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Title: CORROSION-RESISTANT ELECTRO-CATALYSTS AND SUPPORTS FOR ELECTROCHEMICAL ENERGY CONVERSION
Creator: Wang, Guanxiong
Date: 2016, 2016-12
Description: Polymer electrolyte fuel cells (PEFCs) convert chemical energy of fuels (eg. Hydrogen) directly to electrical energy with excellent power...
Show morePolymer electrolyte fuel cells (PEFCs) convert chemical energy of fuels (eg. Hydrogen) directly to electrical energy with excellent power density, high efficiency, and zero emissions. Several challenges have delayed the commercialization of fuel cells with one being the high cost and durability of the carbon-supported-platinum-based (Pt/C) electrocatalysts. The lifetime/durability issue is critical as insufficient durability/reliability of the catalysts affects the lifetime and economical viability of these devices. Carbon support corrosion is a major durability issue since the corrosion reaction is thermodynamically favorable but kinetically sluggish under normal operating conditions. The potential transients that occur during start and stop in automotive applications can lead to electrode potential excursions of up to 1.5 V and contribute to carbon corrosion. The best way to mitigate support corrosion in PEFCs is to replace the carbon supports with alternatives having high electronic conductivity, surface area and porosity. This dissertation investigates the following carbon alternatives: (i) tin doped indium oxide (ITO) and (ii) 1:1 mixed oxides of ruthenia and silica (RSO). Microstructure characterization and electrochemical evaluations, including accelerated stress tests (start-up/shut-down and load cycling protocols) were performed to evaluate ORR activity, fuel cell performance, and electrochemical stability under PEFC operating conditions. The ITO support and 40%Pt/ITO catalysts demonstrated exceptional electrochemical stability (and reasonable ORR activity) in rotating disk electrode (RDE) experiments under accelerated potential cycling that mimicked automotive drive cycles. However, Pt/ITO exhibited poor performance and stability during MEA evaluation in a PEFC. X-ray photoelectron spectroscopy (XPS) was employed to reveal the degradation modes of Pt/ITO during PEFC operation and it was found that the increase in the surface hydroxide concentration generates a passivating In(OH)3 layer that increases electrode resistance and undermines PEFC performance. The influence of the catalyst support on PEM degradation during PEFC operation was also studied. Rotating ring-disk electrode (RRDE) experiments were employed to estimate the fraction of H2O2 generated during the ORR on the supports (C and RSO) and catalysts (benchmark Pt/C and Pt/RSO). The percentage of H2O2 generated on C and Pt/C was 50% higher than that on RSO and Pt/RSO thus explaining the observed oxidative degradation resistance of the PEM with the latter supports/catalysts.
Ph.D. in Chemical Engineering, December 2016
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Title: TOWARDS COMPREHENSIVE COUNTERMEASURES AGAINST CYBER ATTACKS TO IMPROVE SYSTEM SURVIVABILITY
Creator: Wang, Li
Date: 2012-11-20, 2012-12
Description: Survivability refers to the capability of a system to ful ll its mission, in a timely manner, in the presence of attacks, failures, or...
Show moreSurvivability refers to the capability of a system to ful ll its mission, in a timely manner, in the presence of attacks, failures, or accidents. For many distributed systems, ensuring their survivability under directed attacks is critical. Tra c analysis, conducted by the attacker, could reveal the protocol being carried out by the components. Furthermore, having inferred the protocol, the attacker can use the pattern of the messages as a guide to the most critical components. In this thesis, we rst thwart these directed attacks by using message forwarding to reduce tra c di erences, thus diverge attackers from directed attack to random attack, which probabilistically prolongs the availability of important components in the system. Then, we investigate how to improve system availability when the system is under random attack. Although the attackers cannot di erentiate the di erences between critical and non-critical components, they can intelligently decide how to invest their resources by rationally selecting the number of components to attack. Under this case, how to maintain system reliability is another challenging issue. This thesis further discusses the attacker-defender problem and analyzes how to maximize system reliability under rational attacks. When one or more system processing elements are compromised by attackers, how to select applications and deploy their tasks to the remaining processing elements so that the system availability is maximized is also investigated in this thesis. To be more speci c, we assume the applications may have di erent values towards system availability and may or may not share the same composing tasks, and we presented two di erent approaches, i.e., Genetic Algorithm (GA) based approach and Max-Min-Min based approach to solving this problem. GA-based approach produces near optimal solutions and it can be used o -line when the performance is important and timing complexity is not the primary concern. While the Max-Min-Min based approach is computationally e cient and it is used when the timing is critical.
