Search results

Title: TWO ESSAYS IN SUSTAINABILITY AND ASSET RETURN PREDICTABILITY
Creator: Nguyen, Lanh Vu Thuc
Date: 2021
Description: Our paper consists of two chapters in Financial Modeling for Sustainability and Asset Return Predictability. Recent developments in data...
Show moreOur paper consists of two chapters in Financial Modeling for Sustainability and Asset Return Predictability. Recent developments in data scraping and analytical methods have enhanced the possibility to construct the data and modeling required to examine the topics in each chapter. Chapter 1 proposes a simple yet strategic model involving a personal financial system to achieve a sustainable and prosperous future. The proposed model emphasizes the optimization of carbon footprints of one person at a time through the decentralization of the electricity use. While describing steps to develop a decentralized system considering electricity as a credit product, the model also underlines the importance of geographic economic dimensions and energy market prices due to their anticipated impact on the effectiveness of designing strategies for optimizing individuals’ energy use habits. Geographical conditions as well as market electricity prices can be used to signal individual energy use scores over time, therefore could also be instrumental in customizing energy use habits as the users realize variations in their energy use scores resulting from hourly electricity price changes at their locations. In other words, not only the changes in the individual’s behavior, but also the changes in the geographical conditions and community of users will affect the improvement of energy use behaviors of an individual over time using our model. We believe that the proposed model can be efficiently adopted to take on challenges threatening the future sustainability. While describing the basic characteristics of the model, we also open the possibility for future studies its capabilities to reduce carbon footprints from other societal choices, for example, using water, managing waste, or designing sustainable transportation systems. In Chapter 2, we examine asset return predictability, which is an important topic in finance with rich literature. Much of the current literature considers dividend yield as the main predictor for expected returns, and the main discussion centers around confirming or rejecting the predictive power of dividend yield with mixed evidence. However, dividend payments have been consistently declining and public firms have been increasingly using stock repurchase as the alternative to return values to shareholders. We aim to contribute to the literature by investigating a panel data of total equity payout, which takes into account not only dividend payout but also other forms of payment such as stock repurchase, as the main predictor for expected returns. In the asset return predictability literature, existing studies gather stock repurchase data from financial statements. In this paper, we manually construct our database of returns and payouts of public companies from various sources to create precise firm-level total equity payout dataset without relying on approximations from annual financial statements. This study adds to understanding of total equity payout and stock returns by analyzing a finer granularity than an annum and cross section of stock returns.
Show less

Title: A SCALABLE AND CUSTOMIZABLE SIMULATION PLATFORM FOR ACCURATE QUANTUM NETWORK DESIGN AND EVALUATION
Creator: Wu, Xiaoliang
Date: 2021
Description: Recent advances in quantum information science enabled the development of quantum communication network prototypes and created an opportunity...
Show moreRecent advances in quantum information science enabled the development of quantum communication network prototypes and created an opportunity to study full-stack quantum network architectures. The scale and complexity of quantum networks require cost-efficient means for testing and evaluation. Simulators allow for testing hardware, protocols, and applications cost-effectively before constructing experimental networks. This work develops SeQUeNCe, a comprehensive, customizable quantum network simulator. We have explored SeQUeNCe for quantum communication network evaluation. We use SeQUeNCe to study the performance of the quantum network with different hardware and applications. Additionally, we extend SeQUeNCe to a parallel discrete-event simulator by using the message passing interface (MPI). We comprehensively analyze the benefit and overhead of parallelization. The parallelization technique significantly increases the scalability of SeQUeNCe. In the future, we would like to improve SeQUeNCe in three aspects. First, we plan to continue reducing overhead from parallelization and increasing the scalability of SeQUeNCe. Second, we plan to investigate means to model quantum memory, entanglement protocols, and control protocols to enrich simulation models in the SeQUeNCe library. Third, we plan to integrate hardware with SeQUeNCe to enable high-fidelity analysis.
Show less

