, which is a measure of difficulty learning a ...


Power Of Near-Peers: Conceptualizing And Testing A Near-Peer Mentoring Model In Raising Youths' Self-Efficacy In Computer Programming, Chongning Sun 2021 Utah State University

Power Of Near-Peers: Conceptualizing And Testing A Near-Peer Mentoring Model In Raising Youths' Self-Efficacy In Computer Programming, Chongning Sun

All Graduate Theses and Dissertations

Self-efficacy is seen as a barrier for youth, females in particular, to enter computer science (CS). In this study, I presented a near-peer mentoring model that focused on changing the mentee’s self-efficacy in CS. The present study had three objectives: (a) to design a near-peer mentoring model (i.e., a conceptual model) around the sources of information that influence self-efficacy, (b) to develop a mentor training model based on the conceptual model, and (c) to test the effectiveness of the training model in increasing mentees’ self-efficacy in the context of a summer App programming camp. The present study adopted ...


Data-Driven Recommendation Of Academic Options Based On Personality Traits, Aashish Ghimire 2021 Utah State University

Data-Driven Recommendation Of Academic Options Based On Personality Traits, Aashish Ghimire

All Graduate Theses and Dissertations

The choice of academic major and, subsequently, an academic institution has a massive effect on a person’s career. It not only determines their career path but their earning potential, professional happiness, etc. [1] About 40% of people who are admitted to a college do not graduate within six years. Yet, very limited resources are available for students to help make those decisions, and each guidance counselor is responsible for roughly 400 to 900 students across the United States. A tool to help these decisions would benefit students, parents, and guidance counselors.

Various research studies have shown that personality traits ...


Privacy Is Infringed In Plain Sight And How To Dissapear, Zachary Taylor 2021 California State University, San Bernardino

Privacy Is Infringed In Plain Sight And How To Dissapear, Zachary Taylor

Electronic Theses, Projects, and Dissertations

This culminating project explored how Amazon, Apple, Facebook, Google, and Microsoft infringe on their user's information privacy. Focus was on tools and techniques one can use to strengthen their information privacy. Privacy or information privacy was defined as the right to have some control over how your personal information is collected and used. This project will also introduce a verity of open-source tools and techniques that would help the unsuspected user to maintain their privacy.The questions asked were: what are some common techniques that Amazon, Apple, Facebook, Google, or Microsoft use to gain personal information?, At what cost ...


Evolving Efficient Floor Plans For Hospital Emergency Rooms, Alex Ramsey 2021 University of Nebraska at Omaha

Evolving Efficient Floor Plans For Hospital Emergency Rooms, Alex Ramsey

Theses/Capstones/Creative Projects

Genetic Algorithms find wide use in optimization problems across many fields of research, including crowd simulation. This paper proposes that genetic algorithms could be used to create better floor plans for hospital emergency rooms, potentially saving critical time in high risk situations. The genetic algorithm implemented makes use of a hospital-specific crowd simulation to accurately evaluate the effectiveness of produced layouts. The results of combining genetic algorithms with a crowd simulation are promising. Future work may improve upon these results to produce better, more optimal hospital floor plans.


Visual Analysis Of Historical Lessons Learned During Exercises For The United States Air Force Europe (Usafe), Samantha O'Rourke 2021 University of Nebraska at Omaha

Visual Analysis Of Historical Lessons Learned During Exercises For The United States Air Force Europe (Usafe), Samantha O'Rourke

Theses/Capstones/Creative Projects

Within the United States Air Force, there are repeated patterns of differences observed during exercises. After an exercise is completed, forms are filled out detailing observations, successes, and recommendations seen throughout the exercise. At the most, no two reports are identical and must be analyzed by personnel and then categorized based on common themes observed. Developing a computer application will greatly reduce the time and resources used to analyze each After Action Report. This application can visually represent these observations and optimize the effectiveness of these exercises. The visualization is done through graphs displaying the frequency of observations and recommendations ...


Achieving Hate Speech Detection In A Low Resource Setting, Peiyu Li 2021 Utah State University

Achieving Hate Speech Detection In A Low Resource Setting, Peiyu Li

All Graduate Theses and Dissertations

Online social networks provide people with convenient platforms to communicate and share life moments. However, because of the anonymous property of these social media platforms, the cases of online hate speeches are increasing. Hate speech is defined by the Cambridge Dictionary as “public speech that expresses hate or encourages violence towards a person or group based on something such as race, religion, sex, or sexual orientation”. Online hate speech has caused serious negative effects to legitimate users, including mental or emotional stress, reputational damage, and fear for one’s safety. To protect legitimate online users, automatically hate speech detection techniques ...