PH.D in Computer Science, December 2012
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Title: DIRECT DIFFEOMORPHIC REPARAMETERIZATION FOR CORRESPONDENCE OPTIMIZATION IN STATISTICAL SHAPE MODELING
Creator: Li, Kang
Date: 2015, 2015-05
Description: This dissertation proposes an efficient optimization approach for obtaining shape correspondence across a group of objects for statistical...
Show moreThis dissertation proposes an efficient optimization approach for obtaining shape correspondence across a group of objects for statistical shape modeling. With each shape represented in a B-spline based parametric form, the correspondence across the shape population is cast as an issue of seeking a reparametrization for each shape so that a quality measure of the resulting shape correspondence across the group is optimized. The quality measure is the description length of covariance matrix of the shape population, with landmarks sampled on each shape. The movement of landmarks on each B-spline shape is controlled by the reparameterization of the B-spline shape. The reparameterization itself is also represented with B-splines and B-spline coefficients are used as optimization parameters. We have developed formulations for ensuring the bijectivity of the reparameterization. A gradient-based optimization approach is developed, including techniques such as constraint aggregation and adjoint senstivity for efficient, direct di↵eomorphic reparameterization of landmarks to improve the group-wise shape correspondence. Numerical experiments on both synthetic and real 2D and 3D data sets demonstrate the efficiency and e↵ectiveness of the proposed approach.This dissertation proposes an efficient optimization approach for obtaining shape correspondence across a group of objects for statistical shape modeling. With each shape represented in a B-spline based parametric form, the correspondence across the shape population is cast as an issue of seeking a reparametrization for each shape so that a quality measure of the resulting shape correspondence across the group is optimized. The quality measure is the description length of covariance matrix of the shape population, with landmarks sampled on each shape. The movement of landmarks on each B-spline shape is controlled by the reparameterization of the B-spline shape. The reparameterization itself is also represented with B-splines and B-spline coefficients are used as optimization parameters. We have developed formulations for ensuring the bijectivity of the reparameterization. A gradient-based optimization approach is developed, including techniques such as constraint aggregation and adjoint senstivity for efficient, direct di↵eomorphic reparameterization of landmarks to improve the group-wise shape correspondence. Numerical experiments on both synthetic and real 2D and 3D data sets demonstrate the efficiency and e↵ectiveness of the proposed approach.
Ph.D. in Mechanical and Aerospace Engineering, May 2015
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Title: BIOPHYSICAL AND BIOCHEMICAL STUDY OF NATIVE AND EDITED DYSTROPHIN ROD REGION
Creator: Mangat, Khushdeep
Date: 2014, 2014-12
Description: Duchenne Muscular Dystrophy (DMD) is a severe X-linked recessive disease affecting 1 in 3500 boys that is characterized by the degeneration of...
Show moreDuchenne Muscular Dystrophy (DMD) is a severe X-linked recessive disease affecting 1 in 3500 boys that is characterized by the degeneration of muscle function and strength. The cause of this disease lies in gene defects that eliminate expression of the protein dystrophin. Becker Muscular Dystrophy, BMD is a milder form of disease that has a later onset and much longer survival (up to the 7th decade of life, compared to median survival of 25 years for DMD patients) because of the presence of low levels of modified dystrophin protein. BMD is very heterogeneous, however, and many cases are nearly as severe as DMD. A major therapy for DMD involves exon skipping, which produces modified forms of dystrophin that are very similar to BMD. However, how these edits impact the function of dystrophin, and how they are linked to the severity of BMD or the BMD-like state produced in DMD exon skip therapy is unknown. We investigated this in two specific cases involving a specific panel of BMD defects linked to a major cause of death, dilated cardiomyopathy (DCM). We also investigated the contribution of various exons to interaction with a signaling partner of dystrophin, neuronal nitric oxide synthetase (nNOS).
Ph.D. in Biological and Chemical Sciences, December 2014
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Title: A PARAMETRIC STUDY OF THE THERMAL PERFORMANCE OF DIFFERENT WALL SYSTEMS AT VARIOUS CLIMATE ZONES
Creator: Lai, Se Yen
Date: 2013, 2013-12
Description: One of the most common energy conservative measures used is designing an air-tight and a well-insulated envelope. While there is an abundance...
