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Martin Wanielista - Bmp Trains Model Features - January 31, 2020, Martin Wanielista
Martin Wanielista - Bmp Trains Model Features - January 31, 2020, Martin Wanielista
BMP Trains
Dr. Martin Wanielista's slides from his PowerPoint presentation during the BMPTRAINS workshop on January 30-31, 2020.
Martin Wanielista - Bmp Trains Intro & Navigation - January 31, 2020, Martin Wanielista
Martin Wanielista - Bmp Trains Intro & Navigation - January 31, 2020, Martin Wanielista
BMP Trains
Dr. Martin Wanielista's slides from his PowerPoint presentation during the BMPTRAINS workshop on January 30-31, 2020.
Rich Magee - Bmp Trains - January 31, 2020, Rich Magee
Rich Magee - Bmp Trains - January 31, 2020, Rich Magee
BMP Trains
Rich Magee's slides from his PowerPoint presentation during the BMPTRAINS workshop on January 30-31, 2020.
Ikiensinma Gogo-Abite - Bmp Trains Presentation - January 31, 2020, Ikiensinma Gogo-Abite
Ikiensinma Gogo-Abite - Bmp Trains Presentation - January 31, 2020, Ikiensinma Gogo-Abite
BMP Trains
Dr. Ikiensinma Gogo-Abite's slides from his PowerPoint presentation during the BMPTRAINS workshop on January 30-31, 2020.
Martin Wanielista - Bmp Trains Example Application - January 31, 2020, Martin Wanielista
Martin Wanielista - Bmp Trains Example Application - January 31, 2020, Martin Wanielista
BMP Trains
Dr. Martin Wanielista's slides from his PowerPoint presentation during the BMPTRAINS workshop on January 30-31, 2020.
Mike Hardin - Bmp Trains - January 31, 2020, Mike Hardin
Mike Hardin - Bmp Trains - January 31, 2020, Mike Hardin
BMP Trains
Dr. Mike Hardin's slides from his PowerPoint presentation during the BMPTRAINS workshop on January 30-31, 2020.
Eric Livingston - Bmp Trains - January 31, 2020, Eric Livingston
Eric Livingston - Bmp Trains - January 31, 2020, Eric Livingston
BMP Trains
Eric Livingston's slides from his PowerPoint presentation during the BMPTRAINS workshop on January 30-31, 2020.
Harvey Harper - Morning Presentation Slides - January 30, 2020, Harvey H. Harper Iii
Harvey Harper - Morning Presentation Slides - January 30, 2020, Harvey H. Harper Iii
BMP Trains
Dr. Harvey Harper's slides from the morning presentation at the January 30, 2020 BMP Trains workshop.
Harvey Harper - Afternoon Presentation Slides - January 30, 2020, Harvey H. Harper Iii
Harvey Harper - Afternoon Presentation Slides - January 30, 2020, Harvey H. Harper Iii
BMP Trains
Dr. Harvey Harper's slides from the afternoon presentation at the January 30, 2020 BMP Trains workshop.
