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Title: DYNAMIC CONIC FINANCE VIA BACKWARD STOCHASTIC DIFFERENCE EQUATIONS AND RECURSIVE CONSTRUCTION OF CONFIDENCE REGIONS
Creator: Chen, Tao
Date: 2016, 2016-07
Description: This thesis consists of two major parts, and it contributes to the fields of mathematical finance and statistics. The contribution to...
Show moreThis thesis consists of two major parts, and it contributes to the fields of mathematical finance and statistics. The contribution to mathematical finance is made via developing new theoretical results in the area of conic finance. Specifically, we have advanced dynamic aspects of conic finance by developing an arbitrage free theoretical framework for modeling bid and ask prices of dividend paying securities using the theory of dynamic acceptability indices. This has been done within the framework of general probability spaces and discrete time. In the process, we have advanced the theory of dynamic sub-scale invariant performance measures. In particular, we proved a representation theorem of such measures in terms of a family of dynamic convex risk measures, and provided a representation of dynamic risk measures in terms of BS Es. The contribution to statistics is of fundamental importance as it initiates the theory underlying recursive computation of confidence regions for finite dimensional parameters in the context of stochastic dynamical systems. In the field of engineering, particularly in the field of control engineering, the area of recursive point estimation came to great prominence in the last forty years. However, there has been no work done with regard to recursive computation of confidence regions. To partially fill this gap, the second part of the thesis is devoted to recursive construction of confidence regions for parameters characterizing the one-step transition kernel of a time-homogeneous Markov chain.
Ph.D. In Applied Mathematics, July 2016
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Title: TWO-DIMENSIONAL AND AXISYMMETRIC BUBBLE RISE USING THE LEVEL SET METHOD
Creator: Dominik S, Michael
Date: 2013, 2013-07
Description: Gas bubbles in liquids are important in many industries, including power gen- eration, steel making, as well as chemical and waste water...
Show moreGas bubbles in liquids are important in many industries, including power gen- eration, steel making, as well as chemical and waste water treatment. A fundamen- tal understanding of the bubble rising physics is helpful in many practical applica- tions. A new level set code for incompressible, multiphase ows using the vorticity- streamfunction formulation in both two-dimensional and axisymmetric cases has been developed. The level set method is well suited to treating multiphase ows having complex interface shapes that may undergo topological changes such as merging and splitting of bubbles. Previous numerical and experimental results for single and mul- tiple bubbles are used to determine the numerical parameters that should be used for the new code and to demonstrate the accuracy of the model. The shape and ter- minal velocities of air bubbles in mineral oil and water are found to duplicate other experimental and calculated results very closely. Results have been compared from two-dimensional and axisymmetric versions of the code for bubbles merging with var- ious surface tension. It is found that prior to merging of the bubbles, the results for velocities and bubble shapes are very similar. However, surface tension is found to have a greater in uence on the axisymmetric results. Once the bubbles merge, the combined bubble evolves toward the same shape and terminal velocity of a single bub- ble having the same volume. The initial acceleration of a single air bubble in water is analyzed and found to be approximately 3:3g, not 2g, which is the predicted value from added mass analysis based on potential ow theory. When the liquid density is increased, the acceleration is also found to increase.
PH.D in Mechanical and Aerospace Engineering, July 2013
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Title: Developing Practical Tools and Algorithms for Biomedical Image Compression and Analysis
Creator: Duan, Bin
Date: 2024
Description: Biomedical imaging is fundamental to advancing medical research and clinical diagnostics, offering critical insights into complex biological...
