Engineering Commons^™

Deep Reinforcement Learning-Based Project Prioritization For Rapid Post-Disaster Recovery Of Transportation Infrastructure Systems, Yongcheol Lee, Kunhee Choi Ph.D, Pedram Ghannad

Publications

Among various natural hazards that threaten transportation infrastructure, flooding represents a major hazard in Region 6's states to roadways as it challenges their design, operation, efficiency, and safety. The catastrophic flooding disaster event generally leads to massive obstruction of traffic, direct damage to highway/bridge structures/pavement, and indirect damages to economic activities and regional communities that may cause loss of many lives. After disasters strike, reconstruction and maintenance of an enormous number of damaged transportation infrastructure systems require each DOT to take extremely expensive and long-term processes. In addition, planning and organizing post-disaster reconstruction and maintenance projects of transportation infrastructures are …

Enterprise Environment Modeling For Penetration Testing On The Openstack Virtualization Platform, Vincent Karovic Jr., Jakub Bartalos, Vincent Karovic, Michal Gregus

Journal of Global Business Insights

The article presents the design of a model environment for penetration testing of an organization using virtualization. The need for this model was based on the constantly increasing requirements for the security of information systems, both in legal terms and in accordance with international security standards. The model was created based on a specific team from the unnamed company. The virtual working environment offered the same functions as the physical environment. The virtual working environment was created in OpenStack and tested with a Linux distribution Kali Linux. We demonstrated that the virtual environment is functional and its security testable. Virtualizing …

A Cdzntese Gamma Spectrometer Trained By Deep Convolutional Neural Network For Radioisotope Identification, Sandeep K. Chaudhuri, Joshua W. Kleppinger, Ritwik Nag, Kaushik Roy, Rojina Panta, Forest Agostinelli, Amit Sheth, Utpal N. Roy, Ralph B. James, Krishna C. Mandal

Publications

We report the implementation of a deep convolutional neural network to train a high-resolution room-temperature CdZnTeSe based gamma ray spectrometer for accurate and precise determination of gamma ray energies for radioisotope identification. The prototype learned spectrometer consists of a NI PCI 5122 fast digitizer connected to a pre-amplifier to recognize spectral features in a sequence of data. We used simulated preamplifier pulses that resemble actual data for various gamma photon energies to train a CNN on the equivalent of 90 seconds worth of data and validated it on 10 seconds worth of simulated data.

Deep Learning-Based Penetration Depth Prediction In Al/Cu Laser Welding Using Spectrometer Signal And Ccd Image, Sanghoon Kang, Minjung Kang, Yong Hoon Jang, Cheolhee Kim

Mechanical and Materials Engineering Faculty Publications and Presentations

In the laser welding of thin Al/Cu sheets, proper penetration depth and wide interface bead width ensure stable joint strength and low electrical conductance. In this study, we proposed deep learning models to predict the penetration depth. The inputs for the prediction models were 500 Hz-sampled low-cost charge-coupled device (CCD) camera images and 100 Hz-sampled spectral signals. The output was the penetration depth estimated from the keyhole depth measured coaxially using optical coherence tomography. A unisensor model using a CCD image and a multisensor model using a CCD image and the spectrometer signal were proposed in this study. The input …

Evaluation Of In-Cab Air Quality For Nonroad Diesel Construction Equipment, Phil Lewis, Sherif El Khouly, Adam Mayer, Jeremy Johnson

The Professional Constructor

Previous research indicates that air quality near the cabs of nonroad diesel equipment may exceed recommended exposure limits for certain pollutants. The objective of this case study was to collect and analyze air pollutant data near the cabs of nonroad diesel equipment while performing real world activities. Using state-of-the-art instrumentation, the research team conducted 24 tests on nine different items of nonroad equipment. The team collected data related to pollutant concentrations of carbon monoxide, carbon dioxide, nitric oxide, nitrogen dioxide, particulate matter, and black carbon. Average concentrations of carbon monoxide and nitric oxide did not exceed published exposure limits on …

Understanding And Avoiding Ai Failures: A Practical Guide, Robert Williams, Roman Yampolskiy