Show moreOne of the most common energy conservative measures used is designing an air-tight and a well-insulated envelope. While there is an abundance of high-efficiency building envelope designs in the market which offer low thermal conductivity and high R-values as well as various studies on the thermal performance of various wall constructions, the results were often based on simplified study model and are not incompliance with the current building code. Most studies also focus on only one particular climate zone and one type of wall construction. This research aims to examine the thermal performance of different types of wall construction based on the traditional building envelope design materials in various climate zones based on insulation and air cavity placements on a non-simplified reference model that is used for construction. Study models developed are incompliance with the American Society of Heating, Refrigerating, and Air-Conditioning Engineers [ASHRAE] 90.1-2010 based on U.S. Department of Energy [DOE] Commercial Prototype Building Model. The thermal performance of the wall will be determined using two different methods. The first method will be using Building Energy Modeling [BEM] software where the exterior wall construction will be modified based on DOE reference models where the results for the overall annual energy consumption [AEC] will be compared. AEC results showed small differences between study models which are negligible. The second method is the Total Thermal Constant [TTC] method, where the thermal lag will be compared. The building structures that will be used are a steel-framed structure which represents a medium office and a wood-framed structure which represents a quick service restaurant. TTC results were able to determine the least favorable study model.
M.S. in Civil Engineering, December 2013
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Title: STRUCTURE AND FUNCTION OF NATIVE AND EDITED DYSTROPHIN RODS
Creator: Sahni, Neha
Date: 2011-05-10, 2011-05
Description: The purpose of this study is to examine the biophysical properties of the rod region of the dystrophin protein. This is important due to the...
Show moreThe purpose of this study is to examine the biophysical properties of the rod region of the dystrophin protein. This is important due to the severity of the disease Duchenne Muscular Dystrophy, (DMD), which is associated with the malfunction of this protein. DMD is one of the most serious single gene genetic defects of man. This rod region consists of a number of repeat motifs called spectrin type repeats or STRs. The thermodynamical and biochemical stability analysis shows, which single motifs are unstable on their own and which ones become more stable when linked to their appropriate tandem neighbors. This knowledge will impact strategies to produce modified mini dystrophins for gene therapy. Exon skipping therapy is an emerging approach to treat such genetic diseases. This is done by the administration of modified antisense oligonucleotides, AONs, which can interfere with exon splicing process and eliminate certain exons from the mature transcript. Furthermore, the rod region has a number of ancillary functions, such as providing secondary binding sites for actin, neuronal NO synthetase and phospholipids, which may be adversely perturbed by the edits.
Ph.D. in Biological, Chemical, and Physical Sciences, May 2011
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Title: APPLICABILITY OF THE INTERVAL ANALYSIS METHOD TO RELIABILITY ASSESSMENT OF STRUCTURES
Creator: Taha, Raguez A.
Date: 2012-11-26, 2012-12
Description: The scope of this study is focused on the applicability of the interval method to the reliability analysis of structures. The study includes...
Show moreThe scope of this study is focused on the applicability of the interval method to the reliability analysis of structures. The study includes using the traditional probability methods in several applications and comparing the results with the interval analysis. Accordingly, the interval arithmetic rules are applied in several examples and the results are compared with those from the traditional probability theory concepts. Specifically, the procedure for using the interval methods was applied to the development of the probability of failure for a simple structural member; and for a link in a network system. Through three simple examples, the research shows that the interval method offers comparable results with those from the traditional first-order reliability method. The procedure based on the interval method, however, may offer advantages, especially in cases where the uncertainties in various parameters describing the reliability of a system are large. In the presence of large uncertainties, the traditional methods of reliability analysis, based on the first order approximation, may lose their accuracy. In these cases, the interval method may offer a simple method yet with more accurate results.
M.S. in Civil Engineering, December 2012
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Title: DAMAGE DETECTION OF STRUCTURES USING INTERVAL FINITE ELEMENT METHOD
Creator: Venkitaraman, Shyamala
Date: 2012-04-16, 2012-05
Description: Health assessment and damage detection for existing structures is an essential procedure for their safe and reliable operation so that any...
Show moreHealth assessment and damage detection for existing structures is an essential procedure for their safe and reliable operation so that any catastrophic failure may be prevented in a timely manner. However, results obtained from a health assessment of a structure possess uncertainties in measurements, system properties and loads. Furthermore, the conventional deterministic structural analyses are incapable of considering these uncertainties, thereby resulting in error when estimating the state of health of a structure. Interval (unknown-but-bounded) representation is one method to quantify uncertainty in a physical system. Using an interval variable, the uncertain parameter is bounded between extreme values. In this work, a new method for damage assessment of structures is developed that utilizes the results from structural health assessment as uncertain input parameters in an interval finite element analysis scheme. This method, due to its capability of considering uncertainties, offers a more robust process for estimating the possible existence of damage and overall health of the structure. As an illustrative example, the method is applied for a failed sign support structure. First, the structure's response from previous health assessment procedure was used to construct uncertain interval responses. Then using these interval responses as input parameters, an interval finite element method was performed. The results of the analysis verify and correlate with the failure location of the actual structure. Moreover, the lifetime assessment of the structure obtained from this method is the lower bound of, and correlates with the actual failure time of the structure.