Show moreBiomedical imaging is fundamental to advancing medical research and clinical diagnostics, offering critical insights into complex biological structures and processes. However, the inherent complexity and variability of biomedical images demand the development of specialized tools and algorithms for accurate and efficient analysis. In this thesis, we present a suite of solutions aimed at addressing two central challenges in biomedical imaging: efficient data storage and advanced image analysis.First, we develop high-ratio compression techniques that drastically reduce the storage requirements of biomedical images while preserving their analytical fidelity. These methods enable us to archive and manage vast datasets more efficiently, without compromising the critical details necessary for research and diagnostics. By minimizing compression artifacts, we ensure the integrity of the images, allowing for fast data transmission and seamless long-term storage without loss of quality.For image analysis, we introduce advanced algorithms that significantly enhance the precision and performance of key imaging tasks. Our segmentation methods, leveraging multi-scale non-local correlations, allow us to accurately delineate complex tissues and cellular structures in challenging biological images. In the area of neuronal tracing, we create algorithms that improve the accuracy of mapping intricate connections in densely labeled multi-spectral datasets, providing deeper insights into biological networks. Furthermore, we propose a robust image registration algorithm that corrects alignment errors in multi-modal and longitudinal datasets, ensuring precise and reliable integration for downstream analyses.By combining these innovations, we offer a practical toolkit that streamlines both the storage and analysis of biomedical images. Our work has the potential to significantly enhance research and diagnostic processes, providing tools that improve efficiency, accuracy, and scalability in biomedical imaging.
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Title: Investigating Variables Influencing Diagnostic Discrepancies Between the ADOS-2 and SRS-2
Creator: Boosalis, Emily
Date: 2024
Description: This study aims to investigate variables that may influence the alignment between the ADOS 2 and SRS-2 assessment scores in children with...
Show moreThis study aims to investigate variables that may influence the alignment between the ADOS 2 and SRS-2 assessment scores in children with autism spectrum disorder (ASD). Specific variables include gender, age, race, ethnicity, comorbid diagnoses, family history of ASD, intellectual functioning, and language skills. A sample of 165 children aged 2 to 17 was analyzed using Pearson’s r correlation coefficients to assess the alignment of total and domain scores. Additionally, univariate moderation analyses were conducted to explore the impact of demographic and clinical factors on the relationship between the SRS-2 total T-score and ADOS-2 total CS. Findings reveal no significant linear correlations between the ADOS-2 total CS and SRS-2 total T-score, nor between their specific domain scores, contrary to our initial hypotheses. However, moderation analyses indicate that gender identity significantly impacts the relationship, with stronger associations observed in girls compared to boys. This suggests that clinicians should be aware of discrepancies between clinician observations and parent reports, advocating for a multi-method assessment approach. The study emphasizes the need for tailored diagnostic strategies that consider individual differences, enhancing diagnostic accuracy and intervention efficacy for diverse ASD presentations. Ultimately, this research highlights the complexities of ASD assessment and underscores the importance of integrating multiple informants and assessment modalities for a comprehensive understanding of each child's unique profile. Future direction for research and clinical work are discussed.
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Title: Effect of Temperature on Salmonella Growth During Sprouting and Post-Harvest Storage of Broccoli Sprouts
Creator: Anant, Shuchita
Date: 2024
Description: Sprouts, such as broccoli, are a popular and nutritious food source. The microbial contamination of sprouts is often associated with seeds....
Show moreSprouts, such as broccoli, are a popular and nutritious food source. The microbial contamination of sprouts is often associated with seeds. The optimal conditions for germination and growth of seeds are similar to those needed for the proliferation of microorganisms such as Salmonella and Escherichia coli. These conditions, along with the fact that sprouts are usually consumed raw or lightly cooked contribute significantly to the risk of sprouts in causing foodborne illness outbreaks. This study evaluated the effect of temperature on the growth of Salmonella in broccoli sprouts during sprouting and post-harvest storage. The impact of pathogen load and seed treatment were also examined. Five hundred grams of broccoli seeds inoculated with 1 or 5 log CFU/g of Salmonella were treated either with water or 20,000 ppm Ca(OCl)2 for 15 min. Treated seeds were sprouted in glass jars at 4°C for 21 days or 20°C for 7 days. Harvested sprouts were stored at 4, 7, 10 for 21 days or at 25°C for 7 days. Samples were taken for analysis of Salmonella levels by plate count and culture enrichment. For seeds inoculated with a high or low level of Salmonella and treated with water, the pathogen grew and reached ~8 logs during sprouting at 20°C, while it decreased by 3 or 2 logs, respectively, during 21 days of sprouting at 4°C. For sprouts grown at 20°C, Salmonella population did not change during postharvest storage regardless of storage temperature. For sprouts grown at 4°C, no Salmonella proliferation was observed when the harvested sprouts were stored at 4, 7, or 10°C. But during storage at 25°C, the pathogen increased by 4 or 2 logs in sprouts grown from seeds inoculated at the high or low level, respectively. Seed treatment with 20,000 ppm Ca(OCl)2 reduced Salmonella on seeds by less than 1 log CFU/g. Salmonella growth during sprouting and storage of sprouts grown from Ca(OCl)2 treated seeds followed the same trend as that observed in sprouts grown from seeds treated with water. Sprouting at low temperatures inhibited pathogen proliferation. It was concluded that maintaining the cold chain (at below 10°C) during storage of sprouts is critical to prevent pathogen regrowth.