Emulsion Characterization Study For Improved Bilgewater Treatment And Management, Daniela Diaz Hernandez
Emulsion Characterization Study For Improved Bilgewater Treatment And Management, Daniela Diaz Hernandez
Electronic Theses and Dissertations, 2020-
The need for proper management of bilgewater to meet discharge regulations (e.g., 15 ppm oil) has revealed the necessity to expand the current understanding of bilgewater emulsions. This study proposed to evaluate emulsion stability under various environmental conditions and to identify governing parameters for emulsion formation. The stabilizing properties of eight-commercial cleaners and two-neat surfactants were evaluated. In situ characterization techniques were used for monitoring emulsion stability. Additionally, a needle-type pH microsensor and fluorescence spectroscopy were used for analyzing mass transfer at the oil-water interface. Water quality of extracted bilgewater showed to highly vary between vessels (e.g., conductivity: 1.74 -- …
Improving Air Pollution Exposure Estimation Using Cell Phone Location Data And Low-Cost Sensors, Xiaonan Yu
Improving Air Pollution Exposure Estimation Using Cell Phone Location Data And Low-Cost Sensors, Xiaonan Yu
Electronic Theses and Dissertations, 2020-
Human exposure estimation to air pollution plays an important role in epidemiological studies which are designed to reveal correlations between human exposures to certain air pollutants and certain diseases, such as asthma, cardiovascular disease and reproductive diseases. Traditionally, when people's mobile data is hard to get, home location is used to estimate people's exposures assuming that people stay at home all the time. Whereas, people move and it is more accurate to estimate people's exposures including people's mobility. In our study, we showcased two methods to obtain people's mobile data: Google Maps location history (GMLH) data and Call Detailed Record …
Prediction Of Pedestrians' Red Light Violations Using Deep Learning, Shile Zhang
Prediction Of Pedestrians' Red Light Violations Using Deep Learning, Shile Zhang
Electronic Theses and Dissertations, 2020-
Pedestrians are regarded as Vulnerable Road Users (VRUs). Each year, thousands of pedestrians' deaths are caused by traffic crashes, which take up 16% of the total road fatalities and injuries in the U.S. (FHWA, 2018). Crashes can happen if there are interactions between VRUs and motorized transportation. And pedestrians' unexpected crossings, such as red-light violations at the signalized intersections, would expose them to motorized transportation and cause potential collisions. This thesis is intended to predict the pedestrians' red-light violation behaviors at the signalized crosswalks based on an LSTM (Long Short-term Memory) neural network. With video data collected from real traffic …
Modeling Of Incident Type And Incident Duration Using Data From Multiple Years, Sudipta Dey Tirtha
Modeling Of Incident Type And Incident Duration Using Data From Multiple Years, Sudipta Dey Tirtha
Electronic Theses and Dissertations, 2020-
We develop a model system that recognizes the distinct traffic incident duration profiles based on incident type. Specifically, a copula-based joint framework with a scaled multinomial logit model (SMNL) system for incident type and a grouped generalized ordered logit (GGOL) model system for incident duration to accommodate for the impact of observed and unobserved effects on incident type and incident duration. The model system is estimated using traffic incident data from 2012 through 2017 for the Greater Orlando region, employing a comprehensive set of exogenous variables – incident characteristics, roadway characteristics, traffic condition, weather condition, built environment and socio-demographic characteristics. …
Water Reclamation Using Functionalized Forward Osmosis Membrane, Fnu Joshua
Water Reclamation Using Functionalized Forward Osmosis Membrane, Fnu Joshua
Electronic Theses and Dissertations, 2020-
This study investigated water reclamation from an impaired-quality water using forward osmosis (FO) membrane functionalized by nano zero valent iron (nZVI) loaded polyelectrolyte multilayer films. Stormwater runoff was selected as the impaired-quality water, which served as a feed solution (FS) and a NaCl salt solution at a concentration representing reverse osmosis (RO) concentrate was used a draw solution (DS). RO concentrate is another impaired-quality water that is discharged to the environmental with little or no treatment. A commercial cellulose triacetate (CTA) FO membrane was modified using poly allylamine hydrochloride (PAH) (a polycation) and poly acrylic acid (PAA) (a polyanion) following …
Bias And Sensitivity Of Nonlinear Models For Seismic Response Of Ordinary Standard Bridges, Andres Rodriguez Caballero
Bias And Sensitivity Of Nonlinear Models For Seismic Response Of Ordinary Standard Bridges, Andres Rodriguez Caballero
Electronic Theses and Dissertations, 2020-
