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Title: COMPUTATIONAL COST OF SIMULATING MEAN EXIT TIME USING STOCHASTIC DIFFERENTIAL EQUATIONS
Creator: Liu, Fanjing
Date: 2016, 2016-05
Description: Stochastic di erential equations play an important role in modern science, including engineering, physics, computer science and nance. It has...
Show moreStochastic di erential equations play an important role in modern science, including engineering, physics, computer science and nance. It has been shown that numerically solving stochastic di erential equation is a productive methodto deal with such problems. In this work, we try to analyze the procedure of numerically computing the mean exit time of some stochastic processes from a given boundary using Monte Carlo simulations. The two methods, including the Euler-Maruyama Method and Milstein's higher order method, will be explained and used extensively when we simulate paths of the random process. The simulated processes generated through the methods will then be used to identify the exit times. Later we use the average of the exit times as a numerical solution of Mean Exit Time. We compare the e ciency of the above two methods by evaluating their computational complexity and CPU cost of reaching the same level of accuracy.
M.S. in Applied Mathematics, May 2016
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Title: STEREO-BASED DEPTH MAP PROCESSING: ESTIMATION AND REFINEMENT
Creator: Loghman, Maziar
Date: 2016, 2016-12
Description: During the past decade, research in 3D video has become a hot topic owing to advancements in both hardware and software. Amongst different...
Show moreDuring the past decade, research in 3D video has become a hot topic owing to advancements in both hardware and software. Amongst different methods proposed for representing 3D data, multi-view video plus depth (MVD) format has gained a lot of attention. Most of such 3D algorithms rely on a per-pixel depth representation of the scene called a depth map. Depth maps are very useful for rendering virtual views and have lead to advancements in 3D compression algorithms. Generating an accurate and dense depth map is one of the important prerequisite for many 3D video applications. In this thesis, we highlight the following major problems in MVD. * Depth map estimation * Depth map refinement * Depth map coding In order to generate an accurate depth map, we propose a method based on Census transform with adaptive window patterns and semi-global optimization. A modified cross-based cost aggregation technique is proposed which helps to calculate a more reliable depth map. In order to further enhance the quality of the generated depth map, a novel multi-resolution anisotropic diffusion based algorithm is presented. The proposed depth refinement algorithm computes a dense depth map in which the holes have been filled and the object boundaries are sharpened. The next part of the research is based on depth map coding. In depth map coding, a considerable amount of time is required to investigate the mode decision pro- cess for every block of depth pixels. However, in real-time purposes, we can partially skip the mode selection step. In this thesis, we propose a novel depth intra-coding scheme for 3D video coding based on HEVC standard. The core idea of the proposed method is motivated by the fact that depth maps have specific characteristics that distinguish them from those of color images. By analyzing the reference depth maps based on homogeneousness of different regions, for some particular blocks, the DMM full-RD search is skipped and the mode is selected based on the previous similar tree- blocks. By this means, the time complexity of the encoding process is significantly reduced.
Ph.D. in Electrical Engineering, December 2016
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Title: STATISTICAL LEARNING IN SOCIAL INTERACTIONS: ANTICIPATION OF CAREGIVER FEEDBACK TO COMMUNICATIVE BEHAVIOR IN PRELINGUISTIC INFANTS
Creator: Lossia, Amanda Kathryn
Date: 2014, 2014-05
Description: A growing body of literature has demonstrated that infants are able to detect patterns in structured external environmental stimuli through a...
Show moreA growing body of literature has demonstrated that infants are able to detect patterns in structured external environmental stimuli through a statistical learning mechanism. The present study examines whether statistical learning operates as a learning mechanism in social interactions as well. Prior research using an ABA experimental design demonstrated that infants modified their communicative behavior when the level of contingent caregiver feedback to infant gestures was altered (Miller & Lossia, 2013). These findings are extended in the present study by examining whether the infants developed modified expectations for caregiver feedback when the pattern of contingent feedback was altered, which might function as a possible mechanism for the changes seen in infant communicative behavior. Anticipatory looking to the caregiver was used as a measure of infants’ expectations for caregiver responsiveness. Results showed differences in anticipatory looking to the caregiver across periods. The pattern of anticipatory looking did not fully explain the changes seen in infant communicative behavior. However, the findings do suggest that infants detected the change in caregiver feedback and modified their expectations, providing support for the presence of a statistical learning mechanism in social interactions.
M.S. in Psychology, May 2014
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Title: THERMAL ANALYSIS OF PM MACHINES FOR HIGH PERFORMANCE ELECTRIC VEHICLES
Creator: La Marca, Frank
Date: 2016, 2016-07
Description: As demand grows for electrification of the automotive industry, the need for a traction motor becomes imperative. There has been considerable...
Show moreAs demand grows for electrification of the automotive industry, the need for a traction motor becomes imperative. There has been considerable effort by electric machine manufacturers to develop and build a traction motor that meets the speci- fications of the automobile industry. One of the limiting factors in the design of an electric automobile is the thermal performance of a traction motor. This thesis focuses on thermal analysis of an electric machine with a major focus on a machine that operates in an automotive environment. Thermal analysis of the electric machine will be focus on the analysis of an electric machine that is used in a FSAE electric racecar. Theory behind various thermal extraction methods are reviewed, including heat transfer and the fluid dynamics of an electric machine. Thermal modeling methods are also investigated, including analytical methods and numerical methods such as finite element analysis and computational fluid dynamics. The importance of thermal modeling of an electric machine is to understand the heat transfer occurring in the machine. In high performance electric machines the limiting factor of the machine the temperature rise when torque is applied. In- vestigation of the heat transfer of a machine can identify the hot spot of the machine and methods of reduction. This will allow for more current applied and more torque which will give a higher density machine.
