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Title: MEAN EXIT TIME FOR RADIALLY SYMMETRICAL DYNAMICAL SYSTEMS DRIVEN
Creator: Luan, Yuanchao
Date: 2013, 2013-12
Description: Stochastic differential equations (SDEs) driven by non-Gaussian L´evy noises have attracted much attention recently [1, 29]. In [12], the...
Show moreStochastic differential equations (SDEs) driven by non-Gaussian L´evy noises have attracted much attention recently [1, 29]. In [12], the authors studied a scalar SDE driven by a non-Gaussian L´evy motion, and numerically investigate mean exit time and escape probability for arbitrary noise intensity in one dimensional case. In the present thesis, we utilize a different strategy to explore a numerical method for the problem in two dimensional cases. To be specific, we assume the solution u(x) is radially symmetric with respect to the origin, and then represent the equation using radial coordinate, reducing the problem into one dimensional case. Then main difficulty is that, in the integral term, appears a Gauss Hypergeometric function and the unknown function u(r), which makes the error estimates complicated. We exploit some properties of Gauss Hypergeometric function, and finally make out a way for estimating the error [19]. Up to now we are only able to deal with this problem with 0 < α ≤ 1, since our numerical scheme does not converge when 1 < α < 2. Then we compare our numerical solutions with the analytical ones which are given in [3], and they coincide very well. KeyWords: Stochastic dynamical systems; non-Gaussian L´evy motion; L´evy jump measure; First exit time
M.S. in Applied Mathematics, December 2013
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Title: ANALYSIS OF VARIATION IN MULTISTAGE MANUFACTURING PROCESS BASED ON TREE REGRESSION
Creator: Chen, Zhefu
Date: 2014, 2014-05
Description: In a multistage manufacturing process, variation propagates in the process when we produce products from stage to stage. Since there are...
Show moreIn a multistage manufacturing process, variation propagates in the process when we produce products from stage to stage. Since there are limits of reducing variation through process in traditional industrial management and it is hard to monitor the process when the engineering domain knowledge is insufficient. We investigated statistical methods based on piecewise tree regression model including: CART, Bayesian CART, Bayesian treed linear model and Bayesian treed Gaussian process to multistage manufacturing process. The difference performances between models were discussed in a wafer manufacturing process case as a result comparison. Key Words: Multistage process, variation propagation, process monitoring, piecewise tree regression
M.S. in Applied Mathematics, May 2014
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Title: DEPTH MAP PROCESSING FOR MULTI-VIEW VIDEO PLUS DEPTH
Creator: Vijayanagar, Krisha Rao
Date: 2014, 2014-05
Description: The world of multimedia and visual entertainment has grown in leaps and bounds in the past decade with 3-D television being one of the biggest...
Show moreThe world of multimedia and visual entertainment has grown in leaps and bounds in the past decade with 3-D television being one of the biggest technologies. Amongst several formats proposed for representing 3-D content, multi- view video plus depth (MVD) format has gained a lot of interest in the past few years. MVD requires that each view of a particular scene be accompanied by a per-pixel depth. This introduces new problems for compression and transmission of MVD content because a depth map has di erent characteristics from a color image. Keeping the MVD format and depth map characteristics in mind, we highlight three majors problems that plague the MVD format, namely, 1. depth map re nement. 2. depth map compression. 3. novel view synthesis using the depth map at the decoder side. In order to re ne a depth map, we propose a multi-resolution anisotropic di usion algorithm that is optimized to run in real-time thus ensuring that the encoder does not su er from additional latency. Next, we propose two unique solutions for compressing them. We rst propose a solution using the Layered Depth Video (LDV) concept using a rate-distortion optimized quadtree decomposition of the LDV using a novel two-mode block truncation code with improved prediction. We also propose a compression solution using compressive sensing (CS) concepts by creating a hybrid rate-optimized CS codec. This codec achieves two goals:- rstly, block classi cation to ensure lower decoder complexity and secondly, rate-distortion optimization of the measurement rate for each block that is to be compressively sensed. We then look at the view synthesis component of the MVD tool-chain which x is a time-sensitive process. Keeping decoding latency in mind, we propose a lookup- table based approach to the 3-D warping process with a simpli ed hole- lling algorithm that is not only competitive quality-wise with other schemes but is several times faster too. It is hopeful that the presented techniques can be used successfully to create MVD architectures for applications that need low-complexity encoding solutions.
PH.D in Electrical Engineering, May 2014
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Title: REAL TIME STATIC SCENE 3D RECONSTRUCTION USING DEPTH SENSORS FOR AUGMENTED TELEOPERATION
Creator: Srinivasan, Ranga Ramanujam
Date: 2015, 2015-05
Description: In the first part of this Master’s Thesis, literature survey is done to find the best performing algorithm in terms of real-time performance...
