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Title: The Effect of Salmonella Enteritidis on the Thermal Properties of Egg Albumen and Yolk
Creator: Chadha, Isha
Date: 2011-11-27, 2011-12
Description: Salmonella-inoculated and uninoculated fresh eggs were microwave processed to achieve pasteurization. However, quality degradation was...
Show moreSalmonella-inoculated and uninoculated fresh eggs were microwave processed to achieve pasteurization. However, quality degradation was observed in the albumen of inoculated eggs but not in the uninoculated eggs although the processing was the same. Previous work showed that dielectric properties of egg albumen and yolk do not change in the presence of the bacteria. A new hypothesis was therefore proposed that heat capacity is affected by its presence. If an egg has a lowered heat capacity it will become hotter for a given amount of microwave energy input than eggs having normal heat capacities. The goal of the experiments was to determine whether Salmonella at varying concentrations and different incubation times affects the temperature-dependent thermal properties of egg albumen and yolk during in-shell growth. Although the main concern was Salmonella’s effect on the heat capacity of albumen, the equipment used could measure thermal conductivity as well and measurements on yolk were included for completeness. The thermal properties of both egg albumen and yolk were measured by the KD2 Pro thermal properties analyzer (Decagon Instruments, Pullman, WA) via the supplied 30 mm dual-needle sensor. Variables were temperature (7oC, 30oC, 40oC, 50oC, 55oC and 60oC), bacterial inoculum (0, 103, 106, 108 cfu/ml) and incubation time (0 or 30 hours). The measurements showed no significant difference in thermal properties between inoculated and uninoculated samples of egg albumen and yolk regardless of change in temperature, bacterial concentration and incubation period. The absence of an effect on either the dielectric (previous study) or thermal (present study) parameters by the presence of Salmonella leaves unexplained the quality differences between similarly processed inoculated and uninoculated eggs. A biochemical explanation based on the interaction between metabolic byproducts and egg proteins, affecting how they denature, is a topic for future research.
M.S. in Food Safety and Technology, December 2011
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Title: RATE AND TEMPERATURE DEPENDENT MECHANICAL BEHAVIOR AND MODELING OF AL-CU ALLOY SYSTEM
Creator: Tran, Henry
Date: 2011-12-19, 2011-12
Description: Deformation of materials in army applications such as fragment impact, projectile penetration and air blast/shock waves involves high strain...
Show moreDeformation of materials in army applications such as fragment impact, projectile penetration and air blast/shock waves involves high strain rates, large strains, high pressures and rapid changes in temperature, where overall performance ultimately depends on the evolution of flow stress, failure initiation and propagation, generally in the form of adiabatic shear banding (ASB), under these severe loading conditions. Some of 2XXX series aluminum-copper (Al-Cu) alloys such as Al 2519-T87 have been successfully used in Lightweight Armored Vehicles in the U.S. Army because of their good ballistic properties. More recently, an Al-Cu-Mg-Ag alloy designated as Al 2139-T8 has emerged in 2004 as a strong candidate in damage critical applications with higher strength and high-strain-rate performance than its predecessors. Its better ballistic performance is believed to be due to the underlying microstructure. The objective of this study is to investigate mechanical and deformation behavior of Al-Cu material system to develop a fundamental understanding of the effect of composition and microstructural features on overall dynamic behavior. To this end, a systematic approach is adopted to start from single crystal Al and move towards polycrystalline Al, then Al-Cu, and all the way to Al-Cu-Mg-Ag system. Current thesis study constitutes a part of this ongoing work and, therefore, only covers single crystal Al ([001] and [111] directions), polycrystalline Al, and Al-0.1%Cu. Compressive mechanical response of each one of these materials has been investigated in a wide strain rate range that covers quasi-static (from 10-4 to 100 s-1) and dynamic (from 102 to 104 s-1) strain rate regimes. With the exception of single crystal Al (because of limited supplies), additional experiments have been conducted at 120C and 220C within the same strain rate range to understand their thermal softening behavior in varying strain rate regimes. Based on and driven by experimental results, a modified Johnson-Cook model is proposed to describe their rate and temperature dependent constitutive behavior. Finally, in order to investigate susceptibility of these materials and varying microstructures to adiabatic shear localization the two specimen geometries, namely “top hat” and “shear-compression specimen”, have been evaluated. In this evaluation, emphasis is placed upon reliable quantification of strain field within the gage section. Shear compression specimen has been identified to be the best candidate to use in future studies that will explore the tendency of each one of these materials to failure by adiabatic shear banding.
M.S. in Mechanical and Aerospace Engineering, December 2011
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Title: Development of a novel ultra-nanocrystalline diamond (UNCD) based photocathode and exploration of its emission mechanisms
Creator: Chen, Gongxiaohui
Date: 2020
Description: High quality electron sources are one of the most commonly used probing tools used for the study of materials. Photoemission cathodes, capable...