M.S. in Electrical Engineering, July 2016
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Title: MODELS AND SIMULATIONS OF SPROUTING ANGIOGENESIS
Creator: Langman, Catherine
Date: 2016, 2016-05
Description: All living mammalian cells need to consume oxygen and nutrients for cellular processes and need a way to remove waste from those cellular...
Show moreAll living mammalian cells need to consume oxygen and nutrients for cellular processes and need a way to remove waste from those cellular processes. Capillary networks provide places for such exchanges to occur. The process of creating new capillaries from existing blood vessels is called angiogenesis. Understanding angiogenesis is critical to the advancement of knowledge in the life sciences, as well as in medical applications where blood vessels play an important role. Angiogenesis is a complex process composed of many subprocesses which are not yet fully understood and take place over varying temporal and spatial scales. Mathematically modeling and simulating angiogenesis, and evaluating the capillary networks that result from angiogenesis, can help further understanding of angiogenesis and improve therapeutic treatments. This thesis examines mathematical models and simulations of sprouting angiogenesis and proposes two generic models of sprouting angiogenesis based on descriptions found in educational and scientific literature. Future research opportunities for scientific study and educational study using these models as a starting place are discussed.
M.S. in Applied Mathematics, May 2016
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Title: MOTION OF BUBBLY FLUID IN A TANK
Creator: Langman, Michael
Date: 2014, 2014-07
Description: Computational uid dynamics is the numerical study of the motion of uids. In this thesis, an introduction to uid mechanics is presented and the...
Show moreComputational uid dynamics is the numerical study of the motion of uids. In this thesis, an introduction to uid mechanics is presented and the governing equations of uid mechanics are derived. The open-source computational uid dynamics library OpenFOAM is then used to simulate uid dynamics and to model the formation and movement of bubbles in a tank.
M.S. in Applied Mathematics, July 2014
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Title: MOBILITY IMPROVEMENT BENEFIT ANALYSIS OF SIGNAL TIMING OPTIMIZATION FOR URBAN STREET NETWORK
Creator: Zhang, Ji
Date: 2015, 2015-05
Description: The traffic congestion problem especially in urban areas is getting increasingly severe due to the ever-growing auto travel demand in the...
Show moreThe traffic congestion problem especially in urban areas is getting increasingly severe due to the ever-growing auto travel demand in the United States during the past few decades. In general, insufficient capacity can be solved by system expansion. However, expanding system is not feasible anymore because of the land scarcity in urban areas and its high cost. From this point of view, transportation operations that lead to the optimal system usage are more preferable thanks to their relatively low cost and remarkable consequences. Several performance indices were used in order to assess the effects of a given transportation operation. This study introduces a new method for evaluating the mobility performance of the transportation system before and after a transportation operation. And the mobility benefit is converted into monetary value. Further, a Life-Cycle Benefit Analysis is conducted to expand the evaluation process to the time dimension. An experimental study is performed to apply this method on the urban street network in Chicago downtown area that contains 917 intersections and 1675 roadway segments before and after a network-wide signal timing optimization treatment. Based on this application, the results indicate a few potential advantages and disadvantages of this system-wide signal timing optimization methodology.
M.S. in Civil, Architectural and Environmental Engineering, May 2015
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Title: MOBILITY IMPROVEMENT BENEFIT ANALYSIS OF SIGNAL TIMING OPTIMIZATION FOR URBAN STREET NETWORK
Creator: Zhang, Ji
Date: 2015, 2015-05
Description: The traffic congestion problem especially in urban areas is getting increasingly severe due to the ever-growing auto travel demand in the...
Show moreThe traffic congestion problem especially in urban areas is getting increasingly severe due to the ever-growing auto travel demand in the United States during the past few decades. In general, insufficient capacity can be solved by system expansion. However, expanding system is not feasible anymore because of the land scarcity in urban areas and its high cost. From this point of view, transportation operations that lead to the optimal system usage are more preferable thanks to their relatively low cost and remarkable consequences. Several performance indices were used in order to assess the effects of a given transportation operation. This study introduces a new method for evaluating the mobility performance of the transportation system before and after a transportation operation. And the mobility benefit is converted into monetary value. Further, a Life-Cycle Benefit Analysis is conducted to expand the evaluation process to the time dimension. An experimental study is performed to apply this method on the urban street network in Chicago downtown area that contains 917 intersections and 1675 roadway segments before and after a network-wide signal timing optimization treatment. Based on this application, the results indicate a few potential advantages and disadvantages of this system-wide signal timing optimization methodology.
M.S. in Civil Engineering, May 2015
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Title: LOW TEMPERATURE STORAGE METHODS FOR SKINNED MANDUCA SEXTA FLIGHT MUSCLE
Creator: Liu, Xue
Date: 2015, 2015-12
Description: The flight muscle of the Hawk moth, Manduca sexta, is a synchronous muscle and an emerging model system for structure and function studies of...
