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Articles 2341 - 2370 of 3476
Full-Text Articles in Computer Sciences
Disputing Dijkstra, And Birthdays In Base 2, Mark Guzdial, Joel C. Adams
Disputing Dijkstra, And Birthdays In Base 2, Mark Guzdial, Joel C. Adams
University Faculty Publications and Creative Works
No abstract provided.
Design And Implementation Of Kawaii Robots By Japanese And American University Students Using Remote Collaboration, Dave Berque, Hiroko Chiba, Michiko Ohkura, Midori Sugaya, Peeraya Sripian, Tipporn Laohakangvalvit
Design And Implementation Of Kawaii Robots By Japanese And American University Students Using Remote Collaboration, Dave Berque, Hiroko Chiba, Michiko Ohkura, Midori Sugaya, Peeraya Sripian, Tipporn Laohakangvalvit
Computer Science Faculty publications
This paper describes our approach to the design and implementation of virtual Kawaii robots and spaces by Japanese and American university students using remote collaboration. Because of the COVID-19 pandemic, we had to change our planned 7-week collaboration from in-person to virtual with a resultant change in the target product of our collaboration from real robots to virtual robots. Based on our new plan, students designed virtual spaces with robot pairs, proposed evaluation items for the robot pairs, evaluated their designs, and analyzed the results. The students designed each robot pair with the goal that one robot would be more …
Wg2An: Synthetic Wound Image Generation Using Generative Adversarial Network, Salih Sarp, Murat Kuzlu, Emmanuel Wilson, Ozgur Guler
Wg2An: Synthetic Wound Image Generation Using Generative Adversarial Network, Salih Sarp, Murat Kuzlu, Emmanuel Wilson, Ozgur Guler
Engineering Technology Faculty Publications
In part due to its ability to mimic any data distribution, Generative Adversarial Network (GAN) algorithms have been successfully applied to many applications, such as data augmentation, text-to-image translation, image-to-image translation, and image inpainting. Learning from data without crafting loss functions for each application provides broader applicability of the GAN algorithm. Medical image synthesis is also another field that the GAN algorithm has great potential to assist clinician training. This paper proposes a synthetic wound image generation model based on GAN architecture to increase the quality of clinical training. The proposed model is trained on chronic wound datasets with various …
3d Printing Of Human Microbiome Constituents To Understand Spatial Relationships And Shape Parameters In Bacteriology, Jacques Izard, Teklu Kuru Gerbaba, Shara R. P. Yumul
3d Printing Of Human Microbiome Constituents To Understand Spatial Relationships And Shape Parameters In Bacteriology, Jacques Izard, Teklu Kuru Gerbaba, Shara R. P. Yumul
Department of Food Science and Technology: Faculty Publications
Effective laboratory and classroom demonstration of microbiome size and shape, diversity, and ecological relationships is hampered by a lack of high-resolution, easy-to-use, readily accessible physical or digital models for use in teaching. Three-dimensional (3D) representations are, overall, more effective in communicating visuospatial information, allowing for a better understanding of concepts not directly observable with the unaided eye. Published morphology descriptions and microscopy images were used as the basis for designing 3D digital models, scaled at 20,000×, using computer-aided design software (CAD) and generating printed models of bacteria on mass-market 3D printers. Sixteen models are presented, including rod-shaped, spiral, flask-like, vibroid, …
Efficient Algorithms For Trajectory-Aware Mobile Crowdsourcing, Chung-Kyun Han
Efficient Algorithms For Trajectory-Aware Mobile Crowdsourcing, Chung-Kyun Han
Dissertations and Theses Collection (Open Access)
Mobile crowdsourcing, a subclass of crowdsourcing dealing with location-specific tasks, is prevalent in our daily life. From sensing urban environment such as noise, air pollution to package delivery, various location-specific tasks are posted on mobile crowdsourcing platforms to tap on the pool of crowdsourced workers. Many digital platforms compete with each other to expand and retain their pool of crowdsourced workers. Comparing with the traditional workforce, crowdsourced workers do not dedicate their time to do tasks fully and have strong spatiotemporal preferences. The ignorance of crowdsourced workers’ mobility patterns and the lack of personalization would lead to crowdsourced workers’ exodus, …
Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan
Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan
Theses and Dissertations
One of the fundamental problems of robotics and navigation is the estimation of relative pose of an external object with respect to the observer. A common method for computing the relative pose is the Iterative Closest Point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in down-stream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this thesis a novel method for estimating uncertainty from sensed data is introduced. …
Unsupervised Clustering Of Rf-Fingerprinting Features Derived From Deep Learning Based Recognition Models, Christian T. Potts
Unsupervised Clustering Of Rf-Fingerprinting Features Derived From Deep Learning Based Recognition Models, Christian T. Potts
Theses and Dissertations
RF-Fingerprinting is focus of machine learning research which aims to characterize wireless communication devices based on their physical hardware characteristics. It is a promising avenue for improving wireless communication security in the PHY layer. The bulk of research presented to date in this field is focused on the development of features and classifiers using both traditional supervised machine learning models as well as deep learning. This research aims to expand on existing RF-Fingerprinting work by approaching the problem through the lens of an unsupervised clustering problem. To that end this research proposes a deep learning model and training methodology to …
Enhanced Space Object Detection Without Prior Knowledge Of The Point Spread Function, Grant F. Graupmann
Enhanced Space Object Detection Without Prior Knowledge Of The Point Spread Function, Grant F. Graupmann
Theses and Dissertations
Since the point detector was created, other detection algorithms have been created that increase the probability of detection, while still keeping the same probability of false alarm. The point detector still has uses, such as when there is no prior knowledge of the point spread function (PSF). The matched filter correlator (MFC) detector is reliant on prior knowledge of the PSF. This has been an issue in cases where the PSF information is potentially inaccurate or unknown. This thesis utilizes MFC detector in a manner that it has never been used before, along with a new detection algorithm, the Pearson's …
A Cyber Threat Taxonomy And A Viability Analysis For False Injections In The Tcas, John W. Hannah
A Cyber Threat Taxonomy And A Viability Analysis For False Injections In The Tcas, John W. Hannah
Theses and Dissertations
This thesis provided background information on the Traffic Collision Avoidance System (TCAS). Additionally, the thesis developed a threat taxonomy for TCAS, resulting in the determination that a false injection attack presents the most comprehensive risk. Moreover, the thesis presents the development of a program to determine what ranges, altitudes, and relative bearings are most vulnerable to a false injection attack. The program includes test for all requirements of a successful false injection. Furthermore, the thesis presents an analysis of results and creates threat maps as situational awareness tools. Lastly, the thesis discusses potential solutions to the false injection attack, covers …
Performance Of Various Low-Level Decoder For Surface Codes In The Presence Of Measurement Error, Claire E. Badger
Performance Of Various Low-Level Decoder For Surface Codes In The Presence Of Measurement Error, Claire E. Badger
Theses and Dissertations
Quantum error correction is a research specialty within the area of quantum computing that constructs quantum circuits that correct for errors. Decoding is the process of using measurements from an error correcting code, known as error syndrome, to decide corrective operations to perform on the circuit. High-level decoding is the process of using the error syndrome to perform corrective logical operations, while low-level decoding uses the error syndrome to correct individual data qubits. Research on machine learning-based decoders is increasingly popular, but has not been thoroughly researched for low-level decoders. The type of error correcting code used is called surface …
