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Articles 1 - 4 of 4
Full-Text Articles in Engineering
Procure-To-Pay Software In The Digital Age: An Exploration And Analysis Of Efficiency Gains And Cybersecurity Risks In Modern Procurement Systems, Drew Lane
MPA/MPP/MPFM Capstone Projects
Procure-to-Pay (P2P) softwares are an integral part of the payment and procurement processing functions at large-scale governmental institutions. These softwares house all of the financial functions related to procurement, accounts payable, and often human resources, helping to facilitate and automate the process from initiation of a payment or purchase, to the actual disbursal of funds. Often, these softwares contain budgeting and financial reporting tools as part of the offering. As such an integral part of the financial process, these softwares obviously come at an immense cost from a set of reputable vendors. In the case of government, these vendors mainly …
A Compiler Target Model For Line Associative Registers, Paul S. Eberhart
A Compiler Target Model For Line Associative Registers, Paul S. Eberhart
Theses and Dissertations--Electrical and Computer Engineering
LARs (Line Associative Registers) are very wide tagged registers, used for both register-wide SWAR (SIMD Within a Register )operations and scalar operations on arbitrary fields. LARs include a large data field, type tags, source addresses, and a dirty bit, which allow them to not only replace both caches and registers in the conventional memory hierarchy, but improve on both their functions. This thesis details a LAR-based architecture, and describes the design of a compiler which can generate code for a LAR-based design. In particular, type conversion, alignment, and register allocation are discussed in detail.
Image-Based Roadway Assessment Using Convolutional Neural Networks, Weilian Song
Image-Based Roadway Assessment Using Convolutional Neural Networks, Weilian Song
Theses and Dissertations--Computer Science
Road crashes are one of the main causes of death in the United States. To reduce the number of accidents, roadway assessment programs take a proactive approach, collecting data and identifying high-risk roads before crashes occur. However, the cost of data acquisition and manual annotation has restricted the effect of these programs. In this thesis, we propose methods to automate the task of roadway safety assessment using deep learning. Specifically, we trained convolutional neural networks on publicly available roadway images to predict safety-related metrics: the star rating score and free-flow speed. Inference speeds for our methods are mere milliseconds, enabling …
Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal
Relation Prediction Over Biomedical Knowledge Bases For Drug Repositioning, Mehmet Bakal
Theses and Dissertations--Computer Science
Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying other essential relations (e.g., causation, prevention) between biomedical entities is also critical to understand biomedical processes. Hence, it is crucial to develop automated relation prediction systems that can yield plausible biomedical relations to expedite the discovery process. In this dissertation, we demonstrate three approaches to predict treatment relations between biomedical entities for the drug repositioning task …