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Title: A STRUCTURAL ANALYSIS FRAMEWORK FOR CONCRETE FACED ROCKFILL DAMS
Creator: Quiroz, Juan E.
Date: 2013, 2013-12
Description: Concrete Faced Rockfill Dams (CFRD’s) are commonly built around the world. As energy demands soar and construction methods evolve, the...
Show moreConcrete Faced Rockfill Dams (CFRD’s) are commonly built around the world. As energy demands soar and construction methods evolve, the interest for construction of CFRD’s with larger heights has increased tremendously. However, because of construction of higher CFRD’s, some dams have experienced considerable fractures at the concrete faces. Well known cases include Campos Novos (Brazil), Barra Grande (Brazil), and Mohale (South Africa), where in some instances these cracks have led to dewatering of the reservoir to allow for the concrete slabs repairs. The development of these fractures may be attributed to the highly deformable rockfill body. In general, the state-of-the-art design of CFRD’s is mostly based on common practice rather than rigorous analysis procedures. And as such, cracking problems because of deformability of the rockfill may not be properly predicted unless a detailed analysis is performed. In this work, a new framework for analysis of CFRD’s is developed that is capable of predicting the possible concrete-facing failure. As a part of this framework, a comprehensive non-linear finite element analysis (FEA) scheme is developed to model the construction sequence, the contact interaction between the concrete facing and the rockfill body, and the impounding of the reservoir. As a case study, using the developed framework, the Kárahnjúkar CFRD (Iceland, 198m height) is analyzed, the results are validated by the field measurements, and mitigation measures suggestions are provided. This methodology, based on the results of the investigation, provides guidelines and establishes a framework for analysis of CFRD’s that can be used for design purposes.. Keywords: CFRD, Concrete Faced, Rockfill, Dam, Finite Element Analysis.
PH.D in Structural Engineering, December 2013
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Title: THE STRUCTURAL AND MAGNETIC STABILITY OF SELECT FERROUS HEUSLER SYSTEMS
Creator: Hasier, John J.
Date: 2017, 2017-05
Description: Heusler based functional or smart materials are a deep well of solutions to future energy, heat transport and mechanization problems. The half...
Show moreHeusler based functional or smart materials are a deep well of solutions to future energy, heat transport and mechanization problems. The half-metallic ferromagnetic nature of these crystalline intermetallic compounds is the source of their extraordinary properties. The loss of this magnetic ordering places limits on the range of application temperatures making knowledge of the Curie point of these novel materials essential for understanding of their limitations. High throughput continuous wavelet transform spectrum analysis of magnetic balance data generated on a custom modified Setaram Setsys Evolution 16/18 Differential Scanning Calorimeter- Differential Thermal Analyzer with simultaneous Thermogravimetric Analyzer was performed on select Fe, Co and Mn based Heusler compounds. The phase stability of Co-Fe-Si compounds is explored in relation to the high-Curie Temperature Co2FeSi and Fe2CoSi compounds via generation of equilibrium ternary isothermal phase diagrams at 1160 C and 800 C to enable greater control of the microstructure for future thermomechanically processed bulk smart device fabrication.
Ph.D. in Materials Science and Engineering
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Title: THE BIOENCLOS© FAÇADE PANEL: FROM SELECTION TO DESIGN, ASSESSMENT, AND BEYOND
Creator: Hassan, Ahmed Ali
Date: 2017, 2017-05
Description: Bio-polymeric materials derived from renewable biomass have successfully replaced conventional materials in many applications. Despite...
Show moreBio-polymeric materials derived from renewable biomass have successfully replaced conventional materials in many applications. Despite covering 10-15% of the current global plastic market, the application of the Bio-polymeric materials in the field of building facades has hitherto been limited. Unlike the conventional façade materials, Bio-polymeric materials can lessen the carbon footprint of the building façade significantly, reduce a considerable percentage of heat loss, and contribute in alleviating the amount of C&D waste dumped in landfills each year. This will help in saving the natural resources, conserving landfill spaces, decreasing pollution rates, and reducing the overall building weight and energy consumption. Accordingly, this research aims at developing a revolutionary lightweight building façade panel, made from Bio-polymeric agri-based materials, to replace the curtain wall glass and aluminum panel in office buildings, and to assess its impact on the environment, the building energy consumption, thermal performance and structural stability. To achieve that, the research discusses in the first place the potentiality of employing these materials while exploring the main physical and environmental challenges they may confront when introduced to the building facades realm. Secondly, the research adopts rigorous selection criteria to facilitate proposing innovative opaque/transparent materials capable of handling all the environmental, thermal, optical, functional, and economic considerations of the building facade. Thus, 1236 state-of-the-art Bio-polymeric materials have been exposed to a strict methodical screening process through structured quantifiable constraints. MCDM methods have then been employed to enable sorting and ranking the resulted set of candidates considering their order-of-preference in achieving the aforementioned performance criteria. Finally, computational simulation tests have been carried out to ensure that the BioEnclos© Façade Panel satisfies all the energy and building code requirements in terms of heat transfer, energy performance, optical properties, and structural behavior. Consequently, the simulation findings have demonstrated the great capabilities the BioEnclos© Façade Panel can provide to the future of the building façades. Through its several options, the BioEnclos© Façade Panel can reduce the weight of the entire building façade by a range of 43-53%. It also can improve the façade’s thermal resistance and energy savings by a range of 31-52%. In addition, it can maximize the visible light transmittance through the façade’s assembly by a range of 15-31%. Moreover, the BioEnclos© Façade Panel can be commissioned in different colors/textures with good UV radiation resistance, self-extinguishing abilities, exceptional 50-70% reduction in CO2 emissions, and multiple end-of-life options.