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Title: Synthesis and Photophysical Characterization of Novel Organic Triplet Donor–Acceptor Dyads for Light-Harvesting/Modulation Application
Creator: Yun, Young Ju
Date: 2022
Description: Donor–acceptor chromophoric systems (D–A) are important scaffolds for several light-harvesting/initiated processes and devices, including...
Show moreDonor–acceptor chromophoric systems (D–A) are important scaffolds for several light-harvesting/initiated processes and devices, including light-emitting diodes, photo-catalytic/redox systems, and photovoltaic cells. It has been hypothesized that for efficient photophysical processes (viz. energy/charge-transfer or excited-state interactions); it is ideal to tether the donor and acceptor chromophores into molecular dyads. To this end, I devised and synthesized several dyads by tethering an organic triplet energy donor and various polyaromatic chromophores (e.g., perylene derivatives and anthracene derivatives) onto a conjugated-/non-conjugated-linker (phenylene- and triptycene- linker, respectively). During the 4-5 years of my Ph.D., I synthesized a total of five (5) dyads: o–, p–3, and dyads 3–5. These systems were fully characterized using different spectroscopy tools/techniques. The spectroscopy investigations of the dyads have allowed me to decipher two important energy transfer pathways: through-bond and through-space with the phenylene linker and only through-space energy with the triptycene linker. Furthermore, the investigations led to the discovery that geometrical features such as face-to-face (co-facial) or slip-stacked interactions between the donor and acceptors chromophores might dictate the dynamic/kinetic of light-induced energy transfer in the dyads. Findings from my graduate research project paved the way for developing molecular engineering studies for light-harvesting/modulation applications.Subsequently, I was able to employ the dyads of my interest to achieve intramolecular and intermolecular triplet energy transfer (TEnT) triplet-triplet annihilation-based photon upconversion (TTA-PUC).
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Title: Exploring the role of perceived trustworthiness on leader humility's effectiveness
Creator: Pickett, Meghan L.
Date: 2024
Description: Over the last decade, several studies have uncovered the value of leader humility; however, these findings fail to consider the contextual...
Show moreOver the last decade, several studies have uncovered the value of leader humility; however, these findings fail to consider the contextual factors that may alter when and how humility plays a role. The current study looks to bridge this gap, by exploring how the effectiveness of perceived leader humility on follower outcomes (i.e., state learning goal orientation, feedback seeking behaviors, and employee engagement) is contingent upon follower perceptions of the leader’s trustworthiness. Data was collected from 160 leader-follower dyads across a variety of industries, using a cross-sectional design. Results from the study reinforced earlier findings that leader humility is often associated with positive follower outcomes such as seeking more feedback and reporting a higher learning goal orientation; however, these results were contingent upon how trustworthy they perceived the leader to be. Additionally, the study found evidence that perceptions of leader trustworthiness were related to group-based differences (e.g., age, gender). Together, these findings serve as a reminder that studying leader behaviors in isolation often risks simplifying the complex reality most leader’s face when trying to implement leader behaviors and skills.
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Title: Optimization of Large-Scale NOMA With Incidence Matrix Design and Physical Layer Security
Creator: Hwang, Eli W.
Date: 2024
Description: The Non-Orthogonal Multiple Access (NOMA) system is recognized for its capability to achieve higher spectral efficiency and massive...