Title: CARING FOR THE CAREGIVER: INTERPERSONAL FACTORS AND DEPRESSION AS PARALLEL-SERIAL MEDIATORS BETWEEN STIGMA AND SUICIDAL IDEATION
Creator: Tsen, Jonathan Y.
Date: 2022
Description: Background/Objectives: This study applied Joiner's Interpersonal PsychologicalTheory to a caregiver population, by describing relationships...
Show moreBackground/Objectives: This study applied Joiner's Interpersonal PsychologicalTheory to a caregiver population, by describing relationships among affiliate stigma, thwarted-belongingess (TB), perceived-burdensomeness (PB), and depression, and suicidal ideation (SI). Participants/Setting: 243 adult caregivers participated in this study via Prolific Academic and caregiver-related websites. Design/Main Outcome Measures: This study used a cross-sectional, survey-based design including demographics, the Affiliate Stigma Scale (α=.93), Interpersonal Needs Questionnaire-15 (α=.95), Center of Epidemiology Studies–Depression-10 (α=.90), and Depressive Symptom Inventory— Suicide Subscale (α = .91) via Qualtrics. Analyses run on SPSSv27/Hayes’ PROCESS macro. Results: Parallel-serial mediation found after controlling for covariates that the total indirect effect of affiliate stigma on SI through both TB and PB then through depression was significant, B = .0271, SE = .0062, β = .1659, 95%CI [.0152, .0393]. Conclusions: Findings indicated that affiliate stigma indirectly affected SI through both TB and PB then through depression. Interventions to improve caregiver wellbeing should capitalize on both improving interpersonal functioning and depressive symptoms in tandem in order to reduce SI risk.
Show less

Title: SYNTHESIS AND APPLICATION OF ORGANOMETALLIC PRECURSORS FOR TUNGSTEN AND MOLYBDENUM SULFIDE
Creator: Liu, Bo
Date: 2021
Description: Transition metal chalcogenides (TMCs) have unique properties. They are promising materials for the next generation electrical devices due to...
Show moreTransition metal chalcogenides (TMCs) have unique properties. They are promising materials for the next generation electrical devices due to their suitable band gap, outstanding electron mobility, and controllable atomic thickness. In the last few decades, atomic layer deposition (ALD) has been one of the hottest research frontiers for the fabrication of TMCs films. Signification progress has been made on the varieties of material grown by ALD and the improvement of ALD equipment. However, the fast-evolving microelectronic industry set higher requirements for the ALD application. In the potential electronic fabrication process, low-temperature preparation and non-corrosive procedure are critical for the advanced device architecture. Thus the novel precursor development and the investigation of reaction mechanism are necessary. In addition, as the comprehensive research of film deposition, the prevailing crystallographic defects on the as-prepared films are another appealing thing for us to think about and try to eliminate for better film quality. Therefore, this dissertation will describe the precursor ligand design and its effect on the morphology, the development of W/Mo precursors for tungsten/molybdenum disulfide, and the defect passivation of tungsten diselenide films.In chapter 2, a series of heteroleptic tungsten precursors of tetrathiotungstates (WS42-) were prepared through the facile ligand transfer method. Ligand variation has a significant effect on the crystallinity of the resulting tetrathiotungstate products. Crystalline tetrathiotungstates with preferred orientation were prepared from the reaction of synthesized precursors with H2S at room temperature. Results indicated the morphologies and crystallinities of the tetrathiotungstates can be well controlled by their ligand behaviors which give us a better understanding of the growth mechanism. Chapters 3 and 4 focus on the development of W and Mo precursors for W/Mo disulfide and their performance in wet chemistry reactions and ALD. WS2 can be synthesized at the ambient temperature in solution by the non-redox reaction. WS2 film growth can be achieved at the exciting low temperature of 125°C by ALD. Based on the performance of the tungsten precursor, a new molybdenum dimer precursor with improved reactivity was synthesized, and MoSx can be prepared at the ambient temperature in seconds. X-ray absorption spectroscopy (XAS) was also utilized to investigate the interaction between the organometallic precursor and the SiO2 surface. Chapter 5 will focus on the defect passivation of WSe2 films for the improvement of their electrical performance. Precursors were synthesized, and the wet chemistry method was designed for oxidation removal and vacancy healing. Raman spectroscopy was used as the express characterization method to reveal the treatment results. A promising healing reagent was screened out, and the repaired films were fabricated to field-effect transistors (FETs) for electrical measurements. The final results showed the electrical performance of the WSe2 films was improved after the convenient chemical treatment.
Show less