M.S. in Civil Engineering, May 2012
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Title: POLYMER ELECTROLYTE MEMBRANES FOR ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE SYSTEMS: FUEL CELLS AND REDOX FLOW BATTERIES
Creator: Yun, Sukhwan
Date: 2014, 2014-12
Description: Direct methanol fuel cells (DMFCs) and redox flow batteries (RFBs) are well-known electrochemical energy conversion/storage systems that...
Show moreDirect methanol fuel cells (DMFCs) and redox flow batteries (RFBs) are well-known electrochemical energy conversion/storage systems that utilize redox reactions to convert or store electricity. Ion exchange membranes (IEMs) are used in DMFCs and RFBs as electrolyte separators. The critical requirements for IEMs in these applications are high ionic conductivity, low electrolyte permeability, high stability, and low cost. Silsesquioxane (SQO)-based sulfonated poly(etheretherketone) composite membranes were synthesized. Morphological changes in the composite membranes resulting from the introduction of SQO were studied using small-angle x-ray scattering. A sharp decrease in proton conductivity with SQO loading (> 20 wt%) was attributed to morphological changes in the membrane, including agglomeration and inhomogeneous dispersion of SQO particles within the ionic domains. Anion exchange membranes (AEMs) based on quaternized cardo-poly(etherketone) (QPEK-C) were prepared and evaluated for all-vanadium RFB (VRFB) applications. The QPEK-C AEMs with different degrees of functionalization (0.9–1.6) exhibited sulfate ion conductivities ranging between 5.6 and 15.2 mS cm-1 at 30 oC. The AEM had a lower VO2+ permeability (2.8×10-8 cm2 s-), compared to that of Nafion® 212 (2.9±0.2 ×10-7 cm2 s-1), which was attributed to the Donnan exclusion effect. The mechanical strength of QPEK-C AEM degraded by 35% after exposure to a 1.5 M VO2+ solution for 1500 hours due to the oxidation of aromatic rings. A single-cell VRFB employing the AEM separator yielded current and energy efficiencies (at 30 mA cm-2) of 97-99% and 80-82 %, respectively. Enhanced sulfate ion conductivity (8.4 ± 0.2 mS cm-1) and decreased VO2+ permeability (0.53×10-9 cm2 s-1) were achieved by incorporating 20 wt% of n-(trimethoxysilylpropyl)-n,n,n-trimethylammonium additives into QPEK-C, (the pristine QPEK-C AEM yielded corresponding values of 4.5 ± 0.5 mS cm-1 and 1.09×10-9 cm2 s-1). About 99% coulombic efficiency was achieved with the VRFBs employing the composite AEM. However, a rapid reduction of the ionic conductivity down to the value of the pristine membrane was observed when the composite AEM was immersed in 1.5 M VO2+ solution for 3 days. Vanadium-cerium RFBs (V-Ce RFBs) evaluated with QPEK-C AEM separators yielded identical energy efficiency (84%) to corresponding RFBs evaluated with Nafion® 212. However, after over 20 charge-discharge cycles, the V-Ce RFB with the AEM separator yielded unchanged efficiency and capacity, while a 50% loss of capacity was observed with the Nafion® separator. This suggested that QPEK-C AEMs are promising candidates for RFB separators when different cations are used in the two electrolyte solutions, in that they act as efficient barriers that preclude the intermixing of the cations due to the Donnan exclusion effect.
Ph.D. in Chemical Engineering, December 2014
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Title: B-SPLINE BASED ROBUST FORMULATION IN TOPOLOGY OPTIMIZATION
Creator: Gu, Yu
Date: 2014, 2014-12
Description: In this thesis, we extend the B-spline based density representation to robust topology optimization. The B-spline based representation has...
Show moreIn this thesis, we extend the B-spline based density representation to robust topology optimization. The B-spline based representation has been shown to have the ability of preventing checker-boards. With separate analysis and design mesh, the B-spline based filter is also competitive on computation storage compared with usual density filter. However, the current B-spline based representation is not robust where gray transitions exist. The recent proposed robust formulation highlights the manufacturability that simulates under- or over- etching designs compared with intermediate design. The robustness is demonstrated through three test cases. The minimum length control for quadratic B-splines is analytically derived with respect to knot span size and threshold. Our study about the characteristics of rectangular domain of B-spline based representation, shows that the optimized designs are comparable to those by density filter.