Show moreThe Non-Orthogonal Multiple Access (NOMA) system is recognized for its capability to achieve higher spectral efficiency and massive connectivity. NOMA is intended to transmit massive user communications. The incidence matrix governs the relationship between users and resources for the Code domain NOMA (CD-NOMA). However, NOMA studies focus less on the design and optimization of the incidence matrix.Therefore, this thesis aims to investigate the development of a secure and large-scale NOMA system based on incidence matrix design. The main contributions are outlined as follows: Firstly, this research introduces a novel NOMA system. Distinct from existing studies, the NOMA system is based on combinatorial design. This innovative approach, coupled with a unique constellation design, eliminates the surjective mapping from the linear adding data of multiusers, reducing the complexity of constellation design and Multiuser Detection (MUD). The characteristics of the incidence matrix designs, Simple Orthogonal Multi-Arrays (SOMA), are explored, which display a distinct Latin Square pattern. The SOMA design's unique structure allows for the creation of a highly flexible and fair resource allocation matrix. The NOMA system's theoretical performance analysis equations are established, supporting dynamic adaptability and optimization. The design is validated by Monte Carlo simulation. Compared to other NOMA schemes, it offers higher degrees of freedom and lower complexity while maintaining graceful error rates to transmit a larger number of users. Secondly, a novel NOMA system utilizing incidence matrix information in the uplink is investigated. The incidence matrix pattern is exploited for MUD to achieve large-scale user connectivity. The incidence matrix is designed based on two critical mathematical concepts: parallel classes in hypergraph theory and orthogonal arrays (OAs) in combinatorial designs. Unlike other NOMA schemes, which require modification of their receiver and transmitter to decode superimposed multiuser signals, the unique pattern of the OA structure enables the use of conventional modulators. Consequently, the system load increases and the complexity and latency are reduced. The order of magnitude of the decoding complexity can be significantly reduced from O(N^3) to O(N) compared to the conventional minimum mean-square estimation (MMSE) decoder. Monte Carlo simulation validates that this novel NOMA system outperforms other NOMA designs in terms of error rate, data rate, and system size. Finally, a reconfigurable convolutional encoder design that integrates security and error correction based on physical layer security (PLS) and randomness is developed. This design addresses concerns over privacy, security, and reliability of Internet of Things devices in edge computing networks. The lightweight Convolutional encoders are designed to ensure security by updating the transfer function dynamically with user data. The reconfigurability of the design is achieved by replacing the fixed adder that represents the generator polynomials with the switch adder, enabling the use of 87 billion distinct updating structures, thereby enhancing the versatility of the design. BER-based PLS paradigms are demonstrated in the simulation. In the simulation, the robustness and randomness of this design are further validated through tests suggested by the National Institute of Standards and Technology for cryptographically secure pseudorandom number generators, such as the monobits, longest one, and run tests.
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Title: Exploring the role of perceived trustworthiness on leader humility's effectiveness
Creator: Pickett, Meghan L.
Date: 2024
Description: Over the last decade, several studies have uncovered the value of leader humility; however, these findings fail to consider the contextual...
Show moreOver the last decade, several studies have uncovered the value of leader humility; however, these findings fail to consider the contextual factors that may alter when and how humility plays a role. The current study looks to bridge this gap, by exploring how the effectiveness of perceived leader humility on follower outcomes (i.e., state learning goal orientation, feedback seeking behaviors, and employee engagement) is contingent upon follower perceptions of the leader’s trustworthiness. Data was collected from 160 leader-follower dyads across a variety of industries, using a cross-sectional design. Results from the study reinforced earlier findings that leader humility is often associated with positive follower outcomes such as seeking more feedback and reporting a higher learning goal orientation; however, these results were contingent upon how trustworthy they perceived the leader to be. Additionally, the study found evidence that perceptions of leader trustworthiness were related to group-based differences (e.g., age, gender). Together, these findings serve as a reminder that studying leader behaviors in isolation often risks simplifying the complex reality most leader’s face when trying to implement leader behaviors and skills.
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Title: INTEGRATED DECISION SUPPORT SYSTEM FOR THE SELECTION AND IMPLEMENTATION OF DELAY ANALYSIS IN CONSTRUCTION PROJECTS
Creator: Yang, Juneseok
Date: 2022
Description: The goal of this study is to establish an objective, user-friendly, and reliable decision support system, called delay analysis selection and...