Title: Control and Operation of Microgrids and Networked Microgrids
Creator: Sheikholeslami, Mehrdad
Date: 2022
Description: This dissertation presents the practical operation and control of microgrids and networked microgrids, particularly, the networked IIT Campus...
Show moreThis dissertation presents the practical operation and control of microgrids and networked microgrids, particularly, the networked IIT Campus Microgrid (ICM) and Bronzeville Community Microgrid (BCM). Microgrids (MGs) provide a potential solution to accommodating renewable and distributed energy resources (DERs). MGs and the networked form of MGs, i.e., networked microgrids or NMGs, have received significant attention in the past two decades. However, several details are often neglected in the literature that need to be considered for the practical operations of MGs and NMGs. First, there is a need for a step-by-step sequence of operations (SOO) that clearly defines the procedures for changing the operation modes of MGs and NMGs for their reliable and resilient operation. Second, there is a need to develop new control strategies for the centralized and distributed control of MGs and NMGs that are resilient to extreme events and are also more sustainable than the ones available in the literature. Third, there is a need for developing the model of MGs and NMGs in a real-time simulator to safely evaluate the performance of the control and operation of MGs and NMGs. Finally, to close the engineering loop, there is a need to connect the digital and physical layers which are known as digital twins. This dissertation proposes solutions for these four requirements and presents results to evaluate the performance of the proposed solutions. First, an SOO is proposed to enable the reliable and safe transition between different microgrid operation modes. The proposed SOO is adaptable to any MG and NMG with minor modifications. Second, for the centralized control, a DER control model is proposed that allows for the regulated power exchange between networked MGs to ensure information privacy and respect the electrical boundary of each MG. For the distributed control, two control schemes are proposed that are resilient to extreme cases, allow the integration of renewable energy resources (RES), and require the minimum intervention of the operators. Third, several techniques are proposed that can be adopted for developing the real-time models of MGs and NMGs. Finally, as a proof of concept, a digital twin of a microgrid with connections between the physical and digital layers is implemented and tested. The IIT Campus Microgrid (ICM) and Bronzeville Community Microgrid (BCM), as well as their networked form (networked ICM-BCM), are selected as the practical testbeds and are modeled in Real-time Digital Simulator (RTDS). The RTDS model is interfaced with microgrid master controllers (MMC) for real-time data exchange and the performance of the MMCs and the distributed control strategies are tested to illustrate the importance of adopted methods in the real-time control of MGs and NMGs. Finally, a proof of concept for the digital twin of ICM is presented.
Show less

Title: Essays on Clean Energy Finance and Cryptocurrency Market
Creator: Xie, Yao
Date: 2021
Description: This dissertation includes four essays with several empirical investigations in the areas of clean energy finance and cryptocurrencies.In the...
Show moreThis dissertation includes four essays with several empirical investigations in the areas of clean energy finance and cryptocurrencies.In the first essay, I investigate the heterogeneous relationship between various determinants of the clean energy market across all subsectors of the clean energy stock market. My findings reveal that VIX is the most significant predictor of all clean energy subsectors conditional volatility. During the COVID-19 stress period, economic uncertainty measures become more significant measures. The heterogeneity of clean energy market persists in the out-of-sample results. These results suggest that portfolio diversification for different clean energy subsector is necessary. In the second essay, I study the safe haven property of several volatility indexes on clean energy subsectors. I compare the current COVID-19 stress period and the time before. The results show that market volatility and commodity volatility are good safe haven assets during the COVID-19 period. But they are not safe haven assets against the clean energy subsector before the pandemic period. Among all volatility indexes, gold volatility index is the most effective safe haven assets. In the third essay, I investigate the characteristics of Bitcoin as a financial asset. A comprehensive set of information variables under five categories: macroeconomics, blockchain technology, other markets, stress level, and investor sentiment. The empirical results show that blockchain technology, stress level and investor sentiment have strong predicting power on Bitcoin returns. In the fourth essay, I aim to study how extreme sentiment measures from Google Trend and Wikipedia Pageviews affect both traditional cryptocurrency, such as Bitcoin and stablecoin, like Tether. Our results show that Tether’s return is not affected by the extreme sentiment measures during the COVID-19 stress period which suggests that stablecoin can offer price stability.
Show less

Title: Relations Between Inhibitory Control, Teacher Support, and Externalizing Behaviors in Elementary School Children
Creator: Kurian, Jennifer
Date: 2021
Description: The aim of this study was to examine the relation between child hot and cool inhibitory control (IC) at the beginning of the school year and...
Show moreThe aim of this study was to examine the relation between child hot and cool inhibitory control (IC) at the beginning of the school year and externalizing behaviors at the end of the year, and to determine if teacher support moderates this relation in early elementary school. Participants included a diverse sample of 138 children in grades 1 (n = 62) and 2 (n = 76), with a mean age of 7.2 years (SD = 10.1 months), about half of whom were male. Hot IC was assessed with the Puzzle Box Task and cool IC with the Happy-Sad Stroop Task. Teacher support was rated by independent observers using the Adapted Teaching Style Rating Scale. A composite teacher-report score based on ratings on subscales from two measures, the Strengths and Weaknesses of Attention Deficit Hyperactive Disorder Symptoms and Normal Behavior and the Strengths and Difficulties Questionnaire, was used to assess externalizing behavior at both time points. Results of hierarchical regression analyses revealed that, contrary to expectation, neither hot nor cool IC significantly predicted child externalizing behavior at the end of the school year. A moderation analysis also failed to show a significant moderating effect for teacher support. The only variable that significantly predicted externalizing behavior at the end of the year was externalizing behavior at the beginning of the year. There were significant concurrent associations between hot IC and externalizing behaviors at both the beginning and end of the school year. These findings suggest that externalizing behaviors in early elementary school are relatively stable. Thus, early and comprehensive intervention may be critical for implementing prevention strategies designed to increase self-regulation and thereby decrease externalizing behaviors after formal school entry.
Show less