Show moreThe flight muscle of the Hawk moth, Manduca sexta, is a synchronous muscle and an emerging model system for structure and function studies of muscle. (Tu & Daniel, 2004). There are several interesting properties of Manduca sexta flight muscle. In its physiological characteristics, like mammalian skeletal and cardiac striated muscle, it is a synchronous muscle. However, it is much more similar structurally to the more widely known asynchronous insect flight muscles of Drosophila and Lethocerus. Up to now there has been no good method for storing Manduca sexta flight muscle for a long time. It is often difficult to match the time of obtaining live moths muscle and scheduled X-ray or mechanics experiment. Usually, best results are obtained by using freshly prepared muscle fibers. It would be highly desirable to find storage conditions that can maintain the structural and physiological functions in vitro for days or weeks rather than needing to be prepared fresh from living tissue for every experiment. (Yu-Shu Cheng, MS thesis IIT, 2013). Muscle proteins will degrade over a periods of days even in the presence of protease inhibitors even at low temperature. Here we aimed to find storage conditions which would work best for Manduca sexta flight muscle. In this thesis, trehalose, in combination with glycerol, was evaluated as an addition storage solution as a cryoprotectant to protect the muscle fiber from the low temperature. At very low temperature, organisms became dehydrated. Loss of liquid water from cells can cause irreversible damage, so they will not function even when rehydrated. Here we show that using both glycerol and trehalose as cryoprotectants in storage solution, the muscle fiber maintain high maximum active force for up to a month in storage.
M.S. in Biology, December 2015
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Title: DESIGN AND IMPLEMENTATION OF A POWER ASSISTED DRIVETRAIN FOR A WHEELCHAIR
Creator: Hou, Ruoyu
Date: 2012-04-06, 2012-05
Description: Over the last two decades, the number of people who have difficulty walking and need wheelchairs has been found to be increasing due to an...
Show moreOver the last two decades, the number of people who have difficulty walking and need wheelchairs has been found to be increasing due to an aging population caused by a low birth rate and advances in medical treatment. Based on a recent survey, a power assisted wheelchair is the latest one in the commercial wheelcair market. The power assisted wheelchair offers users an opportunity for physical activity, but it is often too expensive for customers. This has led to the design of more advanced and economical power assisted drivetrain systems for wheelchairs. In this thesis, a novel controller has been designed. Instead of using a torque sensor for measuring and amplifying human force, the proposed controller uses two infrared sensors to trigger two motors. Using this information in addition to the information from a motion sensor that detects the road angle variation, appropriate torque command is generated. The drivetrain requires the embedded controller has a strong I/O control function, but also high speed signal processing ability for realizing real time control. Therefore, a DSP (Digital Signal Processor) which integrates flexbile multiple PWM signal generator to drive two motors, two Hall sensors for motor position and speed feedback is considered as one of the strongest controllers for power assisted drivetrain implementation. This thesis has two main contributions: a) it presents a novel power assisted motor control strategy, including six-step motor control, Environmental Adaptive control and Push-Go control method; and b) it develops an embedded controller not only on the testbench, also on the wheelchair to realize this control strategy. The designed controller is low cost and compact.
M.S. in Electrical Engineering, May 2012
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Title: ORGANOFUNCTIONALIZED OXOMETALATES: SYNTHESIS, STRUCTURE, AND PROPERTIES OF A NEW CLASS OF MIXED-METAL TETRAMETALATE CLUSTERS
Creator: Shuaib, Damola Taye
Date: 2022
Description: Oxometalates (OMs) are metal-oxide clusters with addenda mental atom mainly V, Mo, and W and bridged by oxide anions. Prototypical examples...
Show moreOxometalates (OMs) are metal-oxide clusters with addenda mental atom mainly V, Mo, and W and bridged by oxide anions. Prototypical examples like polyoxometalates (POMs) are completely inorganic. While clusters with nuclearities ranging from 6 to 18 are common for purely inorganic examples, those with less than nuclearity 6 are rare. Therefore, functionalization by covalent interaction with organic moiety via self-assembly has been utilized as a viable route for making compact clusters with nuclearity of 4 and below. These compounds constitute the organo-functionalized examples of the purely inorganic structure ([XMaOb]n-) POM. Reports of organo-functionalized tetrametalates (TMs), ([MxOyLz])n- (where M = metal, x = 4 and L represents an organic ligand) are sparse. Mixed metal species are especially interesting as potential redox active materials as they contain energetically distinct potential redox centers. OMs have ability to accept electrons in a chemically reversible manner through the terminal oxo-ligand (M=Ot) leading to dπ–pπ electron transfer. Considering the rich structural and electronic properties of these complexes, four neutral mixed-metal (M-V) tetrametalate clusters, [(CoIICl)2(VIVO)2{((HOCH2CH2)(H)N(CH2CH2O))(HN(CH2CH2O)2}2] (1), [(ZnIICl)2(VIVO)2{((HOCH2CH2)(H)N(CH2CH2O))(HN(CH2CH2O)2}2] (2), [CoII2(VIVOF)2{((HOCH2CH2)(H)N(CH2CH2O))(HN(CH2CH2O)2)}2] (3), and [ZnII2(VIVOF)2{((HOCH2CH2)(H)N(CH2CH2O))(HN(CH2CH2O)2)}2] (4) containing unprecedented oxometallocyclic {M2V2X2N4O8}(M = Co, Zn; X = F, Cl) frameworks decorated with diethanolamine ligand in bidentate and tridentate manners. The type of halo-ligand has direct influence on the geometry of the metal M and UV-Vis reflectance spectra revealed changes in electronic structure consistent with charge transfer processes expected. Computational and magnetic properties studies revealed that the ground state multiplicity of 1 is confirmed as an open-shell singlet with a prediction of an isotropic exchange coupling of -6.6 cm-1 but less clear for 2. The vanadium centers are best described as a V(IV) center and the cobalt centers are high-spin Co(II) centers. Less orbital destabilization was observed due to weaker interaction of Cl- ligand on Co than what was observed for O2- ligand on V centers. In 2, there are four weakly coupled spin centers, where the isotropic exchange couplings are defined as J1, J2’, and J2’’. These couplings are approximated as J1 = 1.5/+11.7 