The implementation of nonlinear structural analysis under large deformation demands has enabled more realistic response prediction in comparison with the classical linear approaches. However, the sensitivity to modeling assumptions, element and material formulations, implementations, and parameter selection may lead to unreliable results. While previous works have led to a better understanding of how to best model nonlinear static responses of bridge components and systems, the introduction of dynamic loads and the corresponding material hysteresis presents an additional source of variability in the nonlinear responses. The current research involves the analysis of two ordinary standard bridges in California under seismic load …
Numerical Analysis On The Geomechanical Mechanisms And Stability Of Sinkholes In Central Florida, Moataz Soliman
Numerical Analysis On The Geomechanical Mechanisms And Stability Of Sinkholes In Central Florida, Moataz Soliman
Electronic Theses and Dissertations, 2020-
Sinkholes are a common geohazard in karst areas that can threaten human life and causes significant damage to infrastructure. Approximately 18% of the United States falls into karst area where overburden soils are underlain by soluble carbonate rocks. In Florida, sinkhole-related insurance claims between 2006 and the third quarter of 2010 amounted to $1.4 billion according to the Florida Office of Insurance Regulation. Effective methods and tools for the sinkhole detection and characterization are necessary. Numerical analysis can play an important role in determining the stability of sinkholes and understanding the failure mechanism under varied subsurface geological conditions. In this …
Evaluating The Performance And Impacts Of Seawater Regeneration In An Anion Exchange Process, Daniel Whalen
Evaluating The Performance And Impacts Of Seawater Regeneration In An Anion Exchange Process, Daniel Whalen
Electronic Theses and Dissertations, 2020-
This research investigated the use of seawater regeneration for anion exchange (AIX) processes. Seawater and salt-supplemented seawater regeneration of chloride-form anion resin were evaluated in regard to (1) operational performance efficiency of sulfate and natural organic matter removal, (2) competing exchange of bromide during regeneration, and (3) brominated disinfection by-product (DBP) formation due to bromide leakage. The first component involved bench-scale research that revealed that seawater-based regeneration led to bromide leakage that could be mitigated to an average of 1.82 mg/L using 1% salt-supplemented seawater, and 1.25 mg/L using 3% salt-supplemented seawater. Conceptual cost comparisons revealed that the use of …
The Impacts Of Wave Energy Conversion On Coastal Morphodynamics In A Changing Climate, Cigdem Ozkan
The Impacts Of Wave Energy Conversion On Coastal Morphodynamics In A Changing Climate, Cigdem Ozkan
Electronic Theses and Dissertations, 2020-
Fossil fuels, i.e., petroleum, natural gas, and coal, are the primary sources of global energy. Studies on the impacts of fossil fuels on climate change have shown the immediate need to reduce greenhouse gas emissions and adopt sustainable alternatives since these emissions result in warmer atmospheric temperatures, ocean acidification, glacier melting, sea level rise, and many other ramifications. In recent years, these alarming results have prompted governments worldwide to develop adaptation strategies for climate change, leading to increased investments in renewable energy resources. Globally, solar energy, wind energy, and hydropower have been the leading sources of renewable energy. Ocean wave …
Econometric Frameworks For Multivariate Models: Application To Crash Frequency Analysis, Tanmoy Bhowmik
Econometric Frameworks For Multivariate Models: Application To Crash Frequency Analysis, Tanmoy Bhowmik
Electronic Theses and Dissertations, 2020-
Econometric crash frequency models are a major analytical tool employed for examining the critical factors influencing crash occurrence. However, there are several methodological challenges associated with existing models suggesting a continual need to develop advanced econometric framework to address these gaps. The current dissertation contributes towards addressing the methodological challenges in crash frequency analysis for analyzing multiple crash frequency variables for the same study unit by proposing advanced econometric approaches. The first part of the dissertation contributes to safety literature by conducting a comparison exercise between the two major streams of multivariate approaches - (1) simulation-based approach and (2) analytical …
Ultraviolet Irradiation Combined With Chlorine Dioxide Pre-Oxidation For Disinfection By-Product Control, Paula Campesino
Ultraviolet Irradiation Combined With Chlorine Dioxide Pre-Oxidation For Disinfection By-Product Control, Paula Campesino
Electronic Theses and Dissertations, 2020-