Title: ANALYTICAL APPROACH TO ESTIMATE ROTOR TEMPERATURE IN SWITCHED RELUCTANCE MOTOR
Creator: Koujalagi, Shweta Manohar
Date: 2022
Description: Motors contribute most of the loads. Motors find major applications in automobile industries, household appliances, industrial equipment, and...
Show moreMotors contribute most of the loads. Motors find major applications in automobile industries, household appliances, industrial equipment, and other areas. With the time, engineers and industries found some of the drawbacks or disadvantages of using induction motors in certain applications. They started developing other types of motors that are more efficient than existing ones. Among those, switched reluctance motor, referred as SRM is the one. SRMs are simple in construction, rugged and highly efficient motors.Even though SRM has higher efficiency, it still contribute some losses in the form of heat which will increase the temperature of SRM. If the temperature increases beyond certain limit, cable insulation fails, degrades rotor capability of aligning characteristics, damages bearings, etc. Therefore, it is important to understand the flow of heat in SRM. This thesis focuses on heat transfer analysis from stator coil to rotor of SRM using analytical method and numerical method such as finite element analysis from available coil temperature without using any kind of sensors. Analytical and FEA models are built separately to obtained rotor temperatures at various coil temperatures and rotor speeds. Finally, analytical results are validated with FEA model results. Therefore, once the rotor temperature is estimated accurately, model can be implemented in automotive and other industrial applications to continuously monitor the rotor temperature. It is important to monitor temperature to avoid damage of SRM by thermal effects.
Show less

Title: RADIAL MAP ASSESSMENT APPROACH FOR DEEP LEARNING DENOISED CARDIAC MAGNETIC RESONANCE RECONSTRUCTION SHARPNESS
Creator: Mo, Fei
Date: 2021
Description: Deep Learning (DL) and Artificial Intelligence (AI) play important roles in the computer-aided medical diagnostics and precision medicine...
Show moreDeep Learning (DL) and Artificial Intelligence (AI) play important roles in the computer-aided medical diagnostics and precision medicine fields, capable of complementing human operators in disease diagnosis and treatment but optimizing and streamlining medical image display. While incredibly powerful, images produced via Deep Learning or Artificial Intelligence should be analyzed critically in order to be cognizant of how the algorithms are producing the new image and what the new imagine is. One such opportunity arose in the form of a unique collaborative project: the technical development of an image assessment tool that would analyze outputs between DL-based and non DL-based Magnetic Resonance Imaging reconstruction methods.More specifically, we examine the operator input dependence of the existing reference method in terms of accuracy and precision performance, and subsequently propose a new metric approach that preserves the heuristics of the intended quantification, overcomes operator dependence, and provides a relative comparative scoring approach that may normalize for angular dependence of examined images. In chapter 2 of this thesis, we provide a background description pertaining to the two imaging science principles that yielded our proposed method description and study design. First, if treated naively, the examined linear measurement approach exhibits potential bias with respect to the coordinate lattice space of the examined image. Second, the examined DL-based image reconstruction methods used in this thesis warrants an elaborate and explicit description of the measured noise and signal present in the reconstructed images. This specific reconstruction approach employs an iterative scheme with an embedded DL-based substep or filter to which we are blinded. In chapters 3 and 4 of this thesis, the imaging and DL-based image reconstruction experiments are described. These experiments employ cardiac MRI datasets from multiple clinical centers. We first outline the clinical and technical background for this approach, and then examine the quality of DL-based reconstructed image sharpness by two alternative methods: 1) by employing the gold-standard method that addresses the lattice point irregularity using a ‘re-gridding’ method, and 2) by applying our novel proposed method inspired by radial MRI k-space sampling, which exploits the mathematical properties of uniform radial sampling to yield the target voxel counts in the ‘gridded’ polar coordinate system. This new measure of voxel counts is shown to overcome the limitation due to the operator-dependence for the conventional approach. Furthermore, we propose this metric as a relative and comparative index between two alternative reconstruction methods from the same MRI k-space.
Show less