Faculty and Staff Scholarship

As AI technologies increase in capability and ubiquity, AI accidents are becoming more common. Based on normal accident theory, high reliability theory, and open systems theory, we create a framework for understanding the risks associated with AI applications. This framework is designed to direct attention to pertinent system properties without requiring unwieldy amounts of accuracy. In addition, we also use AI safety principles to quantify the unique risks of increased intelligence and human-like qualities in AI. Together, these two fields give a more complete picture of the risks of contemporary AI. By focusing on system properties near accidents instead of …

Potential Impact Of Contour Bunds On Diclofenac Removal For Stormwater Control In Rangeland Applications, Braden Alan Whitehead

Master's Theses

Diclofenac (DCF) and other emerging contaminants have been found in environments worldwide. These contaminants may enter the environment due to the application of treated wastewater, biosolids and direct excrement related to veterinary application. Leakage from the soils toward the groundwater is largely controlled by sorption and microbial degradation. Most studies on the environmental fate of DCF have focused on degradation during wastewater treatment processes. However, little is known about their behavior in soil. In this study, the combined effect of adsorption and degradation of diclofenac has been investigated in four (4) 24 ft³ agricultural soil-filled beds designed to mimic …

A Study Of Non-Computing Majors' Growth Mindset, Self-Efficacy And Perceived Cs Relevance In Cs1, Jae Hyuk Yoo

Master's Theses

As the demand for programming skills in today’s job market is rapidly increasing for disciplines outside of computing, CS courses have experienced spikes in enrollment for non-majors. Students in disciplines including art, design and biological sciences are now often required to take introductory CS courses. Previous research has shown the role of growth mindset, self-efficacy and relevance in student success within CS but such metrics are largely unknown for non-majors. In this thesis, we surveyed non-majors in CS1 at Cal Poly, San Luis Obispo during the early and late weeks of the quarter to gain insights on their growth mindset, …

Subnational Map Of Poverty Generated From Remote-Sensing Data In Africa: Using Machine Learning Models And Advanced Regression Methods For Poverty Estimation, Lionel N. Hanke

Master's Theses

According to the 2020 poverty estimates from the World Bank, it is estimated that 9.1% - 9.4% of the global population lived on less than $1.90 per day. It is estimated that the Covid-19 pandemic further aggravated the issue by pushing more than 1% of the global population below the international poverty line of $1.90 per day (WorldBank, 2020). To provide help and formulate effective measures, poverty needs to be located as exact as possible. For this purpose, it was investigated whether regression methods with aggregated remote-sensing data could be used to estimate poverty in Africa. Therefore, five distinct regression …

Impossibility Results In Ai: A Survey, Mario Brcic, Roman Yampolskiy

Faculty and Staff Scholarship

An impossibility theorem demonstrates that a particular problem or set of problems cannot be solved as described in the claim. Such theorems put limits on what is possible to do concerning artificial intelligence, especially the super-intelligent one. As such, these results serve as guidelines, reminders, and warnings to AI safety, AI policy, and governance researchers. These might enable solutions to some long-standing questions in the form of formalizing theories in the framework of constraint satisfaction without committing to one option. In this paper, we have categorized impossibility theorems applicable to the domain of AI into five categories: deduction, indistinguishability, induction, …

Death In Genetic Algorithms, Micah Burkhardt, Roman Yampolskiy

Faculty and Staff Scholarship

Death has long been overlooked in evolutionary algorithms. Recent research has shown that death (when applied properly) can benefit the overall fitness of a population and can outperform sub-sections of a population that are “immortal” when allowed to evolve together in an environment [1]. In this paper, we strive to experimentally determine whether death is an adapted trait and whether this adaptation can be used to enhance our implementations of conventional genetic algorithms. Using some of the most widely accepted evolutionary death and aging theories, we observed that senescent death (in various forms) can lower the total run-time of genetic …

Electrostatic Flocking Of Salt-Treated Microfibers And Nanofiber Yarns For Regenerative Engineering, Alec Mccarthy, Kossi Loic M. Avegnon, Phil A. Holubeck, Demi Brown, Anik Karan, Navatha Shree Sharma, Johnson V. John, Shelbie Weihs, Jazmin Ley, Jingwei Xie

Mechanical Engineering Faculty Publications

Electrostatic flocking is a textile technology that employs a Coulombic driving force to launch short fibers from a charging source towards an adhesive-covered substrate, resulting in a dense array of aligned fibers perpendicular to the substrate. However, electrostatic flocking of insulative polymeric fibers remains a challenge due to their insufficient charge accumulation. We report a facile method to flock electrostatically insulative poly(ε-caprolactone) (PCL) microfibers (MFs) and electrospun PCL nanofiber yarns (NFYs) by incorporating NaCl during pre-flock processing. Both MF and NFY were evaluated for flock functionality, mechanical properties, and biological responses. To demonstrate this platform's diverse applications, standalone flocked NFY …