Show moreHigh quality electron sources are one of the most commonly used probing tools used for the study of materials. Photoemission cathodes, capable of producing ultra-short and ultra-high intensity beams, are a key component of accelerator based light sources and some microscopy tools. High quantum efficiency (QE), low intrinsic emittance, and long lifetime (or good vacuum tolerance) are three of the most critical features for a photocathode; however, these are difficult to achieve simultaneously and trade-offs need to be made for different applications. In this work, a novel semi-metallic material of nitrogen-incorporated ultrananocrystalline diamond ((N)UNCD) has been studied as a photocathode. (N)UNCD has many of the unique diamond properties, such as low intrinsic as-grown surface roughness (at the order of 10~nm) due to its nanometer scale crystalline size, relatively long lifetime in air, high electrical conductivity with nitrogen doping, and potentially high QE performance due to the high grain boundary densities where most of electron emission occurs. High contrast interference of incident and reflected radiation within (N)UNCD thin films was observed, and this feature allows fast thickness determination based on an analytical optics methodology. This method has been extended to study and calculate the etching rates of two commonly used O$_2$ and H$_2$ plasmas for use with future (N)UNCD microfabrication processes. The mean transverse energy (MTE) of (N)UNCD was determined over a wide UV range in a DC photogun. Unique MTE behavior was observed; it did not scale with photon energy unlike most metals. This behavior is associated with emission from spatially-confined states in the graphite regions (with low electron effective mass) between the diamond grains. Such behavior suggests that beam brightness many be increased by the simple mechanism of increasing the photon energy so that the QE increases, while the MTE remains constant.Two individual (N)UNCD photocathodes synthesized two years apart have been characterized in a realistic RF photogun. Both the QE and intrinsic emittance were characterized. It was found that the QE of $\sim4.0\times 10^{-4}$, is more than an order of magnitude higher than that of most commonly used metal cathodes (such as Cu and Nb). The intrinsic emittance (0.997~$\mu$m/mm) is comparable to that of photocathodes now deployed in research accelerators. The most impressive feature is the excellent robustness of (N)UNCD material; there was no evidence of performance degradation, even after years-long atmospheric exposure. The results of this work demonstrate that a cathode made of (N)UNCD material is able to achieve balanced performance of three of the primary critical photocathode figures-of-merit.
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Title: Characterization of Radiation Damage Effects in High-Energy Neutrino Target Graphite using Low-Energy Ions
Creator: Burleigh, Abraham C.
Date: 2023
Description: Exposure of graphite targets to high intensity proton beams at neutrino production facilities causes changes in the target material that can...
Show moreExposure of graphite targets to high intensity proton beams at neutrino production facilities causes changes in the target material that can result in a shortened operation lifetime. The dominant factors in this process are currently thought to be mechanical in nature resulting primarily from microstructural effects that lead to thermal and structural changes in bulk material properties. As currently planned beam facilities with increased proton energy and intensity begin to come online it will be important to thoroughly understand these processes, and ideally to be able to predict the effects of new beam designs on target properties. Direct analysis of targets exposed to existing high-energy proton beams is complicated by several factors, such as very limited access to proton beam facilities, high associated costs, irradiation times on the order of months, and the resulting radioactivity of irradiated samples that requires special facilities for post-irradiation examination. Much of the existing literature concerning irradiation damage in graphite has been focused on the needs of the nuclear engineering community, however high-energy proton targets operate in a much different environment. In comparison to graphite irradiated in a nuclear reactor, graphite used in proton beam targets receives a higher dose rate, have greater gas production, and experience short irradiation pulses as opposed to continuous irradiation. Low-energy ion irradiation offers a method of inducing similar levels of radiation damage to high-energy protons while avoiding many of the difficulties and limitations associated with high-energy proton beams and the corresponding activated specimen testing. My research described in this thesis focused on investigating how low-energy ion irradiation could be used to induce the same or similar types of microstructural alteration and mechanical property degradation as that seen in high-energy neutrino production target graphites by varying damage levels and irradiation temperatures prior to post-irradiation characterization.
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Title: Investigation of Electrochemical Properties and Fabrication of Lithium- and Sodium-ion Batteries
Creator: Chen, Changlong
Date: 2023
Description: Since the successful commercialization of Li-ion battery, the opportunity in creating a sustainable world with evenly-distributed energy...
Show moreSince the successful commercialization of Li-ion battery, the opportunity in creating a sustainable world with evenly-distributed energy supply and less environmental concerns has been significantly increased. This triggered tremendous efforts from both academy and industry in building better Li-ion batteries. Along the research and development over past 30 years, the performance of current Li-ion batteries has met some basic needs in our daily life, such as powering electronic devices and electric vehicles for a short time, while superior capabilities, like extended operating life, stable function under extreme circumstances, is always pursued. Under the pressure from these ever-growing demands, the corresponding Li-ion battery production is faced with a lot of new challenges. Regarding the battery production, the present Li-ion battery manufacturing heavily relies on the use of certain repo-toxic solvent, N-methyl-2-pyrrolidone (NMP), which arouses safety concerns to human health. In the pursuit of a higher energy density, silicon anode, bearing ten times the gravimetric capacity of commercially-dominating graphite anode, is intensively studied as the anode material for next-generation Li-ion batteries. However, its degradation mechanism is not completely revealed yet, which makes the methods of effective optimizations hard to be developed. In terms of the cost control, Na-ion batteries have been revisited and have received extra attention in the past decade owing to the abundance in raw materials and the high compatibility with state-of-art Li-ion industry while blank space in understanding primary electrochemical properties, such as impedance signals, has not been totally filled. This will also cause the misunderstandings in such interpretation and, thereby, postpone the pace of relevant advancement. Targeting these proposed issues, this thesis provides a series of feasible solutions via careful investigation and rational analysis with the aid of various advanced (non)electrochemical techniques, which offers a few unique perspectives in studying Li- and Na-ion batteries, and further facilitates the following research and development in the corresponding communities.
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Title: Effect of Phosphorus Additions on Polycrystalline Ni-base Superalloys
Creator: Li, Linhan
Date: 2020
Description: In recent years, advanced polycrystalline Ni-base superalloys have been developed with elevated levels of γ′ forming elements and high level...