Title: LOAD ANALYSIS BASED ON MACHINE LEARNING IN POWER SYSTEMS
Creator: Lu, Dan
Date: 2017, 2017-05
Description: The dissertation is composed by four parts, first, load sampling for SCUC based on Principal Component Analysis (PCA) and Kernel Density...
Show moreThe dissertation is composed by four parts, first, load sampling for SCUC based on Principal Component Analysis (PCA) and Kernel Density Estimation (KDE); second, load forecasting based on PCA and Bayesian ridge regression; third, anomalies detection based on Machine Learning methodology; fourth the long-term planning of Battery-based Energy Storage Transportation (BEST) in power system. Mathematical models are constructed to fulfill the research of the three targets, and numerical examples are used to test the models. The first three parts are based on PCA, which reduced the load dimensions. In the first part, a robust power system Unit Commitment (UC) is the aim to fulfil the possible load. In the second part, a novel short-term nodal load forecasting is raised to give better prediction of the next day load to improve the next data UC scheduling. In the third part, anomalies are detected in the reduced power flow space based on the pattern identified in the lower dimensional space. The purpose of the fourth part is to find ways of better utilizing the existing resources from integrating the frontier technology, the mobility of more compact and higher capacity batteries. Mix-integer programming (MIP) is used in the formulation.
Ph.D. in Electrical Engineering, May 2017
Show less

Title: METHODOLOGY FOR VEHICLE EMISSION IMPACTS ANALYSIS FROM SIGNAL TIMING OPTIMIZATION OF AN URBAN STREET NETWORK
Creator: Lu, Pu
Date: 2017, 2017-05
Description: The pace of urban street capacity expansion is much slower than the growth of vehicle travel, leading to several traffic congestions. To...
Show moreThe pace of urban street capacity expansion is much slower than the growth of vehicle travel, leading to several traffic congestions. To mitigate traffic congestion expanding capacity is not feasible for many cases due to the high cost and space restriction. Improving the efficient use of the available capacity becomes the solution. Traffic signal optimization is one of the most widely used ways of efficient capacity utilization. Concurrent to traffic signal optimization, more smooth traffic operations in term of reasonably higher speed and a reduced traffic delay will in turn change vehicle emissions. This research aims to quantify changes in vehicle emissions resulted from traffic signal optimization by introducing a new methodology for quantifying network wide vehicle emissions and real world application in of the Chicago urban network for validation. The proposed methodology considers undersaturation and oversaturation of traffic conditions and urban street segments with varying speeds for different types of vehicles and pollutants by hour of the day and location within the network. It begins with information collection and research through a review of existing methods for urban street network vehicle emission estimation, intersection vehicle emission evaluation, and the running vehicle emission modeling. The proposed methodology focuses on three elements: estimation of emissions from vehicles stopped at intersections and for vehicles cruising along segments, as well as analysis of network wide vehicle emissions and changes in overall network vehicle emissions by time of the day and by areas. Major steps of methodology application included the use of Chicago TRANSIMS model implementing optimized signal timing plans to obtain refined traffic volumes at intersections and on segments, increased vehicle operating speeds, changed green splits, and vehicle compositions for all intersections and segments in the urban street network, the application of an intersection vehicle emission model for stopped vehicles and a segment vehicle emission model for vehicles cruising on segments, and the network wide analysis of vehicle emission changes by vehicle type and pollutant type in a 24-hour period within an urban street network, respectively. The proposed methodology for intersection vehicle emission estimation was successfully applied to a dense urban street network in Chicago for each approach per cycle and then extended for intersections in hours of the day to analyze the impacts of traffic changes at intersections on exhaust changes. In order to develop the network vehicle emission analysis method, it is essential to evaluate the segment vehicle emissions. This is achieved by using the concept of vehicle specific power which is used to estimate emissions of cruising vehicles considered along with vehicle speeds and speed changes and hence analyzing changes in segment vehicle emissions affected by traffic volume changes derived from signal timing optimization. The decreased number of vehicles stopped at intersections by applying signal timing optimization will reduce intersection emissions, hence reducing overall network vehicle emissions. In addition to have vehicle emissions got reduced at intersections, the increasing vehicle speed for vehicles on segments could further reduce vehicle emissions on segments.
Ph.D. in Civil Engineering, May 2017
Show less