Ph.D. in Architecture, May 2017
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Title: INTERACTIONS BETWEEN NANOFLUIDS AND A SOLID SUBSTRATE: ROLE OF pH AND NANOFLUID PARTICLE CONCENTRATION ON THE THREE-PHASE CONTACT ANGLE
Creator: Horiuchi, Hiroki
Date: 2013, 2013-12
Description: We investigate the effect of pH on the interactions between a silica slurry and a silica wafer substrate (TEOS) made by the chemical vapor...
Show moreWe investigate the effect of pH on the interactions between a silica slurry and a silica wafer substrate (TEOS) made by the chemical vapor deposition of tetraethylorthosilicate gas in order to understand the optimization of the Chemical Mechanical Polishing (CMP) process and develop a high-performance silica slurry. The nature of the interactions is probed by the solid-liquid interfacial energy and the electrostatic surface potential at the solid surface. An overview of the CMP process is discussed in Chapter 1. Conventional techniques used to measure the electrostatic potential at the solid/liquid interface, such as the streaming potential and potentiometric titration method, are reviewed. Although there are many techniques for measuring the surface potential of powders, such as potentiometric titration and zeta potential measurement, there is no well-established technique for measuring the surface potential of the silica wafer. Therefore, in this research, we developed a methodology to determine the surface potential and surface charge density of a silica wafer substrate in contact with a slurry. We developed a novel method for calculating the surface potential and surface charge density using the experimental data of the three-phase contact angle in conjunction with the Young- Lippmann and the Poisson-Boltzmann equations. The surface chemistry of silica is discussed in Chapter 2 to elucidate the origin of the surface charge due to the ionization of the silanol groups on a silica wafer. Since the silica wafer is always in contact with the aqueous solution during the CMP process, we specifically focus on the behavior of silica in aqueous solutions. xvi In Chapters 3 and 4, the three-phase contact angle (TPCA) on silica is measured as a function of the pH by the goniometric technique. The surface potential and surface charge density at the silica/water surface are calculated by a model based on the Young- Lippmann equation in conjunction with the Gouy-Chapman model for the electric double layer. In measurements of the TPCA on silica, two distinct regions are identified with a boundary at pH 9.5—showing a dominance of the surface ionization of silanol groups below pH 9.5 and a dominance of the dissolution of silica into the aqueous solution above pH 9.5. Since the surface chemistry changes above pH 9.5, the model is applied to solutions below pH 9.5 (ionization dominant) for the calculation of the surface potential and surface charge density at the silica/aqueous interface. In order to evaluate the model, a galvanic mica cell was made of a mica sheet and the surface potential was measured directly at the mica/water interface. The model results are validated by the experimental data from the literature, as well as the results obtained by the potentiometric titration method and the electro-kinetic measurements. The interactions between the nanofluid and solid surface are explored in Chapter 5. Measurements of three-phase contact angle of the nanofluid on a silica substrate show that the contact angle decreases as the volume fraction increases due to the formation of particle layers on the solid surface. We conclude that it is driven by the depletion attractions between the nanoparticles and a solid surface. In the calculations, the energy (based on Young’s equation) and the structural energy of silica particles (based on statistical mechanics---Henderson’s equation) are in good agreement, indicating that the formation of the nanoparticle layering occurs near the solid surface, as expected. We reference the measurement of the forces between two mica surfaces by Israelachvili and xvii Pashley (1983 and 1984) to calculate the interaction energy against the distance between the two surfaces; we found that the strong repulsive force (hydration force) at a short distance (less than 2 nm) gives rise to enough energy to change the three-phase contact angle. In addition, the calculated inter-particle energy due to the hydration force (by using a statistical mechanics approach, see Trokhymchuck et al. 2001) shows that the hydration force can dramatically increase the inter-particle energy in the case of a volume fraction of water that is from 40 to 45%. The inter-particle energy corresponds to the energy change of 3-5⁰ in the three-phase contact angle, which is same as that found in our experimental data obtained from the contact angle measurements. Finally, we conclude that the hydration force between the silica particles on the solid surface plays an important role in altering the interfacial energy between a solid and liquid.
PH.D in Chemical Engineering, December 2013
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Title: A FORGOTTEN FOUNDATION OF THE BAUHAUS: PSYCHO-PHYSIOLOGICAL AESTHETICS AND THE INCEPTION OF MODERN DESIGN THEORY
Creator: Kalkatechi, Mina
Date: 2016, 2016-12
Description: This dissertation investigates the Bauhaus during its activity in Weimar and Dessau, as a pedagogical paradigm of modern era that drew upon...