Show moreIn recent years, advanced polycrystalline Ni-base superalloys have been developed with elevated levels of γ′ forming elements and high level of refractory elements as solid-solution strengtheners in an effort to extend the temperature capability. Moreover, the properties of the grain boundaries become more important and this necessitates the need to study of effects of minor additions of interstitial P for grain structure optimization. Due to the increased level of refractory elements employed, powder-processed Ni-base superalloys tend to have a high propensity to form Topologically Close-Packed (TCP) phases, which was found to be further promoted by the addition of P. A systematic study of the phase stability of high refractory content powder-processed Ni-base superalloys with three levels of P additions revealed an increased tendency to form Laves phase as a function of P additions. Additions of P were discovered to not only depress the incipient melting temperature to stabilize the eutectic Laves phase, but also promote Laves phase formation during the aging heat treatment and the following isothermal exposure. During the thermal exposure, excessive formation of Laves phase promoted the formation of a basket-weave structure comprised of an intertwined mixture of Laves and Sigma phase. The stabilization of the Laves phase structure due to P additions was found to be consistent with Density Functional Theory (DFT) calculations and could be rationalized through structure maps that relate the valence electron concentration and relative size differences. Additionally, a variation of grain structure obtained via either a sub-solvus or super-solvus solution heat treatment was noted to some extent vary the P segregation level at high-angle grain boundaries, thereby affecting the phase stability. For a sub-solvus solutioned grain structure that possessed a high length density of high-angle grain boundaries, the Laves phase formation was depressed for alloys with a low level of P addition. However, the phase stability variation associated with Laves phase formation was moderate when high concentrations of P were present. The effect of P addition on the γ′ microstructure variation is limited, which was confirmed by microstructure observations as well as through the short-term 0.6%-strain stress relaxation tests at high temperature. Heat treatment variations to modify the secondary and tertiary γ′ microstructures were discovered to exert a much more significant influence on the 0.6%-strain stress relaxation behavior. When a higher initial strain of 2% was applied, the stress relaxation behavior of the powder-processed Ni-base superalloys was found to be microstructure independent. The creep ductility of Waspaloy was determined to be notably reduced by the P additions due to the enhanced precipitation of M23C6 carbide at the grain boundaries. Excessive precipitation of M23C6 carbide increased the likelihood of brittle fracture when tested under low temperature/high stress creep conditions. However, the P addition as well as the excessive precipitation of M23C6 carbide did not impact the creep behavior as the dominant deformation was transgranular in nature when tested under high temperature/low stress conditions.
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Title: Nanopore sensing for environmental and biomarker analysis
Creator: Arora, Pearl
Date: 2024
Description: Nanopore stochastic sensing is a powerful analytical tool for detecting target molecules through a nanoscale pore. The analyte and electrolyte...
Show moreNanopore stochastic sensing is a powerful analytical tool for detecting target molecules through a nanoscale pore. The analyte and electrolyte ions are subjected to a voltage bias which drives them to translocate through the nanopore, resulting in disruptions in the ionic current. These disruptions are translated to blockage events which can serve as a signature of the analyte. Owing to its unique features of single-molecule and label-free sensing, nanopore technique has been exploited in a wide array of applications such as detection of metal ions, proteins, DNA, microRNA, toxic agents etc. In this dissertation, projects showcasing nanopore’s sensing capability of different biomarkers and in the detection of a wide range of target molecules based on non-covalent interactions are presented. Particularly in the first two projects, nanopore detection of ferric ions relevant to environmental regulation as well as a biomarker for human health and a miRNA-based biomarker for oral cancer and oral related diseases are summarized. Ferric ions, which are benign if present in balanced quantities but can be toxic otherwise, are detected by using an engineered multifunctional nanopore and a chelating organophosphonic acid ligand. The chelate complex formed after ferric ions bind to ligand gives significantly different event signatures than the free ligand in the solution enabling ferric ion detection. Even in the presence of interfering ions, the ferric ions could be recognized easily because of the conformational changes brought in the nanopore lumen by the interaction of the interfering metal ions with the His-tags of the nanopore which in turn resulted in variations in the characteristics of blocking events. In the second project, miR31, an oral cancer biomarker, is selectively detected with the help of an engineered nanopore, and a DNA based probe. Several probes with variations in length, composition and position of the overhangs or probes with no overhangs were compared and studied as the probes play a crucial role in capturing the target of interest with high specificity. Our strategically designed probe emerged as the most effective in capturing the target even in presence of large background from human saliva samples and enhanced the sensitivity of the system. In the first two projects, nanopores are utilized for selective and specific detection of certain target molecules. However, in order to analyze diverse range of analytes, numerous sensing systems have to be constructed which can be a time-consuming and challenging task. To circumvent this limitation, in the third project, diverse recognition sites based on various non-covalent interactions are incorporated into the α-hemolysin protein pore to achieve detection of not just a single analyte but broad category of molecules such as cations, anions, aromatic and hydrophobic compounds.
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Title: Using Niobium surface encapsulation and Rhenium to enhance the coherence of superconducting devices
Creator: Crisa, Francesco
Date: 2024
Description: In recent decades, the scientific community has grappled with escalating complexity, necessitating a more advanced tool capable of tackling...