Title: NEUROPSYCHOLOGICAL PROFILES IN ADULTS WITH SICKLE CELL DISEASE
Creator: Piper, Lauren E.
Date: 2014, 2014-12
Description: Cognitive impairment is documented in individuals with sickle cell disease (SCD). Studies investigating cognitive impairment in this...
Show moreCognitive impairment is documented in individuals with sickle cell disease (SCD). Studies investigating cognitive impairment in this population have primarily examined group differences in neuropsychological performance, which may have overlooked the heterogeneity of cognitive functioning. The objectives of this study were to determine whether distinct cognitive profiles occur in individuals with SCD and, if so, to examine potential differences in demographic, clinical, and psychosocial characteristics. Participants with SCD (n = 73) and similarly matched controls (n = 82), completed a brief neuropsychological protocol (Hachinski et al., 2006) and self-report measures of pain and mood-related symptoms. Cluster analysis was used to identify groups of participants based on their cumulative scores across the domains of executive functioning, language, memory, and visuospatial ability. Multivariate analysis of variance (MANOVA) was used to compare the cluster groups across the four cognitive domains. Analysis of variance (ANOVA) and chi-square tests were used to compare cluster groups on demographic, clinical, and psychosocial characteristics. Results indicated three distinct cognitive subtypes: (1) executive and memory impaired (56% of participants); (2) globally impaired (14%); and (3) cognitively intact (30%). The three cluster groups did not differ on most demographic factors, stroke history, or pain severity, but differed on level of education and current mood-related distress. Results demonstrated the presence of distinct cognitive profiles in adults with SCD, with a proportion of cognitively intact individuals. Implications for intervention and cognitive rehabilitation are discussed.
M.S. in Psychology, December 2014
Show less

Title: THE SIMPLE EQUAL FLOW PROBLEM ON GENERALIZED NETWORKS
Creator: Fidler, Mary E.
Date: 2011-07, 2011-07
Description: We study algorithms for the simple equal ow problem on generalized networks. Network ows problems are concerned with optimization of the ow of...
Show moreWe study algorithms for the simple equal ow problem on generalized networks. Network ows problems are concerned with optimization of the ow of commodities over a network, a directed graph. In a network, the amount of ow that leaves a node equals the ow that arrives at the destination node. However, generalized networks have arc multipliers which change the rate of ow on each arc. A classical network ow problem is the min cost ow problem which asks for minimum cost required for the ow of a commodity that satis es individual commodity requirements of each node in a network. The simple equal ow problem considers the min cost ow problem with an additional non-network constraint that requires certain arcs to have equal ow. Ahuja et al. [2] developed a combinatorial parametric algorithm, binary search algorithm, and capacity scaling algorithm for the simple equal ow problem. In this thesis, we extend the rst two algorithms to generalized networks. To do so, we must rst reformulate the simple equal ow problem on generalized networks to parameterize the equal ow arcs. The resulting linear program creates a piecewise linear convex curve as a function of the parameter. Then, we exploit the simplex algorithm derived combinatorial basis of generalized networks to determine the distance between breakpoints of the piecewise parametric linear convex curve of optimal solutions, which helps to determine the appropriate termination condition for the algorithms. This allows us to formulate the modi ed combinatorial parametric algorithm and the modi ed binary search algorithm, and their running times.
M.S. in Applied Mathematics, July 2011
Show less

Title: SKINNING AND STORAGE METHODS FOR STRUCTURAL AND FUNCTIONAL STUDIES OF MANDUCA SEXTA FLGHT MUSCLE
Creator: Zhang, Mengjie
Date: 2012-04-22, 2012-05
Description: Like mammalian cardiac muscle, the flight muscle of the hawk-moth Manduca sexta is synchronous. However, it also has significant structural...
Show moreLike mammalian cardiac muscle, the flight muscle of the hawk-moth Manduca sexta is synchronous. However, it also has significant structural similarities with asynchronous insect flight muscle systems, such as those of Drosophila and Lethocerus. Different physiological function depends on the underlying different molecular structures. Although Drosophila and Lethocerus have been well studied, Menduca sexta is still a newly developed research model. Many different skinning and storage methods are being used worldwide for in vitro studies of a wide variety of muscle systems. Here our goal is to develop better skinning solution and storage condition which will maintain muscle structure and function as well as intact muscle. To achieve this end, several kinds of skinning solutions and storage conditions were evaluated by laser and X-ray mechanical experiments. The solution from HAMM Lab (University of Washington) showed the best ability to destroy plasma membrane, without affecting muscle interior structure and function. For two storage conditions, 4°C without glycerol and -20°C with 50% glycerol, both laser and X-ray experiments show the latter one is better, which means muscles stored at -20°C with 50% glycerol have faster and stronger reaction for high calcium solution, and also have sharper peaks in X-ray diffraction patterns. The presence of protease inhibitors is also necessary to maintain the contraction ability of muscle. Furthermore, the X-ray experiments for muscle fibers stored at -20°C with 50% glycerol and -80°C with 75% glycerol, show the expected results, which the muscles stored at latter condition show far superior X-ray diffraction patterns, especially in meridional reflections and layer lines. The lower temperature can minimize protein degradation. Notably, incubating muscles in glycerol solutions at 4°C before storing them at -80°C, and washing muscles thoroughly after stored at 75% glycerol, are critical to ensure that all of the glycerol goes in and out of muscle fibers, respectively. The significance of these findings is that it now appears to be possible to store prepared Manduca sexta flight muscles for at least eight days at -80°C with good structural preservation enabling a large class of future experiments not requiring fresh deliveries of moth from the suppliers.
M.S. in Biology, May 2012
Show less

