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Spring 2023

Kullar, Jagbir S.

With rising demands in industry for reliable electrical cable distribution networks comes an inherent need for utility providers to know well the condition of the assets in their network. Heightened expectations from regulators and consumers require methods of reliability assessment to improve...

Spring 2023

Shojaee, Seyedamir

In this dissertation, a machine-learning method is utilized to enhance the accuracy of wake parameters calculated by Reynolds Averaged Navier Stokes (RANS) k-ω SST model of flow on and around wall-mounted rectangular cylinders. Using high-quality results from Large Eddy Simulation (LES), this...

Fall 2021

Mohammadhosseinzadeh Golabchi, Hamidreza

Considering the high rates of labor resources in construction projects clearly indicates the importance of appropriate labor resource management methods. Accurate labor resource allocation is a substantial step towards successful labor resource management. With the recent developments in the area...

Fall 2020

Zhanbyrtayev, Madi

The ubiquity of the Internet-of-Things (IoT) devices in everyday life allows various sensors to be utilized in networked systems for solving a number of real-world problems. Models utilizing specific sensing modalities achieve impressive performance in understanding human activity and are used in...

Fall 2021

Jafari, Parinaz

The management of project documentation involves processing a large amount of important information embedded in different contract and project specification documents. Although contract-related documentation is critical for effective information flow and—in turn—successful project management, it...

2020-01-01

Shafi, Hareem, Velswamy, Kirubakaran, Ibrahim, Fadi, Huang,Biao

This work proposes a two-level hierarchical constrained control structure for reinforcement learning (RL) with application in a Primary Separation Vessel (PSV). The lower level is concerned with servo tracking and regulation of the interface level against variances in ore quality by manipulating...

2022-01-01

Xiunan Wang, Hao Wang, Pouria Ramazi, Kyeongah Nah, Mark Lewis

Accurate prediction of the number of daily or weekly confirmed cases of COVID-19 is critical to the control of the pandemic. Existing mechanistic models nicely capture the disease dynamics. However, to forecast the future, they require the transmission rate to be known, limiting their prediction...

2022-03-10

Xiunan Wang, Hao Wang, Pouria Ramazi, Kyeongah Nah, Mark Lewis

Accurate prediction of the number of daily or weekly confirmed cases of COVID-19 is critical to the control of the pandemic. Existing mechanistic models nicely capture the disease dynamics. However, to forecast the future, they require the transmission rate to be known, limiting their prediction...

Fall 2020

Yin, Xianfei

The municipal drainage system is a key component of every modern city’s infrastructure. However, as the drainage system ages, its pipes gradually deteriorate at rates that vary based on the conditions of utilization (i.e., intrinsic conditions) and other extrinsic factors such as the presence of...

Spring 2022

Aghaei, Nikoo

Data augmentation is a strong tool for enhancing the performance of deep learning models using different techniques to increase both the quantity and diversity of training data. Cutout was previously proposed, in the context of image classification, as a simple regularization technique that...