Show moreIn recent decades, the scientific community has grappled with escalating complexity, necessitating a more advanced tool capable of tackling increasingly intricate simulations beyond the capabilities of classical computers. This tool, known as a quantum computer, features processors composed of individual units termed qubits. While various methods exist for constructing qubits, superconducting circuits have emerged as a leading approach, owing to their parallels with semiconductor technology.In recent years, significant strides have been made in optimizing the geometry and design of qubits. However, the current bottleneck in the performance of superconducting qubits lies in the presence of defects and impurities within the materials used. Niobium, owing to its desirable properties, such as high critical temperature and low kinetic inductance, stands out as the most prevalent superconducting material. Nonetheless, it is encumbered by a relatively thick oxide layer (approximately 5 nm) exhibiting three distinct oxidation states: NbO, NbO$_2$, and Nb$_2$O$_5$. The primary challenge with niobium lies in the multitude of defects localized within the highly disordered Nb$_2$O$_5$ layer and at the interfaces between the different oxides. In this study, I present an encapsulation strategy aimed at restraining surface oxide growth by depositing a thin layer (5 to 10 nm) of another material in vacuum atop the Nb thin film. This approach exploits the superconducting proximity effect, and it was successfully employed in the development of Josephson junction devices on Nb during the 1980s.In the past two years, tantalum and titanium nitride have emerged as promising alternative materials, with breakthrough qubit publications showcasing coherence times five to ten times superior to those achieved in Nb. The focus will be on the fabrication and RF testing of Nb-based qubits with Ta and Au capping layers. With Ta capping, we have achieved the best T1 (not average) decay time of nearly 600 us, which is more than a factor of 10 improvements over the bare Nb. This establishes the unique capping layer approach as a significant new direction for the development of superconducting qubits.Concurrently with the exploration of materials for encapsulation strategies, identifying materials conducive to enhancing the performance of superconducting qubits is imperative. Ideal candidates should exhibit a thin, low-loss surface oxide and establish a clean interface with the substrate, thereby minimizing defects and potential sources of losses. Rhenium, characterized by an extremely thin surface oxide (less than 1 nm) and nearly perfect crystal structure alignment with commonly used substrates such as sapphire, emerges as a promising material platform poised to elevate the performance of superconducting qubits.
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Title: Utilizing Concurrent Data Accesses for Data-Driven and AI Applications
Creator: Lu, Xiaoyang
Date: 2024
Description: In the evolving landscape of data-driven and AI applications, the imperative for reducing data access delay has never been more critical,...
Show moreIn the evolving landscape of data-driven and AI applications, the imperative for reducing data access delay has never been more critical, especially as these applications increasingly underpin modern daily life. Traditionally, architectural optimizations in computing systems have concentrated on data locality, utilizing temporal and spatial locality to enhance data access performance by maximizing data and data block reuse. However, as poor locality is a common characteristic of data-driven and AI applications, utilizing data access concurrency emerges as a promising avenue to optimize the performance of evolving data-driven and AI application workloads.This dissertation advocates utilizing concurrent data accesses to enhance performance in data-driven and AI applications, addressing a significant research gap in the integration of data concurrency for performance improvement. It introduces a suite of innovative case studies, including a prefetching framework that dynamically adjusts aggressiveness based on data concurrency, a cache partitioning framework that balances application demands with concurrency, a concurrency-aware cache management framework to reduce costly cache misses, a holistic cache management framework that considers both data locality and concurrency to fine-tune decisions, and an accelerator design for sparse matrix multiplication that optimizes adaptive execution flow and incorporates concurrency-aware cache optimizations.Our comprehensive evaluations demonstrate that the implemented concurrency-aware frameworks significantly enhance the performance of data-driven and AI applications by leveraging data access concurrency.Specifically, our prefetch framework boosts performance by 17.3%, our cache partitioning framework surpasses locality-based approaches by 15.5%, and our cache management framework achieves a 10.3% performance increase over prior works. Furthermore, our holistic cache management framework enhances performance further, achieving a 13.7% speedup. Additionally, our sparse matrix multiplication accelerator outperforms existing accelerators by a factor of 2.1.As optimizing data locality in data-driven and AI applications becomes increasingly challenging, this dissertation demonstrates that utilizing concurrency can still yield significant performance enhancements, offering new insights and actionable examples for the field. This dissertation not only bridges the identified research gap but also establishes a foundation for further exploration of the full potential of concurrency in data-driven and AI applications and architectures, aiming at fulfilling the evolving performance demands of modern and future computing systems.
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Title: Defense-in-Depth for Cyber-Secure Network Architectures of Industrial Control Systems
Creator: Arnold, David James
Date: 2024
Description: Digitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To...