Analysis Of The Vertical Movement Of Active Gnss Stations As A Result Of Semidiurnal Tides, Rose Pearson, Eugen Niculae

Conference papers

Ireland is subject to the constant effects and influence of semidiurnal tides. Western coastal regions are exposed to tidal ranges up to and exceeding five metres, consequentially introducing varied water volumes with temporal intervals. In addition, the Earth is elastic in composition, resulting in morphing and warping at the hands of celestial and oceanic forces.

This study looked at Online Precise Point Positioning (PPP) service to accurately monitor the vertical movement of coastal lands. In addition, GNSS Static Post-processing was conducted to discern which method of the global navigation satellite system (GNSS) processing is best for detecting VLM (vertical land …

Vacuum Infusion Of Composites: Durability Of Hybrid Large Area Additive Tooling For Vacuum Infusion Of Composites, Nathan Northrup, Jason Weaver, Andy R. George

Faculty Publications

The durability of a hybrid large area additively manufactured fiberglass ABS mold for vacuum infusion of composites was evaluated. The validation was done by designing and fabricating a mold for a custom test artifact and analyzing the surface geometry over the course of multiple infusions until tool failure. After printing and machining, the mold required a sealer to maintain vacuum integrity. The mold was able to produce 10 parts successfully before the sealed tool surface began to tangibly roughen, resulting in increased difficulty of demolding and a rougher surface finish. After the 14th infusion, the part required destructive force to …

Prefabrication In Buildings With Focus On Emerging Mep Rack Systems, Mark Daniels, M.G. Matt Syal

The Professional Constructor

The growth in technology and automation has influenced the construction industry to explore prefabrication alternatives in building design and construction. In addition, the shortage of skilled labor is accelerating the push for the adoption of prefabrication in building industry. This paper provides an overview of the present construction market and labor trends and summarizes various levels and categories of prefabrication. It then provides detailed information on an emerging MEP prefabricated solution known as the MEP rack systems. The implementation of the MEP rack systems is discussed with the help of a hospital case study project. It concludes with the discussion …

Case Study Of Using Unmanned Aircraft Systems To Support Bridge Inspections, Joseph M. Burgett, Gurcan Comert

The Professional Constructor

This paper presents the results of a case study conducted to evaluate the potential benefit of unmanned aircraft systems (UAS), commonly referred to as drones, as a tool to improve the bridge inspection workflow. The study conducted two experiments to determine how well deficiencies could be detected using a UAS. Both experiments were conducted using the same test bridge. The first experiment was carried out by the bridge inspection engineers (BIEs), who had previously inspected the bridge using traditional methods. They used the drone to search for inspection points identified in the inspection report. The second experiment was conducted by …

Stick Built Vs. Panelize Wall/Truss Framing For New Home Construction: A Time Study Labor Comparison., Eric A. Holt, Jim Anzlovar, Alexander Welsh

The Professional Constructor

Due to many trends in the construction industry (material cost increase, labor shortages, supply chain issues, pandemic, market demand outpacing supply), the homebuilding industry is looking for alternative ways to frame homes. In response to the National Housing Endowment (NHE) Request for Proposal, the researchers reviewed the literature on the housing market’s current state regarding the scale and scope of the skilled construction framers shortage and the current market share of single-family framing method; stick-built vs. panelization. Working with industry part ners, the team analyzed time studies for multiple new home builds. It was found that panelized wall framing systems …

Minority And Female Participation In Construction Industry Apprenticeship Programs, Richard Bruce, Aaron Sauer, Patrick Sells, Curtis Bradford

The Professional Constructor

According to the U.S. Bureau of Labor Statistic’s Current Population Survey, nearly 90 percent of the 10.7 million people employed in the construction industry are white males (2021). This statistic will remain unchanged unless more minorities and females are recruited into the industry. For craft workers, a primary recruitment mechanism is the registered apprenticeship program. This study analyzes the U.S. Department of Labor’s Registered Apprenticeship Database (RAPIDs) from 2000 to 2019 to identify trends for new apprentices. The study found that there was no change in the proportion of new female apprentices in the previous 20 years and no change …