Show moreThis dissertation investigates the Bauhaus during its activity in Weimar and Dessau, as a pedagogical paradigm of modern era that drew upon different aesthetic ideas of its past, which were set in motion by a vigorous interaction with human sciences during the era of 1890-1914. As a much-contested account of modernism, the story of the Bauhaus has been rewritten in many ways. While the dominant narrative considered the school as a forceful, autonomous entity that stood triumphant in its supposed denial of history and an innovation in modern pedagogy, studies that challenge this autonomy have been exclusive to social and political precedents of the Wilhelmine era. Yet, there remains a significant need in scholarship to fully grasp the scope of the Bauhaus as an aesthetic paradigm that goes beyond an elusive devotion to modern aesthetic ideals. My inquiry aims to position the Bauhaus as an outcome of a broader epistemological framework of its immediate past. Primarily set to address the aesthetics of everyday objects, scientific endeavors in psychology and psychophysiology during this time initiated a new aesthetics, whose main aim I argue, was to render a more humanistic prospect for modern art and architecture. This different connotation of modernity was decisive to counteract the extreme skepticism and negative mentality towards technological progress that was devoid of emotion and affect. Through discussing four discursive themes, I concoct a trajectory of different artistic attempts during 1890-1914 that act as precedents to those of the Bauhaus in 1920s. By so doing, this study highlights a significant contribution to inception of modern design at the Bauhaus: the interaction of human sciences with aesthetics at the turn of the century. This new aesthetics sought to understand its perceptual borders and created a theory of affect that engaged the Bauhaus more than it has been acknowledged in the scholarship. Although this new theory pervaded artistic realms through its interaction with social aspects of design, theories of craft and industry, and modern abstraction, it still remains a forgotten contribution to the Bauhaus. As such, the era of 1890-1914 shaped modern architectural theory more vigorously than previously realized.
Ph.D. in Architecture, December 2016
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Title: THE DESIGN AND ANALYSIS OF A MULTI-PERFORMANCE 3D PRINTED CONSTRUCTION UNIT: AN ALGORITHM TO UPGRADE THE STRUCTURAL, ENVIRONMENTAL AND ASSEMBLY PERFORMANCE IN MASONRY UNITS CONSTRUCTION
Creator: Kalkatechi, Maryam
Date: 2016, 2016-12
Description: This dissertation investigates the design and prototyping process of a new masonry unit. Drawing on the advantages offered by 3D printing...
Show moreThis dissertation investigates the design and prototyping process of a new masonry unit. Drawing on the advantages offered by 3D printing industry, it seeks to improve the unit’s structural efficiency and at the same time experiment with the potential benefits of ABS plastic for its realization. The first step of this process was to formulate a parametric algorithm based on a construction unit that provided different data-sketches. Through a case-by-case analysis, the research process either used these data-sketches as the preliminary step of analysis, or used trial and error to experiment first-hand with 3D printing processes to delineate the scope of their implementation and to account for the design consequences that production techniques brought upon the final product. By such examinations, the aim is to propose a new structural system that forms a new tectonic language and offers constructability solutions for a new wall system. As the most inexpensive and available plastic, using ABS plastic for 3D printed masonry units is a promising endeavor, which all the more necessitates addressing its design challenges. To do so, this research conceived of a 3D printed unit as an arrangement of cells that combined different considerations such as handling the unit, its structural performance and modularity in a uniform, ergonomic and sustainable wall system. The key features of this assembly comprised of a waffle plate that attached the EPS panel to the slab, a sprayed EPS, the ABS plastic unit that had ties as a design element for EPS installation, an interlocking snap-fit joint that vertically fastened the units together, and a custom-designed dovetail joint for horizontal connections. The parametric algorithm modified and redefined individual cells in the corners to realize these connections. The final step of this process entailed a comprehensive comparison of the proposed wall system to alternative wall systems, namely a solid wall system, an ICF wall system, and a cavity wall system for thickness, weight and thermal performance. Using Rescheck software, I compared these wall systems to a base model set in Chicago. Ultimately, this research is a detailed elaboration of a problem-solving process that exploits the capabilities of parametric design beyond its common emphasis on creating new geometries, by means of which the proposed system offers practical solutions to the prevalent challenges in masonry unit construction.
Ph.D. in Architecture, December 2016
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Title: EFFICIENT ALGORITHMS FOR POWER ASSIGNMENT PROBLEMS
Creator: Qiao, Kan
Date: 2015, 2015-05
Description: Power assignment problems take as input a directed simple graph G = (V;E) and a cost function c : E ! R+. A solution to this problem assigns...