Show moreDigitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To achieve these gains, the Internet of Things (IoT) has become an integral component of network infrastructures. However, integrating embedded devices expands the network footprint and softens cyberattack resilience. Additionally, legacy devices and improper security configurations are weak points for ICS networks. As a result, ICSs are a valuable target for hackers searching for monetary gains or planning to cause destruction and chaos. Furthermore, recent attacks demonstrate a heightened understanding of ICS network configurations within hacking communities. A Defense-in-Depth strategy is the solution to these threats, applying multiple security layers to detect, interrupt, and prevent cyber threats before they cause damage. Our solution detects threats by deploying an Enhanced Data Historian for Detecting Cyberattacks. By introducing Machine Learning (ML), we enhance cyberattack detection by fusing network traffic and sensor data. Two computing models are examined: 1) a distributed computing model and 2) a localized computing model. The distributed computing model is powered by Apache Spark, introducing redundancy for detecting cyberattacks. In contrast, the localized computing model relies on a network traffic visualization methodology for efficiently detecting cyberattacks with a Convolutional Neural Network. These applications are effective in detecting cyberattacks with nearly 100% accuracy. Next, we prevent eavesdropping by applying Homomorphic Encryption for Secure Computing. HE cryptosystems are a unique family of public key algorithms that permit operations on encrypted data without revealing the underlying information. Through the Microsoft SEAL implementation of the CKKS algorithm, we explored the challenges of introducing Homomorphic Encryption to real-world applications. Despite these challenges, we implemented two ML models: 1) a Neural Network and 2) Principal Component Analysis. Finally, we hinder attackers by integrating a Cyberattack Lockdown Network with Secure Ultrasonic Communication. When a cyberattack is detected, communication for safety-critical elements is redirected through an ultrasonic communication channel, establishing physical network segmentation with compromised devices. We present proof-of-concept work in transmitting video via ultrasonic communication over an Aluminum Rectangular Bar. Within industrial environments, existing piping infrastructure presents an optimal solution for cost-effectively preventing eavesdropping. The effectiveness of these solutions is discussed within the scope of the nuclear industry.
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Title: Improving Localization Safety for Landmark-Based LiDAR Localization System
Creator: Chen, Yihe
Date: 2024
Description: Autonomous ground robots have gained traction in various commercial applications, with established safety protocols covering subsystem...
Show moreAutonomous ground robots have gained traction in various commercial applications, with established safety protocols covering subsystem reliability, control algorithm stability, path planning, and localization. This thesis specifically delves into the localizer, a critical component responsible for determining the vehicle’s state (e.g., position and orientation), assessing compliance with localization safety requirements, and proposing methods for enhancing localization safety.Within the robotics domain, diverse localizers are utilized, such as scan-matching techniques like normal distribution transformations (NDT), the iterative closest point (ICP) algorithm,probabilistic maps method, and semantic map-based localization.Notably, NDT stands out as a widely adopted standalone laser localization method, prevalent in autonomous driving software such as Autoware and Apollo platforms.In addition to the mentioned localizers, common state estimators include variants of Kalman Filter, particle filter-based, and factor graph-based estimators. The evaluation of localization performance typically involves quantifying the estimated state variance for these state estimators.While various localizer options exist, this study focuses on those utilizing extended Kalman filters and factor graph methods. Unlike methods like NDT and ICP algorithms, extended Kalman filters and factor graph based approaches guarantee bounding of estimated state uncertainty and have been extensively researched for integrity monitoring.Common variance analysis, employed for sensor readings and state estimators, has limitations, primarily focusing on non-faulted scenarios under nominal conditions. This approach proves impractical for real-world scenarios and falls short for safety-critical applications like autonomous vehicles (AVs).To overcome these limitations, this thesis utilizes a dedicated safety metric: integrity risk. Integrity risk assesses the reliability of a robot’s sensory readings and localization algorithm performance under both faulted and non-faulted conditions. With a proven track record in aviation, integrity risk has recently been applied to robotics applications, particularly for evaluating the safety of lidar localization.Despite the significance of improving localization integrity risk through laser landmark manipulation, this remains an under explored territory. Existing research on robot integrity risk primarily focuses on the vehicles themselves. To comprehensively understand the integrity risk of a lidar-based localization system, as addressed in this thesis, an exploration of lidar measurement faults’ modes is essential, a topic covered in this thesis.The primary contributions of this thesis include: A realistic error estimation method for state estimators in autonomous vehicles navigating using pole-shape lidar landmark maps, along with a compensatory method; A method for quantifying the risk associated with unmapped associations in urban environments, enhancing the realism of values provided by the integrity risk estimator; a novel approach to improve the localization integrity of autonomous vehicles equipped with lidar feature extractors in urban environments through minimal environmental modifications, mitigating the impact of unmapped association faults. Simulation results and experimental results are presented and discussed to illustrate the impact of each method, providing further insights into their contributions to localization safety.
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Title: Empowering Visually Impaired Individuals With Holistic Assistance Using Real-Time Spatial Awareness System
Creator: Yu, Xinrui
Date: 2024
Description: The integration of artificial intelligence (AI) into daily life opens unprecedented avenues for enhancing the experiences of visually impaired...
Show moreThe integration of artificial intelligence (AI) into daily life opens unprecedented avenues for enhancing the experiences of visually impaired individuals, offering them greater autonomy and quality of life. This thesis introduces a Visually Impaired Spatial Awareness (VISA) system designed to assist visually impaired individuals holistically through a structured approach. At the foundational level, the VISA system incorporates several key technologies to interpret the surroundings and assist in basic navigation tasks. It utilizes Augmented Reality (AR) markers to facilitate recognition of places and aid in navigation, employs neural network models for advanced object detection and tracking, and leverages depth information for accurate object localization. Progressing to the intermediate level, the VISA system integrates the data obtained from object detection and depth sensing to assist in more complex navigational tasks such as obstacle avoidance and pathfinding toward a desired destination. At the advanced level, the VISA system synthesizes the capabilities developed at the foundational and intermediate levels to enhance the spatial awareness of visually impaired users, allowing them to undertake complex tasks, such as navigating complex environments and locating specific items. The VISA system also emphasizes efficient human-machine interaction, incorporating text-to-speech and speech-to-text technologies to facilitate natural and intuitive communication between the user and the system. The VISA system's performance was evaluated in different environments simulating real-world scenarios. The experimental results show that the user can interact with our system intuitively with minimal effort, and affirm that the VISA system can effectively assist the visually impaired user in locating and reaching for objects, navigating indoors, identifying merchandise, and recognizing both handwritten and printed texts.
