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Title: AMERICA'S NEW HOME
Creator: Klinger, Ryan J.
Date: 2013-04-30, 2013-05
Description: The role of the American nuclear single-family home has shifted significantly in the past 100 years.It began with the introduction and...
Show moreThe role of the American nuclear single-family home has shifted significantly in the past 100 years.It began with the introduction and expanded availability of the automobile by Henry Ford in 1908. Though private ownership of single-family homes steadily increased in the early part of the Twentieth Century, the majority of the existing housing market remained on rental. As a result of the stock market crash in 1929, the American housing market saw its first decline in the growth rate of new properties being built and occupied. Following the crash, the housing market experienced its first declining growth rate of the century. It was not until the late 1940s, with the end of World War II and the G.I. Bill’s introduction, that Americans saw an unprecedented increase in private homeownership nationwide. Pre-fabricated building processes, adapted from assembly-line production during World War II, radically transformed standard building methodologies for production of housing communities. Levittown, Pennsylvania was the primary example of this new fast-paced method of construction beginning in 1948. In the two decades following World War II, single-family homeownership surpassed rentals to become the majority of occupied housing units in the United States. The housing market took another hit in the economic decline of the 1970s. An economic downturn and an oil embargo that occurred during the 1970s produced a rising demand for rental properties that weakened the demand for newly-built singlefamily homes. In 1980 FHA revised its form of financing private homeownership and the American single-family home was now available to an expanded demographic of qualified owners. ix This resulted in another expansion of units being built and occupied from the later 1980s through the early 2000s. In 2007 America saw this come to an end; the American housing market crashed, forcing homeowners across the country into premature foreclosure. Private homeownership, once a central aspiration of the American Dream, is now shattered on a wide scale. As we move into the next phase of the American singlefamily home, many wonder if it will survive as a building model and reemerge as a prominent housing typology. It is the sole purpose of this investigation to establish the new face of the singlefamily home in an urban setting. The Gap Neighborhood on Chicago’s South Side will be used as an example. The investigation’s conclusion will provide the architectural community, as well as the target client-population, with a prototypical case study for the emerging single-family dwelling unit.It will serve as a comprehensive model that has reacted to the current issues that remain as a result of the housing crisis.
M.S. in Architecture, May 2013
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Title: INVESTIGATING THE IMPACT OF LOCAL REAL-TIME TRAFFIC INFORMATION PROVISION STRATEGY IN A CONNECTED VEHICLE SYSTEM
Creator: Chen, Shuwei
Date: 2013, 2013-12
Description: Nowadays connected vehicle systems (CVS), including vehicle-to-vehicle communication and vehicle-to-infrastructure communication. CVS has been...
Show moreNowadays connected vehicle systems (CVS), including vehicle-to-vehicle communication and vehicle-to-infrastructure communication. CVS has been recognized as a promising technology, which enables a new generation of in-vehicle routing guidance to help vehicle avoid traffic congestion with real-time traffic information provision and relief traffic congestion in network level. However, since current guidance system mainly relies on independent, selfish-routing mechanism and global real-time traffic information is uniformly provided to all users, it has a great potential that exceeding volume of traffic flow will be guided into some light traffic corridors within a short time period and cause its traffic congestions. This kind of traffic congestion may oscillate between two or several alternative corridors from time to time. Motived by the above view, the proposed research seeks to address this traffic congestion oscillation through a local information provision strategy. The range of the local information is scoped by the minimum bonding rectangle, and ellipse method, and A* algorithm is employed to provide route guidance for vehicles. The performance of the proposed information proposition strategy is measured by the network system travel time (i.e. system cost). A series of experiments, built upon a designed simulation framework using Borman expressway corridor network as test-bed, are conducted to investigate the performance of our information provision strategy under different traffic conditions, penetrations, information update frequency. Our results indicates that the proposed local information proposal strategy outperforms global information provision congested traffic condition. Under medium or high network traffic load, it produces 10-25% system travel time reduction as compared to global information provision case. Moreover, this benefit xii becomes more significant as more vehicle using real-time information to guide their trip (i.e. high penetration). In addition, we find that if the real-time information can be refreshed more frequently, the system performance would be improved further given vehicles are guided based on the proposed information provision strategy. Keyword: real-time information; TIS; simulation.
M.S. in Civil Engineering, December 2013
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Title: APPROXIMATION OF STOCHASTIC DIFFERENTIAL EQUATIONS WITH NON-GAUSSIAN NOISE AND APPLICATION TO A VOLATILITY MODEL
Creator: Jianhua, Wang
Date: 2015, 2015-05
Description: In recent decades, stochastic processes with non-Gaussian noise are widely utilized in financial models. The a-stable Levy motion, one type of...