Carbon Dioxide Uptakes By Acetylene By-Products Through Gas–Solid And Gas–Solid–Liquid Reactions, Maisa El Gamal, Ameera Mohammad, Suhaib Hameedi, Hadeel Alzawahreh

All Works

In this work, carbon dioxide uptake value by acetylene by-products was evaluated through two types of carbonation reactions. In the first reaction, solid acetylene by-products were reacted with a simulated effluent CO2 gas (10% CO2 and 90% air) and the maximum uptake value of carbon dioxide per unit mass of reacted solids was calculated. In the second reaction, the mixed solid acetylene by-product with distilled water at a specific mass to volume ratio was reacted with the same effluent CO2 gas to compare the maximum CO2 uptake value with the first reaction. It was found that a superior CO2 uptake …

Date Palm Waste Pyrolysis Into Biochar For Carbon Dioxide Adsorption, Imen Ben Salem, Mariam Badawi Saleh, Jibran Iqbal, Maisa El Gamal, Suhaib Hameed

All Works

Mitigation of CO2 is a very popular research currently, it is ultimately beneficial to find new ways that are sustainable, low cost and gas emission friendly. Therefore, with biochar’s characteristics and properties it has great potential to be used as a CO2 capture and storage media. The objectives of reducing palm waste by using the low-cost, sustainable method for reducing and storing CO2, characterize the DPL biochar through FTIR, XRD, SEM, EDX, and then evaluate the efficiency of the date palm leaf waste biochar in adsorbing CO2 through the Gas–Solid analyzer technology. Date palm leaf was set in pyrolysis process …

We Are On The Way: Analysis Of On-Demand Ride-Hailing Systems, Guiyun Feng, Guangwen Kong, Zizhuo Wang

Research Collection Lee Kong Chian School Of Business

Problem definition: Recently, there has been a rapid rise of on-demand ride-hailing platforms, such as Uber and Didi, which allow passengers with smartphones to submit trip requests and match them to drivers based on their locations and drivers’ availability. This increased demand has raised questions about how such a new matching mechanism will affect the efficiency of the transportation system—in particular, whether it will help reduce passengers’ average waiting time compared with traditional street-hailing systems. Academic/practical relevance: The on-demand ride-hailing problem has gained much academic interest recently. The results we find in the ride-hailing system have a significant …

Cell-Permeable Succinate Increases Mitochondrial Membrane Potential And Glycolysis In Leigh Syndrome Patient Fibroblasts, Ajibola B. Bakare, Raj R. Rao, Shilpa Iyer

Biomedical Engineering Faculty Publications and Presentations

Mitochondrial disorders represent a large group of severe genetic disorders mainly impacting organ systems with high energy requirements. Leigh syndrome (LS) is a classic example of a mitochondrial disorder resulting from pathogenic mutations that disrupt oxidative phosphorylation capacities. Currently, evidence-based therapy directed towards treating LS is sparse. Recently, the cell-permeant substrates responsible for regulating the electron transport chain have gained attention as therapeutic agents for mitochondrial diseases. We explored the therapeutic effects of introducing tricarboxylic acid cycle (TCA) intermediate substrate, succinate, as a cell-permeable prodrug NV118, to alleviate some of the mitochondrial dysfunction in LS. The results suggest that a …

Detecting Driver Drowsiness With Multi-Sensor Data Fusion Combined With Machine Learning, Hovannes Kulhandjian

Mineta Transportation Institute

According to the National Highway Traffic Safety Administration, in 2017 drowsy driving resulted in 50,000 injuries across 91,000 police-reported accidents, as well as almost 800 deaths. Through the application of visual and radar sensors combined with machine learning, this research developed a drowsy driver detection system aimed to prevent potentially fatal accidents. The working prototype of Advanced Driver Assistance Systems can be installed in present-day vehicles to detect drowsy drivers with over 95% accuracy. It integrates two types of visual surveillance to examine the driver for signs of drowsiness. A camera is used to monitor the driver’s eyes, mouth and …

Network Modeling Of Hurricane Evacuation Using Data-Driven Demand And Incident-Induced Capacity Loss Models, Yuan Zhu, Kaan Ozbay, Kun Xie, Hong Yang, Ender Foruk Morgul