The use of ultraviolet (UV) light and chlorine dioxide (ClO2) as an advanced oxidation process (AOP) has been investigated at the bench-scale to understand the effects of their use on disinfection by-product (DBP) formation potential (FP) in chlorinated groundwater (GW) and surface water (SW) supplies. Two GWs and two SWs of varying qualities were subject to a series of AOP treatment sequences at the bench scale: sodium hypochlorite, to serve as a baseline; ClO2-Cl2, UV-Cl2, and UV-ClO2-Cl2. In these treatment sequences, Cl2 is used as a primary and secondary disinfectant. Several water quality parameters were measured throughout the experiments, including …
A Deep Learning Approach For Real-Time Crash Risk Prediction At Urban Arterials, Pei Li
A Deep Learning Approach For Real-Time Crash Risk Prediction At Urban Arterials, Pei Li
Electronic Theses and Dissertations, 2020-
Real-time crash risk prediction aims to predict the crash probabilities within a short time period, it is expected to play a crucial role in the advanced traffic management system. However, most of the existing studies only focused on freeways rather than urban arterials because of the complicated traffic environment of the arterials. This thesis proposes a long short-term memory convolutional neural network (LSTM-CNN) to predict the real-time crash risk at arterials. The advantage of this model is it can benefit from both LSTM and CNN. Specifically, LSTM captures the long-term dependency of the data while CNN extracts the time-invariant features. …
Traffic Speed Prediction And Mobility Behavior Analysis Using On-Demand Ride-Hailing Service Data, Jiechao Zhang
Traffic Speed Prediction And Mobility Behavior Analysis Using On-Demand Ride-Hailing Service Data, Jiechao Zhang
Electronic Theses and Dissertations, 2020-
Providing accurate traffic speed prediction is essential for the success of Intelligent Transportation Systems (ITS) deployments. Accurate traffic speed prediction allows traffic managers take proper countermeasures when emergent changes happen in the transportation network. In this thesis, we present a computationally less expensive machine learning approach XGBoost to predict the future travel speed of a selected sub-network in Beijing's transportation network. We perform different experiments for predicting speed in the network from future 1 min to 20 min. We compare the XGBoost approach against other well-known machine learning and statistical models such as linear regression and decision tree, gradient boosting …
Climatic And Topologic Controls On The Complexity Of River Networks, Sevil Ranjbar Moshfeghi
Climatic And Topologic Controls On The Complexity Of River Networks, Sevil Ranjbar Moshfeghi
Electronic Theses and Dissertations, 2020-
The emergence and evolution of channel networks are controlled by the competition between the hillslopes and fluvial processes on the landscape. Investigating the geomorphic and topologic properties of these networks is important for developing predictive models describing the network dynamics under changing environment as well as for quantifying the roles of processes in creating distinct patterns of channel networks. In this dissertation, the response of landscapes to changing climatic forcing via numerical-modeling and field observations was investigated. A new framework was proposed to evaluate the complexity of catchments using two different representations of channel networks. The structural complexity was studied …
Understanding The Socio-Infrastructure Systems During Disaster From Social Media Data, Kamol Chandra Roy
Understanding The Socio-Infrastructure Systems During Disaster From Social Media Data, Kamol Chandra Roy
Electronic Theses and Dissertations, 2020-
Our socio-infrastructure systems are becoming more and more vulnerable due to the increased severity and frequency of extreme events every year. Effective disaster management can minimize the damaging impacts of a disaster to a large extent. The ubiquitous use of social media platforms in GPS enabled smartphones offers a unique opportunity to observe, model, and predict human behavior during a disaster. This dissertation explores the opportunity of using social media data and different modeling techniques towards understanding and managing disaster more dynamically. In this dissertation, we focus on four objectives. First, we develop a method to infer individual evacuation behaviors …
Chemically Stabilized Oil-In-Water Emulsion Separation Using A Custom Aquaporin-Based Polyethersulfone (Pes) Forward Osmosis Membrane System, Annmarie Ricchino
Chemically Stabilized Oil-In-Water Emulsion Separation Using A Custom Aquaporin-Based Polyethersulfone (Pes) Forward Osmosis Membrane System, Annmarie Ricchino
Electronic Theses and Dissertations, 2020-
The stability of oil-in-water emulsions is enhanced by the presence of surfactants in the water, thereby increasing difficulty of remediation. In this study, mineral oil and a standard bilge mix (SBM) were used as model oils for forward osmosis (FO) performance evaluation and two different high-concentration feed solutions (FS) were tested: 10,000 and 100,000 ppm oil/surfactant (9:1 Oil/Surfactant, wt %). It was hypothesized that the charge-charge interactions between the surfactant portion of the micelles and the membrane would play an important role in membrane fouling. Therefore, the effects of both an anionic surfactant (sodium dodecyl sulfate [SDS]) and a nonionic …