Show moreIn recent decades, stochastic processes with non-Gaussian noise are widely utilized in financial models. The a-stable Levy motion, one type of non-Gaussian noise processes, provides robust data ts and events simulations in financial world. Due to "heavy" tails and path jumps property, the a-stable Levy motion modeling becomes extremely popular among financial decision makers and risk hedgers. The a-stable Levy motion, however, usually has neither closed form of probability density function nor the higher moments, which raises implement obstacles. We exhibited distributions of a-stable random variables by different values. In contrast to the Gaussian distribution, the a-stable distribution illustrated the "heavy" tails and shape skews with various parameters. We analyzed jump behaviors along with calculating tails probabilities. We exploited scenario simulation method to solve stochastic differential equations with a-stable Levy motions. Except Euler scheme, we derived two strong convergence 1.0 order numerical schemes via the Wagner-Platen expansion. After we executed the schemes on the Merton Jump-Diffusion model, we roughly proved the convergence order of the schemes. We successfully applied the derived schemes to simulate a sophisticated stochastic volatility model with skewed a-stable Levy motions. With the approximated underlying asset process, we priced an european call option value and visualized implied volatility curve. As the result, we concluded the logarithm of underlying asset follows a skewed distribution rather than a symmetric one.
M.S. in Applied Mathematics, May 2015
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Title: The Relationship Between Default and Volatility and Its Impact on Counterparty Credit Risk
Creator: Yang, Jiarui
Date: 2012-07-16, 2012-07
Description: This thesis presents a uni ed framework for studying the impact of the correlation between interest rate volatility and counterparty default...
Show moreThis thesis presents a uni ed framework for studying the impact of the correlation between interest rate volatility and counterparty default probability on the credit risk of collateralized interest-rate derivative contracts. A defaultable term structure model is proposed in which the default risk is correlated with interest rate volatility. In particular, an existence and uniqueness theorem of this model is proved. The pricing formula of credit derivatives under the proposed model is derived and the stochastic interest rate model and credit model are calibrated together . Finally, given all the parameters calibrated by the unscented Kalman lter, a sensitivity analysis of the impact of the correlation between interest rate volatility and a counterparty's default probability on the credit risk of collateralized interest-rate derivative contracts is presented.
Ph.D. in Applied Mathematics, July 2012
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Title: MEDIATORS FOR QUALITY OF LIFE IN SURVIVORS WITH BRAIN INJURY
Creator: Johnson, Kristina S.
Date: 2017, 2017-07
Description: Injury to the brain can range in cause, severity, and outcomes. Individuals with brain injury may experience both physical and cognitive...
Show moreInjury to the brain can range in cause, severity, and outcomes. Individuals with brain injury may experience both physical and cognitive impairments. Not only can a patient experience a wide range of symptoms, these symptoms also can vary drastically in severity. Research has shown that these symptoms play a role in a person’s quality of life following injury: the worse a person’s symptoms are, the lower they report their quality of life. However, recent research suggests that psychosocial factors may mediate the relationships between disability severity and quality of life across multiple rehabilitation populations. Two of the previously researched psychosocial constructs include social support and a sense of mastery over the disability or disease. The purpose of this study was to examine a structural model hypothesizing the mediating role of these two constructs on the relationship between symptom severity and quality of life among adults with brain injury. Participants in this study included 183 individuals with brain injury recruited through state brain injury organizations across the United States to participate in an online survey study. Using structural equation modeling (SEM), results demonstrated good model fit. (χ2(15, n = 183) = 13.68). Normed Bentler-Bonnet fit index (NFI) was .97; Goodness-of-Fit statistic (GFI) was .98; Adjusted-goodness-of-fit (AGFI) was .96; and Comparative fit index (CFI) was 1.00 (indices exceeding .90 indicate acceptable fit). Examination of the direct effects showed that perceived social support and sense of mastery are negatively associated with symptom severity (-.19 and -.66 respectively). Additionally, perceived social support was positively associated with mastery (.30). Both mastery and social support were moderately related to quality of life (.46 and .53, respectively). Rmediation analysis revealed perceived social support and mastery fully mediate the relationship between symptom severity and quality of life. Additionally, mastery partially mediated the relationship between social support and quality of life. These findings highlight the importance of incorporating these psychosocial factors into clinical interventions with hopes of increasing levels of perceived social support and mastery, and ultimately promoting quality of life. Further research is needed to explore the best strategies to increase support and mastery within the brain injury population and to identify additional psychosocial factors that may be mediators of quality of life.