Comparison Of Machine Learning Techniques On Trust Detection Using Eeg, James R. Elkins
Comparison Of Machine Learning Techniques On Trust Detection Using Eeg, James R. Elkins
Theses and Dissertations
Trust is a pillar of society and is a fundamental aspect in every relationship. With the use of automated agents in todays workforce exponentially growing, being able to actively monitor an individuals trust level that is working with the automation is becoming increasingly more important. Humans often have miscalibrated trust in automation and therefore are prone to making costly mistakes. Since deciding to trust or distrust has been shown to correlate with specific brain activity, it is thought that there are EEG signals which are associated with this decision. Using both a human-human trust and a human-machine trust EEG dataset …
Infiniband Network Monitoring: Challenges And Possibilities, Kyle D. Hintze
Infiniband Network Monitoring: Challenges And Possibilities, Kyle D. Hintze
Theses and Dissertations
Within the realm of High Performance Computing, the InfiniBand Architecture is among the leading interconnects used today. Capable of providing high bandwidth and low latency, InfiniBand is finding applications outside the High Performance Computing domain. One of these is critical infrastructure, encompassing almost all essential sectors as the work force becomes more connected. InfiniBand is not immune to security risks, as prior research has shown that common traffic analyzing tools cannot effectively monitor InfiniBand traffic transmitted between hosts, due to the kernel bypass nature of the IBA in conjunction with Remote Direct Memory Access operations. If Remote Direct Memory Access …
Low-Cost Terrestrial Demonstration Of Autonomous Satellite Proximity Operations, Zackary R. Hewitt
Low-Cost Terrestrial Demonstration Of Autonomous Satellite Proximity Operations, Zackary R. Hewitt
Theses and Dissertations
The lack of satellite servicing capabilities significantly impacts the development and operation of current orbital assets. With autonomous solutions under consideration for servicing, the purpose of this research is to build and validate a low-cost hardware platform to expedite the development of autonomous satellite proximity operations. This research aims to bridge the gap between simulation and existing higher fidelity hardware testing with an affordable alternative. An omnidirectional variant of the commercially available TurtleBot3 mobile robot is presented as a 3-DOF testbed that demonstrates a satellite servicing inspection scenario. Reference trajectories for the scenario are generated via optimal control using the …
Stereo Camera Calibrations With Optical Flow, Joshua D. Larson
Stereo Camera Calibrations With Optical Flow, Joshua D. Larson
Theses and Dissertations
Remotely Piloted Aircraft (RPA) are currently unable to refuel mid-air due to the large communication delays between their operators and the aircraft. AAR seeks to address this problem by reducing the communication delay to a fast line-of-sight signal between the tanker and the RPA. Current proposals for AAR utilize stereo cameras to estimate where the receiving aircraft is relative to the tanker, but require accurate calibrations for accurate location estimates of the receiver. This paper improves the accuracy of this calibration by improving three components of it: increasing the quantity of intrinsic calibration data with CNN preprocessing, improving the quality …
Application Of The Monte-Carlo Tree Search To Multi-Action Turn-Based Games With Hidden Information, Connor M. Pipan
Application Of The Monte-Carlo Tree Search To Multi-Action Turn-Based Games With Hidden Information, Connor M. Pipan
Theses and Dissertations
Traditional search algorithms struggle when applied to complex multi-action turn-based games. The introduction of hidden information further increases domain complexity. The Monte-Carlo Tree Search (MCTS) algorithm has previously been applied to multi-action turn-based games, but not multi-action turn-based games with hidden information. This thesis compares several Monte Carlo Tree Search (MCTS) extensions (Determinized/Perfect Information Monte Carlo, Multi-Observer Information Set MCTS, and Belief State MCTS) in TUBSTAP, an open-source multi-action turn-based game, modified to include hidden information via fog-of-war.