Title: AN ACCELERATING COUETTE FLOW IN NEK5000: APPLICATIONS IN OCEANOGRAPHY AND MAGNETOHYDRODYNAMICS
Creator: Miksis, Zachary M.
Date: 2017, 2017-05
Description: Nek5000 is a highly scalable spectral element code used in a broad array of problems in computational fluid dynamics. In this thesis, we focus...
Show moreNek5000 is a highly scalable spectral element code used in a broad array of problems in computational fluid dynamics. In this thesis, we focus on applying the code to a model problem of an accelerating Couette flow, or a hydrodynamic flow between two plates, of which the top plate is accelerating and the bottom plate is stationary, and verifying the numerical methods as applied to this problem. We obtain an analytical solution to the hydrodynamic flow problem, and use this to analyze the effects of changing time step length, the size of the computational mesh, and the computational polynomial order on the accuracy and stability of Nek5000. Additionally, we discuss the addition of an applied magnetic field to the hydrodynamic Couette flow, and provide a formulation for an exact solution to this magnetohydrodynamic problem that can be used to further verify Nek5000 in a similar fashion to the hydrodynamic problem.
M.S. In Applied Mathematics, May 2017
Show less

Title: TOPICS IN GRAPH FALL-COLORING
Creator: Mitillos, Christodoulos
Date: 2016, 2016-07
Description: Graph fall-coloring, also known as idomatic partitioning or independent domatic partitioning of graphs, was formally introduced by Dunbar,...
Show moreGraph fall-coloring, also known as idomatic partitioning or independent domatic partitioning of graphs, was formally introduced by Dunbar, Hedetniemi, Hedetniemi, Jacobs, Knisely, Laskar, and Rall in 2000 [1] as a simple extension of graph coloring and graph domination. It asks for a partition of the vertex set of a given graph into independent dominating sets. In this thesis, we will study a number of questions related to this concept. In the rst chapter we will give a brief background to graph theory, and introduce the topic of graph fall-coloring, after looking at the fundamental topics it builds on. In the second chapter, we identify the e ects on fall-colorability of various graphical operators, and look at the fall-colorability of certain families of graphs. In the third chapter we will explore certain constructions which create fall-colorable graphs given certain restrictions, and look at the interaction of fall-colorings and non-fall-colorings. Finally, in the fourth chapter, we lay the foundations to establish a connection between fall-coloring and certain existing open problems in graph theory, providing new possible avenues for exploring their solutions. We then provide two applied problems which can be solved with fall-coloring, and which motivate the notion of fall-nearcoloring. We also provide further questions in fall-coloring for future research. Keywords: Graph Fall-coloring, Idomatic Partition, Independent Dominating Sets, Chromatic number, Graph products.
Ph.D. in Applied Mechanics, July 2016
Show less

Title: DYNAMIC RECONFIGURATION OF THE DISTRIBUTION NETWORK WITH UNCERTAINTIES CONSIDERING DISTRIBUTED GENERATOR
Creator: Zhang, Hao
Date: 2015, 2015-05
Description: The thesis focuses on the reconfiguration process of the electrical distribution system, which reduces the real power loss in the system...
Show moreThe thesis focuses on the reconfiguration process of the electrical distribution system, which reduces the real power loss in the system through optimizing the topology of the distribution system. The model selected for the reconfiguration process of the distribution system is an MILP (mixed-integer linear programming). In addition, an adjusted MILP model with distributed generator. DG is formulated, in which the DG can follow the requirement of real operation in an active way. The major contribution of this thesis is to add the time-dimension and uncertainties. In addition, compared to other methods, the addition of other features into the MILP model can be done easily since the linking constraints can be added into the whole model in a simple way. Through the linking constraints, the reconfiguration of distribution system can transfer from a static model of one time spot with constant supply and demand data to the dynamic optimization-based model that can deal with the entire time horizon and the uncertainty at specific hour. It makes the model closer to the reality. Finally the numerical result is used to verify the concept proposed in this thesis.
M.S. in Electrical Engineering, May 2015
Show less