Show moreThe goal of this study is to establish an objective, user-friendly, and reliable decision support system, called delay analysis selection and implementation system (DASIS), which allows delay analysts and practitioners in the construction industry to select a type of delay analysis that is most appropriate for given conditions and to perform the selected type of delay analysis. DASIS integrates a delay analysis selection system (DASS) module and an implementation module (DAIS) that performs the type of delay analysis selected by DASS in construction projects.The model that operates the DASS module consists of (1) four different delay analysis approaches currently available to practitioners; (2) a set of 26 attributes that affect the selection of a type of delay analysis; (3) a case-base involving 3,776 cases described by these 26 attributes and their corresponding output values (i.e., the most appropriate delay analysis approach); (4) a set of 7 categories consisting of subsets of attributes; (5) the weights of the attributes and the categories; and (6) a spreadsheet designed in Microsoft Excel that performs the calculations involved in case-based similarity assessment. The implementation module is a computerized analytics and automation platform that performs the type of delay analysis selected by DASS. In developing the DASS module, 26 attributes that influence the selection of the most appropriate type of delay analysis were identified based on a thorough literature review and were organized in seven categories. These attributes were used to evaluate the four types of delay analysis (i.e., static, dynamic, additive, and subtractive analyses). Based on the results of this evaluation, a case-base of 3,776 cases was generated while considering the constraints of each category. The weights of the attributes and categories were determined by using several methods. To determine the best-fit between a target case (defined by its 26 attributes) and the 3,776 cases stored in the case-base were used to perform a case-based similarity assessment to calculate weighted case similarity scores, and to find the best-informed solution to the delay analysis type selection problem. In developing the DAIS module, the four types of delay analysis were coded in Microsoft Excel using macros programmed in Visual Basic for Applications (VBA). This automated tool performs the selected delay analysis by DASS. The fully integrated DASIS model finds the best-fit match between a target case and cases stored in the case-base by means of similarity assessment methods by using weighted case similarity scores, hence identifying the most appropriate type of delay analysis for use in the target case, performs the selected type of delay analysis and generates a report about the results of the delay analysis to the analyst instantaneously, allowing the contractual parties to settle the issues quickly. This study is the first attempt to establish an objective decision support system (DASS) to assist delay analysts by automating the selection of a type of delay analysis using combinations of well recognized and reliable attributes and similarity assessment techniques. In addition, DASS is immediately followed by DAIS in an integrated system (DASIS) that does not only do the selection of the most appropriate type of delay analysis, but that also implements the selected delay analysis, hence providing ease of use and high speed. A case study based on fictitious scenarios is presented to demonstrate and validate the research approach. The use of the entropy weight method to calculate the weights of the attributes can be considered a minor limitation of the study. Finally, DASIS can be reformulated as a web-based application that allows analysts to work online using ordinary browsers anywhere and anytime.
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Title: Optimization of Large-Scale NOMA With Incidence Matrix Design and Physical Layer Security
Creator: Hwang, Eli W.
Date: 2024
Description: The Non-Orthogonal Multiple Access (NOMA) system is recognized for its capability to achieve higher spectral efficiency and massive...
Show moreThe Non-Orthogonal Multiple Access (NOMA) system is recognized for its capability to achieve higher spectral efficiency and massive connectivity. NOMA is intended to transmit massive user communications. The incidence matrix governs the relationship between users and resources for the Code domain NOMA (CD-NOMA). However, NOMA studies focus less on the design and optimization of the incidence matrix.Therefore, this thesis aims to investigate the development of a secure and large-scale NOMA system based on incidence matrix design. The main contributions are outlined as follows: Firstly, this research introduces a novel NOMA system. Distinct from existing studies, the NOMA system is based on combinatorial design. This innovative approach, coupled with a unique constellation design, eliminates the surjective mapping from the linear adding data of multiusers, reducing the complexity of constellation design and Multiuser Detection (MUD). The characteristics of the incidence matrix designs, Simple Orthogonal Multi-Arrays (SOMA), are explored, which display a distinct Latin Square pattern. The SOMA design's unique structure allows for the creation of a highly flexible and fair resource allocation matrix. The NOMA system's theoretical performance analysis equations are established, supporting dynamic adaptability and optimization. The design is validated by Monte Carlo simulation. Compared to other NOMA schemes, it offers higher degrees of freedom and lower complexity while maintaining graceful error rates to transmit a larger number of users. Secondly, a novel NOMA system utilizing incidence matrix information in the uplink is investigated. The incidence matrix pattern is exploited for MUD to achieve large-scale user connectivity. The incidence matrix is designed based on two critical mathematical concepts: parallel classes in hypergraph theory and orthogonal arrays (OAs) in combinatorial designs. Unlike other NOMA schemes, which require modification of their receiver and transmitter to decode superimposed multiuser