Show morePower assignment problems take as input a directed simple graph G = (V;E) and a cost function c : E ! R+. A solution to this problem assigns every vertex a nonnegative power, p(v). We use H = (V;B(p)) to denote the spanning subgraph of G created by this power assignment. Let B(p) denote the set of all the links established between pairs of nodes in V under the power assignment p. The minimization problem then is to find the minimum power assignment, Pp(v), subject to H satisfying a specific property. 4 variants of this problem are discussed in this paper (a) Min-Power Strong Connectivity: H = (V;B(p)) is strongly connected. (b) Min-Power Broadcast: H = (V;B(p)) has a path from the fixed source z to every other vertex. (c) Min-Power Connectivity with 2-level power (Symmetric): c : E ! f0; 1g and H = (V;B(p)) is connected. (d) Min- Power Strong Connectivity with 2-level power (Asymmetric): c : E ! f0; 1g and H = (V;B(p)) is strongly connected. We give the exact solution using an improved integer linear program for problem (a) and (b) (We do not have a section for the integer linear program of Min-Power Broadcast problem since it is very similar to Min-Power Strong connectivity). Then we try to speedup current best approximation algorithms while preserving their approximation ratio. For problem (a), we give a fast variant of 1:85-approximation algorithm with running time O(n2 log2 n). For problem (b), we give a fast variant of 2(1 + ln n)-approximation algorithm for the most general cost model with running time O(n3) and a fast variant of 4:2- approximation algorithm for 2-dimensional cost model with running time O(nm), where n = jV j and m = jEj. For both problem (c) and (d), We give 5 3-approximation algorithms that run in O(m (n)), where (n) is the inverse Ackermann function.
Ph.D. in Computer Science, May 2015
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Title: MULTIVARIABLE ADAPTIVE IDENTIFICATION, FAULT DETECTION, DIAGNOSIS AND CONTROL OF ARTIFICIAL PANCREAS SYSTEMS
Creator: Turksoy, Kamuran
Date: 2015, 2015-05
Description: An artificial pancreas control system automates insulin pumps by using a closed-loop controller that receives information from sensors,...
Show moreAn artificial pancreas control system automates insulin pumps by using a closed-loop controller that receives information from sensors, computes the optimal insulin amount to be infused and manipulates the infusion rate of the pump for continuous blood glucose regulation in patients with type 1 diabetes. An integrated multivariable adaptive artificial pancreas control system is developed. Multivariable recursive time-series models are developed by using additional physiological measurements from a sport armband. The multivariable models are obtained with a proposed constrained weighted recursive identification algorithm to guarantee the stability conditions and satisfy the physiological properties of human body and glucose-insulin dynamics. Hypoglycemia early alarm system is developed based on the multivariable time-series models. By use of the physiological measurements, different thresholds are defined for different conditions such as meal, exercise and sleep for prevention of hypoglycemia. Generalized predictive control based adaptive control algorithm is proposed for blood glucose regulation in patients with type 1 diabetes. The control algorithm is completely adaptive and does not require any manual announcements. A meal detection algorithm is implemented into the control algorithm. Meals are detected based on the estimation of rate of appearance of glucose by use of Unscented Kalman filter. A novel framework is developed for meal bolus when a meal is detected. An artificial pancreas control system automates insulin pumps by using a closed-loop controller that receives information from sensors, computes the optimal insulin amount to be infused and manipulates the infusion rate of the pump for continuous blood glucose regulation in patients with type 1 diabetes. An integrated multivariable adaptive artificial pancreas control system is developed. Multivariable recursive time-series models are developed by using additional physiological measurements from a sport armband. The multivariable models are obtained with a proposed constrained weighted recursive identification algorithm to guarantee the stability conditions and satisfy the physiological properties of human body and glucose-insulin dynamics. Hypoglycemia early alarm system is developed based on the multivariable time-series models. By use of the physiological measurements, different thresholds are defined for different conditions such as meal, exercise and sleep for prevention of hypoglycemia. Generalized predictive control based adaptive control algorithm is proposed for blood glucose regulation in patients with type 1 diabetes. The control algorithm is completely adaptive and does not require any manual announcements. A meal detection algorithm is implemented into the control algorithm. Meals are detected based on the estimation of rate of appearance of glucose by use of Unscented Kalman filter. A novel framework is developed for meal bolus when a meal is detected. In addition to all, a fault detection and diagnosis algorithm is also developed. Multiway principal component analysis is used for detection of system failures. All proposed algorithms are tested with both simulation and clinical experiments. The result indicates that the proposed integrated artificial pancreas system provide significant improvements. The prosed system is able to deal with blood glucose regulation problem under various challenging conditions. Being fully automated and adaptive, it provides many advantages to patients with type 1 diabetes.
Ph.D. in Biomedical Engineering, May 2015
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Title: A SPECTRAL ELEMENT SOLVER FOR SIMULATING TURBULENT FLOWS IN COMPLEX GEOMETRIES
Creator: Kandala, Sriharsha
Date: 2015, 2015-07
Description: Flows in urban street canopies are quite complex both physically and geometrically and often unique to the specific canopy. Understanding the...