cm-1, J2’ = -22.1/-14.8 cm-1, and J2’’ = +4.2/+4.8 cm-1. Although J2’’ is predicted to be weakly ferromagnetic in nature, whereas the fit suggested a weak antiferromagnetic interaction for each of the V(IV)-Co(II) couplings. The low-temperature magnetic susceptibility suggests a Type III spin frustration present in the system. However, competing magnetic interactions are known to be operative in tetranuclear system which is even observed to be more prominent in the mixed-metal tetranuclear system considering the edge-sharing consequence on magnetic behavior. A new route to metal complex synthesis via in situ ligand transformation from diethanolamine to bicine by disproportionation and oxidation reactions yielded three isostructural mononuclear clusters Bis[N,N-bis(2-hydroxyethyl)glycinato]-Cobalt(II) 5, Bis[N,N-bis(2-hydroxyethyl)glycinato]-Nickel(II) 6, and Bis[N,N-bis(2-hydroxyethyl)glycinato]-Copper(II) 7. The observed transformation is predicted to proceed through nucleophilic substitution (SN2) as expected for substituted ammines. These metal complexes are characterized by various analytical techniques such as, FT-IR and UV-Vis spectroscopies, single crystal and powdered X-ray diffraction analyses, Energy-Dispersed X-ray spectroscopy, magnetic properties measurements, thermal gravimetric analysis, bond valence sum calculations etc. Based on their features and detailed structure-property-application analyses, the clusters showed great potentials for catalysis, materials for digital tools, chemical sensing, molecular magnets and precursors as molecular building blocks for extended open frameworks.
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Title: Choice-Distinguishing Colorings of Cartesian Products of Graphs
Creator: Tomlins, Christian James
Date: 2022
Description: A coloring $f: V(G)\rightarrow \mathbb N$ of a graph $G$ is said to be \emph{distinguishing} if no non-identity automorphism preserves every...
Show moreA coloring $f: V(G)\rightarrow \mathbb N$ of a graph $G$ is said to be \emph{distinguishing} if no non-identity automorphism preserves every vertex color. The distinguishing number, $D(G)$, of a graph $G$ is the smallest positive integer $k$ such that there exists a distinguishing coloring $f: V(G)\rightarrow [k]$ and was introduced by Albertson and Collins in their paper ``Symmetry Breaking in Graphs.'' By restricting what kinds of colorings are considered, many variations of distinguishing numbers have been studied. In this paper, we study proper list-colorings of graphs which are also distinguishing and investigate the choice-distinguishing number $\text{ch}_D(G)$ of a graph $G$. Primarily, we focus on the choice-distinguishing number of Cartesian products of graphs. We determine the exact value of $\text{ch}_D(G)$ for lattice graphs and prism graphs and provide an upper bound on the choice-distinguishing number of the Cartesian products of two relatively prime graphs, assuming a sufficient condition is satisfied. We use this result to bound the choice distinguishing number of toroidal grids and the Cartesian product of a tree with a clique. We conclude with a discussion on how, depending on the graphs $G$ and $H$, we may weaken the sufficient condition needed to bound $\text{ch}_D(G\square H)$.
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Title: Development of validation guidelines for high pressure processing to inactivate pressure resistant and matrix-adapted Escherichia coli O157:H7, Salmonella spp. and Listeria monocytogenes in treated juices
Creator: Rolfe, Catherine
Date: 2020
Description: The fruit and vegetable juice industry has shown a growing trend in minimally processed juices. A frequent technology used in the functional...
Show moreThe fruit and vegetable juice industry has shown a growing trend in minimally processed juices. A frequent technology used in the functional juice division is cold pressure, which refers to the application of high pressure processing (HPP) at low temperatures for a mild treatment to inactivate foodborne pathogens instead of thermal pasteurization. HPP juice manufacturers are required to demonstrate a 5-log reduction of the pertinent microorganism to comply with FDA Juice HACCP. The effectiveness of HPP on pathogen inactivation is determinant on processing parameters, juice composition, packaging application, as well as the bacterial strains included for validation studies. Unlike thermal pasteurization, there is currently no consensus on validation study approaches for bacterial strain selection or preparation and no agreement on which HPP process parameters contribute to overall process efficacy.The purpose of this study was to develop validation guidelines for HPP inactivation and post-HPP recovery of pressure resistant and matrix-adapted Escherichia coli O157:H7, Salmonella spp., and Listeria monocytogenes in juice systems. Ten strains of each microorganism were prepared in three growth conditions (neutral, cold-adapted, or acid-adapted) and assessed for barotolerance or sensitivity. Pressure resistant and sensitive strains from each were used to evaluate HPP inactivation with increasing pressure levels (200 – 600 MPa) in two juice matrices (apple and orange). A 75-day shelf-life analysis was conducted on HPP-treated juices inoculated with acid-adapted resistant strains for each pathogen and examined for inactivation and recovery. Individual strains of E. coli O157:H7, Salmonella spp., and L. monocytogenes demonstrated significant (p <0.05) differences in reduction levels in response to pressure treatment in high acid environments. E. coli O157:H7 was the most barotolerant of the three microorganism in multiple matrices. Bacterial screening resulted in identification of pressure resistant strains E. coli O157:H7 TW14359, Salmonella Cubana, and L. monocytogenes MAD328, and pressure sensitive strains E. coli O15:H7 SEA13B88, S. Anatum, and L. monocytogenes CDC. HPP inactivation in juice matrices (apple and orange) confirmed acid adaptation as the most advantageous of the growth conditions. Shelf-life analyses reached the required 5-log reduction in HPP-treated juices immediately following pressure treatment, after 24 h in cold storage, and after 4 days of cold storage for L. monocytogenes MAD328, S. Cubana, and E. coli O157:H7 TW14359, respectively. Recovery of L. monocytogenes in orange juice was observed with prolonged cold storage time. These results suggest the preferred inoculum preparation for HPP validation studies is the use of acid-adapted, pressure resistant strains. At 586 – 600 MPa, critical inactivation (5-log reduction) was achieved during post-HPP cold storage, suggesting sufficient HPP lethality is reached at elevated pressure levels with a subsequent cold holding duration.