signals, the unique pattern of the OA structure enables the use of conventional modulators. Consequently, the system load increases and the complexity and latency are reduced. The order of magnitude of the decoding complexity can be significantly reduced from O(N^3) to O(N) compared to the conventional minimum mean-square estimation (MMSE) decoder. Monte Carlo simulation validates that this novel NOMA system outperforms other NOMA designs in terms of error rate, data rate, and system size. Finally, a reconfigurable convolutional encoder design that integrates security and error correction based on physical layer security (PLS) and randomness is developed. This design addresses concerns over privacy, security, and reliability of Internet of Things devices in edge computing networks. The lightweight Convolutional encoders are designed to ensure security by updating the transfer function dynamically with user data. The reconfigurability of the design is achieved by replacing the fixed adder that represents the generator polynomials with the switch adder, enabling the use of 87 billion distinct updating structures, thereby enhancing the versatility of the design. BER-based PLS paradigms are demonstrated in the simulation. In the simulation, the robustness and randomness of this design are further validated through tests suggested by the National Institute of Standards and Technology for cryptographically secure pseudorandom number generators, such as the monobits, longest one, and run tests.
Show less

Title: Exploring the role of perceived trustworthiness on leader humility's effectiveness
Creator: Pickett, Meghan L.
Date: 2024
Description: Over the last decade, several studies have uncovered the value of leader humility; however, these findings fail to consider the contextual...
Show moreOver the last decade, several studies have uncovered the value of leader humility; however, these findings fail to consider the contextual factors that may alter when and how humility plays a role. The current study looks to bridge this gap, by exploring how the effectiveness of perceived leader humility on follower outcomes (i.e., state learning goal orientation, feedback seeking behaviors, and employee engagement) is contingent upon follower perceptions of the leader’s trustworthiness. Data was collected from 160 leader-follower dyads across a variety of industries, using a cross-sectional design. Results from the study reinforced earlier findings that leader humility is often associated with positive follower outcomes such as seeking more feedback and reporting a higher learning goal orientation; however, these results were contingent upon how trustworthy they perceived the leader to be. Additionally, the study found evidence that perceptions of leader trustworthiness were related to group-based differences (e.g., age, gender). Together, these findings serve as a reminder that studying leader behaviors in isolation often risks simplifying the complex reality most leader’s face when trying to implement leader behaviors and skills.
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Title: Development of Human Brain Atlas Resources
Creator: Qi, Xiaoxiao
Date: 2020
Description: Digital human brain atlases play an increasingly critical role and are widely used in neuroimaging studies such as developing biomarkers,...
Show moreDigital human brain atlases play an increasingly critical role and are widely used in neuroimaging studies such as developing biomarkers, training data for machine learning algorithms, functional connectivity analysis and so on. A brain atlas typically consists of brain templates of different imaging modalities that are representative of individual brains under study in a standard atlas space and semantic labels that delineate brain regions according to the characteristics of the underlying tissue.The IIT Human Brain Atlas project has developed the state-of-the-art diffusion tensor imaging (DTI) template, high angular resolution diffusion imaging (HARDI) template, and anatomical templates for the young adult brain in a standardized space. The probabilistic maps of gray matter (GM) labels and tissue segmentations were also constructed based on the anatomical information of the atlas. This thesis introduced an enhanced T1-weighted template that were developed by combining information from both diffusion and anatomical data. The GM labels and tissue segmentation maps in the standardized space were also improved. Existing white matter (WM) atlases typically lack specificity in terms of brain connectivity. A new approach named regionconnect was developed in this work based on precalculated average healthy adult brain connectivity information stored in standard space in a fashion that allows fast retrieval and integration. This thesis first generated and evaluated the white matter connectome of the IIT Human Brain Atlas v.5.0. Next, the new white matter connectome was used to develop multi-layer, connectivity-based labels for each white matter voxel of the atlas, consistent with the fact that each voxel may contain axons from multiple connections. The regionconnect algorithm was then developed to rapidly integrate information contained in the multi-layer labels across voxels of a white matter region and to generate a list of the most probable connections traversing that region. The regionconnect algorithm as well as the white matter tractogram and connectome, multi-layer, connectivity-based labels, and associated resources developed for the IIT Human Brain Atlas v.5.0 in this work are available at www.nitrc.org/projects/iit. Furthermore, it was well established that use of a young adult atlas in studies of older adults is inappropriate due to the age-related characteristic changes of the brain, resulting in an increasing demand of digital brain atlases for the older adults. To fulfill this demand, a function of fiber orientation distribution (fODF) template that is representative of older adults was developed in a standardized atlas space for studies of white matter of older adult human brains, which built a solid foundation for the development of the white matter resources for the older adults human brain atlas.