Show moreIn the first part of this Master’s Thesis, literature survey is done to find the best performing algorithm in terms of real-time performance and quality of 3D reconstruction from depth images. Kinfu of PCL is found to be the best in terms of real-time performance and maintainability, as it is open-source software, with thousands of users working on to improve it. The primary part of the thesis is to improve on the 3D reconstruction quality of Kinfu and this is achieved by improving on the three important stages of Kinfu, Depth Filtering, Pose-estimation and 3D reconstruction. A new Anisotropic depth filtering kernel is proposed and it is found to give 23% quantitative improvement over baseline Kinfu. A modified pose-estimation which incorporates the uncertainty or error characteristics of the depth measured as part of the ICP algorithm is proposed. This results in a 51% quantitative improvement and a big subjective quality improvement over baseline Kinfu. A similar approach based on depth error characteristics but applied to 3D reconstruction stage which is based on an already published paper [1], is implemented. All the improvements in each of the three stages are combined together, to get a robust, real-time 3D reconstruction framework.
M.S. in Electrical Engineering, May 2015
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Title: Garfield Station Area Rehabilitation Project
Creator: Oh, Soohyun
Date: 2011-04-25, 2011-05
Description: Architecture is significantly associated with people. Because architecture is design of life, activities and spaces for people. Therefore,...
Show moreArchitecture is significantly associated with people. Because architecture is design of life, activities and spaces for people. Therefore, architectural behavior does not have only a physical impact but also social and economic impact on the area. Especially the architectural elements can help to development an area and provide an enhanced economic aspect, cultural activities and social communication to inhabitants in underdeveloped or backward area. The Garfield Station Area Rehabilitation Project is a grand scale development project that comprehends urban scheme, site master plan and architectural design phases. The goal of the project, consistent throughout all phases, is to transform the abandoned Washington Park Community into a recovered, preserved and developed community with its rich history by promoting cultural, social and economical incentives to be linked to the Hyde Park Community.
M.S. in Architecture, May 2011
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Title: SECURITY-CONSTRAINED UNIT COMMITMENT RESERVE DETERMINATION IN JOINT ENERGY AND ANCILLARY SERVICES AUCTION
Creator: Ganji Tanha, Mohammad Mahdi
Date: 2012-07-25, 2012-07
Description: This study presents the method in which the energy and ancillary services auction is simultaneously cleared in electricity market. By the...
Show moreThis study presents the method in which the energy and ancillary services auction is simultaneously cleared in electricity market. By the security-constraint unit commitment model proposed in this study Independent System Operators (ISO) can determines the sufficient amount of reserve which is necessary to maintain security and reliability of the system. Before the fixed reserve requirement either equal to a percentage of the system peak load or a thermal unit with highest capacity is considered in energy and ancillary service auction in market clearing. The disadvantage of this method is high cost and insufficiency. When it is insufficient the system operator needs to committee more thermal units or does the load curtailment. At the time the fixed quantity is more than needed customers pay more although it is not necessary. Here the sufficient amount of reserve is determined based on the contingency which has been simulated. Contingencies include thermal unit outage and line outage is considered. The amount of reserves is obtained based on thermal units’ physical constraints and the rate offered in the electricity market. Then the integration of wind generation and its effects on the quantity of the reserve determination is considered. Since the wind power generation brings uncertainties to the power system we need to consider scenarios. In order to generate wind power generation scenarios we use Monte Carlo simulation. Since the number of scenarios are too much and increase the problem complexity we use Fast backward/forward scenario reduction. This problem is solved through direct optimization problem including the minimization of the operational cost as well as satisfying the network security constraints when contingency happens.
M.S. in Electrical Engineering, July 2012
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Title: DISPARITY ESTIMATION WITH SEGMENT-BASED MULTI-STEP DISPARITY REFINEMENT
Creator: Anand, Bhaskar
Date: 2012-07-20, 2012-07
Description: Stereo Vision is one of the fundamental problems of computer vision and one of the oldest and heavily investigated areas of 3D Vision. Recent...
Show moreStereo Vision is one of the fundamental problems of computer vision and one of the oldest and heavily investigated areas of 3D Vision. Recent advances in stereo matching methodologies have allowed researchers to develop several stereo vision techniques. But it has been observed that most of these methodologies mainly focus on only one aspect, either the execution time or the quality of the generated depth map. While attempts to maximize the quality of the depth map have been successfully achieved, it is however observed that the execution time has increased signi cantly, thereby rendering them un t for real time implementation. In this thesis, an attempt to solve the above said problem is presented, in which we combine the e ects of two important stereo matching concepts, one attempting to increase the depth map quality, while the other being that of having an algorithmic structure so that in future, it can be used for real-time implementation. By applying hardware-friendly methods to the framework of segment based stereo matching, the method is said to achieve a good quality depth map. This work also discusses the various challenges which it takes care of plus the study of performance compared to existing methods.