Civil & Environmental Engineering Faculty Publications

The development of a hurricane evacuation simulation model is a crucial task in emergency management and planning. Two major issues affect the reliability of an evacuation model: one is estimations of evacuation traffic based on socioeconomic characteristics, and the other is capacity change and its influence on evacuation outcome due to traffic incidents in the context of hurricanes. Both issues can impact the effectiveness of emergency planning in terms of evacuation order issuance, and evacuation route planning. The proposed research aims to investigate the demand and supply modeling in the context of hurricane evacuations. This methodology created three scenarios for …

Routing Policy Choice Prediction In A Stochastic Network: Recursive Model And Solution Algorithm, Tien Mai, Xinlian Yu, Song Gao, Emma Frejinger

Research Collection School Of Computing and Information Systems

We propose a Recursive Logit (STD-RL) model for routing policy choice in a stochastic time-dependent (STD) network, where a routing policy is a mapping from states to actions on which link to take next, and a state is defined by node, time and information. A routing policy encapsulates travelers’ adaptation to revealed traffic conditions when making route choices. The STD-RL model circumvents choice set generation, a procedure with known issues related to estimation and prediction. In a given state, travelers make their link choice maximizing the sum of the utility of the outgoing link and the expected maximum utility until …

A Learning And Optimization Framework For Collaborative Urban Delivery Problems With Alliances, Jingfeng Yang, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The emergence of e-Commerce imposes a tremendous strain on urban logistics which in turn raises concerns on environmental sustainability if not performed efficiently. While large logistics service providers (LSPs) can perform fulfillment sustainably as they operate extensive logistic networks, last-mile logistics are typically performed by small LSPs who need to form alliances to reduce delivery costs and improve efficiency, and to compete with large players. In this paper, we consider a multi-alliance multi-depot pickup and delivery problem with time windows (MAD-PDPTW) and formulate it as a mixed-integer programming (MIP) model. To cope with large-scale problem instances, we propose a two-stage …

The Empathetic Car: Exploring Emotion Inference Via Driver Behaviour And Traffic Context, Shu Liu, Kevin Koch, Zimu Zhou, Simon Foll, Xiaoxi He, Tina Menke, Elgar Fleisch, Felix Wortmann

Research Collection School Of Computing and Information Systems

An empathetic car that is capable of reading the driver’s emotions has been envisioned by many car manufacturers. Emotion inference enables in-vehicle applications to improve driver comfort, well-being, and safety. Available emotion inference approaches use physiological, facial, and speech-related data to infer emotions during driving trips. However, existing solutions have two major limitations: Relying on sensors that are not built into the vehicle restricts emotion inference to those people leveraging corresponding devices (e.g., smartwatches). Relying on modalities such as facial expressions and speech raises privacy concerns. By contrast, researchers in mobile health have been able to infer affective states (e.g., …

Characterization Of Anisotropic Materials Using Scattered Field Measurements, Hirsch M. Chizever

Theses and Dissertations

This research uses monostatic far-zone scattered field measurements to estimate the permittivity of biaxial materials at X-Band. Utilizing Radar Cross Section (RCS) measurement techniques, this effort examines the efficacy of whole-sample TEM illumination in the estimation of anisotropic permittivity, in contrast with traditional subsample illumination methods. The research examines the impact that dielectric supports have on measurement error and uncertainty in permittivity estimates. Following an incremental approach, the research first demonstrates successful estimation of permittivity for isotropic spheres followed by a Teflon isotropic cube. Finally, the method is applied to uniaxial and biaxial cubes whose anisotropic permittivity is validated through …

Physically Unclonable Characteristics For Verification Of Transmon-Based Quantum Computers, Leleia A. Hsia

Theses and Dissertations

Future national security can be strengthened by verifying and securing the quantum computing supply chain. This dissertation proposes physically unclonable characteristics (PUCs), a method of quantum hardware verification inspired by classical physically unclonable functions, for future application to quantum processors implemented with transmon qubits. Qualitative and quantitative analysis is provided on the development of PUCs, including identifying qubit characteristics and qubit discrimination methods suitable for PUCs. Characteristics tested on IBM Quantum services include T1 and T2 coherence times, single-qubit and multi-qubit gate error rates, readout error rates, quantum process tomography metrics, and random benchmarking metrics. Results show that non-parametric qubit …

New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams

Theses and Dissertations

A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …