Open Access. Powered by Scholars. Published by Universities.®
- Publication
-
- Civil & Environmental Engineering Theses & Dissertations (1)
- Computational Modeling & Simulation Engineering Theses & Dissertations (1)
- Computer Science Faculty Publications (1)
- Electrical & Computer Engineering Faculty Publications (1)
- Engineering Management & Systems Engineering Faculty Publications (1)
- Publication Type
Articles 1 - 5 of 5
Full-Text Articles in Entire DC Network
Enhanced Traffic Incident Analysis With Advanced Machine Learning Algorithms, Zhenyu Wang
Enhanced Traffic Incident Analysis With Advanced Machine Learning Algorithms, Zhenyu Wang
Computational Modeling & Simulation Engineering Theses & Dissertations
Traffic incident analysis is a crucial task in traffic management centers (TMCs) that typically manage many highways with limited staff and resources. An effective automatic incident analysis approach that can report abnormal events timely and accurately will benefit TMCs in optimizing the use of limited incident response and management resources. During the past decades, significant efforts have been made by researchers towards the development of data-driven approaches for incident analysis. Nevertheless, many developed approaches have shown limited success in the field. This is largely attributed to the long detection time (i.e., waiting for overwhelmed upstream detection stations; meanwhile, downstream stations …
Truck Trailer Classification Using Side-Fire Light Detection And Ranging (Lidar) Data, Olcay Sahin
Truck Trailer Classification Using Side-Fire Light Detection And Ranging (Lidar) Data, Olcay Sahin
Civil & Environmental Engineering Theses & Dissertations
Classification of vehicles into distinct groups is critical for many applications, including freight and commodity flow modeling, pavement management and design, tolling, air quality monitoring, and intelligent transportation systems. The Federal Highway Administration (FHWA) developed a standardized 13-category vehicle classification ruleset, which meets the needs of many traffic data user applications. However, some applications need high-resolution data for modeling and analysis. For example, the type of commodity being carried must be known in the freight modeling framework. Unfortunately, this information is not available at the state or metropolitan level, or it is expensive to obtain from current resources.
Nevertheless, using …
Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe
Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe
Engineering Management & Systems Engineering Faculty Publications
Special information has a significant role in disaster management. Land cover mapping can detect short- and long-term changes and monitor the vulnerable habitats. It is an effective evaluation to be included in the disaster management system to protect the conservation areas. The critical visual and statistical information presented to the decision-makers can help in mitigation or adaption before crossing a threshold. This paper aims to contribute in the academic and the practice aspects by offering a potential solution to enhance the disaster data source effectiveness. The key research question that the authors try to answer in this paper is how …
Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin
Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin
Electrical & Computer Engineering Faculty Publications
This guest editorial summarizes the Special Section on Machine Learning in Optics.
Outlier Profiles Of Atomic Structures Derived From X-Ray Crystallography And From Cryo-Electron Microscopy, Lin Chen, Jing He, Angelo Facchiano
Outlier Profiles Of Atomic Structures Derived From X-Ray Crystallography And From Cryo-Electron Microscopy, Lin Chen, Jing He, Angelo Facchiano
Computer Science Faculty Publications
Background: As more protein atomic structures are determined from cryo-electron microscopy (cryo-EM) density maps, validation of such structures is an important task. Methods: We applied a histogram-based outlier score (HBOS) to six sets of cryo-EM atomic structures and five sets of X-ray atomic structures, including one derived from X-ray data with better than 1.5 Å resolution. Cryo-EM data sets contain structures released by December 2016 and those released between 2017 and 2019, derived from resolution ranges 0–4 Å and 4–6 Å respectively. Results: The distribution of HBOS values in five sets of X-ray structures show that HBOS is sensitive distinguishing …