M.S. in Electronical Engineering, July 2012
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Title: PEGYLATION OF FIBRONECTIN AND ITS FUNCTIONAL DOMAINS: EFFECT ON STABILITY AND BIOLOGICAL ACTIVITY
Creator: Zhang, Chen
Date: 2013, 2013-07
Description: Delayed wound healing in many chronic wounds has been linked to the lack of extracellular matrix (ECM) support and the degradation of...
Show moreDelayed wound healing in many chronic wounds has been linked to the lack of extracellular matrix (ECM) support and the degradation of fibronectin (FN) by an abnormally high protease level. The ECM is important in wound healing because it provides physical and chemical cues that direct tissue growth and development. FN is a key ECM protein that attracts and binds different molecules and cells and thereby supports biological responses associated with wound healing. The goal of my study is two fold: (1) To create an ECM analogue based on a composite of polyethylene glycol (PEG) hydrogels and FN binding domains and (2) To stabilize FN against proteolytic degradation by conjugating it to PEG. To address the first goal, I used Michael addition chemistry to covalently link the cell-binding domain of FN, III9−10, to PEG diacrylate and cross-linked the conjugate to PEG hydrogels. The conjugation of PEG to III9−10 was through cysteines in the affinity tag Glutathione S Transferase (GST). The conjugate of GST-III9−10 and PEG was characterized by: (i) Circular dichroism studies to determine secondary structure, (ii) Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) to determine molecular weight, and (iii) Ellmans reagent to determine the efficiency of PEG conjugation to GST-III9−10. The conjugate of PEG and GST-III9−10 had comparable secondary structure to GST-III9−10. SDS-PAGE studies showed that up to three PEG molecules were attached to one GST-III9−10 molecule. The efficiency of PEG conjugation was greater than 90% and occurred within 30 minutes after PEG diacrylate addition. Adhesion assays were used as a metric of biological activity. These assays demonstrated that on a molar basis cell adhesion and spreading were significantly higher on PEG hydrogels with GST-III9−10 than those with the commonly used arginine-glycine-aspartic acid (RGD) peptide. Scaffold rigidity is an important biological cues that influence xi cell responses. However, a comparative study of rigidity on GST-III9−10 and RGD functionalized PEG hydrogels demonstrated that differences in rigidity could not account for differences in cell adhesion and spreading between RGD and GST-III9−10 functionalized PEG hydrogels. Thus as ECM analogues, GST-III9−10 functionalized hydrogels provide more robust biochemical cues than RGD functionalized hydrogels. Studies of PEG hydrogel composites with mixtures of III9−10 and a fibronectin binding domain demonstrated that biological responses of adhesion and spreading and extracellular matrix assembly could be controlled by varying the ratio of these two domains and the rigidity of the PEG hydrogels. FN was stabilized against proteolytic degradation by covalent attaching it to PEG or by PEGylating it. FN was first isolated from human plasma by gelatin affinity chromatography and then PEGylated using two methods. The first method is to PEGylate human plasma fibronectin (HPFN) at cysteine residues with 3.4 kDa PEG diacrylate. The second method is to PEGylate HPFN at lysine residues on the surface with 2-10 kDa PEG Succinimidyl carboxy methyl esters. Cysteine PEGylation of HPFN was first carried out because cysteines are concentrated in the amino- terminus of HPFN which leaves two-thirds of the molecule, including the cell-binding domain, unperturbed. PEGylation of HPFN on cysteines resulted in a molecule that supported cell adhesion, spreading, focal adhesion formation and cell migration in a comparable manner to native HPFN. Moreover, PEGylated HPFN was incorporated into the ECM in a similar manner to native HPFN when present in the culture media but not when coated on a surface indicating that PEGylation on cysteines modified some biological activity of HPFN. Additionally, HPFN PEGylated by this manner could not bind denatured collagen or gelatin. The gelatin-binding domain is at the site of cysteine PEGylation. The second approach for PEGylation of HPFN was through lysine residues xii on the surface of the protein. This approach was used because it targeted different amino acid residues in FN. The length of PEG and extent of PEGylation have been reported to influence biological activity of proteins. In the second approach, both PEG length and extent were varied. HPFN completely PEGylated on lysines residues was significantly more proteolytically stable than native HPFN but had reduced cell attachment and spreading. Furthermore, cell spreading and attachment on surfaces conjugated with this lysine PEGylated HPFN decreased with increasing PEG length. Partially PEGylated HPFN was synthesized by masking the cell and gelatin binding domains during PEGylation. The partially PEGylated HPFN supported cell adhesion and spreading in a similar manner to native HPFN and was more proteolytically stable. For the partially PEGylated HPFN, the size of PEG poly had no significant influence on the attachment and spreading of cells. These studies are the first attempt by any laboratory to stabilize FN against proteolytic degradation while retaining activity and show the feasibility of this approach as a potential therapeutic approach. The work presented here shows a two-prong approach by which the problem of ECM degradation and deficiency chronic wound healing can be addressed. The first approach for addressing ECM deficiency is through a scaffold design methodology. The novelty of the scaffold approach is that it uses the cell-binding domains of FN instead of the often-used RGD peptide. I demonstrate that a PEG hydrogel with the cell-binding domain produces a more robust biological response in cells than a PEG hydrogel with the RGD peptide. I also demonstrate that varying different functional domains of fibronectin can be used to controllably stimulate multiple biological responses. The second approach demonstrates a method by which FN, a key ECM protein, is stabilized against proteolytic degradation without perturbing its activity. These studies of creating PEG-FN conjugates are the first of their kind. Collectively, the data that I present in this thesis will lead to novel therapeutic methods for treating chronic wounds.
PH.D in Chemical Engineering, December 2012
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Title: MODELING THE PERFORMANCE OF A SOLAR CHIMNEY WITH BUILT-IN PHASE CHANGE MATERIALS TO IMPROVE NATURAL VENTILATION
Creator: Khorraminejad, Aysan
Date: 2014, 2014-12
Description: The use of solar chimneys to improve natural ventilation in buildings has been shown to yield energy savings while maintaining thermal comfort...
Show moreThe use of solar chimneys to improve natural ventilation in buildings has been shown to yield energy savings while maintaining thermal comfort in some climate zones. However, one disadvantage is that the ability to control passive ventilation with solar chimneys is often limited by temporal variations of building function and diurnal weather patterns. The unique thermal properties of phase change materials (PCMs) may provide opportunities to manage some of the limitations of solar chimney strategies in buildings through the timed storage and release of thermal energy, which can aid in minimizing daytime heat gains and increasing the effectiveness of nighttime flushing by natural ventilation. This work explores the potential of PCMs combined with solar chimneys to support the passive ventilation of buildings using whole building energy simulation. Results are intended to inform architects and engineers on best practices for incorporating PCMs in buildings with solar chimneys. A model of a prototype office building designed to ASHRAE Standard 90.1 was developed in EnergyPlus and investigated in five U.S. climate zones. A total of 1023 energy simulations were performed to address the following research questions: (1) In what U.S. climate zone is the use of PCMs most appropriate? (2) Can PCMs improve night flushing ventilation when used with a solar chimney? (3) What are the optimal locations for installation of PCMs in building and solar chimney construction in order to provide optimal cooling load reductions? and (4) How do PCM properties influence cooling load reductions? Results demonstrate that the solidification and melting process of PCMs can indeed be used to prolong natural ventilation for night flushing in the evening and nighttime, particularly in climate zones with large diurnal outdoor temperature fluctuations. Results also suggest the following: (1) the optimal location for installation of PCMs in most climates is within the structure of south-facing envelope assemblies; (2) the PCM melting temperature should be equal to or greater than the zone set point temperature; (3) thicker PCMs can yield slightly more cooling energy savings than thinner PCMs; and (4) the thermal conductivity of PCMs does not appear to have a substantial influence on performance.
Ph.D. in Architecture, December 2014
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Title: Towards a Secure and Resilient Smart Grid Cyberinfrastructure Using Software-Defined Networking
Creator: Qu, Yanfeng
Date: 2022
Description: To enhance the cyber-resilience and security of the smart grid against malicious attacks and system errors, we present software-defined...
Show moreTo enhance the cyber-resilience and security of the smart grid against malicious attacks and system errors, we present software-defined networking (SDN)-based communication architecture design for smart grid operation. Our design utilizes SDN technology, which improves network manageability, and provides application-oriented visibility and direct programmability, to deploy the multiple SDN-aware applications to enhance grid security and resilience including optimization-based network management to recover Phasor Measurement Unit (PMU) network connectivity and restore power system observability; Flow-based anomaly detection and optimization-based network management to mitigate Manipulation of demand of IoT (MadIoT) attack. We also developed a prototype system in a cyber-physical testbed and conducted extensive evaluation experiments using the IEEE 30-bus system, IEEE 118-bus system, and IIT campus microgrid.
