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Articles 1 - 6 of 6
Full-Text Articles in Engineering
Efficient Privacy-Aware Imagery Data Analysis, Yifan Tian
Efficient Privacy-Aware Imagery Data Analysis, Yifan Tian
Doctoral Dissertations and Master's Theses
The widespread use of smartphones and camera-coupled Internet of Thing (IoT) devices triggers an explosive growth of imagery data. To extract and process the rich contents contained in imagery data, various image analysis techniques have been investigated and applied to a spectrum of application scenarios. In recent years, breakthroughs in deep learning have powered a new revolution for image analysis in terms of effectiveness with high resource consumption. Given the fact that most smartphones and IoT devices have limited computational capability and battery life, they are not ready for the processing of computational intensive analytics over imagery data collected by …
Markov Decision Process Approach To Strategize National Breast Cancer Screening Policy In Data-Limited Settings, Vijeta Deshpande
Markov Decision Process Approach To Strategize National Breast Cancer Screening Policy In Data-Limited Settings, Vijeta Deshpande
Masters Theses
Early diagnosis is a promising strategy to reduce premature mortalities and for optimal use of resources. But the absence of mathematical models specific to the data settings in LMIC’s impedes the construction of economic analysis necessary for decision-makers in the development of cancer control programs. This thesis presents a new methodology for parameterizing the natural history model of breast cancer based on data availabilities in low and middle income countries, and formulation of a control optimization problem to find the optimal screening schedule for mammography screening, solved using dynamic programming. As harms and benefits are known to increase with the …
Machine Learning With Multi-Class Regression And Neural Networks: Analysis And Visualization Of Crime Data In Seattle, Erkin David George
Machine Learning With Multi-Class Regression And Neural Networks: Analysis And Visualization Of Crime Data In Seattle, Erkin David George
Honors Projects
This article examines the implications of machine learning algorithms and models, and the significance of their construction when investigating criminal data. It uses machine learning models and tools to store, clean and analyze data that is fed into a machine learning model. This model is then compared to another model to test for accuracy, biases and patterns that are detected in between the experiments. The data was collected from data.seattle.gov and was published by the City of Seattle Data Portal and was accessed on September 17, 2018. This research will be looking into how machine learning models can be used …
Liquidated Damages: An Analysis Of Their Use And Effectiveness, Alfredo N. Aragon
Liquidated Damages: An Analysis Of Their Use And Effectiveness, Alfredo N. Aragon
Construction Management
A construction company’s success and/or failure is dependent upon project completion with respect to time and budget. Failure to meet the contract completion date results in a loss of profit for owners and contractors alike. In order to help mitigate project delays, liquidated damage clauses have been included into construction contracts. Incorporating provisions within the construction contracts in the form of liquidated damages aims to help shift the financial burden when there is a failure to meet contractual obligations, hopefully offering quick compensation for delays. Unlike general or actual damages, liquidated damages are pre-defined and agreed upon prior to entering …
Stability In Government, Emerging Technology, And Decentralized Economies: An Analysis Of Alternative Uses Of Cryptocurrencies, Mickayla Stogsdill
Stability In Government, Emerging Technology, And Decentralized Economies: An Analysis Of Alternative Uses Of Cryptocurrencies, Mickayla Stogsdill
Chancellor’s Honors Program Projects
No abstract provided.
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 …