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Title: Evaluating antimicrobial efficacy of GS-2 on reusable food packaging materials
Creator: Birje, Nupoor Prasad
Date: 2024
Description: Packaging plays an important role in maintaining the quality and safety of fresh produce throughout storage, transportation and end-use by...
Show morePackaging plays an important role in maintaining the quality and safety of fresh produce throughout storage, transportation and end-use by consumers. Single-use packaging poses several environmental impacts; therefore use of reusable packaging is being encouraged in the fresh produce supply chain. However, the utilization of harmful chemicals and inadequate sanitation standards limit the reuse of packaging materials. To overcome these limitations, this study focuses on testing a non-toxic, water-soluble antimicrobial; GS-2 coating to facilitate the reuse of food packaging and reduce the risk of microbial contamination. In this study, the antimicrobial activity of GS-2 was evaluated against foodborne pathogens; Escherichia coli, Listeria monocytogenes and Salmonella enterica on plastic and cardboard coupons at 1 h and 15 min treatment times and 0.3%, 1% and 3% concentration. These coupons were also stored at 4℃ and 90% R.H. and 18℃ and 45% R.H. inoculated on different days up to 42 d with E. coli or L. monocytogenes to study retention of activity of GS-2. Additionally, the efficacy of GS-2 to reduce transfer of bacteria from cardboard and plastic to tomato was investigated. The initial level of inoculum was 9 log CFU/surface for all experiments. Cardboard and plastic without GS-2 were used to compare the reduction of bacteria on the treated surfaces. The differences in the population of bacteria were evaluated using Student’s T-Test and ANOVA; p <0.05 was considered significant. With 3% GS-2 concentration on plastic, there was > 4.50 log CFU/surface reduction of all three bacteria in 1 h. There was a lower reduction of the population on cardboard as compared to plastic for all bacteria, the reduction obtained was 1.83, 2.65 and 3.42 log CFU/surface for E. coli, L. monocytogenes and S. enterica, respectively, in 1 h. There was no significant difference between 15 min and 1 h treatments for cardboard. Further, the highest reduction of bacteria was obtained with 3% GS-2 on plastic. For cardboard, no significant difference in population reduction was obtained for E. coli or S. enterica, with 1% or 3% GS-2. However, for L. monocytogenes there was a higher reduction with 3%. GS-2 remained active on the surface of plastic and cardboard for a period of six weeks. For cardboard, there was a lower reduction of bacteria and there was no trend in the population reduction from 0 to 42 d, with the populations remaining within a range of 4-5 log CFU/surface. There was a significant transfer of E. coli or L. monocytogenes from plastic surfaces without GS-2 to tomato at 5-6 log CFU/tomato. However, the transfer of bacteria from the GS-2-coated plastic to the tomato was below the limit of enumeration. For cardboard, the population was below the limit of enumeration, irrespective of the GS-2 coating. Based on the results, GS-2 is a promising antimicrobial that reduces the microbial load on packaging surfaces and prevents cross-contamination of fresh produce. The retention of GS-2 activity makes it suitable for reusable packaging applications.
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Title: EVALUATION OF TIME-FREQUENCY DISTRIBUTIONS FOR ULTRASONIC IMAGING APPLICATIONS
Creator: Lu, Juan
Date: 2013-05-01, 2013-05
Description: This thesis presents the performance evaluation of generalized time-frequency distributions (GTFD) and model-based time-frequency (TF)...
Show moreThis thesis presents the performance evaluation of generalized time-frequency distributions (GTFD) and model-based time-frequency (TF) estimation of ultrasonic signals. Two new TF distributions which are related to generalized time-frequency distribution have been examined. These methods are singular value decomposition of Choi-Williams distribution (CWD-SVD), and 2D (time and frequency) Gaussian kernel applied to generalized time-frequency distribution. The application of Short-Time Fourier Transform (STFT) is studied for chirplets estimation. Then, the Wigner distribution (also called the Wigner-Ville distribution) of estimated Chirplets yield a precise TF representation. The performance of the STFT, the Morlet wavelet transform, the Wigner distribution (WD), the CWD and the CWD-SVD are compared. CWD-SVD is a very effective algorithm to keep the high clarity of the Wigner distribution and to suppress the undesirable cross-terms resulting from multi-component signals. The Gaussian echo model is used to obtain the analytical TF distribution. For CWD the proper range of exponential kernel parameter, , is attained. This range allows CWD to sustain a high concentrated auto-terms and significant suppression of cross-terms. For this range of the CWD-SVD extracts high clarity auto-terms and facilitate eliminating the residual cross-terms. To remove the cross-terms, singular value decomposition algorithm extracts basis functions corresponding to auto-terms. After discarding the basis functions and singular values of the cross-terms and noise, the basis functions and their singular values of auto-terms are used to reconstruct the TF distribution. The results of multi-component Gaussian echoes with significant time and frequency overlaps show that the CWD-SVD is able to eliminate residual cross-terms for xi which the CWD failed to eliminate. The numerical analysis of multi-component Gaussian echoes indicates that CWD-SVD has the ability to resist noise resulting in accurate estimates of center frequencies and arrival times. The generalized time-frequency distribution with 2D Gaussian kernel is able to separate two extremely close Gaussian echoes in the time-frequency domain. In this study, typical values of the 2D Gaussian kernel parameters for efficient cross-terms elimination are provided. The relationship between the kernel's parameters and Gaussian echoes' parameters is deduced. A practical method for TF analysis is to decompose the signal into sparse chirplets. Decomposition requires chirplet parameter estimation. In this study, the parameters of a signal which is composed of two overlapping chirplets are estimated using STFT. By this method the estimation results are found to be accurate confirming that the STFT is an effective method for decomposing and estimating chirplets in a multi-component signal.