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Title: SIMULTANEOUS RELEASE OF BIOACTIVE AFLIBERCEPT AND DEXAMETHASONE FROM A MICROSPHERE- AND NANOPARTICLE-HYDROGEL OCULAR DRUG DELIVERY SYSTEM FOR THE ENHANCED TREATMENT OF NON-RESPONSIVE PATIENTS WITH CHOROIDAL NEOVASCULARIZATION
Creator: Rudeen, Kayla M
Date: 2022
Description: There is a growing subset of wet age-related macular degeneration (AMD) patients who do not fully respond to standard of care treatment, which...
Show moreThere is a growing subset of wet age-related macular degeneration (AMD) patients who do not fully respond to standard of care treatment, which consists of bimonthly/monthly bolus intravitreal injections of anti-vascular endothelial growth factors (anti-VEGFs). Some of these patients may respond to a combination therapy of anti-VEGF and corticosteroids. One treatment option uses a dexamethasone implant that releases for six months. This regimen, however, requires both the bimonthly/monthly intravitreal injections of anti-VEGF and semiannual intravitreal injections of the dexamethasone implant. Combining the two treatments into a single drug delivery system (DDS) would reduce the total number of injections, reducing the risk of potential complications (endophthalmitis, retinal detachment, intravitreal hemorrhage, increased intraocular pressure, and cataract) as well as the socioeconomic burden of treatment.The overarching goal of this study was to develop a single DDS that simultaneously releases anti-VEGF (aflibercept) and corticosteroid (dexamethasone) for the treatment of non-responsive wet AMD patients. Our laboratory previously developed a thermoresponsive, biodegradable microparticle-hydrogel DDS that releases anti-VEGF over a period of six months. The aims of the study were to (1) modify this system to include dexamethasone-loaded nanoparticles, optimize release kinetics for both drugs, and characterize the DDS; (2) evaluate the in vivo treatment efficacy in a laser-induced choroidal neovascularization (CNV) model; and (3) investigate the impacts of temperature and storage on the DDS integrity.
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Title: Workload Interference Analysis and Mitigation on Dragonfly Class Networks
Creator: Kang, Yao
Date: 2022
Description: Dragonfly class of networks are promising interconnect topologies that support current and next-generation high-performance computing (HPC)...
Show moreDragonfly class of networks are promising interconnect topologies that support current and next-generation high-performance computing (HPC) systems. Serving as the "central nervous system", Dragonfly tightly couples tens of thousands of compute nodes together by providing high-bandwidth, low-latency data exchange for exascale computing capability. Dragonfly can support unprecedented system scale at a reasonable cost thanks to its hierarchical architecture. In Dragonfly systems, network resources such as routers and links are arranged into identical groups.Groups are all-to-all connected through global links, and routers within groups are connected via local links. In contrast to the fully connected inter-group topology, connections for the routers within groups are designed according to the system requirement. For example, the one-dimensional all-to-all connection is favored for higher network bandwidth, a two-dimensional grid arrangement can be constructed to support larger system size, and a tree structure router connection is built for the extreme system scale. The hierarchical design with groups enables the topology to support unprecedented system size while maintaining a low-diameter network. Packets can be minimally delivered by simply traversing the network hierarchy between groups through global links and reaching their destinations through local links. In case of network congestion, packets can be non-minimally forwarded through any intermediate group to increase the system throughput. As a result, all network resources are shared such that links and routers are not dedicated to any node pair. While link utilization is increased, shared network resources lead to inevitable network contention among different traffic flows, especially for the systems that hold multiple workloads at the same time. This network contention is observed as the workload interference that causes degraded system performance with delayed workload execution time. In this thesis, we first model and analyze the workload interference effect on Dragonfly+ topology through extensive system simulation.Based on the comprehensive interference study, we propose Q-adaptive routing, a multi-agent reinforcement learning based solution for Dragonfly systems. Compared with the existing routing solutions, the proposed Q-adaptive routing can learn to forward packets more efficiently with smaller packet latency and higher system throughput. Next, we demonstrate that intelligent routing algorithms such as Q-adaptive routing can greatly mitigate workload interference and optimize the overall system performance. Subsequently, we propose a dynamic job placement strategy for workload interference prevention. When combined with Q-adaptive routing, dynamic job placement gives users the flexibility to either reduce workload interference from communication intensive applications or protect target applications for higher performance stability.
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Title: MULTICRITERIA DECISION-MAKING METHODOLOGY WITH TRADEOFF ANALYSIS FOR TRANSPORTATION BUDGET ALLOCATION
Creator: Truong, Tung Quoc
Date: 2022
Description: Transportation agencies in the United States nowadays rely on tax dollars for maintaining surface transportation infrastructure, which mainly...