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Title: Modeling, Analysis and Computation of Tumor Growth
Creator: Lu, Min-Jhe
Date: 2022
Description: In this thesis we investigate the modeling, analysis and computation of tumor growth.The sharp interface model we considered is to understand...
Show moreIn this thesis we investigate the modeling, analysis and computation of tumor growth.The sharp interface model we considered is to understand how the two key factors of (1) the mechanical interaction between the tumor cells and their surroundings, and (2) the biochemical reactions in the microenvironment of tumor cells can influence the dynamics of tumor growth. From this general model we give its energy formulation and solve it numerically using the boundary integral methods and the small-scale decomposition under three different scenarios.The first application is the two-phase Stokes model, in which tumor cells and the extracellular matrix are both assumed to behave like viscous fluids. We compared the effect of membrane elasticity on the tumor interface and the curvature-weakening one and found the latter would promote the development of branching patterns.The second application is the two-phase nutrient model under complex far-field geometries, which represents the heterogeneous vascular distribution. Our nonlinear simulations reveal that vascular heterogeneity plays an important role in the development of morphological instabilities that range from fingering and chain-like morphologies to compact,plate-like shapes in two-dimensions.The third application is for the effect of angiogenesis, chemotaxis and the control of necrosis. Our nonlinear simulations reveal the stabilizing effects of angiogenesis and the destabilizing ones of chemotaxisand necrosis in the development of tumor morphological instabilities if the necrotic core is fixed. We also perform the bifurcation analysis for this model.In the end, as a future work, we propose new models through Energetic Variational Approach (EnVarA) to shed light on the modeling issues.
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Title: DO GENERAL EDUCATION HIGH SCHOOL STUDENTS IN A BASIC PHYSICAL SCIENCE COURSE IMPROVE UPON ATTITUDES TOWARD SCIENCE LEARNING AND CONTENT MASTERY FOLLOWING VIRTUAL/REMOTE FLIPPED INSTRUCTION OR VIRTUAL/REMOTE NON – FLIPPED INQUIRY – BASED INSTRUCTION?
Creator: Martino, Robert S.
Date: 2022
Description: As we progress further into the 21st Century, high school science is being challenged on how to best deliver instruction to students. Teacher ...
Show moreAs we progress further into the 21st Century, high school science is being challenged on how to best deliver instruction to students. Teacher – centered instruction has long been de – emphasized in favor of inquiry – based instruction, although teacher – centered instruction still exists to a noticeable extent. Inquiry – based instruction, while more student – centered in its common practice, still involves the teacher as a guide during classroom direct instruction. Research has been ongoing to identify new and dynamic forms of science concept delivery that serve the needs of diversified science instruction (Keys & Bryan, 2001; Saldanha, 2007). Virtual instruction has become more commonplace, and it was fully implemented during this study. It has become incumbent upon science education researchers to explore and identify the most effective means of virtual instruction, means that are student – centered, engaging, interesting, and that both improve student science content understanding and attitudes toward science. Flipped instruction is a more recently – incorporated form of student – centered instruction that has students experiencing classroom routines at home and homework routines in class, and that is why this instruction is referred to as being “flipped.” Hunley (2016) examined teacher and student perception of flipped instruction in a science classroom, while Howell (2013) explored it in a ninth – grade physical science honors classroom. At the onset of this study, relatively few studies were available about this newer form of instruction within high school science instruction, no studies were available that involved high school general education physical science courses, and certainly no studies were available that compared virtual/flipped and non – flipped general education physical science instruction at the onset of this study. This study researched the effect of virtually – implemented flipped instruction on high school students’ understanding and attitude toward science. Instruction was completely virtual/remote (online), and at home, for all students in this study. In investigating the effect of this type of instruction, this study examined student academic performance and attitudes (and intentions and beliefs) toward science in two units of a high school Integrated Chemistry and Physics (Physical Science) course. Sixty – six students from Southlake High School, a midwestern U.S. high school, took part in the study. Sixty – four of those students took the unit assessments. Half of the students (test group) were instructed via virtual/remote flipped instruction and the other half (control group) were instructed via virtual/remote non – flipped, inquiry – based instruction during the first unit. During the second unit, the test group students who were instructed via virtual/remote flipped instruction switched with the control group and were instructed via virtual/remote non-flipped inquiry – based instruction, while the control group students who were instructed via virtual/remote non-flipped instruction were instructed via virtual/remote flipped instruction. The students in both groups were surveyed three times, using the Behaviors, Related Attitudes, and Intentions Toward Science (BRAINS) (Summers, 2016) instrument student questionnaire and survey for their attitudes (and beliefs and intentions) toward science (once prior to the first unit, once after the first unit, and once following the second unit). Student test results and survey responses were then analyzed to identify which instructional style was more effective for student learning and whether student attitudes (and intentions, and beliefs) favored one instructional style over the other. Student science attitudes (and beliefs and intentions) and academic performance were evaluated throughout the study. There was an increase in control group student science attitudes (and beliefs and intentions), from the pre – study survey to the post – unit 1 survey following their receipt of non – flipped virtual/remote instruction in the first unit. There was a lower increase in test group student science attitudes (and beliefs and intentions), from lower pre – study attitudes (compared with the control group) following the test group’s receipt of flipped virtual/remote instruction in the first unit,. Following the second unit, both the control group