Institutional Repository
ATTENTION: UDSpace will not accept new deposits or material between Monday, November 13th, and Monday, December 4th, as we upgrade the underlying repository software. Access to materials in UDSpace is unaffected, but logging into UDSpace with an account will not be available during this time.
The UDSpace Institutional Repository collects and disseminates research material from the University of Delaware.
- Faculty, staff, and graduate students can deposit their research material directly into UDSpace. Faculty may use UDSpace to fulfill the University of Delaware Faculty Senate Open Access Resolution, and in many cases may use it to fulfill open access requirements from grant funding agencies.
- Departments can use UDSpace to publish or distribute their working papers, technical reports, or other research material.
- UDSpace also includes all doctoral dissertations from winter 2014 forward, and all master's theses from fall 2009 forward.
To learn more about UDSpace, and how you can make your research openly accessible to the public, visit our UDSpace Policies website.
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Recent Submissions
Towards C-V2X Enabled Collaborative Autonomous Driving
(IEEE Transactions on Vehicular Technology, 2023-08-14) He, Yuankai; Wu, Baofu; Dong, Zheng; Wan, Jian; Shi, Weisong
Intelligent vehicles, including autonomous vehicles and vehicles equipped with ADAS systems, are single-agent systems that navigate solely on the information collected by themselves. However, despite rapid advancements in hardware and algorithms, many accidents still occur due to the limited sensing coverage from a single-agent perception angle. These tragedies raise a critical question of whether single-agent autonomous driving is safe. Preliminary investigations on this safety issue led us to create a C-V2X-enabled collaborative autonomous driving framework (CCAD) to observe the driving circumstance from multiple perception angles. Our framework uses C-V2X technology to connect infrastructure with vehicles and vehicles with vehicles to transmit safety-critical information and to add safety redundancies. By enabling these communication channels, we connect previously independent single-agent vehicles and existing infrastructure. This paper presents a prototype of our CCAD framework with RSU and OBU as communication devices and an edge-computing device for data processing. We also present a case study of successfully implementing an infrastructure-based collaborative lane-keeping with the CCAD framework. Our case study evaluations demonstrate that the CCAD framework can transmit, in real-time, personalized lane-keeping guidance information when the vehicle cannot find the lanes. The evaluations also indicate that the CCAD framework can drastically improve the safety of single-agent intelligent vehicles and open the doors to many more collaborative autonomous driving applications.
E3-UAV: An Edge-Based Energy-Efficient Object Detection System for Unmanned Aerial Vehicles
(IEEE Internet of Things Journal, 2023-08-03) Suo, Jiashun; Zhang, Xingzhou; Shi, Weisong; Zhou, Wei
Motivated by the advances in deep learning techniques, the application of Unmanned Aerial Vehicle (UAV)-based object detection has proliferated across a range of fields, including vehicle counting, fire detection, and city monitoring. While most existing research studies only a subset of the challenges inherent to UAV-based object detection, there are few studies that balance various aspects to design a practical system for energy consumption reduction. In response, we present the E3-UAV, an edge-based energy-efficient object detection system for UAVs. The system is designed to dynamically support various UAV devices, edge devices, and detection algorithms, with the aim of minimizing energy consumption by deciding the most energy-efficient flight parameters (including flight altitude, flight speed, detection algorithm, and sampling rate) required to fulfill the detection requirements of the task. We first present an effective evaluation metric for actual tasks and construct a transparent energy consumption model based on hundreds of actual flight data to formalize the relationship between energy consumption and flight parameters. Then we present a lightweight energy-efficient priority decision algorithm based on a large quantity of actual flight data to assist the system in deciding flight parameters. Finally, we evaluate the performance of the system, and our experimental results demonstrate that it can significantly decrease energy consumption in real-world scenarios. Additionally, we provide four insights that can assist researchers and engineers in their efforts to study UAV-based object detection further.
Partnering with North American University Presses to Open and Preserve Humanities and Social Sciences Scholarship
(Association of College and Research Libraries, 2023) Pucci, Alicia; Johnson, Annie
University presses play a crucial role when it comes to advancing scholarship in the humanities and social sciences. The Association of University Presses, for example, has over 150 members around the world and publishes 12,000 new books annually. Despite this output, university press content is largely missing from institutional repositories. While presses and institutional repositories each make their own unique contribution to the scholarly publishing landscape, this chapter argues that academic libraries with institutional repositories can and should partner with university presses and other mission-driven publishers. Indeed, such partnerships are key to rethinking institutional repositories, which for too long have focused on providing access to scientific journal articles.
Neurobiological metric of cortical delay discounting differentiates risk for self- and other-directed violence among trauma-exposed individuals
(Journal of Psychopathology and Clinical Science, 2023-09-07) Sheehan, Ana E.; Bounoua, Nadia; Stumps, Anna; Miglin, Rickie; Huerta, Wendy; Sadeh, Naomi
Self- and other-directed violence (SDV/ODV) contribute to elevated rates of mortality. Early trauma exposure shows robust positive associations with these forms of violence but alone does not distinguish those at heightened risk for later engagement in SDV/ODV. Novel assessment metrics could aid early identification efforts for individuals with vulnerabilities to violence perpetration. This study examined a novel neurobiological measure of impulsive choice for reward as a potential moderator of associations between childhood trauma exposure and lifetime SDV/ODV. A high-risk community sample of 177 adults (89 men; 50.3%) were assessed for childhood trauma exposure, engagement in SDV (e.g., suicide attempts), and ODV (e.g., assault). A cortical delay discounting (C-DD) measure was created using a multivariate additive model of gray matter thickness across both hemispheres, previously found to be positively associated with susceptibility to impulsivity and externalizing disorders. Childhood trauma exposure was positively associated with ODV and SDV; however, these relationships differed as a function of C-DD. Engagement in ODV increased as scores on C-DD increased, and SDV increased as scores on C-DD decreased. Furthermore, moderation revealed biological sex differences, as the association between childhood trauma and SDV depended on C-DD for women but not for men. Findings from the present work demonstrate that risk conferred by childhood trauma exposure to violence varied as a function of a C-DD. Together, these findings point to the utility of neurobiological markers of impulsive decision-making for differentiating risk for violence among individuals with a history of trauma exposure.
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(2021) Morgan, Paige
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