M.S. in Psychology, July 2017
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Title: MODELING STRATEGIC COMPETITION, TACTICAL DESIGN, AND OPERATIONAL PLANNING TO IMPROVE SUPPLY CHAIN PERFORMANCE
Creator: Li, Chia-hang
Date: 2017, 2017-05
Description: A supply chain is a network of facilities responsible for the production and delivery of goods and services from the initial raw materials to...
Show moreA supply chain is a network of facilities responsible for the production and delivery of goods and services from the initial raw materials to the end customers. Supply chain management, therefore, involves management of activities both within and among the organizations throughout the chain at every level of business management. In this dissertation, we address three specific supply chain problems at three distinct level of business management: (1) Operational capacity and production planning; (2) Tactical closed-loop channel structure design; and (3) Strategic platform competition. In each work, we identify strategies that lead the supply chain improvements.
Ph.D. in Management Science, May 2017
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Title: INFILL HOUSE – HANOI, VIETNAM
Creator: Luu, Dung Q
Date: 2017, 2017-05
Description: In 1986, the ‘Economic Reform’ had brought significant economic success to Vietnam. The cities such as Hanoi, HoChiMinh City, and Danang,...
Show moreIn 1986, the ‘Economic Reform’ had brought significant economic success to Vietnam. The cities such as Hanoi, HoChiMinh City, and Danang, expanded enormously, and building activities increased to accommodate population growth and housing demand. The rapidly increased income allowed middle-class and upper-class families to pursue their dreams to own a private home. However, most housing projects were built without any city guidelines and lacked thoughtful design. [5] Because of high land prices and valuable frontage for business uses, most new private buildings and houses, 3 to 5 stories, were built to maximize their footprint, on very long and narrow frontage properties. Many of these infill houses were constructed, however they had limited daylight and poor natural ventilation. [4] For my thesis, I have studied typologies of the Vietnamese infill house. The study analyzes 4 types of infill sites based on different site access. In response to the analysis, six house schemes were developed on two of the types of long and narrow infill sites, in the high-density area of Hanoi, Vietnam. The design investigates different site strategies, and applies suitable building techniques to create viable living spaces that improve natural daylight and ventilation.
M.S. in Architecture, May 2017
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Title: NOVEL AUTONOMOUS DRONE ARCHITECTURE WITH WIRELESS NETWORK USING REAL-TIME SIGNAL PROCESSING AND MOBILE DEVICE FOR ASSISTING RESCUE SERVICE
Creator: Kim, Heekyung
Date: 2015, 2015-12
Description: The Autonomous Drone can be economically one of the effective and efficient tools for disaster management. In this research, for disaster...
Show moreThe Autonomous Drone can be economically one of the effective and efficient tools for disaster management. In this research, for disaster relief operations, Autonomous Drone Architecture with wireless network provides disaster assistance by tracking a survivor and getting important information from multiple sensors on it. [1] ADWN architecture consist of two different platforms, Raspberry pi and Arduino, to separate their roles of the process, which are like collecting the sensor data and sending control signal from Raspberry Pi to Arduino. Once gathering data from sensors and transmitting it to Raspberry Pi, it can analysis by applying signal processing formula in real-time. [2] In this case, Raspberry Pi can multitask process and use various language libraries such as OpenCV, Python, and others. Also, Raspberry Pi can add lots of sensors, a camera, and other kinds of boards. Using these features, transmitted data can be processed in real-time and be sending to Arduino to control with reduced error. These strength of ADWN architecture provides scalability and high availability to control drone as a disaster assistance.
M.S. in Electrical Engineering, December 2015
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Title: NOVEL 8-T CNFET SRAM CELL DESIGN FOR FUTURE ULTRA-LOW POWER MICROELECTRONICS
Creator: Kim, Youngbae
Date: 2016, 2016-05
Description: In deep sub-micron technology, leakage power consumption has become a major concern in VLSI circuits, especially for SRAM, which is used to...
Show moreIn deep sub-micron technology, leakage power consumption has become a major concern in VLSI circuits, especially for SRAM, which is used to build the cache in System-on-Chip (SOC). In this paper, a low power 8-T SRAM cell, based on carbon nanotube field effect transistor (CNFET), is proposed to circumvent the leakage power issue. Experiment datas show that the proposed SRAM cell can save 97.94% static power consumption compared to existing 6T CNFET SRAM cell. In case of writing, the proposed SRAM cell consumes 39.27% less power than the traditional SRAM cell for writing 0 and 58.79% less for writing 1. Also, because of the adoption of a colaborated voltage sense amplifier and independent read component, our 8T SRAM shows much improved delay performance, the delay is observed to reduce by approximate 30% in write operation and approximate 90% in read operation.