Show moreFlows in urban street canopies are quite complex both physically and geometrically and often unique to the specific canopy. Understanding the physics of these flows is important for various applications like prediction and control of dispersion in urban environments and efficient navigation of Micro-Air Vehicles (MAV) in gusty velocity fields among others. These flows are turbulent and the velocity fields are characterized by a wide range of spatial and temporal scales. Traditionally, given the exorbitant number of grid points required for accurate resolution of all flow features in computer simulations, experimental measurements supplemented with theory were the only feasible choice for understanding these flows. However with rapid increase in computing power and development of highly scalable algorithms to harness this power, numerical simulations are increasingly becoming feasible for higher Reynolds number flows. In the current work, flow in a model urban street canyon is studied using high-fidelity three-dimensional computational fluid dynamics simulations. Specsolve, a parallel spectral element solver capable of running parallel simulations utilizing thousands of processors, is developed for this purpose. The simulation domain used in this study consists of a 5 by 7 array of obstacles representative of a typical urban environment with the canyon aspect ratio corresponding to the skimming flow regime. These simulations do not use any turbulence model and are stabilized using a filtering procedure. Hot-wire data obtained from the wind tunnel experiments performed on an identical domain are used to prescribe realistic inflow boundary conditions upstream of the array. Numerical simulations were performed for cases where the flow is perpendicular to the array and with the flow at 15 degree angle of incidence. A grid resolution study is conducted to zero-in on the spectral element mesh required to resolve all important flow features for the 0 degree angle of incidence case. Mean velocity, coherent-structures and turbulence characteristics are used to describe the most important flow features in the domain. Streetwise evolution of flow is studied and the results indicate that flow reaches an equilibrium state by the third street.
Ph.D. in Mechanical and Aerospace Engineering, July 2015
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Title: SYNTHESIS AND POST-SYNTHETIC MODIFICATION OF TETRAZINE-BASED ORGANIC FRAMEWORKS
Creator: Kang, Lili
Date: 2016, 2016-05
Description: Porous organic polymers (POPs) have been studied extensively over the past decade. The intrinsic porosity and tunable chemical structures have...
Show morePorous organic polymers (POPs) have been studied extensively over the past decade. The intrinsic porosity and tunable chemical structures have seen applications in gas storage, separations, and even catalysis. However, a vast majority of the POPs rely on a narrow class of monomeric units and polymerization conditions which limit the diversity of functionality in the polymers, and hence their chemical properties. To get around these issues, a micro- and mesoporous tetrazine-based organic framework with BET surface area of 170 m2/g was synthesized through palladium catalyzed cross-coupling reaction. The structure of the polymer was confirmed by solid-state 13C NMR, ATR-IR, and EDX. The 1,2,4,5-tetrazine units on the struts of the framework were active toward inverse electron-demand Diels-Alder reactions, allowing for a post-synthetic introduction of different functionalities into the tetrazinebased organic frameworks (TzOF). The structures of modified polymers were verifed by solid-state 13C NMR and ATR-IR. To eliminate the use of transition metals during synthesis, a new class of sulfur-containing tetrazine-based organic framework was designed and synthesized by nucleophilic aromatic substitution reactions. The resulting mesoporous polymer framework, with 3,6-dithio-1,2,4,5-tetrazine unit on the struts, showed BET surface are of 38 m2/g. The structure of the framework was confirmed by ATR-IR and EDX. Post-synthetic modifications of the polymer were also achieved by reacting with dienophiles through inverse electron-demand Diels-Alder reactions. The structures of modified polymers were verified by ATR-IR. These two synthetic methods we have developed for tetrazine-based organic frameworks and their ability to introduce functionality post-synthetically brought additional functionalities to the POP family.
Ph.D. in Chemistry, May 2016
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Title: INFORMATION VISUALIZATION TECHNIQUES FOR ONLINE IDENTITY PRESENTATION: A MULTIDIMENSIONAL APPROACH
Creator: Mahmud, Athir
Date: 2016, 2016-07
Description: Information visualization offers a unique method to assist users in understanding large quantities of data, such as that which is found in...
Show moreInformation visualization offers a unique method to assist users in understanding large quantities of data, such as that which is found in social media. The recent surge in the use of social media platforms, the abundance of data generated, and the implications about what this data means has made it increasingly necessary to provide feedback to these users about what they and others are presenting online. Thus, it is critical for these individuals to access this information and gain some level of visual understanding regarding their own identities or that of a particular group. This dissertation is organized in the format of a three-paper dissertation. Chapter 1 is the introduction for the subsequent three chapters and provides background on information visualization and identity presentation in social media, while exploring theoretical approaches to visual perception and design. Chapter 2 demonstrates a variety of past and current multidimensional information visualization techniques that are relevant to social media data, as related to online identity presentation. The overview includes data portraits, motion-based visualization, music visualization, and textual structures. Chapter 3 introduces CarrinaCongress, an information visualization dashboard that affords users with the ability to compare two members of Congress in order to better understanding the elected officials’ tweets and external information. Chapter 4 presents HadithViz, a motion-based information visualization dashboard that borrows from video game interfaces and focuses on event-based tweets, as defined by hashtags related to sexism in the video gaming industry. Finally, Chapter 5 is the conclusion to this dissertation and will summarize the three individual studies, discuss limitations and implications, and provide recommendations that future work consist of simple, accessible visualizations that are based on existing visual languages and can be interpreted by a wide-ranging audience.