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Title: Evaluating Speech Separation Through Pre-Trained Deep Neural Network Models
Creator: Prabhakar, Deeksha
Date: 2023
Description: Speaker separation involves separating individual speakers from a mixture of voices or background noise, known as the "cocktail party problem....
Show moreSpeaker separation involves separating individual speakers from a mixture of voices or background noise, known as the "cocktail party problem." This refers to the ability to focus on a specific sound while filtering out other distractions.In this analysis, we propose the idea of obtaining features present in the original data and then evaluating the impact they have on the ability of the model to separate the mixed audio streams. The dataset is prepared such that these feature values can be used as predictor variables to various models like Logistic Regression, Decision Trees, SVM (both rbf and linear kernel), XGBoost, AdaBoost, to obtain the most contributing features that is the features that will lead to a better separation. These results shall then be analyzed to conclude the features that affect separating the audio streams the most. Initially, 400 audio streams are selected from the VoxCeleb dataset and combined to form 200 single utterances. After the mixes are obtained, the pre-trained Speechbrain model, sepformer-whamr is used. This model separates the audio mixes given as input and obtain two outputs that should be as close as possible to the original ones. A feature list from the 400 chosen audios is obtained and then the effect of certain features on the model's capability to distinguish between multiple audio sources in a mixed recording is assessed. Two analysis parameters- permutation feature importance and SHAP values are used to conclude which features have more effect on separation. Our hypothesis is that the features contributing the most to a good separation are invariant across datasets. To test this hypothesis, we obtain 1,000 audio streams from the Mozilla Common Voice Dataset and perform the same experimental methodology described above. Our results demonstrate that the features we extract from VoxCeleb dataset are indeed invariant and aid in separating the audio streams of the Mozilla Common Voice dataset.
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Title: Shared Authentic Leadership and Team Attitudes: The Role of Social Support and Team Diversity
Creator: Shu, Frank
Date: 2023
Description: Across 15 weeks, data from 48 interdisciplinary teams were collected to test the direct and indirect effects of shared authentic leadership on...
Show moreAcross 15 weeks, data from 48 interdisciplinary teams were collected to test the direct and indirect effects of shared authentic leadership on team attitudes (i.e., team work engagement & team satisfaction). Under the conservation of resources (COR) theory, team social support was considered a team resource, mediating the relationship between shared authentic leadership and team attitudes respectively. Functional diversity was also examined as a moderator between team social support and team attitudes. Results revealed that shared authentic leadership was a significant and positive predictor of team attitudes. However, team social support was not found to be a significant mediator. On the other hand, functional diversity was able to partially moderate the relationship between socio-emotional social support and team work engagement. A discussion of the results, strengths, and limitations of this study will be provided at the end of this manuscript.
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Title: Development of MIITRA T1w, DTI and FOD templates of the older adult brain in a common space
Creator: Wu, Yingjuan
Date: 2022
Description: Human brain atlases play an important role in neuroimaging studies and are commonly used as references for spatial normalization, tissue...