M.S. in Electrical Engineering, May 2016
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Title: LAM MUTANT LARVAE WITH MELANOTIC MASSES DO NOT SURVIVE WITH THEIR SIBLINGS THAT DO NOT DEVELOP MASSES
Creator: Cui, Yi
Date: 2012-04-28, 2012-05
Description: Melanotic masses are black nodules that form inside larvae and can be found in multiple mutants (Minakhina & Steward, 2006). There are two...
Show moreMelanotic masses are black nodules that form inside larvae and can be found in multiple mutants (Minakhina & Steward, 2006). There are two types of melanotic masses, the immune-related masses and the non-hemocyte-associated masses (Minakhina & Steward, 2006). Immune-related melanotic masses form in lam mutants (Markovic et.al, 2009). We now show all lam mutant larvae survived and 33% of the them developed melanotic masses when grown on fresh food, however, only 66% of them survived and none of them formed melanotic masses when living in the frassfood; the mixture of poo medium collected from wild type larvae vials. We find that frassfood lethality is not recipe specific, since the results were similar on normal yeast mashed potato medium and Nutrifly food. Our results also identified that it is bacteria in frassfood that kills lam mutant larvae with melanotic masses because the survival and melanotic mass incidence of lam mutant larvae were similar to fresh food when antibiotics were added to frassfood. However lam mutant larvae with melanotic masses are not generally sensitive to bacteria because all lam mutant larvae showed sensitivity to S. marcescens. Besides, since there is no frassfood lethality observed on Relish mutants, we propose that the humoral response was not affected in the lam mutants. The frassfood lethality to larvae with melanotic masses was also observed in neither cactus mutants nor the hopTum-l mutants, so the immune defects that caused melanotic masses in these two mutants do not lead to the frassfood lethality. Finally, we show that the frassfood lethality is not exactly the same in lam overexpressing larvae with melanotic masses and lam C overexpressing larvae with melanotic masses to the lam/Df larvae with melanotic masses. Thus it is possible that the gut immunity was affected in lam mutants with melanotic masses so that they were killed by the bacteria in frassfood.
M.S. in Biology, May 2012
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Title: MEASUREMENT MODEL OF IONOSPHERIC ELECTRON CONTENT WITH CYGNSS
Creator: Zhang, Jordi Xing
Date: 2013, 2013-12
Description: Global ionospheric imaging is currently limited by a lack of significant quantities of observations over the oceans. This deficiency of...
Show moreGlobal ionospheric imaging is currently limited by a lack of significant quantities of observations over the oceans. This deficiency of measurements arises because coverage from Global Navigation Satellite System (GNSS) remote sensing tools is typically limited to regions over land by using ground-based receivers. This dissertation presents the opportunity to estimate ionospheric data over the oceans by using reflected GNSS signals received by the upcoming Low-Earth Orbit (LEO) satellite constellation Cyclone Global Navigation Satellite System (CYGNSS). CYGNSS is currently being developed by NASA primarily for hurricane predictions. Its eight micro-satellites will have a single-frequency Global Positioning System (GPS) receiver onboard and zenith and nadir antennas that collect GPS signals reflecting from the ocean surface of Earth. This study investigates the possibility of leveraging CYGNSS for a secondary science mission, using GNSS-Reflectometry for ionospheric remote sensing. A mathematical model is developed that retrieves ionospheric electron content by using ranging measurements from direct and ocean-reflected GPS signals onboard CYGNSS satellites. The measurement model terms can be grouped as geometric raypath and signal refraction components due to the troposphere and the ionosphere. Each term of the model is analyzed and quantified by applying fundamental physical principles and empirical models. The implementation of a multi-orbit simulation estimates the magnitudes of anticipated electron content measurements with CYGNSS.
M.S. in Mechanical and Aerospace Engineering, December 2013
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Title: THE VAPORIZATION PHENOMENA OF FUEL DROPLETS EXPOSED TO ASYMMETRIC RADIANT HEATING USING PLANAR LASER-INDUCED FLUORESCENCE
Creator: Ammigan, Kavin
Date: 2012-04-17, 2012-05
Description: Droplet vaporization under asymmetric conditions is prevalent in many combustion related devices where fuel droplets may either experience...