M.S. in Mechanical and Aerospace Engineering, December 2014
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Title: DATA SHARING WITH PRIVACY AND SECURITY
Creator: Qian, Jianwei
Date: 2019
Description: Data is a non-exclusive resource and has synergistic effects. Open data sharing will enhance the utilization of big data’s value and...
Show moreData is a non-exclusive resource and has synergistic effects. Open data sharing will enhance the utilization of big data’s value and tremendously boost economic growth and transparency. Data sharing platforms have emerged worldwide, but with very limited services. Security is one of the main reasons why most data are not commonly shared. This dissertation aims to tackle several security issues in building a trustworthy data sharing ecosystem. First, I reveal the privacy risks in data sharing by designing de-anonymization and privacy inference attacks. Second, I present an analysis of the relationship between the attacker's knowledge and the privacy risk of data sharing, and try quantifying and estimating the risk. Then, I propose anonymization algorithms to protect the privacy of participants in data sharing. Finally, I survey the status quo, privacy and security concerns, and opportunities in data trading. This dissertation involves various data types with a focus on graph data and speech data; it also involves various forms of data sharing including collection, publishing, query, and trading.
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Title: LOW-DOSE CARDIAC SPECT USING POST-FILTERING, DEEP LEARNING, AND MOTION CORRECTION
Creator: Song, Chao
Date: 2019
Description: Single photon emission computed tomography (SPECT) is an important technique in use today for the detection and evaluation of coronary artery...
Show moreSingle photon emission computed tomography (SPECT) is an important technique in use today for the detection and evaluation of coronary artery diseases. The image quality in cardiac SPECT can be adversely affected by cardiac motion and respiratory motion, both of which can lead to motion blur and non-uniform heart wall. In this thesis, we mainly investigate imaging de-noising algorithms and motion correction methods for improving the image quality in cardiac SPECT on both standard dose and reduced dose.First, we investigate a spatiotemporal post-processing approach based on a non-local means (NLM) filter for suppressing the noise in cardiac-gated SPECT images. Since in recent years low-dose studies have gained increased attention in cardiac SPECT owing to its potential radiation risk, to further improve the image quality on reduced dose, we investigate a novel de-noising method for low-dose cardiac-gated SPECT by using a three dimensional residual convolutional neural network (CNN). Furthermore, to reduce the negative effect of respiratory-binned acquisitions and assess the benefit of this approach in both standard dose and reduced dose using simulated acquisitions. Inspired by the success in respiratory correction, we investigate the potential benefit of cardiac motion correction for improving the detectability of perfusion defects. Finally, to combine the benefit of above two types of motion correction, dual-gated data acquisitions are implemented, wherein the acquired list-mode data are further binned into a number of intervals within cardiac and respiratory cycle according to the electrocardiography (ECG) signal and amplitude of the respiratory motion.
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Title: CITIZENSHIP PRESSURE, JOB STRESS, AND WORK-TO-FAMILY CONFLICT: THE MODERATING ROLE OF FLEXIBILITY IDIOSYNCRATIC DEALS
Creator: Ahmed, Shujaat Farah
Date: 2020
Description: Organizational expectations of employee performance have been expanding over time from traditional core task behaviors to include extra duties...
Show moreOrganizational expectations of employee performance have been expanding over time from traditional core task behaviors to include extra duties which may not be out of volition (Bolino, Turnley, Gilstrap, & Suazo, 2010). However, this extra work comes at a price, as employees are exhausted (Bolino et al., 2010) which can have health implications. Yet, no previous studies have examined the mechanism by which citizenship pressure is related to work interfering with family (WIF) conflict. Consequently, this study investigated an underlying mechanism, job stress, through which citizenship pressure was hypothesized to be related to work-family conflict from the work perspective, i.e., WIF conflict. This study also sought to identify the moderating role of flexibility idiosyncratic deals (i-deals) in the relationship of citizenship pressure with a) job stress, and b) WIF conflict. Data were collected across two waves with a time separation of one month in between waves. A total of 323 workers (mean age = 36.2) across industries in the United States participated in the study. Sixty-three percent identified as women, and 37% were men. Regression analyses were used to test the first three hypotheses. PROCESS was used to test the remainder of the hypotheses. Results for the regressions indicated that citizenship pressure was related at job stress and WIF conflict. Further, job stress was related to WIF conflict. Subsequently, the mediation hypothesis was significant. However, the moderation, and moderated mediation models were not statistically significant. I conducted post-hoc analyses to determine other possible significant paths in the model. The indirect effect of WIF conflict through the citizenship pressure and job stress link was statistically significant, thereby supporting an alternate mediation hypothesis. Perceived flexibility i-deals significantly moderated citizenship pressure and WIF conflict at time 1 only. The implications of this study are: managers should focus on their employees’ stressor experiences, as extra work beyond one’s specified job role is increasingly expected of employees. By doing so, pressure may be reduced through improving perceptions that employees can negotiate flexibility i-deals. This is especially important in an era of scarce resources, as pressure to go the extra mile is linked to a number of negative outcomes, such as increased WIF conflict and job stress.