Anomaly Detection And Encrypted Programming Forensics For Automation Controllers, Robert W. Mellish
Anomaly Detection And Encrypted Programming Forensics For Automation Controllers, Robert W. Mellish
Theses and Dissertations
Securing the critical infrastructure of the United States is of utmost importance in ensuring the security of the nation. To secure this complex system a structured approach such as the NIST Cybersecurity framework is used, but systems are only as secure as the sum of their parts. Understanding the capabilities of the individual devices, developing tools to help detect misoperations, and providing forensic evidence for incidence response are all essential to mitigating risk. This thesis examines the SEL-3505 RTAC to demonstrate the importance of existing security capabilities as well as creating new processes and tools to support the NIST Framework. …
Two Published Flight Dynamics Models Rewritten In Rust And Structures As An Ecs, Chad A. Willis
Two Published Flight Dynamics Models Rewritten In Rust And Structures As An Ecs, Chad A. Willis
Theses and Dissertations
This thesis explores using the Entity-Component System (ECS) architecture to implement a Flight Dynamics Model (FDM) by re-implementing two published versions in the Rust programming language using the Specs Parallel ECS (SPECS) [1] for military simulation advancement. One FDM is based on Grant Palmers published textbook titled Physics for Game Programmers [2], and another is based on David Bourgs textbook titled Physics for Game Developers [3]. Furthermore, this thesis uses these models within an interactive flight simulator.The ECS architecture is based on the Data-Oriented Design (DOD) paradigm, where Components contain the data and the Systems implement the behavior which transforms …
Aircraft Inspection By Multirotor Uav Using Coverage Path Planning, Patrick H. Silberberg
Aircraft Inspection By Multirotor Uav Using Coverage Path Planning, Patrick H. Silberberg
Theses and Dissertations
All military and commercial aircraft must undergo frequent visual inspections in order to identify damage that could pose a danger to safety of flight. Currently, these inspections are primarily conducted by maintenance personnel. Inspectors must scrutinize the aircraft’s surface to find and document defects such as dents, hail damage, broken fasteners, etc.; this is a time consuming, tedious, and hazardous process. The goal of this work is to develop a visual inspection system which can be used by an Unmanned Aerial Vehicle (UAV), and to test the feasibility of this system on military aircraft. Using an autonomous system in place …
Enumerating And Locating Bluetooth Devices For Casualty Recovery In A First-Responder Environment, Justin M. Durham
Enumerating And Locating Bluetooth Devices For Casualty Recovery In A First-Responder Environment, Justin M. Durham
Theses and Dissertations
It is difficult for first-responders to quickly locate casualties in an emergency environment such as an explosion or natural disaster. In order to provide another tool to locate individuals, this research attempts to identify and estimate the location of devices that would likely be located on or with a person. A variety of devices, such as phones, smartwatches, and Bluetooth-enabled locks, are tested in multiple environments and at various heights to determine the impact that placement and interference played in locating the devices. The hypothesis is that most Bluetooth devices can be successfully enumerated quickly, but cannot be accurately located …
A Framework For Autonomous Cooperative Optimal Assignment And Control Of Satellite Formations, Devin E. Saunders
A Framework For Autonomous Cooperative Optimal Assignment And Control Of Satellite Formations, Devin E. Saunders
Theses and Dissertations
A decentralized, cooperative multi-agent optimal control framework is presented to offer a solution to the assignment and control problems associated with performing multi-agent tasks in a proximity operations environment. However, the framework developed may be applied to a variety domains such as air, space, and sea. The solution presented takes advantage of a second price auction assignment algorithm to optimally task each satellite, while model predictive control is implemented to control the agents optimally while adhering to safety and mission constraints. The solution is compared to a pseudospectral collocation method, and a study on tuning parameters is included.
Amplitude Estimation For The Large Clutter Discrete Removal Algorithm, Hannah Gjermo Chomitz
Amplitude Estimation For The Large Clutter Discrete Removal Algorithm, Hannah Gjermo Chomitz
Theses and Dissertations
A large clutter discrete (LCD) is spectrally bright localized clutter that can cause a false alarm or missed target detection in space-time adaptive processing (STAP) radar data. For passive bistatic STAP, the four step LCD removal (LCDR) algorithm estimates the spatial/Doppler frequency and complex amplitude of the LCD and then removes it from the data. Once the LCD is removed from the data, homogeneous clutter suppression techniques can be used to process the data and search for targets. This research focuses on reducing the complexity of estimating the LCDs complex amplitude. This research proposes a method that directly solves for …
Choosing Isds As A Major: Predictive Analysis, Sarah Johnson
Choosing Isds As A Major: Predictive Analysis, Sarah Johnson
Honors Capstones
No abstract provided.