M.S. in Electrical Engineering, May 2013
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Title: MOTION ESTIMATION METHODS FOR RESPIRATORY GATED SPECT
Creator: Hurtado Jaramillo, Juan Sebastian
Date: 2014, 2014-12
Description: Single photon emission computed tomography (SPECT) is a type of nuclear imaging test that is used for detection of cardiac diseases....
Show moreSingle photon emission computed tomography (SPECT) is a type of nuclear imaging test that is used for detection of cardiac diseases. Unfortunately it suffers from several image degrading factors, including respiratory motion, that can affect the accuracy of diagnosis. Four-dimensional (4D) respiratory gated SPECT helps to correct this issue by performing the acquisition at several intervals and applying motion-compensated reconstruction methods. With this in mind, and to improve 4D reconstruction, three different motion estimation methods (i.e., optical flow equation, center of mass, and template matching) are applied in this project. Three different sets of dose levels are simulated using NCAT and one set of clinical data is used. The results for motion estimation on simulated data show that the template matching methods have better performance overall. Additionally, noise reduction by means of a spatial smoothing filter helps on the reduction of the average error. Rotational motion estimation using principal component analysis (PCA) was also studied to examine if there can be improvements over the translational motion methods. The initial outcome is that there is a small rotation that can be detected on the ideal reconstruction; the compensation of this rotation also helps to reduce the error obtained from translational motion, albeit by a small margin. Unfortunately, the same cannot be said when noisy reconstructions were used.
M.S. in Electrical Engineering, December 2014
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Title: ENSURING SECURITY AND PRIVACY IN BIG DATA SHARING, TRADING, AND COMPUTING
Creator: Jung, Taheo
Date: 2017, 2017-05
Description: We have witnessed huge values of the big data in the last decade, and it is evidential that the data bring large added values to the business...
Show moreWe have witnessed huge values of the big data in the last decade, and it is evidential that the data bring large added values to the business in various areas. Owing to such opportunities, the data collection and archival became one of the most successful business strategies in the industry, and more and more user-generated data are now being acquired, stored, provisioned, and consumed nowadays. Increased collection made human being more closely involved in the life cycle of the big data characterized by the acquisition, storage, provisioning, and consumption, and larger security and privacy challenges emerged. People’s awareness of such threats led to various efforts by the governments, industry, and academia, and our efforts described in this dissertation also belong to them. We have investigated the security and privacy challenges emerging in various parts of the life cycle big data experience nowadays, and I present our major discoveries in this dissertation which are composed of three major parts: (1) security and privacy in storage of big data; (2) theoretic foundations of privacy-preserving data computing; (3) security in big data trading. We addressed new or existing security/privacy threats existing in different parts of the big data life cycle by either leveraging existing works in intelligent ways or by proposing our novel technologies. The contributions of our discoveries cam be summarized as the protection of user privacy and data security while supporting the original functionalities at negligible extra computation/communication/storage overhead.
Ph.D. in Computer Science, May 2017
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Title: SLIP-LINK MODELING OF ENTANGLED POLYMERS: RHEOLOGICAL APPLICATIONS AND EXTRACTING FRICTION FROM ATOMISTIC SIMULATION
Creator: Katzarova, Maria
Date: 2016, 2016-05
Description: The Discrete Slip-link Model (DSM) is a robust mesoscopic theory that has great success predicting the rheology of flexible entangled polymer...
Show moreThe Discrete Slip-link Model (DSM) is a robust mesoscopic theory that has great success predicting the rheology of flexible entangled polymer liquids and gels. In the most coarse-grained version of the DSM, we exploit the university observed in the shape of the relaxation modulus of linear monodisperse melts. For this type of polymer we present analytic expressions for the relaxation modulus. The high-frequency dynamics which are typically coarse-grained out from the DSM are added back into these expressions by using a Rouse chain with fixed ends. We find consistency in the friction used for both fast and slow modes. Using these analytic expressions, the polymer density, the molecular weight of a Kuhn step, Mk, and the low-frequency cross-over between the storage and loss moduli, G' and G", it is now straightforward to estimate model parameter values and obtain predictions over the experimentally accessible frequency range. Moreover it has previously been shown that the two static parameters can be obtained from primitive path analysis of molecular dynamics simulations. In this work, two ways are shown for obtaining the friction parameter (i) from atomistic simulations of short chains using the free-volume theory, and (ii) from atomistic simulations of entangled chains by scaling the chain center-of-mass mean-square displacement from the slip-link model to that of the atomistic simulation. Futhermore three standing challenges for molecular theories of polymers (i) predictions for uniaxial extension of star-branched polymer melts (ii) predictions for blends of star-branched and linear chains and (iii) predictions for normal stress differences in start-up of shear and followoing cessation are addressed here using the DSM. Additionally the DSM is used to predict the mechanical properties of a cross-linked polydimethylsiloxane (PDMS) network swollen with non-reactive entangled PDMS solvent. These successful predictions strongly suggest that the observed rheological modification in the swollen blend arises from the constraint dynamics between the network chains and the dangling ends.