Show moreDroplet vaporization under asymmetric conditions is prevalent in many combustion related devices where fuel droplets may either experience asymmetric thermal radiant heating or travel in velocity and temperature gradients. Asymmetric radiant heating is particularly common in spray flames, counter-flow diffusion flames, regions close to the walls of conventional combustion chambers and more importantly in liquid-fueled microcombustors. In this study, experiments are carried out to observe how droplets vaporize when exposed to asymmetric radiant heating. The experimental set-up consists of applying radiant heating, through a radiant panel heater, to one face of a monodisperse droplet stream while using the planar-laser induced fluorescence (PLIF) diagnostic tool to reveal the spatial vapor distribution around vaporizing droplets. Since most fuels are made up of multiple components, bicomponent droplets are also investigated. Pure acetone droplets as well as mixtures of acetone/alkanes (octane and hexane) and acetone/alcohols (ethanol and 2-propanol) droplets are investigated. Results in the form of PLIF images, reveal asymmetric vapor distributions around the droplets with the apparent induction of Stefan flow from the irradiated droplet surface. Such phenomena have not previously been reported in the literature and have relevance to the overall fuel vaporization process as well as subsequent ignition and pollutant formation processes. To further investigate the experimental results, a convective and radiative heat transfer model is employed to simulate the droplets under corresponding experimental conditions. Results from the model show convective cooling and a strong thermal radiation absorption near the droplets’ surface. The induced asymmetric Stefan flow observed experimentally is therefore a consequence of the high thermal radiation absorption at the droplets’ surface. This study gives both experimental and theoretical results of the vaporization phenomena of asymmetrically irradiated fuel droplets with varying compositions, diameters and irradiation temperatures.
Ph.D. in Mechanical and Aerospace Engineering, May 2012
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Title: Towards the Robust Situation Awareness in Distribution Management System
Creator: Yao, Yiyun
Date: 2019
Description: In distribution systems, intermittent distributed energy resources (DERs) and vol-atile loads will result in a wide variation of system...
Show moreIn distribution systems, intermittent distributed energy resources (DERs) and vol-atile loads will result in a wide variation of system operating conditions. This motivates the establishment of modern distribution management system (DMS) for real-time net-work monitoring, resource optimization, and demand management. Three subproblems are mainly discussed when establishing the robust situation awareness in DMS. A measurement placement problem is proposed to decide the optimal locations and types of measurements to be placed in the distribution systems that minimize the worst-case estimation errors for DSSE over different system operating conditions. Four indices of the estimation error covariance matrix are chosen as the criteria of accuracy. The proposed measurement placement problem is formulated as a mixed-integer sem-idefinite programming (MISDP) problem. To avoid the combinatorial complexity, a con-vex relaxation, followed by a local optimization method, is employed to solve the MISDP problem. The proposed problem and the effectiveness of the proposed solution method are numerically demonstrated on the 33-bus distribution system.Distribution system state estimation (DSSE) is one of the vital components in the next-generation distribution management system (DMS), which allows the operators to monitor the entire system’s operating conditions. Due to the lack of real-time measurements, DSSE has to process measurements whose quality varies significantly across different sources, which causes convergence issue to the Gauss-Newton solver. In this chapter, a semidefinite programming (SDP) framework is developed to reformulate the DSSE problem into a rank- constrained SDP problem. One challenge of this technique is the nonconvex rank-one constraint, which is generally relaxed. However, the relaxed SDP-DSSE problem cannot guarantee a rank-one solution and hence lose optimality. Therefore, we propose two solution approaches, namely the rank reduction approach and the convex iteration approach, to obtain rank-one solutions for the SDP-DSSE problem. The proposed model and the effectiveness of the proposed solution approaches are numerically demonstrated on the IEEE 13-, 34-bus, and 123-bus distribution systems.A SE algorithm based on random measurements selection, which is inspired by the concept of moving target defense (MTD), is developed to prevent and mitigate stealthy cyber-attacks. With the proposed SE, a library of selected measurements scenarios is first generated offline given the available measurements and network topology. During online operation, multiple weighted least square (WLS) based SEs are processed in parallel with randomly picked scenarios from the library. The final solution is selected based on the largest normalized residuals with regard to individual scenarios. The effectiveness of the proposed SE is examined by attack-defense experiments on IEEE 14-bus, 39-bus, 57-bus, and 118-bus systems.
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Title: Statistical Experimental Design and Modeling for Complex Data
Creator: Huang, Xiao
Date: 2018
Description: The ability to handle complex data is essential for new research findings and business success today. With increased complexity, data can...