Ph.D. in Technical Communication, July 2016
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Title: ACCESSIBLE, ALMOST AB INITIO MULTI-SCALE MODELING OF ENTANGLED POLYMERS VIA SLIP-LINKS
Creator: Andreev, Marat
Date: 2014, 2014-12
Description: It is widely accepted that dynamics of entangled polymers can be described by the tube model. Here we advocate for an alternative approach to...
Show moreIt is widely accepted that dynamics of entangled polymers can be described by the tube model. Here we advocate for an alternative approach to entanglement modeling known as slip-links. Recently, slip-links were shown to possess important advantages over tube models, namely they have strong connections to atomistic, multichain levels of description, agree with non-equilibrium thermodynamics, are applicable to any chain architecture and can be used in linear or non-linear rheology. We present a hierarchy of slip-link models that are connected to each other through successive coarse graining. Models in the hierarchy are consistent in their overlapping domains of applicability in order to allow a straightforward mapping of parameters. In particular, the most–detailed level of description has four parameters, three of which can be determined directly from atomistic simulations. On the other hand, the least–detailed member of the hierarchy is numerically accessible, and allows for non-equilibrium flow predictions of complex chain architectures. Using GPU implementation these predictions can be obtained in minutes of computational time on a single desktop equipped with a mainstream gaming GPU. The GPU code is available online for free download.
Ph.D. in Physics, December 2014
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Title: DEVELOPMENT OF A PREDICIlVE FRAMEWORK TO FORECAST VENOUS STENOSIS
Creator: Mahmoudzadeh Akherat, S.m. Javid
Date: 2016, 2016-12
Description: The end stage renal disease (ESRD) patient population is growing at a troubling rate, calling for a focused attention to investigate the...
Show moreThe end stage renal disease (ESRD) patient population is growing at a troubling rate, calling for a focused attention to investigate the chronic kidney diseases, their characteristics and our lines of defense against them. One major medical treatment for ESRD patients is hemodialysis which is facilitated through vascular access (VA). The vascular access of particular interest in this investigation as well as the medical community is the brachiocephalic fistula (BCF), which is a form of arteriovenous fistula (AVF), created surgically by connecting the brachial artery and the cephalic vein. It is commonly used for elderly patients and for those with poor circulation systems, e.g. diabetics. The extreme hemodynamic environment that BCF creates triggers the onset of neointimal hyperplasia (NH) in most of these patients which leads to access failure and a high morbidity and mortality rate. This process happens in a matter of months, providing an excellent translational medicine experimental stage to observe as the vessel walls react and adapt to the new hemodynamically violent conditions. Through extensive analysis of the venous deformation and subsequent hemodynamics of a patient cohort of 160, a prognosticative framework to predict the vein deformation in these patients prior to the occurrence of the failure has been developed. The obtained results are the consequence of the integration of clinical practice and computational science. The proposed method was first based on our hypothesis which roots the NH in non-physiological wall shear stresses (WSS), and was then improved and modified using rigorous optimization and numerical approaches. This finding is essential to the modification of the current VA techniques to increase the patency of the AVFs, to prevent the diminishing functionality of the access, and to increase the life expectancy of ESRD patients. Moreover, this finding will further assist us in comprehension of the human vasculature growth and remodeling (G&R) through bypassing the analysis of unknown biological phenomena, as it is achieved purely by juxtaposing well-defined mathematical, physical, and medical concepts.
Ph.D. in Mechanical and Aerospace Engineering, December 2016
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Title: SEQUENTIAL MONTE CARLO METHODS FOR PARAMETER ESTIMATION, DYNAMIC STATE ESTIMATION AND CONTROL IN POWER SYSTEMS
Creator: Maldonado, Daniel Adrian
Date: 2017, 2017-05
Description: The estimation, operation and control of electrical power systems have always contained a degree of uncertainty. It is expected that, with the...
Show moreThe estimation, operation and control of electrical power systems have always contained a degree of uncertainty. It is expected that, with the introduction of technologies such as distributed generation and demand-side management, the ability of system operators to forecast the dynamic behavior of the system will deteriorate and as a result, the cost of keeping the system together will increase. Sequential Monte Carlo or Particle Filtering is a family of algorithms to efficiently perform inference in non-linear dynamic systems by exploiting their structure without assuming any linearity or normality structure. In this thesis we provide two novel ways of employing these algorithms for inference and control of power systems. First, we motivate the use Bayesian statistics in load modelling by introducing a novel statistical model to capture the aggregated response of a set of loads. We then use the model to characterize load with measurement data and prior information using the Sequential Monte Carlo algorithm. Second, we introduce the Model Predictive Control for power system stabilization. We present the use of the Sequential Monte Carlo algorithm as a way of solving the stochastic Model Predictive Control problem and we compare its performance to existing regulators. In addition, Model Predictive Control is applied to load shedding Finally, we test the performance of the algorithm in a large power system scenario.
Ph.D. in Electrical Engineering, May 2017
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Title: Toward Net Zero Energy: The Correlation Between Achitectural Forms of Tall Buildings and Wind Power Production
Creator: Babsail, Mohammed Omar
Date: 2011-07, 2011-07
Description: Tall buildings are a major component in today’s urban fabric in many parts of the world. The amount of energy they consume is extremely high....