Show moreTransportation agencies in the United States nowadays rely on tax dollars for maintaining surface transportation infrastructure, which mainly comes from fuel tax. However, travel behaviors are changing every day. People and businesses demand better and safer roads. Yet, consumers travel in more fuel-efficient vehicles and buy less gas, which means less revenue for fixing aging roads and highways. Meanwhile, new construction and repair costs increase for our overburdened transportation systems. Transportation agencies, therefore, must use their limited funding more wisely to optimize the service performance and minimize risks (Li, 2018). The budget allocation problem in transportation is not an easy task. The consequences of an ineffective decision in allocating resources are multi-facet both in the short- and long-term, including degrading in the condition of transportation facilities, losing public trust, and increasing backlogs in maintenance and repair. Therefore, transportation agencies are seeking more robust and comprehensive data-driven strategies that take into account of agency’s strategic goals and regulatory requirements, user expectations, nature of the asset, availability of resources, and lifecycle cost analysis in determining the optimal allocation of resources and making the best use of available funds (Li and Sinha, 2004; Sinha and Labi, 2007). The proposed research aims to utilize the concept of multicriteria decision making coupled with a holistic asset management framework to support performance-based allocations of transportation budgets and help transportation agencies achieve the future vision of the nation’s strategic planning requirements to enable sustainable management of the system. A computational study for the real-world dataset obtained by a state Department of Transportation (DOT) is conducted using the proposed budget allocation method. The results from the computational study reveal that the proposed method can derive optimal decision solutions for transportation budget allocation problems and can be utilized by transportation agencies on different scales – urban and rural, in other sectors – public and private, to effectively manage the transportation infrastructure sustainably, by effectively spending transportation budget to maximize service performance and minimize operating costs.
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Title: MEASUREMENT OF ELECTRON NEUTRINO AND ANTINEUTRINO APPEARANCE WITH THE NOνA EXPERIMENT
Creator: Yu, Shiqi
Date: 2020
Description: As a long-baseline neutrino oscillation experiment, the NuMI Off-axis $\nu_e$ Appearance (NOvA) experiment aims at studying neutrino physics...
Show moreAs a long-baseline neutrino oscillation experiment, the NuMI Off-axis $\nu_e$ Appearance (NOvA) experiment aims at studying neutrino physics by measuring neutrino oscillation parameters using the neutrino flux from the Main Injector (NuMI) beam. It has two functionally identical detectors. The near detector is onsite at Fermi National Accelerator Laboratory. The far detector is 810 km away from the source of neutrinos and antineutrinos, at Ash River, Minnesota. At the near detector, muon neutrinos or antineutrinos, before significant oscillations take place, are used to correct the Monte Carlo simulation. At the far detector, the neutrino and antineutrino fluxes after significant oscillations have happened are measured and analyzed to study neutrino oscillation. The NOvA experiment is sensitive to the values of $\sin^2\theta_{23}$, $\Delta m^2_{32}$, and $\delta_{CP}$. The latest values from the NOvA 2020 analysis are as follows: $\sin^2\theta_{23}=0.57^{+0.03}_{-0.04}$, $\Delta m^2_{32}=(2.41\pm0.07)\times10^{-3}$ eV$^2$/c$^4$, and $\delta_{CP}=0.82\pi$ with a wide 1$\sigma$ interval of uncertainty. My study is focused on the neutrino oscillation analysis with NOvA, including detector light model tuning, particle classification with convolutional neural network, electron neutrino and antineutrino energy reconstruction, and oscillation background estimation. Most of my studies have been used in the latest NOvA publication and the NOvA 2020 analysis.
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Title: SAFETY AND MOBILITY IMPACTS ASSESSMENT OF THE CHICAGO BIKE LANE PROGRAM
Creator: Zhao, Yu
Date: 2021
Description: In recent years, bike as a travel mode is getting increasingly popular among large cities in the U.S. These cities also found promoting bike...
Show moreIn recent years, bike as a travel mode is getting increasingly popular among large cities in the U.S. These cities also found promoting bike mode can potentially mitigate traffic congestion issues, reduce carbon emission and improve the quality of life for residents. Therefore, many cities-initiated bike-related programs promote the bike mode from all aspects, such as establishing a shared bike system and developing bike-related facilities. Specifically, bike lane installation is widely seen in large cities as a pivot component of bike promotion programs. Due to the installation of bike lanes on the existing network, vehicles’ safety and mobility performance may be affected due to the variation of facilities. This study attempts to propose a methodology to quantify the safety and mobility impacts on vehicles brought by bike lane installation. The proposed method accounts for safety impact by using predicted crashes in conjunction with field observed crash data for empirical Bayes (EB) before-after comparison group analysis. The mobility impact is captured by comparing the segment average travel time before and after the bike lane installation. Further, vehicle volume information is involved in the consumer surplus computation to quantify the variation in vehicle safety, and mobility performance resulting from the bike lane installation. A case study is conducted using a real data set from the city of Chicago bike lane program. The results reveal that the safety and mobility impacts vary mainly depending on the type of bike lane installed and location.