How Do Monetary Incentives Influence Giving? An Empirical Investigation Of Matching Subsidies On Kiva, Zhiyuan Gao, Zhiling Guo, Qian Tang
How Do Monetary Incentives Influence Giving? An Empirical Investigation Of Matching Subsidies On Kiva, Zhiyuan Gao, Zhiling Guo, Qian Tang
Research Collection School Of Computing and Information Systems
Matching subsidies, through which third-party institutions provide a dollar-for-dollar match of private contributions made through selected campaigns, have served as effective tools to boost fundraising. We utilize a quasi-experiment on a prosocial crowdfunding platform to examine the effectiveness of matching subsidies in shaping funding outcomes and lender behaviors. Although matching subsidies offer matched loans competitive advantages over unmatched loans, we find that total private contributions made to both matched and unmatched loans increase compared to their prematching counterparts, suggesting a positive spillover effect on unmatched loans. However, matching subsidies lead to decreased private contributions made on the platform after a …
Enhancing Healthcare Professional And Caregiving Staff Informedness With Data Analytics For Chronic Disease Management, Na Liu, Robert John Kauffman
Enhancing Healthcare Professional And Caregiving Staff Informedness With Data Analytics For Chronic Disease Management, Na Liu, Robert John Kauffman
Research Collection School Of Computing and Information Systems
An important area in healthcare to which data analytics can be applied is chronic disease management. The chronic care model is mostly patient-centric, so patients have been considered as the end users of data analytics. The information needs of healthcare providers have been overlooked. Drawing upon the theory of informedness and the transtheoretical model of health behavior change, we use a multicase study approach to investigate the information needs of different caregiving stakeholders in the spectrum of chronic diseases, and how data analytics can be designed to meet the varying needs of professionals and staff to support their informedness.
Is The Ground Truth Really Accurate? Dataset Purification For Automated Program Repair, Deheng Yang, Yan Lei, Xiaoguang Mao, David Lo, Huan Xie, Meng Yan
Is The Ground Truth Really Accurate? Dataset Purification For Automated Program Repair, Deheng Yang, Yan Lei, Xiaoguang Mao, David Lo, Huan Xie, Meng Yan
Research Collection School Of Computing and Information Systems
Datasets of real-world bugs shipped with human-written patches are intensively used in the evaluation of existing automated program repair (APR) techniques, wherein the human-written patches always serve as the ground truth, for manual or automated assessment approaches, to evaluate the correctness of test-suite adequate patches. An inaccurate human-written patch tangled with other code changes will pose threats to the reliability of the assessment results. Therefore, the construction of such datasets always requires much manual effort on isolating real bug fixes from bug fixing commits. However, the manual work is time-consuming and prone to mistakes, and little has been known on …
Investigating The Adoption Of Hybrid Encrypted Cloud Data Deduplication With Game Theory, Xueqin Liang, Zheng Yan, Robert H. Deng, Qinghu Zheng
Investigating The Adoption Of Hybrid Encrypted Cloud Data Deduplication With Game Theory, Xueqin Liang, Zheng Yan, Robert H. Deng, Qinghu Zheng
Research Collection School Of Computing and Information Systems
Encrypted data deduplication, along with different preferences in data access control, brings the birth of hybrid encrypted cloud data deduplication (H-DEDU for short). However, whether H-DEDU can be successfully deployed in practice has not been seriously investigated. Obviously, the adoption of H-DEDU depends on whether it can bring economic benefits to all stakeholders. But existing economic models of cloud storage fail to support H-DEDU due to complicated interactions among stakeholders. In this article, we establish a formal economic model of H-DEDU by formulating the utilities of all involved stakeholders, i.e., data holders, data owners, and Cloud Storage Providers (CSPs). Then, …