Show moreThe ability to handle complex data is essential for new research findings and business success today. With increased complexity, data can either be difficult to collect with designed experiments or be difficult to analyze with statistical models. Both kinds of difficulties are addressed in this dissertation.The first part of this dissertation (Chapter 2 and 3) addresses the issue of complex data collection by considering two design of experiment problems. In chapter 2, we consider Bayesian A-optimal design problem under a hierarchical probabilistic model involving both quantitative and qualitative response variables. The objective function was derived and an efficient optimization algorithm was developed. In chapter 3, we consider the A/B-testing problem and propose a novel discrepancy-based approach for designing such an experiment. As the numerical examples show, the A/B-testing experiments designed in this way achieve better group balance and parametric estimation results.In the second part of this dissertation (Chapter 4 and 5), we focus on analyzing complex data with Gaussian process (GP) models. Gaussian process model is widely used for analyzing data with highly nonlinear relationships and emulating complex systems. In Chapter 4, we apply and extend GP model to analyze the in-cylinder pressure data resulted from experiments on a newly-developed dual fuel engine. The resulted model incorporates different data types and achieves good prediction accuracy. In Chapter 5, a generalized functional ANOVA GP model is proposed to tackle the difficulty resulted from high-dimensional feature space, and we develop an efficient algorithm for building such a model from the perspective of multiple kernel learning. The proposed approach outperforms traditional MLE-based GP models on both computational efficiency and prediction accuracy.
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Title: CHARACTERIZATION OF NOVEL PULSED UV-LIGHT SYSTEMS FOR INACTIVATION OF LISTERIA MONOCYTOGENES IN APPLE JUICE AND ON APPLE SURFACE
Creator: Malik, Sargun
Date: 2018
Description: Pulsed light processing can effectively inactivate microorganisms from the surface of foods or in transparent liquid foods. Pulsed light...
Show morePulsed light processing can effectively inactivate microorganisms from the surface of foods or in transparent liquid foods. Pulsed light systems currently available in the market operate at a fixed pulse duration and frequency and might not be optimized for microbial inactivation. A novel pulsed light system (Model X 1100; Xenon Corporation, USA) enables the researchers to adjust various parameters including pulse duration (100-7000μsec), voltage(1000-3000V), frequency (0.1-20Hz),% of energy (0-100%), and energy (up to 9J /cm2 / pulse of optical energy or 2433J / pulse of electrical energy ) . This study evaluated the effect of various parameters (treatment time, voltage, frequency, energy / pulse) on inactivation of Listeria monocytogenes in buffered peptone water (BPW), apple juice, and apple surface. For liquids, a 4-mL of sample (4-mmdepth) artificially inoculated with Listeria monocytogenes was treated in a quartz Petri dish (5.5-cmdiameter). For solid food, the top surface (skin side) of a slice of apple (1×1×0.5cm）was inoculated and exposed to various pulsed light treatment conditions. The results indicated that the impact of these factors vary as many of these factors are inter-related. In general, increasing the frequency, input voltage, pulse duration, and percentage of energy, increased the microbial reduction at the tested conditions (p<0.05). For instance, reductions of 1.21and 5.47 log10 CFU/mL were obtained in BPW and reductions of 1.35 and 4.70 log10 CFU/mL was acquired in apple juice, at 0.1and 0.82Hz, respectively, for a 20-sec treatment at 2500V (50% energy,700 μsec pulse width). Increased energy per pulse resulted in increased microbial reduction. For example, reductions of 2.30, 5.59, 6.69, and 6.69 log10 CFU/mL were obtained at 645, 1241, 1837, and 2433J/ pulse of electrical energy, respectively, in apple juice. Similarly, reductions of 5.34, 6.45, 6.02, and 6.56 log10CFU/mL were obtained at 645, 1241, 1837, and 2433J/ pulse, respectively in BPW. Lower reduction was obtained from the skin surface of the apple, for instance, reductions of 0.70 and 1.19 log10 CFU/ slice were obtained at 0.10 and 0.82 Hz, respectively, after a 10 seconds treatment at 2500V (50%energy). Similarly, reductions of 2.44, 2.43, 3.39, and 3.48 log10 CFU/ slice were obtained at 645, 1241, 1837, and 2433J/ pulse of electrical energy, respectively, after a 15 seconds treatment at 3000V (0.2Hz). The results were similar to the pulsed light treatment with RC 800 system (Xenon Corporation, USA). Absorption of pulsed light energy resulted in temperature increase in the products. Temperature increase of up to 11°C was observed at the treated conditions. The results suggest that this novel pulsed light system can potentially be used for inactivation of Listeria monocytogenes.
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Title: ANALYSIS AND OPTIMIZATION OF VIBRATION AND ACOUSTIC NOISE IN SWITCHED RELUCTANCE MACHINES
Creator: Yaman, Selin
Date: 2019
Description: One of the main drawbacks of switched reluctance machines (SRM) is the vibration and high acoustic noise compared to other electrical motors....
