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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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Title: The Development of T7 Phage Based Imaging Probe and the Nature of Floating Cells in Human Embryonic Stem Cell Culture
Creator: Dasa, Siva Sai Krishna
Date: 2011-05-16, 2011-05
Description: Target specific nanoparticle based nuclear imaging probes have attracted significant attention recently. In most of the cases, these probes...
Show moreTarget specific nanoparticle based nuclear imaging probes have attracted significant attention recently. In most of the cases, these probes were synthesized by conjugating both affinity reagent and chelator molecules on the particle surface chemically. Subsequently, the isotope ions were attached to the particles via metalchelator interactions. Due to the nature of bio-conjugation process, the number of the chelator molecules and the geometry of the affinity reagent are hard to control. To overcome these limitations, a new approach of constructing an imaging probe was developed. In specific, T7 phage was used as a vehicle to synthesize a particle based imaging probe by displaying peptide that had both metal chelating (6 histidine) and targeting (RGD domains on the phage surface. It was demonstrated that the attachment of copper ions to the metal chelating domain does not interfere with target binding. Furthermore, by reducing the metal ions to metal, we were able to generate a very stable peptide templated metal hybrid T7 phage particle as potential target specific imaging probe. The behavior of the probes against both normal and tumor cells was investigated. The presence of floating cells is a common phenomenon in human embryonic stem (hES) cell cultures. Current assumption for the source of floating cells is that they are from apoptosis / senescence, cellular differentiation and other unavoidable imperfections in culture conditions. Inspired by recent studies on mitotic activities in stem cell colony, we believe the existence of floating cells is resulting from essential events required for hES cells proliferation. It was discovered that not all floating cells are dead and the percentage of floating cells over the attached cells was significantly increased with culture time possibly due to the space limitation for cells in the central part of the colonies. By providing more horizontal or vertical space through colony cutting and overlaid membrane insert in the Z direction, the percentages of floating cells were significantly reduced. All these results indicate that continuous cell division across the colonies is responsible for the emergence of floating cells during hES cell culture.
Ph.D. in Biology, May 2011
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Title: WIRELESS LINK SCHEDULING UNDER PHYSICAL INTERFERENCE MODEL
Creator: Ma, Chao
Date: 2014, 2014-07
Description: Latency minimization and capacity maximization are fundamental combinatorial optimization problems in wireless networks. Given a set of...
Show moreLatency minimization and capacity maximization are fundamental combinatorial optimization problems in wireless networks. Given a set of communication links in a multihop wireless network, the former computes a schedule satisfying all link demands with shortest latency, while the latter aims at selecting a maximum feasible subset of these links. We study both the Shortest Link Schedule (SLS) and Maximum Independent Set of Links (MISL) from a theoretical perspective, striving for generalized algorithmic treatments and provable approximation guarantees. Wireless devices are prone to radio frequency interference emanating from other devices. Interference can be major inhibitor to transmission performance, degrading the signal quality or even causing the communication to fail. Several models have been used for modeling wireless interference over the past decades. In contrast to graph-based protocol models, which assume the interference end at some boundary, we consider a more realistic SINR-based physical interference model. Under physical interference model, the problem SLS and MISL are hard to solve due to the technical obstacles caused by the ambient noise, non-local and additive nature of interference. In this dissertation, we consider both fixed transmission powers and power control. We explore interference natures under physical interference model and propose a generalization of independent set, which is capable of modeling the independent sets of wireless links. In addition, we present constant-approximation algorithm for MISL with monotone and sub-linear power assignment in both unidirectional and bidirectional mode, and for MISL with sub-mean power assignment in bidirectional mode. We also present constant-approximation algorithm for Maximum Weighted Independent Set of Links (MWISL) with linear power assignment in both unidirectional and bidirectional mode. For MISL with power control in unidirectional mode, we develop a constant-approximation algorithm with the canonical iterative power assignment.
Ph.D. in Computer Science, July 2014
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Title: FACTORS AFFECTING ACCEPTANCE OF DISABILITY: A PILOT STUDY AMONG CHINESE INDIVIDUALS WITH SPINAL CORD INJURY
Creator: Jiao, Jie
Date: 2012-07-07, 2012-07
Description: In the rehabilitation literature, acceptance of disability has been identified as one of the best indicators of positive adjustment following...