and test group again showed increases in attitude (and beliefs and intentions) compared with the pre – study survey results, with the control group again showing greater increases than the study group. Student academic performance favored the control group as it outperformed the test group in both the first unit and the second unit, even when the test group received the virtually – delivered flipped instruction in the first unit. The findings of the study showed that virtually implemented flipped instruction resulted in no advantage for the test group in terms of greater improvement in attitudes (or beliefs or intentions) toward science and no advantage for the test group in terms of learning science content in general education Integrated Chemistry and Physics (Physical Science). These results indicate that this form of teaching may not be effective in improving general education Physical Science student learning and student attitudes (and beliefs and intentions) toward science. Therefore, the use of virtually implemented flipped instruction in this general education science course will need to be further studied to determine its effect on student learning and student attitudes (or even beliefs and intentions) toward science.
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Title: Resilience Enhancement of Critical Cyber-Physical Systems with Advanced Network Control
Creator: Liu, Xin
Date: 2020
Description: Critical infrastructures are the systems whose failures would have a debilitating impact on national security, economics, public health or...
Show moreCritical infrastructures are the systems whose failures would have a debilitating impact on national security, economics, public health or safety, or any combination of those matters. It is important to improve those systems' resilience, which is the ability to reduce the magnitude and/or duration of disruptive events. However, today’s critical infrastructures, such as electrical power system and transportation system, are deploying advanced control applications with increasing scale and complexity, which leads to the migration of their underlying communication infrastructures from simple and proprietary networks to off-the-shelf network technologies (e.g., IP-based protocols and standards) to handle the intensive and heterogeneous traffic flows. On one hand, this migration provides an opportunity for both academic and industry communities to develop novel ideas on top of existing schemes; on the other hand, it exposes more vulnerabilities for cyber-attacks. Moreover, since the large-scale power system may choose leased networks from Internet service providers (which is a critical infrastructure itself), there exists an interdependency relationship between power and communication infrastructures, where the power transmission control requires message delivery services while the network devices rely on the power supply. These problems raise research challenges to improve the system resilience of critical cyber-physical systems.In this thesis, we focus on resilience enhancement of critical infrastructures from the communication network's aspects. The application domain includes both power and transportation systems. For power systems, we first apply advanced network control techniques (i.e., software-defined network (SDN) and fibbing control scheme) in the transmission grid communication network to improve the grid status restoration process under network failures and cyber-attacks. We develop a unified system model that contains both transmission grid monitoring system (i.e., phasor measurement unit (PMU) network) and communication network, and formalize a mixed-integer linear programming (MILP) problem to minimize the recovery time of system observability with the power and communication domain constraints. We evaluate the system performance regarding the recovery plan generation and installation using IEEE standard systems. However, the advanced network-based control scheme could also lead to problems, since it requires a power supply for the network devices. Thus, we investigate the interdependency relationship between the power grid and communication network and its impact on system resilience. We conduct a survey work that summarizes existing research based on two dimensions: objectives (i.e., failure analysis, vulnerability analysis, failure mitigation, and failure recovery) and methodologies (i.e., analytical solutions, co-simulation, and empirical studies). We also identify the limitations of existing works and propose potential research opportunities in this demanding area. Lastly, based on the review work, we conduct research that focuses on fast power distribution system restoration that involves interdependency constraints. When a natural disaster happens, both power and communication components might be damaged. Furthermore, since they are dependent on each other's service to function correctly, the failures may propagate to the hardware/software that are not affected initially. In this work, we focus on the recovery stage where the failed components in the system are already fully detected and isolated. We construct a mathematical model of the co-existing power and communication system and use optimization techniques to produce a crew dispatch plan that restores power as fast as possible by coordinating damage repairing, switch operation, and communication supply processes. We evaluate the restoration efficiency on the IEEE standard system using both analytical analysis and discrete-event simulation.For the second application domain, railway transportation system, we focus on evaluating the resilience of its communication system that exchanges control and monitoring messages with both on-board driver cabin and remote control center. We use advanced discrete-event simulation techniques to achieve a high-fidelity model of the network which makes the evaluation more concrete and realistic. For the Ethernet-based on-board train communication network (TCN), we develop a parallel simulation platform according to the IEC standard and use it to conduct a case study of a double-tagging VLAN attack on this control network. Another component of the railway communication system is the train-to-ground network that enables the communication between the driving system on the train and the control center that issues commands such as the movement authority messages. We customize the NS3 network simulator to model the LTE-based protocol with a real high-speed train trace dataset from public sources. We evaluate the resilience of the cellular network specifically on the handover process, which happens when the train travels from one base station to another. Due to the high-speed nature, the handover success rate is impacted and there are many protocol-based solutions proposed in this research area. We use the high-fidelity simulation model to evaluate some of them and compare the pros and cons.