Show moreOne of the main drawbacks of switched reluctance machines (SRM) is the vibration and high acoustic noise compared to other electrical motors. The root cause of the high level of acoustic noise is radial forces with high harmonic content. These harmonics may trigger resonant modes in the stator and cause the machine to create high vibration and acoustic noise. To better understand the factors influencing vibration and acoustic noise in an SRM, this dissertation first develops a multi-physics model in ANSYS Workbench environment and carries out a comprehensive analysis of multiple variations in stator and rotor geometries. Based on this understanding, this dissertation identifies distinct factors affecting noise in the machine, which are affected by electromagnetic design and power electronic control. From the electromagnetic perspective, geometrical optimizations in the stator and rotor structures are evaluated to understand the impact on NVH (noise, vibration and harshness) performance. This background is used to develop a fast geometry-sensitive analytical approach to reduce acoustic noise in the machine. While optimizing the geometry for a silent machine design, different design of experiments (DoE) methods and response surface (RS) optimization methods are also compared and presented. Furthermore, material analysis is included in structural design, where high flux material effect on vibration and acoustic noise is observed. The second topic of the NVH analysis is power electronic and switching solutions. In this study, multiple basic and advanced switching techniques have been considered and optimized to reduce acoustic noise under a preset efficiency constraint. Further, a time efficient model of SRM is introduced with vibro-acoustic noise perspective by developing a computationally cost effective SRM modeling. By using this analytical time-efficient NVH model, a current shape optimization is implemented, and results are discussed. Finally, experimental validations are provided for NVH and psychoacoustics analysis for different operating conditions and current control methods.
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Title: THE K+ ACTIVATION MECHANISM OF V. CHOLERAE APBE
Creator: Yang, Jun
Date: 2019
Description: ABSTRACTNa+-translocating NADH: quinone oxidoreductase (NQR) is a protein complex that exists in the respiratory chain of Vibrio cholerae....
Show moreABSTRACTNa+-translocating NADH: quinone oxidoreductase (NQR) is a protein complex that exists in the respiratory chain of Vibrio cholerae. This complex can transport sodium ions to the outside of the plasma membrane. NQR has important influences on the survival and pathogenesis of V. cholerae. Two of the subunits of NQR, NqrC and NqrB, has a covalently bound FMN coenzyme. This FMN is necessary for the activity of NQR complex. A protein, alternative pyrimidine biosynthesis protein (ApbE) can transfer the FMN molecule to NqrB and NqrC covalently. And ApbE is also important to some other flavoproteins like the NOS and RNF. The ApbE protein use the FAD as the substrate to transfer the FMN group to the NqrC and NqrB apo-enzyme. Mg2+ is necessary for the activity of ApbE protein. Sodium and potassium ion are not necessary, but potassium ion can increase the activity of the ApbE by about ten times. In order to understand the mechanism of potassium activation of ApbE, several potassium binding sites were identified by molecular docking in this study. Point mutations of the amino acid residues constituting these sites were performed. The FMN transfer activity and affinity to potassium ions of these mutants were measured. The results suggest that when G125 was mutated, the binding of potassium ions was affected. Therefore, the structure composed of P126 and G125 may play a significant role in the activation of ApbE potassium ions.
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Title: A BOUNDARY INTEGRAL METHOD FOR COMPUTING THE FORCES OF MOVING BEADS IN A THREE-DIMENSIONAL LINEAR VISCOELASTIC FLOW
Creator: Hernandez, Francisco
Date: 2019
Description: Computing the forces acting on particles in fluids is fundamental to understanding particle dynamics and interactions. In this thesis, we...
Show moreComputing the forces acting on particles in fluids is fundamental to understanding particle dynamics and interactions. In this thesis, we study the dynamics of a two-particle system in a three-dimensional linear viscoelastic flow. Using a correspondence principle between unsteady Stokes flow and viscoelastic flow, we reformulate the problem and derive a boundary integral formulation that solves the Brinkman’s equation in the Fourier domain. We show that computational costs can be reduced by carefully eliminating the double-layer potential, and that a unique solution can be obtained by desingularizing the equation. We develop a highly accurate numerical integration scheme to evaluate the resulting boundary integrals. We solve the backward problem by making use of our numerical integration scheme, variable transformations, generalized minimum residual (GMRES) method, and spherical harmonic interpolations. In particular, spherical harmonic interpolations ensure that this numerical scheme is of high accuracy. Our method also has the advantage of working for both unsteady Stokes and linear viscoelastic flow by appropriately adjusting the oscillation frequency. Our numerical results are in agreement with the exact solution for a single-particle system, as well as the asymptotic solution for large particle separation in the two-particle system. Last, we analyze the numerical results for high oscillation frequencies and small particle separation. Our numerical method is shown to only depend on the frequency parameter and the distance between the particles. We find that for high frequencies, the forces on the particles behave differently for unsteady Stokes and linear viscoelastic flows.