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Title: DATA PRIVACY AND DEEP LEARNING IN THE MOBILE ERA: TRACEABILITY AND PROTECTION
Creator: Chen, Linlin
Date: 2020
Description: Privacy and deep learning have been two of the most exciting research trends in both academia and industry. On the one hand, big data rapidly...
Show morePrivacy and deep learning have been two of the most exciting research trends in both academia and industry. On the one hand, big data rapidly expedite lots of data orientated applications, especially like deep learning services. With the tremendous value exhibited by the data, the privacy of data subjects who generate the data, has also raised much attention. Meanwhile more regulations and legislation have been enacted or enforced, intending to enforce the companies and organizations to strictly comply with the personal privacy protection while collecting or utilizing their data. All these moves will substantially change the ways to train the deep learning models and provide AI services, and in some ways might hinder the development of deep learning if not coming up with some sophisticated mechanisms. On the other hand, deep learning has been showing incredibly promising performance in a variety of areas like face recognition, voice recognition, recommendation & advertising, autonomous driving, medical imaging, etc.. This keeps us thinking will deep learning also in turn influence privacy and be leveraged to compromise privacy. Meanwhile we also observe that mobile devices become so ubiquitous that more shares of data are generated on mobile devices, and mostly those data are both extremely sensitive for data subjects as well as extremely valuable for developing deep learning. We shouldn’t neglect the impact of mobile devices on both privacy and deep learning.In this thesis I explore the research on the interactions between privacy and deep learning, especially with the mobile devices being involved in. Specifically I work on: 1). How does privacy change the way we use the data when building deep learning models, and present the mechanism for privacy protection towards deep learning. 2). How does deep learning in turn make privacy more vulnerable to be compromised, and demonstrate the privacy compromise by facilitating deep learning to trace the source mobile devices and link the personal identities.
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Title: Integrity based landmark generation: A method to generate landmark configurations that guarantee mobile robot localization safety
Creator: Chen, Yihe
Date: 2020
Description: From the bronze-age city Nineveh to the modern metropolitan like Tokyo, traffic shape cities and profoundly affect the life of people. Similar...
Show moreFrom the bronze-age city Nineveh to the modern metropolitan like Tokyo, traffic shape cities and profoundly affect the life of people. Similar to how the wide-spreading of automobile had modified the modern cities in early 20th century, we are now standing on the eve of yet another traffic revolution. With the vast spreading of autonomous/semi- autonomous robotics application, it is important for the urban designers to design or retrofit urban environment that is safe and friendly to the autonomous robots; As more robots are deployed in life-critical situations, such as autonomous passenger vehicles, it is imperative to consider their safety, and in particular, their localization safety. While it would be ideal to guarantee safety in any environment without having to physically modify said environment, this is not always possible and one may have add landmarks or active beacons to reach an acceptable level of safety for landmark-based localization. Localization safety is assessed using integrity, the primary safety metric used in open-sky aviation applications that has been recently applied to mobile robots and can ac- count for the impact of rarely occurring, undetected faults. Conventional integrity monitor- ing method has high dependency on GPS system, while the traditional Global Navigation Satellite System - Inertia Measurement Unit (GNSS-IMU) based localization does not ap- plied in the metropolitan areas due to the signal blocking and multi-pathing problem caused by high-rise structures. Thus, this dissertation concentrates on the feature based integrity monitoring method. This dissertation formulates environmental localization safety problem as a system- atic optimization problem: given the robot’s trajectory and the current landmark map, add the minimal number of new landmarks at certain location such that the integrity risk along the trajectory is below a given safety threshold. This dissertation proposes two algorithms to solve the problem: Integrity-based Landmark Generator (I-LaG) and Fast I-LaG. I-LaG adds fewer landmarks but it is relatively computationally expensive; Fast I-LaG is less com- putationally intensive at the expense of more landmarks. Both simulation and experimental results are presented.
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Title: PREPARATION OF MG3SB2-XBIX THERMOELECTRIC MATERIAL AND THEIR LASER SINTERING BEHAVIOR
Creator: Xiao, Xudong
Date: 2020
Description: In the introduction part, a novel thermoelectric material, Zintl compounds were introduced due to its potential high thermoelectric...