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Title: Efficient and Practical Cluster Scheduling for High Performance Computing
Creator: Li, Boyang
Date: 2023
Description: Cluster scheduling plays a crucial role in the high-performance computing (HPC) area. It is responsible for allocating resources and...
Show moreCluster scheduling plays a crucial role in the high-performance computing (HPC) area. It is responsible for allocating resources and determining the order in which jobs are executed. Existing HPC job schedulers typically leverage simpleheuristics to schedule jobs, but such scheduling policies struggle to keep pace with modern changes and technology trends. The study of this dissertation is motivated by two new trends in HPC community: the rapid growth of heterogeneous system infrastructure and the emergence of artificial intelligence (AI) technologies. First, existing scheduling policies are solely CPU-centric. In contrast, systems become more complex and heterogeneous, and emerging workloads have diverse resource requirements, such as CPU, burst buffer, power, network bandwidth, and so on. Second, previous heuristic scheduling approaches are manually designed. Such a manual design process prevents adaptive and informative scheduling decisions. A recent trend in HPC is to intertwine AI to better leverage the investment of supercomputers. This embrace of AI provides opportunities to design more intelligent scheduling methods. In this dissertation, we propose an efficient and practical cluster scheduling framework for HPC systems. Our framework leverages AI technologies and considers system heterogeneity. The framework comprises four major components. First, shared network systems such as dragonfly-based systems are vulnerable to performance variability due to network sharing. To mitigate workload interference on these shared network systems, we explore a dedicated scheduling policy. Next, emerging workloads in HPC have diverse resource requirements instead of being CPU-centric. To cater to this, we design an intelligent scheduling agent for multi-resource scheduling in HPC leveraging the advanced multi-objective reinforcement learning (MORL) algorithm. Subsequently, we address the issues with existing state encoding approaches in RL-driven scheduling, which either lack critical scheduling information or suffer from poor scalability. To this end, we present an efficient and scalable encoding model. Lastly, the lack of interpretability of RL methods poses a significant challenge to deploying RL-driven scheduling in production systems. In response, we provide a simple, deterministic, and easily understandable model for interpreting RL-driven scheduling. The proposed models and algorithms are evaluated with real job traces from production supercomputers. Experimental results show our schemes can effectively improve job scheduling in terms of both user satisfaction and system utilization.
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Title: Data-Driven Modeling for Advancing Near-Optimal Control of Water-Cooled Chillers
Creator: Salimian Rizi, Behzad
Date: 2023
Description: Hydronic heating and cooling systems are among the most common types of heating and cooling systems installed in older existing buildings,...
Show moreHydronic heating and cooling systems are among the most common types of heating and cooling systems installed in older existing buildings, especially commercial buildings. The results of this study based on the Commercial Building Energy Consumption Survey (CBECS) indicates chillers account for providing cooling in more than half of the commercial office building floorspaces in the U.S. Therefore, to address the need of improving energy efficiency of chillers systems operation, research studies developed different models to investigate different chiller sequencing approaches. Engineering-based models and empirical models are among the popular approaches for developing prediction models. Engineering-based models utilize the physical principles to calculate the thermal dynamics and energy behaviors of the systems and require detailed system information, while the empirical models deploy machine learning algorithms to develop relationships between input and output data. The empirical models compared to the engineering-based approach are more practical in a system’s energy prediction because of accessibility to required data, superiority in model implementation and prediction accuracy. Moreover, selecting near accurate chiller prediction models for the chiller sequencing needs to consider the importance of each input variable and its contribution to the overall performance of a chiller system, as well as the ease of application and computational time. Among the empirical modeling methods, ensemble learning techniques overcome the instability of the learning algorithm as well as improve prediction accuracy and identify input variable importance. Ensemble models combine multiple individual models, often called base or weak models, to produce a more accurate and robust predictive model. Random Forest (RF) and Extra Gradient Boosting (XGBoost) models are considered as ensemble models which offer built-in mechanisms for assessing feature importance. These techniques work by measuring how much each feature contributes to the overall predictive performance of the ensemble.In the first objective of this work the frequency of hydronic cooling systems in the U.S. building stock for applying potential energy efficiency measures (EEMs) on chiller plants are explored. Results show that the central chillers inside the buildings are responsible for providing cooling for more than 50% of the commercial buildings with areas greater than 9,000 m2(~100,000 ft2). In addition, hydronic cooling systems contribute to the highest Energy Use Intensity (EUI) among other systems, with EUI of 410.0 kWh/m2 (130.0 kBtu/ft2). Therefore, the results of this objective support developing accurate prediction models to assess the chiller performance parameters as an implication for chiller sequencing control strategies in older existing buildings. The second objective of the dissertation is to evaluate the performance of chiller sequencing strategy for the existing water-cooled chiller plant in a high-rise commercial building and develop highly accurate RF chiller models to investigate and determine the input variables of greatest importance to chiller power consumption predictions. The results show that the average value of mean absolute percentage error (MAPE) and root mean squared error (RMSE) for all three RF chiller models are 5.3% and 30 kW, respectively, for the validation dataset, which confirms a good agreement between measured and predicted values. On the other hand, understanding prediction uncertainty is an important task to confidently reporting smaller savings estimates for different chiller sequencing control strategies. This study aims to quantify prediction uncertainty as a percentile for selecting an appropriate confidence level for chillers models which could lead to better prediction of the peak electricity load and participate in demand response programs more efficiently. The results show that by increasing the confidence level from 80% to 90%, the upper and lower bounds of the demand charge differ from the actual value by a factor of 3.3 and 1.7 times greater, respectively. Therefore, it proves the significance of selecting appropriate confidence levels for implementation of chiller sequencing strategy and demand response programs in commercial buildings. As the third objective of this study, the accuracy of these prediction models with respect to the preprocessing, selection of data, noise analysis, effect of chiller control system performance on the recorded data were investigated. Therefore, this study attempts to investigate the impacts of different data resolution, level of noise and data smoothing methods on the chiller power consumption and chiller COP prediction based on time-series Extra Gradient Boosting (XGBoost) models. The results of applying the smoothing methods indicate that the performance of chiller COP and the chiller power consumption models have improved by 2.8% and 4.8%, respectively. Overall, this study would guide the development of data-driven chiller power consumption and chiller COP prediction models in practice.