Ph.D. in Chemical Engineering, May 2016
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Title: CLOSED-LOOP CONTROL GUST SUPPRESSION AT OF LIFT FOR LONGITUDINAL LOW REYNOLDS NUN4BERS
Creator: Kerstens, Wesley
Date: 2011-07-26, 2011-07
Description: Experiments are conducted to investigate the ability of variable pressure, pulsed-blowing actuators and zero-net-mass-flux actuators to...
Show moreExperiments are conducted to investigate the ability of variable pressure, pulsed-blowing actuators and zero-net-mass-flux actuators to maintain a constant lift force on a low aspect ratio, semi-circular wing in a longitudinally gusting flow. Dynamic models of the lift response to actuation and the lift response to longitudinal gusting are obtained through modern black-box system identification methods. Robust, H∞, closed-loop controllers are synthesized using a mixed sensitivity, loopshaping approach. An additional feed-forward disturbance compensator is designed based on a model of the unsteady aerodynamics. The controllers show suppression of lift fluctuations at low gust frequencies, f < 1Hz (reduced frequency, k < 0.09). At higher frequencies, the control performance degrades due to limitations related to the time for a disturbance, created by the actuators, to convect over the wing and establish the flow field that leads to enhanced lift on the wing. Similar limitations are observed for both wings even though the bandwidth of the zero-net-mass-flux actuators is an order of magnitude higher than that of the pulsed-blowing actuators.
M.S. in Mechanical and Aerospace Engineering, July 2011
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Title: THE EFFECT OF NANOPARTICLE SELF-STRUCTURING ON WETTING AND SPREADING OF NANOFLUIDS ON SOLID SURFACES
Creator: Kondiparty, Kirtiprakash
Date: 2011-11, 2011-12
Description: Nanofluids are suspensions of nanometer-sized particles in liquids. The nanoparticles self-structure at the three-phase contact region...
Show moreNanofluids are suspensions of nanometer-sized particles in liquids. The nanoparticles self-structure at the three-phase contact region resulting in the structural disjoining pressure gradient which causes enhanced the spreading of nanofluids compared to simple fluids without nanoparticles. In this thesis, we attempt to understand the effect of the structural disjoining pressure on the spreading dynamics of nanofluids on solid surfaces. We observed nanoparticle self-structuring phenomena during film thinning on a smooth hydrophilic glass surface using a silica-nanoparticle aqueous suspension and reflected light interferometry. Our experiments revealed that film formed from small drop is thicker and contains more particle layers than a film formed from large drop. The data for the film-meniscus contact angle verses film thickness were obtained and used to calculate the structural energy isotherm of an asymmetric film. We studied the effect of structural disjoining pressure on the wedge meniscus profile formed by an oil drop on solid surface surrounded by nanofluid using Laplace Equation augmented with the structural disjoining pressure. Our analyses indicate that a suitable combination of the nanoparticle concentration, nanoparticle size, contact angle, and capillary pressure can result not only in the displacement of the three-phase contact line, but also in the spontaneous spreading of the nanofluid as a film on solid surface. We validated our theoretical predictions using experiments where we observed spreading of nanofluid on glass surface displacing a sessile drop of canola oil. The dynamic spreading of the nanofluid on a solid surface between a sessile oil drop on solid surface was experimentally measured using reflected light microscopy. We xiv obtained the rate of nanofluid spreading by plotting the position of the inner contact line with time. The nanofluid film was found to spread at a constant velocity. We modeled the spreading dynamics of the nanofluid film using the lubrication approximation of the Navier-Stokes Equation, taking into consideration the structural disjoining pressure in the over-all pressure balance. The model was evaluated by estimating the rate of nanofluid spreading for the 10v% nanofluid. The rate of spreading thus predicted by the dynamics model for 10v% nanofluid was in good agreement with the experimental observations.
Ph.D. in Chemical Engineering, December 2011
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Title: AN OPTIMIZATION OF MANUFACTURING PROCESS SELECTION THROUGH COSTING AND SYSTEMATIC ANALYSIS
Creator: Klima, Kevin
Date: 2017, 2017-05
Description: In order for any company to remain competitive, there is a constant push to cut costs while keeping customers satisfied by providing quality,...
Show moreIn order for any company to remain competitive, there is a constant push to cut costs while keeping customers satisfied by providing quality, robust products. While current methods for predicting the most cost effective manufacturing process have proven to offer a significant amount of utility for design engineers, the issue remains that for a cost estimation to be truly accurate, the component has to be completely or nearly completely designed, which could require a significant amount of upfront development time. The goal was to develop a design tool to predict the most cost effective process to manufacture a new component based solely on already available historical data and basic knowledge of the design requirements of the new part. This study focused on steel components that could be manufactured either as a fabrication or as a casting. Two real-world applications were studied from two separate industries, with each application being designed with each process. Common cost estimation techniques were used to develop models for predicting the cost for each component to offer insight for how the cost would be expected to vary with quantity. As a means of ensuring robustness and that each competing model was structurally equivalent, each model had to pass critical exceptional and fatigue load cases in FEA while also meeting predefined success criteria. Using the results from the structural analysis and cost estimation, a design tool was developed as a means of objectively predicting how a component with similar application requirements would most cost effectively be manufactured based on the desired quantity of parts that needed to be produced. By using historical information of similar components that have the possibility of being manufactured in more than one way, more effective and systematic decision making for how a new component should be manufactured was shown to be possible. A third, independent case study was also selected as a real world example from industry as a means of validating and assessing the sensitivity of the weighting used in the development of the design tool. This was used to further refine the tool for the use in analyzing future components.
M.S. in Manufacturing Engineering, May 2017
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