Show moreTall buildings are a major component in today’s urban fabric in many parts of the world. The amount of energy they consume is extremely high. Architects have been showing an increasing interest in designing highly energy efficient tall buildings to reduce the energy consumption significantly and, more recently, to integrate onsite renewable energy production technologies. This integrative approach is referred to as net zero energy building (net ZEB) design. The applications of wind power in tall buildings have been of interest to many designers as the speed and, therefore, the power of the wind increases with height above the ground. A few notable international projects have been constructed that incorporate building integrated wind turbines (BIWT’s). The research presented in this thesis investigated the correlation between the architectural forms of tall buildings and the enhancement of wind power production in office buildings, towards the realization of net zero energy towers through extensive use of computer simulation software and wind tunnel testing. The wind enhancement characteristics of different case studies were determined, and the Wind Enhancement Factor (WEF) was calculated for each case, along the with annual electricity consumption based on five different climate zones. The results indicated significant wind speed enhancement by over 35% in the single tower with openings, and up to 45% in the twin tower arrangement, multiplying the energy production of the turbines by a factor of over three times. Results also showed that wind turbine technology could significantly contribute toward the net ZEB goal by generating up to 45% of the electricity demand by 2025 if the building is designed with 70% energy efficiency, when compared to the baseline of ASHRAE 90.1-2004.
Ph.D. in Architecture, July 2011
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Title: OPTIMAL LOAD SCHEDULING IN COMMERCIAL AND RESIDENTIAL MICROGRIDS
Creator: Ganji Tanha, Mohammad Mahdi
Date: 2015, 2015-05
Description: Residential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a...
Show moreResidential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a significant resource of demand response. Price-based demand response, which is in response to changes in electricity prices, represents the adjustments in load through optimal load scheduling (OLS). In this study, an efficient model for OLS is developed for residential and commercial microgrids which include aggregated loads in single-units and communal loads. Single unit loads which include fixed, adjustable and shiftable loads are controllable by the unit occupants. Communal loads which include pool pumps, elevators and central heating/cooling systems are shared among the units. In order to optimally schedule residential and commercial loads, a community-based optimal load scheduling (CBOLS) is proposed in this thesis. The CBOLS schedule considers hourly market prices, occupants’ comfort level, and microgrid operation constraints. The CBOLS’ objective in residential and commercial microgrids is the constrained minimization of the total cost of supplying the aggregator load, defined as the microgrid load minus the microgrid generation. This problem is represented by a large-scale mixed-integer optimization for supplying singleunit and communal loads. The Lagrangian relaxation methodology is used to relax the linking communal load constraint and decompose the independent single-unit functions into subproblems which can be solved in parallel. The optimal solution is acceptable if the aggregator load limit and the duality gap are within the bounds. If any of the proposed criteria is not satisfied, the Lagrangian multiplier will be updated and a new optimal load schedule will be regenerated until both constraints are satisfied. The proposed method is applied to several case studies and the results are presented for the Galvin Center load on the 16th floor of the IIT Tower in Chicago.
Ph.D. in Electrical and Computer Engineering, May 2015
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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
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Title: INTENTION AND ACTION: THE THEORY OF PLANNED BEHAVIOR AND EFFECT OF HABIT AND MINDFULNESS ON INFLUENZA VACCINATION
Creator: Mattson, Melissa
Date: 2013, 2013-07
Description: Several models of health behavior have been utilized in attempting to understand vaccination behavior, with mixed success. Additionally, there...
Show moreSeveral models of health behavior have been utilized in attempting to understand vaccination behavior, with mixed success. Additionally, there is a dearth of research on vaccination behavior in young, healthy adults, who are among the primary transmitters of preventable illness. The present study examined the applicability of the Theory of Planned Behavior (TPB) and the effects of past behavior and other health habits on vaccination intentions and influenza vaccine uptake. It also examined the moderating effects of mindfulness on the intention-behavior relationship for influenza vaccination. A total of 244 participants completed measures assessing attitudes, subjective norms, perceived behavioral control (PBC), and vaccination intentions in the TPB; the Self-Report Habit Index for three health behavior habits; and the Mindful Attention Awareness Scale. Participants also completed a follow-up assessment regarding vaccine uptake at the end of the 2012/2013 influenza season. Results indicated that attitudes and subjective norms explained >57% of the variance in vaccination intentions, with subjective norms predicting the largest portion of the variance in intention to receive the vaccine, as hypothesized. Intentions mediated the relationship between attitudes and vaccination, and between subjective norms and vaccination. Intentions and past vaccination predicted vaccination during the 2012/2013 influenza season, although PBC and other health behavior habits did not. Finally, mindfulness did not moderate the intention-behavior relationship for influenza vaccination. These findings provide evidence for the utility of the TPB in explaining vaccination intentions and behavior, as well as for the role that past behavior may play in predicting future vaccination.
PH.D in Psychology, July 2013
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Title: MODELING AND PERFORMANCE ANALYSIS OF DISTRIBUTED COMPUTER NETWORKS WITH DIFFERENTIATED SERVICES
Creator: Monsef, Ehsan
Date: 2015, 2015-07
Description: The rapid growth of data usage in wired and wireless networks has witnessed an increase in diversity of user tra c in the last few decades. A...