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Title: A Kernel-Free Boundary Integral Method for Two-Dimensional Magnetostatics Analysis
Creator: Jin, Zichao
Date: 2023
Description: Performing magnetostatic analysis accurately and efficiently is crucial for the multi-objective optimization of electromagnetic device designs...
Show morePerforming magnetostatic analysis accurately and efficiently is crucial for the multi-objective optimization of electromagnetic device designs. Therefore, an accurate and computationally efficient method is essential. Kernel Free Boundary Integral Method is a numerical method that can accurately and efficiently solve partial differential equations. Unlike traditional boundary integral or boundary element methods, KFBIM does not require an analytical form of Green’s function for evaluating integrals via numerical quadrature. Instead, KFBIM computes integrals by solving an equivalent interface problem on a Cartesian mesh. Compared with traditional finite difference methods for solving the governing PDEs directly, KFBIM produces a well-conditioned linear system. Therefore, the numerical solution of KFBIM is not sensitive to computer round-off errors, and the KFBIM requires only a fixed number of iterations when an iterative method (e.g., GMRES) is applied to solve the linear system.In this research, the KFBIM is introduced for solving magnetic computations in a toroidal core geometry in 2D. This study is very relevant in designing and optimizing toroidal inductors or transformers used in electrical systems, where lighter weight, higher inductance, higher efficiency, and lower leakage flux are required. The results are then compared with a commercial finite element solver (ANSYS), which shows excellent agreement. It should be noted that, compared with FEM, the KFBIM does not require a body-fitted mesh and can achieve high accuracy with a coarse mesh. In particular, the magnetic potential and tangential field intensity calculations on the boundaries are more stable and exhibit almost no oscillations.Furthermore, although KFBIM is accurate and computationally efficient, sharp corners can be a significant problem for KFBIM. Therefore, an inverse discrete Fourier transform (DFT) based geometry reconstruction is explored to overcome this challenge for smoothening sharp corners. A toroidal core with an airgap (C-core) is modeled to show the effectiveness of the proposed approach in addressing the sharp corner problem. A numerical example demonstrates that the method works for the variable coefficient PDE. In addition, magnetostatic analysis for homogeneous and nonhomogeneous material is presented for the reconstructed geometry, and results carried out from KFBIM are compared with the results of FEM analysis for the original geometry to show the differences and the potential of the proposed method.
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Title: Investigation in the Uncertainty of Chassis Dynamometer Testing for the Energy Characterization of Conventional, Electric and Automated Vehicles
Creator: Di Russo, Miriam
Date: 2023
Description: For conventional and electric vehicles tested in a standard chassis dynamometer environment precise regulations on the evaluation of their...
Show moreFor conventional and electric vehicles tested in a standard chassis dynamometer environment precise regulations on the evaluation of their energy performance exist. However, the regulations do not include requirements on the confidence value to associate with the results. As vehicles become more and more efficient to meet the stricter regulations mandates on emissions, fuel and energy consumption, traditional testing methods may become insufficient to validate these improvements, and may need revision. Without information about the accuracy associated with the results of those procedures however, adjustments and improvements are not possible, since no frame of reference exists. For connected and automated vehicles, there are no standard testing procedures, and researchers are still in the process of determining if current evaluation methods can be extended to test intelligent technologies and which metrics best represent their performance. For these vehicles is even more important to determine the uncertainty associated with these experimental methods and how they propagate to the final results. The work presented in this dissertation focuses on the development of a systematic framework for the evaluation of the uncertainty associated with the energy performance of conventional, electric and automated vehicles. The framework is based on a known statistical method, to determine the uncertainty associated with the different stages and processes involved in the experimental testing, and to evaluate how the accuracy of each parameter involved impacts the final results. The results demonstrate that the framework can be successfully applied to existing testing methods and provides a trustworthy value of accuracy to associate with the energy performance results, and can be easily extended to connected-automated vehicle testing to evaluate how novel experimental methods impact the accuracy and the confidence of the outputs. The framework can be easily be implemented into an existing laboratory environment to incorporate the uncertainty evaluation among the current results analyzed at the end of each test, and provide a reference for researchers to evaluate the actual benefits of new algorithms and optimization methods and understand margins for improvements, and by regulators to assess which parameters to enforce to ensure compliance and ensure projected benefits.
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