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Title: Population Dynamics of Listeria monocytogenes in Nut, Seed and Legume Butters
Creator: Zhang, Xinyuan
Date: 2020
Description: Nut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that...
Show moreNut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that some pathogens, such as Listeria monocytogenes, can survive for long periods of time in butters, such as almond butter. However, information on the persistence of L. monocytogenes in butters is lacking. The purpose of this study was to determine the population dynamics of L. monocytogenes in butters stored at 5 and 25°C. Nut (almond, hazelnut, pecan), seed (pumpkin, sesame, sunflower), legume (peanut and soy) and butters containing chocolate (hazelnut and peanut) were inoculated with a 4-strain cocktail of rifampicin-resistant L. monocytogenes at 4 (high inoculation) or 1 log CFU/g (low inoculation). High inoculation butters were mixed by hand for 15 min and 100-g portions were weighed into deli-style containers with lids and stored at 5 or 25°C for 12 mo (370 d). Low inoculation butters were stored in 25- g portions in stomacher bags at 25°C for 6 mo (180 d). During storage, 25 g from the 100- g high inoculation portion or 25 g from the low inoculation samples, in triplicate, were homogenized with 225 mL BPB (or BLEB for FDA BAM enrichments when necessary) and serial dilutions of the homogenate were plated onto BHIA with rifampicin for enumeration of L. monocytogenes. Data were statistically analyzed using Student’s t-test (α=0.05). The average initial population of L. monocytogenes in the butters was 3.58±0.25 log CFU/g for the high inoculation butters; L. monocytogenes was detected through enrichments for all low inoculation butters. After 12 mo storage at 5°C, the population of L. monocytogenes decreased by 1.34, 1.27, 1.72, 2.04 and 0.93 log CFU/g in almond, hazelnut, peanut with chocolate, hazelnut with chocolate and pecan butter, respectively, when inoculated at the higher level. Significantly less population reduction was observed in pumpkin, sesame, soy, peanut and sunflower butters (1.08, 0.61, 0.84, 0.05 and 0.40 log CFU/g, respectively). After 12 mo storage at 25°C, the L. monocytogenes population in all butters, with the exception of sunflower butter, decreased to below the limit of enumeration (1.67 log CFU/g), but the pathogen was still present via enrichment. For low inoculation butters, L. monocytogenes was present as determined by enrichment in all butters in at least one of two trials after 6 mo. The results of this study provide information on the survival of L. monocytogenes in different butter types when stored at different temperatures.
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Title: ATOMIC LAYER DEPOSITION STUDIES OF GOLD AND TUNGSTEN DISULFIDE
Creator: Liu, Pengfei
Date: 2020
Description: In the last few decades, atomic layer deposition (ALD), as a vapor deposition technique and a powerful thin film fabrication method, has...
Show moreIn the last few decades, atomic layer deposition (ALD), as a vapor deposition technique and a powerful thin film fabrication method, has received more and more attention in many fields. A variety of materials can be made by ALD; however, the progress of ALD application is still necessary. Meanwhile, in the process of film fabrication by ALD, the interfacial chemistry is interesting and well worth studying. This dissertation mainly described the process of exploring two materials, gold and tungsten disulfide, fabrication and related content.For the portion of applying ALD in gold thin film deposition, a relatively comprehensive process was explored, studied, analyzed and discussed. Start with the synthesis of the gold precursor, Me2Au(S2CNEt2), the synthetic reaction was explored. By modified the conditions, such as solvent system, twice the yield as previously reported in the literature were achieved. Next, the application of in situ microbalance and infrared spectroscopic technique illuminate the organometallic chemistry during the gold thermal ALD process with Me2Au(S2CNEt2) and ozone. In situ quartz crystal microbalance (QCM) studies give an explanation for the nucleation delay and island growth of gold on a freshly prepared aluminum oxide surface. In situ infrared spectroscopy provides insight to study the surface chemistry during the process, which supports an oxidized gold surface mechanism. The epitaxy of gold thin film was explored by X-ray diffraction. The thermal ALD gold on various substrates reveals out-of-plane orientation, however, in-plane orientation was only existed in the gold film on mica. For the portion of applying ALD in tungsten disulfide fabrication, the early work started with studying the effect of interfaces upon crystallinity. The sulfuration of indium thin film with different interface was explored. Then the idea of “interfaces” was brought into the process of tungsten compounds fabrication. Due to this “indirect” method which made tungsten disulfide by sulfurizing ALD made tungsten compounds (eg. tungsten oxide and tungsten nitride) could not reduce the reaction temperature of tungsten disulfide synthesis to less than 400 °C. Sequently, the “direct” way of tungsten disulfide fabrication which directly utilized tungsten precursor and H2S in ALD system was tested and explored. With the tungsten precursors developed by our group, finally, tungsten disulfide could be fabricated at the temperature as low as 125 °C.