Title: HYBRID BATTERY-ULTRACAPACITOR ENERGY STORAGE SYSTEMS FOR NEXT GENERATION SHIPBOARD POWER SYSTEMS
Creator: Tang, Yichao
Date: 2011-04-22, 2011-05
Description: Batteries and ultracapacitors are likely to be candidates as excellent energy storage technologies for future shipboard power systems. This...
Show moreBatteries and ultracapacitors are likely to be candidates as excellent energy storage technologies for future shipboard power systems. This dissertation explores a hybrid Battery-Ultracapacitor Energy Storage System (BUCESS) for next generation shipboard application. Based on the power requirements of combat ships, a new configuration of the battery and ultracapacitor combined system is introduced for propulsion systems and pulse power loads. For one BUCESS unit, batteries and ultracapacitors are charged and discharged at high voltage level and high power level through a dual active bridge and a double-boost bidirectional converter. The converters are optimally designed to control the bidirectional power flow for batteries and ultracapacitors separately, and to ensure constant voltage regulation of ultracapacitors during charging and discharging. High-frequency switching devices are selected to achieve dc-dc conversion at high voltage and high power levels. The design guidelines and control schemes for simulations are provided for the proposed new topology. Finally, a double-input BUCESS unit is designed, analyzed and simulated to investigate different operation modes of the hybrid energy storage system.
M.S. in Electrical Engineering, May 2011
Show less

Title: DEPTH MAP ENHANCEMENT FOR REAL-TIME 3D RECONSTRUCTION
Creator: Lee, Kitae
Date: 2015, 2015-07
Description: In this paper, we present a novel depth map enhancement for real-time 3D reconstruction by the Microsoft Kinect. The Kinect sensor is...
Show moreIn this paper, we present a novel depth map enhancement for real-time 3D reconstruction by the Microsoft Kinect. The Kinect sensor is relatively affordable and capable of generating high-resolution color image and depth maps of the scene at realtime rates. However, owning the low- cost, there are several artifacts. Generated depth map contains lots of holes, which they are missing information around object boundaries and mis-alignment with color image. The objective of 3D reconstruction is to recreate a real scene, as accurate as possible within a virtual three-dimensional space using a computer. The algorithm of 3D-recosntrution is highly based on the quality of the depth map. This poor depth map could not be applied in potential real-time 3D reconstruction. We present novel multi-step upsampling-based our novel anisotropic diffusion algorithms with generated depth map and color image by Kinect. This method has better performance than existed bilateral filtering and original anisotropic filtering in terms of filling holes, sharpening the boundaries of objects and alignment between depth map and color image. We compare the performance of these filters. It is difficult to do a meaningful comparison of two algorithms with using output of Kinect sensor directly; as for each observation of the same scene, we will get different sensed value. In order to circumvent this problem and to achieve an accurate comparison process, we used dataset from Computer Vision Group at Munchen Technology Universty(TUM). This dataset and the scripts is related to quantitative error metrics are avail at http://vision.in.tum.de/data/datasets/rgbd-‐dataset. We also contribute making our project parallel and GPU computing to satisfy real-time system condition.
M.S. in Electrical Engineering, July 2015
Show less

Title: DISTRIBUTION SYSTEM STATE ESTIMATION
Creator: Li, Lingyan
Date: 2015, 2015-05
Description: This thesis provides a novel method to improve distribution system state estimation by an effective approach to processing bad data in...
Show moreThis thesis provides a novel method to improve distribution system state estimation by an effective approach to processing bad data in measurements. The first part of this research is focused on modeling distribution system state estimation with bad data rejection capability. We apply transmission level model to the distribution level system with specific properties, such as fewer real measurement data for state estimation in the distribution level system, three phase unbalance power flow and so on. For building a robust state estimation model, we optimize the system in the following ways: First, we optimize objective function. We use forecasted load as pseudo measurements. Then we apply different weights to distinguish the forecasted data and actual measurements in the state estimation. Second, we apply three phase power equation in the analysis. We add real power, reactive power, active line power, reactive line flow, voltage magnitude, phase angle and others as nonlinear constraints in the three phase model of state estimation. Third, we flexibly change objective function and constraints in the state estimation model. We can change objective function when state estimation method changes. Meanwhile, we can add power flow and bus limitations in the optimization to avoid state estimation results exceeding power system limitations. Finally, we conduct hybrid calculation. In the first optimization, we filter the bad data. Then, we add another weight to reduce the bad measurement weight and enlarge the good measurement weight. After this process, we get optimized state estimation results. The second part focuses on the implementation of the model. We explain how to preprocess testing case data in this part. The third part is case study. We use IEEE 34 node feeder to test this model. There are four test cases. One test case has no bad data. Other cases have bad data in different types of measurements. We compare these cases with conventional WLS approach. The results obtained from simulation indicate our model has better performance when there is bad data in measurements.
M.S. in Electrical Engineering, May 2015
Show less

repository.iit

Search the repository

Pages

Pages