Singapore Airlines: Profit Recovery And Aircraft Allocation Models During The Covid-19 Pandemic, Michelle L. F. Cheong, Ulysses M. Z. Chong, Anne N. T. A. Nguyen, Su Yiin Ang, Gabriella P. Djojosaputro, Gordy Adiprasetyo, Kendra L. B. Gadong
Singapore Airlines: Profit Recovery And Aircraft Allocation Models During The Covid-19 Pandemic, Michelle L. F. Cheong, Ulysses M. Z. Chong, Anne N. T. A. Nguyen, Su Yiin Ang, Gabriella P. Djojosaputro, Gordy Adiprasetyo, Kendra L. B. Gadong
Research Collection School Of Computing and Information Systems
COVID-19 has severely impacted the global aviation industry, causing many airlines to downsize or exit the industry. For airlines which attempt to sustain their operations, they will need to respond to the increase in passenger and cargo demand, as countries recover slowly from the crisis due to the availability of vaccines. We built a series of spreadsheet models to first project the COVID-19 recovery rates by countries from 2021 to 2025, then forecast the passenger and cargo demand, using historical data as base figures. Using the financial and operation data, the revenue, expense, and profit can be projected, then an …
Learning To Assess The Quality Of Stroke Rehabilitation Exercises, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Bermúdez I Badia
Learning To Assess The Quality Of Stroke Rehabilitation Exercises, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Bermúdez I Badia
Research Collection School Of Computing and Information Systems
Due to the limited number of therapists, task-oriented exercises are often prescribed for post-stroke survivors as in-home rehabilitation. During in-home rehabilitation, a patient may become unmotivated or confused to comply prescriptions without the feedback of a therapist. To address this challenge, this paper proposes an automated method that can achieve not only qualitative, but also quantitative assessment of stroke rehabilitation exercises. Specifically, we explored a threshold model that utilizes the outputs of binary classifiers to quantify the correctness of a movements into a performance score. We collected movements of 11 healthy subjects and 15 post-stroke survivors using a Kinect sensor …
Deep Learning For Anomaly Detection: Challenges, Methods, And Opportunities, Guansong Pang, Longbing Cao, Charu Aggarwal
Deep Learning For Anomaly Detection: Challenges, Methods, And Opportunities, Guansong Pang, Longbing Cao, Charu Aggarwal
Research Collection School Of Computing and Information Systems
In this tutorial we aim to present a comprehensive survey of the advances in deep learning techniques specifically designed for anomaly detection (deep anomaly detection for short). Deep learning has gained tremendous success in transforming many data mining and machine learning tasks, but popular deep learning techniques are inapplicable to anomaly detection due to some unique characteristics of anomalies, e.g., rarity, heterogeneity, boundless nature, and prohibitively high cost of collecting large-scale anomaly data. Through this tutorial, audiences would gain a systematic overview of this area, learn the key intuitions, objective functions, underlying assumptions, advantages and disadvantages of different categories of …
Assessing Code Clone Harmfulness: Indicators, Factors, And Counter Measures, Bin Hu, Yijian Wu, Xin Peng, Jun Sun, Nanjie Zhan, Jun Wu
Assessing Code Clone Harmfulness: Indicators, Factors, And Counter Measures, Bin Hu, Yijian Wu, Xin Peng, Jun Sun, Nanjie Zhan, Jun Wu
Research Collection School Of Computing and Information Systems
Code clones are identical or similar code in software projects. On one hand, developers clone code to achieve higher productivity and thus clones inherently exist; on the other hand, code clones demand extra effort to maintain the consistency between clone instances and may introduce bugs, and thus are often considered harmful for software maintenance and quality. We believe that not all code clones have the same level of harmfulness. A systematic way of assessing the harmfulness level of cloned code would facilitate informed decisions on how to deal with clones. We propose a model for clone harmfulness level assessment with …