Show moreIn the rehabilitation literature, acceptance of disability has been identified as one of the best indicators of positive adjustment following an acquired disability (Elliott, Uswatte, Lewis, & Palmatier, 2000) and has significant implications in vocational rehabilitation and overall community integration (Green, Pratt, & Grigsby, 1984; Melamed, Groswasser, & Stern, 1992; Snead, & Davis, 2002). However, existing literature on acceptance of disability is primarily based on Western samples. The current study focused on people with spinal cord injuries and was the first attempt to apply the construct of acceptance of disability to a mainland Chinese sample. It also examined if demographic variables (i.e., age, gender, education level), disability related variables (i.e., functional limitations, pain), and psychosocial variables (i.e., depression, selfesteem, perceived social support, self-efficacy) are significantly related to AD. Hierarchical Regression revealed that higher self-esteem and less depressive symptoms were significantly associated with better acceptance of disability. The current study also indicated an alarmingly high prevalence of depression among Chinese individuals with spinal cord injury and suggested a mediating effect of depression and self-esteem on social support.
Ph.D. in Psychology, July 2012
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Title: DYNAMIC CONIC FINANCE: NO-ARBITRAGE PRICING AND NO-GOOD-DEAL PRICING FOR DIVIDEND-PAYING SECURITIES IN DISCRETE-TIME MARKETS WITH TRANSACTION COSTS
Creator: Rodriguez, Rodrigo
Date: 2012-06-27, 2012-07
Description: This thesis studies no-arbitrage pricing and dynamic conic nance for dividend-paying securities in discrete-time markets with transaction...
Show moreThis thesis studies no-arbitrage pricing and dynamic conic nance for dividend-paying securities in discrete-time markets with transaction costs. The rst part investigates no-arbitrage pricing for dividend-paying securities in discrete-time markets with transaction costs. We introduce the value process and the self- nancing condition in our context. Then, we prove a version of First Fundamental Theorem of Asset Pricing. Speci cally, we prove that the no-arbitrage condition under the e cient friction assumption is equivalent to the existence of a risk-neutral measure. We formulate an appropriate notion of a consistent pricing system in our set-up, and we prove that if there are no transaction costs on the dividends paid by the securities, then the no-arbitrage condition under the e cient friction assumption is equivalent to the existence of a consistent pricing system. We nish the chapter by deriving dual representations for the superhedging ask price and subhedging bid price of a derivative contract. The second part studies dynamic conic nance in the set-up introduced in the rst part. We formulate the no-good-deal condition in terms of a family of dynamic coherent risk measures, and then we prove a version of the Fundamental Theorem of No-Good-Deal Pricing. The Fundamental Theorem of No-Good-Deal Pricing provides a necessary and su cient condition for the no-good-deal condition to hold. Next, we study the no-good-deal ask and bid prices of a derivative contract. We particularize our results to the dynamic Gain-Loss Ratio, and compute the no-good-deal prices of European-style Asian options in a market with transaction costs.
Ph.D. in Applied Mathematics, July 2012
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Title: Contrails: The Evolution of an Air Force Technical Reports Digitization Project: Contrails ISL Brochure
Creator: Ahrens, Aric G.
Date: 2006-05-04
Description: A presentation given at the 2006 Illinois State Library Annual Government Documents Conference held May 4th, 2006 in Springfield, Illinois....
Show moreA presentation given at the 2006 Illinois State Library Annual Government Documents Conference held May 4th, 2006 in Springfield, Illinois. The presentation describes the efforts to make accessible to researchers and the public a collection of Air Force technical reports left at IIT by Crerar Library when they moved to the University of Chicago. Covered is the period 1996-2006.
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Title: Contrails: The Evolution of an Air Force Technical Reports Digitization Project
Creator: Ahrens, Aric G.
Date: 2006-05-04
Description: A presentation given at the 2006 Illinois State Library Annual Government Documents Conference held May 4th, 2006 in Springfield, Illinois....
Show moreA presentation given at the 2006 Illinois State Library Annual Government Documents Conference held May 4th, 2006 in Springfield, Illinois. The presentation describes the efforts to make accessible to researchers and the public a collection of Air Force technical reports left at IIT by Crerar Library when they moved to the University of Chicago. Covered is the period 1996-2006.
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Title: Contrails: The Evolution of an Air Force Technical Reports Digitization Project: Contrails ISL Meeting Presentation
Creator: Ahrens, Aric G.
Date: 2006-05-04
Description: A presentation given at the 2006 Illinois State Library Annual Government Documents Conference held May 4th, 2006 in Springfield, Illinois....
Show moreA presentation given at the 2006 Illinois State Library Annual Government Documents Conference held May 4th, 2006 in Springfield, Illinois. The presentation describes the efforts to make accessible to researchers and the public a collection of Air Force technical reports left at IIT by Crerar Library when they moved to the University of Chicago. Covered is the period 1996-2006.
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