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Title: NON-INTRUSIVE LOAD MONITORING IN RESIDENTIAL BUILDING
Creator: Lu, Mengqi
Date: 2019
Description: Non-Intrusive Load Monitoring (NILM) is an important application to monitor household appliance activities and provide related information to...
Show moreNon-Intrusive Load Monitoring (NILM) is an important application to monitor household appliance activities and provide related information to house owner or/and utility company via a single sensor installed at the electrical entry of the house. With this information, utilities can do many tasks such as energy conservation, planning generation more wisely, and demand response (DR) study. For house owners, they can understand their bill more clearly and make monthly budget plan. For researchers, NILM system is a good way to do the energy management in buildings and help to provide power information for smart homes design. Thus, an increasing number of new algorithms have been developed in recent years. In these algorithms, researchers either use existing public datasets or collect their own data which causes such problems as insufficiency of electrical parameters, missing of ground-truth data, absence of many appliances, and lack of appliance information. To solve these problems, this dissertation presents a model-based platform for NILM system development, namely Functional Intrusive Load Monitor (FILM). By using this platform, the state transitions and activities of all the involved appliances can be preset by researchers, and multiple electrical parameters such as harmonics and power factor can be monitored or calculated. This platform will help researchers save the time of collecting experimental data, utilize precise control of individual appliance activities, and develop load signatures of devices. Moreover, event detection, as an important part of event-based NILM methods, has a direct impact on the accuracy of the ultimate load disaggregation results in the entire NILM framework. This dissertation also presents a hybrid event detection approach for relatively complex household load datasets that include appliances with long transients, high fluctuations, and/or near-simultaneous actions. The structure, steps, and working principle of this approach are described in detail. The proposed approach does not require additional information about household appliances, nor does it require any training sets.Case studies on different datasets are conducted to evaluate the performance of the proposed approach in comparison with several existing approaches including log likelihood ratio detector with maxima (LLD-Max) approach, active window-based (AWB) approach, and generalized likelihood ratio (GLR) approach. Results show that the proposed approach works well in detecting events in complex household load datasets and performs better than the existing approaches.
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Title: Performance and NOx Emissions Control for Modern Diesel Engine and SCR Systems
Creator: Sui, Wenbo
Date: 2018
Description: High combustion efficiency and low emissions output are two important targets for modern diesel engine system designs and for their control...
Show moreHigh combustion efficiency and low emissions output are two important targets for modern diesel engine system designs and for their control systems. In this work, different control strategies are investigated to improve the combustion efficiency of engines and to reduce the nitrogen oxide (NOx) emissions of vehicles.There are three main contributions of this work. First, to address emissions concerns, neural network based control algorithms were applied to selective catalyst reduction (SCR) systems. Compared with conventional model-based control, the control strategy based on neural networks can reduce the amount of time and cost required for model identification for these complex systems. The neural network controllers are developed and tested in simulations at different operating conditions for the Fe-zeolite SCR system first. In addition, methods for Jacobian information prediction are also discussed. According to the simulation results, the control strategy based on neural networks can track the desired reference and have reasonable NOx reduction efficiencies in most operating conditions. However, the NOx reduction efficiencies are poor at the low temperature situations in Fe-zeolite SCR systems. To improve this issue, the neural network control strategy was applied to a Cu-zeolite SCR and an improvement in the NOx reduction efficiencies was observed with reductions over 98% at different operating conditions. Second, to address efficiency concerns, a nonlinear model-based combustion control approach was investigated. This control approach aims to track a desired optimal combustion timing and leverages a combustion phasing model for a diesel engine that was developed and validated as part of this work. An intake gas properties model is also developed to capture the cylinder-to-cylinder difference of the temperature and pressure at intake valve closing (IVC). An adaptive controller and model-based controller were then designed for the diesel engine. These control strategies are evaluated in simulations and results show that the combustion phasing control system can track the optimal CA50 (crank angle at 50% mass of fuel burned). The combustion phasing control strategies were also expanded for use on dual-fuel compression ignition engines. The dual-fuel compression ignition engine is being considered as one of the candidates for the next generation of the modern diesel engines due to its ability to achieve high combustion efficiency and low emissions. To track the optimal combustion phasing in a dual-fuel engine, a non-linear combustion phasing model for this application was also developed and calibrated based on simulations. With the control-oriented model, controllers based on an adaptive control strategy and a feedforward control strategy are designed. The controllers are evaluated and shown to track the reference CA50s at varied operating conditions.
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