Smartphone Sensor-Based Pedestrian Activity Recognition For P2v Communication And Warning System, Dhrubo Hasan Chowdhury
Smartphone Sensor-Based Pedestrian Activity Recognition For P2v Communication And Warning System, Dhrubo Hasan Chowdhury
Electronic Theses and Dissertations, 2020-
The ubiquity of smartphones has made a remarkable influence on everyone's day to day life. Variety of useful built-in sensors provide smartphones with a convenient floor for data collection and analysis. Application development based on the user's location and movement is not a difficult task nowadays. But injuries and deaths due to smartphone-distracted movement on roadways is on the increase. This study explores the capabilities of smartphone inertial sensors for pedestrian activity recognition. Smartphone distracted movements can be predicted from the associated pedestrian's posture, thus inertial sensors can provide effective solution for this specific task. Volunteers were asked to perform …
Removal Of Chemicals Of Emerging Concern And Mass Transfer Modeling In A Nanofiltration Membrane Process, Carlyn Higgins
Removal Of Chemicals Of Emerging Concern And Mass Transfer Modeling In A Nanofiltration Membrane Process, Carlyn Higgins
Electronic Theses and Dissertations, 2020-
An investigation of 1,4-dioxane and enantiomeric ibuprofen mass transfer in a nanofiltration (NF) membrane process has been completed. Pilot-scale experiments using a 267 gallon per minute (gpm) split-feed, center-port NF process treating pH 6.5 groundwater revealed a consistent 12 percent removal of 1,4-dioxane despite the variable feed concentration (180 nanograms per liter (ng/L) to 38,400 ng/L) when the water flux and temperature were held constant. Bench-scale, flat-sheet NF membrane experiments treating pH 4.0 synthetic water displayed a 34.5 to 49.5 percent removal of racemic ibuprofen. Removal values were dependent on feedwater concentration (1 to 1,500 microgram per liter (µg/L)), pH, …
Evaluation Of Safety And Mobility Benefits Of Connected And Automated Vehicles By Considering V2x Technologies, Md Hasibur Rahman
Evaluation Of Safety And Mobility Benefits Of Connected And Automated Vehicles By Considering V2x Technologies, Md Hasibur Rahman
Electronic Theses and Dissertations, 2020-
The recent development in communication technologies facilitates the deployment of connected and automated vehicles (CAV) which are expected to change the future transportation system. CAV technologies enable vehicles to communicate with other vehicles through vehicle-to-vehicle (V2V) communications and the infrastructure through Vehicle-to-infrastructure (V2I) communications. Since the real-world CAV data is not currently available as of today, simulation is the most commonly used platform to evaluate the future V2X system. Although several studies evaluated the effectiveness of CAVs in a small roadway network, there is a lack of studies analyzing the impact of CAVs at the network level by considering both …
Investigation Of Recurrent Neural Network Architectures Based Deep Learning For Short-Term Traffic Speed Forecasting, Armando Fandango
Investigation Of Recurrent Neural Network Architectures Based Deep Learning For Short-Term Traffic Speed Forecasting, Armando Fandango
Electronic Theses and Dissertations, 2020-
The availability of large tranches of data and its influence on traffic flow, make the problem of short-term traffic speed prediction very complex in nature. For more than 40 years, various statistical time series forecasting methods have been applied for traffic speed prediction, and in the last 20 years, machine learning-based methods have gained prevalence. However, more recently, recurrent neural network (RNN) based methods have emerged to show better results for traffic speed prediction\cite{tian2015pred, zhao2017lstm,fu2017usin,chen2016long,dai2017deep,dai2019deep, kanestrom2017traf,shao2016traf,jia2017traf}. As the interest in applying RNN models to the traffic speed predictions started to grow, we found some critical and important unanswered questions with …
Improving Traffic Safety And Efficiency By Adaptive Signal Control Systems Based On Deep Reinforcement Learning, Yaobang Gong
Improving Traffic Safety And Efficiency By Adaptive Signal Control Systems Based On Deep Reinforcement Learning, Yaobang Gong
Electronic Theses and Dissertations, 2020-
As one of the most important Active Traffic Management strategies, Adaptive Traffic Signal Control (ATSC) helps improve traffic operation of signalized arterials and urban roads by adjusting the signal timing to accommodate real-time traffic conditions. Recently, with the rapid development of artificial intelligence, many researchers have employed deep reinforcement learning (DRL) algorithms to develop ATSCs. However, most of them are not practice-ready. The reasons are two-fold: first, they are not developed based on real-world traffic dynamics and most of them require the complete information of the entire traffic system. Second, their impact on traffic safety is always a concern by …