Show moreThe rapid growth of data usage in wired and wireless networks has witnessed an increase in diversity of user tra c in the last few decades. A network with di eren- tiated services guarantees the provision of Quality of service(QoS) for di erent tra c classes by incorporating various class-based scheduling disciplines. Recently, there has been interest in the study of network performance modeling in networks with di erentiated services. In particular, the performance modeling of di erentiated ser- vice networks in distributed architectures has attracted several network communities. The heterogeneity of user tra c can have major impact on the overall performance of resource allocation problems in computer networks. This work aims at shedding light on the performance modeling of distributed wired and wireless environments with di erentiated services. We study the performance of priority-based distributed schemes for several important network applications: (i) network routing(load balanc- ing) in wired network (ii) network selection in wireless environment (iii) scheduling in Body Area Networks and (vi) Interference mitigation scheme for Wireless Body Area Networks. We will utilize Game-theoretic models to model the interaction between network entities and evaluate the system performance analytically and empirically. Our main objective is to investigate the degree in which various service di erentiation mechanisms have impact on the overall performance of distributed networks. We an- alyze several important equilibria properties such as existence, convergence time, and ine ciency for the studied network scenarios. Extensive simulations are conducted to empirically evaluate our game-theoretic analysis for di erent network applications. First, we study a network of parallel links where each link incorporates General Processor Sharing scheduling mechanism. Using the non-cooperative game model, we investigate the existence and uniqueness of equilibrium points. We study the e ciency of equilibria by deriving an upper bound on the Price of Anarchy (PoA). Finally, we utilize the simulation to compare our PoA bound with actual bound. Second, we study wireless network selection in a distributed environment with Discriminatory Processor Sharing (DPS) scheduling discipline. We consider a set of wireless clients in a network composed of multiple base stations with di erentiated services. The goal of each wireless client is to assign itself to a wireless base station that gives the higher throughput. We formulate the interaction between clients as a weighted congestion game and investigate the existence of equilibria. We show that the equilibrium does not necessarily exists for a general network model. We give several regimes under which the equilibrium is guaranteed to exist. These regimes are implemented either on the base stations or wireless clients. Furthermore, we derive several upper bounds on the equilibrium convergence time and give an extensive simulation to evaluate our results. Third, we consider the interaction between autonomous Wireless Body Area Networks(WBAN) in a crowded environment such as hospital. We propose a dis- tributed approach that mitigates the inter-WBAN interference using the game theory models. The interaction between WBANs is modeled as an in nite repeated game. We propose a "grim" strategy for the formulated game and prove the SPE property under speci c conditions. Furthermore, we investigate the equilibrium by comparing that to a sub-optimal Pareto strategy. We test our results using a speci c simulator designed for WBAN. Finally, we propose a new QoS framework for WBAN architecture. The goal of this framework is to implement a separate QoS layer in the design of WBAN stack protocol so that it becomes independent of the application layer. The framework o ers an application pro le interface where each application can submit its QoS require- ments. The implementation of QoS framework in a separate layer and independent of application layer enables more scalable WBAN application development.
Ph.D. in Computer Engineering, July 2015
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Title: LIGHTLY SUPERVISED MACHINE LEARNING FOR CLASSIFYING ONLINE SOCIAL DATA
Creator: Mohammady Ardehaly, Ehsan
Date: 2017, 2017-05
Description: Classifying latent attributes of social media users has many applications in public health, politics, and marketing. For example, web-based...
Show moreClassifying latent attributes of social media users has many applications in public health, politics, and marketing. For example, web-based studies of public health require monthly estimates of the health status and demographics of users based on their public communications. Most existing approaches are based on supervised learning. Supervised learning requires human annotated labeled data, which can be expensive and many attributes such as health are hard to annotate at the user level. In this thesis, we investigate classification algorithms that use population statistical constraints such as demographics, names, polls, and social network followers to predict individual user attributes. For example, the racial makeup of counties is a source of light supervision came from the U.S. Census to train classification models. These statistics are usually easy to obtain, and a large amount of unlabeled data from social media sites (e.g. Twitter) are available. Learning from Label Proportions (LLP) is a lightly supervised approach when the training data is multiple sets of unlabeled samples and only label distributions of them are known. Because social media users are not a representative sample of the population and constraints are too noisy, using existing LLP models (e.g. linear models, label regularization) is insufficient. We develop several new LLP algorithms to extend LLP to deal with this bias, including bag selection and robust classification models. Also, we propose a scalable model to infer political sentiment from the high temporal big data, and estimate the daily conditional probability of different attributes as a supplement method to polls, for social scientists. Because, constraints are not often available in some domains (e.g. blogs), we propose a self-training algorithm to gradually adapt a classifier trained on social media to a different but similar field. We also extend our framework to deep learning and provide empirical results for demographic classification using the user profile image. Finally, when both textual and profile image are available for a user, we provide a co-training algorithm to iteratively improve both image and text classifications accuracy, and apply an ensemble method to achieve the highest precision.
Ph.D. in Computer Science, May 2017
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