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Title: Exploiting contextual information for deep learning based object detection
Creator: Zhang, Chen
Date: 2020
Description: Object detection has long been an important research topic in computer vision area. It forms the basis of many applications. Despite the great...
Show moreObject detection has long been an important research topic in computer vision area. It forms the basis of many applications. Despite the great progress made in recent years, object detection is still a challenging task. One of the keys to improving the performance of object detection is to utilize the contextual information from the image itself or from a video sequence. Contextual information is defined as the interrelated condition in which something exists or occurs. In object detection, such interrelated condition can be related background/surroundings, support from image segmentation task, and the existence of the object in the temporal domain for video-based object detection. In this thesis, we propose multiple methods to exploit contextual information to improve the performance of object detection from images and videos.First, we focus on exploiting spatial contextual information in still-image based object detection, where each image is treated independently. Our research focuses on extracting contextual information using different approaches, which includes recurrent convolutional layer with feature concatenation (RCL-FC), 3-D recurrent neural networks (3-D RNN), and location-aware deformable convolution. Second, we focus on exploiting pixel-level contextual information from a related computer vision task, namely image segmentation. Our research focuses on applying a weakly-supervised auxiliary multi-label segmentation network to improve the performance of object detection without increasing the inference time. Finally, we focus on video object detection, where the temporal contextual information between video frames are exploited. Our first research involves modeling short-term temporal contextual information using optical flow and modeling long-term temporal contextual information using convLSTM. Another research focuses on creating a two-path convLSTM pyramid to handle multi-scale temporal contextual information for dealing with the change in object's scale. Our last work is the event-aware convLSTM that forces convLSTM to learn about the event that causes the performance to drop in a video sequence.
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Title: IMPACT OF DATA SHAPE, FIDELITY, AND INTER-OBSERVER REPRODUCIBILITY ON CARDIAC MAGNETIC RESONANCE IMAGE PIPELINES
Creator: Obioma, Blessing Ngozi
Date: 2020
Description: Artificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical...
Show moreArtificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical diagnosis, disease prediction, and treatment, with such interests intensifying in the medical image field. AI can automate various cumbersome data processing techniques in medical imaging such as segmentation of left ventricular chambers and image-based classification of diseases. However, full clinical implementation and adaptation of emerging AI-based tools face challenges due to the inherently opaque nature of such AI algorithms based on Deep Neural Networks (DNN), for which computer-trained bias is not only difficult to detect by physician users but is also difficult to safely design in software development. In this work, we examine AI application in Cardiac Magnetic Resonance (CMR) using an automated image classification task, and thereby propose an AI quality control framework design that differentially evaluates the black-box DNN via carefully prepared input data with shape and fidelity variations to probe system responses to these variations. Two variants of the Visual Geometric Graphics with 19 neural layers (VGG19) was used for classification, with a total of 60,000 CMR images. Findings from this work provides insights on the importance of quality training data preparation and demonstrates the importance of data shape variability. It also provides gateway for computation performance optimization in training and validation time.
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Title: Improving self-supervised monocular depth estimation from videos using forward and backward consistency
Creator: Shen, Hui
Date: 2020
Description: Recently, there has been a rapid development in monocular depth estimation based on self-supervised learning. However, these existing self...
Show moreRecently, there has been a rapid development in monocular depth estimation based on self-supervised learning. However, these existing self-supervised learning methods are insufficient for estimating motion objects, occlusions, and large static areas. Uncertainty or vanishing easily occurs during depth inferencing. To address this problem, the model proposed in this thesis further explores the consistency in video and builds a multi-frame model for depth estimation; secondly, by taking advantage of the optical flow, a motion mask is generated, with additional photometric loss applied for those masked regions. Experiments are carried out on the KITTI dataset. The proposed model performs better than the baseline model in quantitative results, and as seen from the depth map, the scale uncertainty and depth incomplete situations are improved in motion objects and occlusions explicitly.
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