Show moreIn the introduction part, a novel thermoelectric material, Zintl compounds were introduced due to its potential high thermoelectric performance in low-temperature applications as thermoelectric devices. Recent researches focused on Mg3Sb2-based Zintl Compounds was summarized in this article, and the general methods and its limitations to fabricate Mg3Sb2-based thermoelectric modules were introduced. Thus, a novel selective laser melting process was introduced, and it has enormous potential to fabricate Mg3Sb2-based thermoelectric modules in commercial applications. What’s more, the challenges of selective laser melting method were also discussed in the articles. For developing selective laser melting as the mature method to fabricate Mg3Sb2-based thermoelectric modules, many works and researches need to be done. In my project, the powder of Mg3.1(Sb0.3Bi0.7)1.99Te0.01 thermoelectric material was synthesized by using the mechanical alloying process and the proper particle size and distribution of powder using for selective laser melting was obtained by increasing the time of mechanical alloying. The thermoelectric properties of the powder prepared by mechanical alloying were measured, and it shows the powder still in a good performance after a long-time mechanical alloying particle reduction process. Finally, the obtained powder was treated by different parameters of continued wave fiber laser. The morphology and composition of the sintered area were analyzed to better understanding the process of laser sintering. More work needs to be done for using a selective laser melting method to fabricate Mg3Sb2-based thermoelectric modules in the future.
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Title: IMPROVING KNOWLEDGE OF MICROBIAL DYNAMICS ON BUILDING MATERIALS UNDER HIGH MOISTURE CONDITIONS
Creator: ZHAO, DAN
Date: 2020
Description: Most buildings experience some kind of high moisture event(s) throughout their life cycles, often resulting from water leaks or migration of...
Show moreMost buildings experience some kind of high moisture event(s) throughout their life cycles, often resulting from water leaks or migration of water vapor through the enclosure. Dampness and moisture in buildings leads to fungal growth and is associated with adverse human health outcomes. Although the dynamics of fungal growth on buildings materials has been investigated for decades, few studies have integrated modern chemical or microbiological analytical methods (e.g., DNA sequencing, qPCR, etc.) to understand microbial dynamics on materials held at high humidity conditions. Moreover, most mold growth prediction models remain relatively simplistic and rely solely on empirical data for visible mold growth. To bridge some of these gaps, this research aims to improve understanding of microbial growth and community dynamics on building materials under high moisture conditions and to improve our ability to predict microbial growth and community dynamics under a variety of conditions. Five distinct but overlapping research objectives are used to achieve these goals, including: (1) evaluating the growth of microorganisms on wetted building materials and identifying relationships between specific microbial taxa, metabolites, and environmental variables; (2) identifying inherent material chemistry drivers of fungal growth susceptibility and their relation to microbial community structure; (3) exploring how fluctuating moisture exposures impact bacterial and fungal growth and dynamics on building materials; (4) investigating microbial interactions using isolated communities on a single material; and (5) evaluating and improving existing mathematical mold growth models.
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Title: ENHANCED OPTICAL TOMOGRAPHY IN DIFFUSE MEDIA USING OPTICAL GATING OF EARLY PHOTONS
Creator: Ghosh, Aishwarya
Date: 2020
Description: Tissue biopsies, where a volume of tissue is removed from a patient, typically through needle extraction, provides critical information about...
Show moreTissue biopsies, where a volume of tissue is removed from a patient, typically through needle extraction, provides critical information about the cellular and molecular aspects of an individual patient’s health and/or disease. However, current pathological assessments of tissue biopsies evaluate less than 1% of the volume of the tissue (e.g., one to a few 5-micron slices are sectioned out of the biopsy and stained/processed for microscopic analysis). Since the bulk of tissue biopsy is carried out through optical imaging (absorption or fluorescence), a more 3D, “whole-biopsy” view is conceivably possible with optical projection tomography (OPT). The challenge with OPT has been that for clinically relevant sized biopsies, most photons undergo multiple scattering events that lead to loss of spatial resolution that makes accurate pathological analysis intractable. In my MS thesis, I worked on the development of an enhanced OPT system that employs optical gating based on non-linear up-conversion of infrared ultrashort laser pulses to isolate “early-arriving” photons that experience significantly less scatter than the bulk of photons transiting a scattering biological sample. Considering the complexity of such a system, the entirety of my MS thesis work was spent constructing and testing the femtosecond optical gated OPT system and though I was unable to validate its operation in biological samples, simulations suggest that the properties we were able to achieve could allow high resolution optical imaging in 0.1-1 cm-diameter specimens.
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Title: THREE ESSAYS IN ENTREPRENEURIAL FINANCE AND COMMODITY MARKETS
Creator: Jia, Jian
Date: 2020
Description: This dissertation includes three essays with a series of empirical investigations in areas of entrepreneurial finance and commodity markets.In...