Scope: Building And Testing An Integrated Manual-Automated Event Extraction Tool For Online Text-Based Media Sources, Matthew Crittenden 2021 William & Mary

Scope: Building And Testing An Integrated Manual-Automated Event Extraction Tool For Online Text-Based Media Sources, Matthew Crittenden

Undergraduate Honors Theses

Building on insights from two years of manually extracting events information from online news media, an interactive information extraction environment (IIEE) was developed. SCOPE, the Scientific Collection of Open-source Policy Evidence, is a Python Django-based tool divided across specialized modules for extracting structured events data from unstructured text. These modules are grouped into a flexible framework which enables the user to tailor the tool to meet their needs. Following principles of user-oriented learning for information extraction (IE), SCOPE offers an alternative approach to developing AI-assisted IE systems. In this piece, we detail the ongoing development of the SCOPE tool, present ...


Performance Implications Of Memory Affinity On Filesystem Caches In A Non-Uniform Memory Access Environment, Jacob Adams 2021 William & Mary

Performance Implications Of Memory Affinity On Filesystem Caches In A Non-Uniform Memory Access Environment, Jacob Adams

Undergraduate Honors Theses

Non-Uniform Memory Access imposes unique challenges on every component of an operating system and the applications that run on it. One such component is the filesystem which, while not directly impacted by NUMA in most cases, typically has some form of cache whose performance is constrained by the latency and bandwidth of the memory that it is stored in. One such filesystem is ZFS, which contains its own custom caching system, known as the Adaptive Replacement Cache. This work looks at the impact of NUMA on this cache via sequential read operations, shows how current solutions intended to reduce this ...


Teachability And Interpretability In Reinforcement Learning, Jeevan Rajagopal 2021 University of Nebraska - Lincoln

Teachability And Interpretability In Reinforcement Learning, Jeevan Rajagopal

Computer Science and Engineering: Theses, Dissertations, and Student Research

There have been many recent advancements in the field of reinforcement learning, starting from the Deep Q Network playing various Atari 2600 games all the way to Google Deempind's Alphastar playing competitively in the game StarCraft. However, as the field challenges more complex environments, the current methods of training models and understanding their decision making become less effective. Currently, the problem is partially dealt with by simply adding more resources, but the need for a better solution remains.

This thesis proposes a reinforcement learning framework where a teacher or entity with domain knowledge of the task to complete can ...


“The Revolution Will Not Be Supervised": An Investigation Of The Efficacy And Reasoning Process Of Self-Supervised Representations, Atharva Tendle 2021 University of Nebraska-Lincoln

“The Revolution Will Not Be Supervised": An Investigation Of The Efficacy And Reasoning Process Of Self-Supervised Representations, Atharva Tendle

Computer Science and Engineering: Theses, Dissertations, and Student Research

Transfer learning technique enables training Deep Learning (DL) models in a data-efficient way for solving computer vision tasks. It involves pretraining a DL model to learn representations from a large and general-purpose source dataset, then fine-tuning the model using the task-specific target dataset. The dominant supervised learning (SL) approach for pretraining representations suffers from some limitations that include expensive labeling and poor generalizability. Recent advancements in the self-supervised learning (SSL) approach made it possible to learn effective representations from unlabeled data. The performance of the fine-tuned DL models based on pretrained SSL representations is on par with the state-of-the-art pretrained ...


A Novel Dynamic Analysis Infrastructure To Instrument Untrusted Execution Flow Across User-Kernel Spaces, Jiaqi HONG, Xuhua DING 2021 Singapore Management University

A Novel Dynamic Analysis Infrastructure To Instrument Untrusted Execution Flow Across User-Kernel Spaces, Jiaqi Hong, Xuhua Ding

Research Collection School Of Computing and Information Systems

Code instrumentation and hardware based event trapping are two primary approaches used in dynamic malware analysis systems. In this paper, we propose a new approach called Execution Flow Instrumentation (EFI) where the analyzer execution flow is interleaved with the target flow in user- and kernel-mode, at junctures flexibly chosen by the analyzer at runtime. We also propose OASIS as the system infrastructure to realize EFI with virtues of the current two approaches, however without their drawbacks. Despite being securely and transparently isolated from the target, the analyzer introspects and controls it in the same native way as instrumentation code. We ...


Tripdecoder: Study Travel Time Attributes And Route Preferences Of Metro Systems From Smart Card Data, Xiancai TIAN, Baihua ZHENG, Yazhe WANG, Hsao-Ting HUANG, Chih-Cheng HUNG 2021 Singapore Management University

Tripdecoder: Study Travel Time Attributes And Route Preferences Of Metro Systems From Smart Card Data, Xiancai Tian, Baihua Zheng, Yazhe Wang, Hsao-Ting Huang, Chih-Cheng Hung

Research Collection School Of Computing and Information Systems

In this paper, we target at recovering the exact routes taken by commuters inside a metro system that are not captured by an Automated Fare Collection (AFC) system and hence remain unknown. We strategically propose two inference tasks to handle the recovering, one to infer the travel time of each travel link that contributes to the total duration of any trip inside a metro network and the other to infer the route preferences based on historical trip records and the travel time of each travel link inferred in the previous inference task. As these two inference tasks have interrelationship, most ...


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