Show moreThis dissertation includes three essays with a series of empirical investigations in areas of entrepreneurial finance and commodity markets.In the first essay, I study the impact of General Data Protection Regulation (GDPR) on investment in new and emerging technology firms. My findings indicate negative post-GDPR effect after its 2018 rollout on EU ventures, relative to their US counterparts, but no such effects following its 2016 enactment.In the second essay, I examine how investors’ tendency to prefer investing in local ventures interacts with the effects of the GDPR on venture investment in EU. I demonstrate that GDPR’s enactment and rollout differentially affect investors as a function of their proximity to ventures. Specifically, I show that GDPR’s rollout in 2018 has a negative effect on EU venture investment and the effects are higher when ventures and lead investors are not in the same country or union. The relationship manifests in the number of deals per month and in the amount invested per deal, and is particularly pronounced for newer and data-related ventures.In the third essay, I formulate two claims about spot and futures return prediction in industrial metal futures market. These claims lead to testable hypotheses, and provide theory-based restrictions for the coefficients of spot and futures return regression. I investigate six industrial metals and find empirical support for my hypotheses. The in-sample and out-of-sample evidence shows that financial variables, proxies for global economic activities, and the basis predict futures and spot price returns consistently with my hypotheses. Furthermore, my out-of-sample trading experiments document economic significance of the restrictions.
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Title: NANOMATERIALS FOR ADVANCED BATTERY CATHODES
Creator: Moazzen, Elahe
Date: 2020
Description: Cathode materials are key components that directly determine the power density of a battery. One of the most effective ways of developing high...
Show moreCathode materials are key components that directly determine the power density of a battery. One of the most effective ways of developing high power density cathodes is bringing them into the nano-scale world, which results in many expected and unexpected properties. Some of the desired characteristics include faster charge/discharge kinetics, improved capacity retention and structural stability due to the higher surface to volume ratio and shorter ion diffusion paths. In this dissertation a number of uniquely designed nano-sized cathode materials and nanocomposites are developed and investigated for alkaline aqueous and lithium ion battery applications. Nickel hydroxide (Ni(OH)2), which is one of the most important cathode materials in alkaline batteries, suffers from low conductivity, which usually leads to inefficient discharge and incomplete utilization of the material. A series of Ni(OH)2/Co(OH)2 core/shell nanoplatelets were synthesized and systematically investigated as cathode materials. Structure-property correlations revealed that electrochemical behavior and reversibility of Co(OH)2 redox conversion depended non-linearly on the average shell thickness, with the best performance (99.6% of theoretical capacity of the composite material) achieved at shell thickness of 1.9 ± 0.3 nm. Two fundamental phenomena were suggested to be responsible for the superior performance: templated shell deposition and galvanic coupling of core and shell materials.Manganese (IV) oxide (MnO2), which is another practical cathode that has a great potential to be utilized for a variety of energy storage systems, still has some major challenges including reversible cycling in rechargeable batteries. One of the most crucial challenges is the fact that polymorphs of MnO2 have different electrochemical activities as aqueous and Li-ion battery cathodes. However, most synthetic samples contain a mixture of polymorphs, which makes the structure-property correlations more complicated. This dissertation reports on systematic studies correlating synthesis, thermal and mechanical processing, and composite formation with polymorph composition, electrochemical performance and ion intercalation mechanisms. Among all the results, several main conclusions were reached: 1) Through control of the synthesis parameters and post-processing, desired phase compositions and nanoparticle morphologies, which optimize MnO2 performance in aqueous alkaline electrolyte, can be achieved. Nanoparticles with higher fraction of the akhtenskite polymorph showed higher reversible capacities in LiOH electrolyte (~210 mAh g-1), with stable performance for over 50 cycles. The effects of sub-nanoparticle organization of MnO2 polymorphs by thermal treatment without any morphology change on cycling performance, phase activation, and charge/discharge mechanisms in LiOH electrolyte as well as the detailed mechanism of the polymorph conversion during annealing were studied and for the first time, demonstrating that the electrochemical activity of MnO2 material strongly depends not only on the lattice structure of individual polymorphs but also on the sub-nanoparticle polymorph architecture and interphases.2) Several processing strategies, including thermal and mechanical processing, and composite fabrication were utilized to develop functional MnO2 cathodes for Li-ion batteries. Improvements in capacity and cycling performance were correlated to the presence of the pyrolusite phase of MnO2 and the crystallite size. Composite fabrication by graphene oxide wrapping also provided significant performance improvements through polymorph composition control and improved conductivity.
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