Show moreHuman brain atlases play an important role in neuroimaging studies and are commonly used as references for spatial normalization, tissue segmentation, automated brain parcellation, seed selection for functional connectivity analyses and fiber-tracking, or standards for algorithm evaluation. A brain atlas typically consists of brain templates of different imaging modalities in a common space and semantic labels that delineate brain regions according to the characteristics of the underlying tissue.High-quality T1-weighted (T1w) and diffusion tensor imaging (DTI) brain templates that are representative of the individuals under study enhance the accuracy of template-based neuroimaging investigations, and when they are also located in a common space they facilitate optimal integration of information on brain morphometry and diffusion characteristics. However, such multimodal templates have not been constructed for the brain of older adults. This thesis introduced an iterative method for construction of multimodal T1w and DTI templates that aims at maximizing the quality of each template separately as well as the spatial matching between templates. The performance of the proposed method was evaluated across iterations and was compared to the performance of state-of-the-art multimodal template construction approaches based on multichannel registration. Using the proposed method, along with other recently developed techniques, high-quality T1w and DTI templates of the older adult brain were developed in a common space at 0.5mm resolution for the MIITRA atlas. In this thesis, the new templates were compared to other available templates in terms of the image quality, inter-subject and inter-modality spatial normalization accuracy achieved when used as a reference, and the representativeness of the older adult brain. Furthermore, as fiber orientation distribution (FOD) model is capable of resolving intravoxel heterogeneity, which overcomes the limitations of the DTI model especially in regions with complex neuronal microarchitecture, FOD template is in high demand to facilitate FOD-based, fixel-based analyses, white matter connectivity studies and white matter parcellations. In this thesis, several FOD template construction methods were compared and a FOD template was developed at 0.5mm resolution for the MIITRA atlas. Overall, the present work brought new insights into multimodal template construction, conducted a thorough, quantitative evaluation of available multimodal template construction methods, and generated much-needed high quality T1w, DTI and FOD templates of the older adult brain in a common space with 0.5mm resolution.
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Title: ENLARGED PERIVASCULAR SPACES IN COMMUNITY-BASED OLDER ADULTS
Creator: Javierre Petit, Carles
Date: 2020
Description: Enlarged perivascular spaces (EPVS) have been associated with aging, increased stroke risk, decreased cognitive function and vascular dementia...
Show moreEnlarged perivascular spaces (EPVS) have been associated with aging, increased stroke risk, decreased cognitive function and vascular dementia. Furthermore, recent studies have investigated the links of EPVS with the glymphatic system (GS), since perivascular spaces are thought to play a major role as the main channels for clearance of interstitial solutes from the brain. However, the relationship of EPVS with age-related neuropathologies is not well understood. Therefore, more conclusive studies are needed to elucidate specific relationships between EPVS and neuropathologies. After demonstration of their neuropathologic correlates, detailed assessment of EPVS severity could provide as a potential biomarker for specific neuropathologies.In this dissertation, our focus was twofold: to develop a fully automatic EPVS segmentation model via deep learning with a set of guidelines for model optimization, and to evaluate both manual and automatic assessment of EPVS severity to investigate the neuropathologic correlates of EPVS, and their contribution to cognitive decline, by combining ex-vivo brain magnetic resonance imaging (MRI) and pathology (from autopsy) in a large community-based cohort of older adults. This project was structured as follows. First, a manual approach was used to assess neuropathologic and cognitive correlates of EPVS burden in a large dataset of community-dwelling older adults. MR images from each participant were rated using a semiquantitative 4-level rating scale, and a group of identified EPVS was histologically evaluated. Two groups of participants in descending order of average cognitive impairment were defined based and studied. Elasticnet regularized ordinal logistic regression was used to assess the neuropathologic correlates of EPVS burden in each group, and linear mixed effects models were used to investigate the associations of EPVS burden with cognitive decline. Second, a fully automatic EPVS segmentation model was implemented via deep learning (DL) using a small dataset of 10 manually segmented brain MR images. Multiple techniques were evaluated to optimize performance, mainly by implementing strategies to reduce model overfitting. The final segmentation model was evaluated in an independent test set and the performance was validated with an expert radiologist. Third, the DL segmentation model was used to segment and quantify EPVS. Quantified EPVS (qEPVS) were evaluated by combining ex-vivo MRI, pathology, and longitudinal cognitive evaluation. EPVS quantification allowed to study qEPVS both in the whole brain and regionally. Two different qEPVS metrics were studied. Elastic-net regularized linear regression was used to assess the neuropathologic correlates of qEPVS within each region of interest (ROI) under study, and linear mixed effects models were used to investigate the associations of qEPVS with cognitive decline. Finally, a preliminary study investigated the longitudinal associations of qEPVS with time. The DL segmentation model was re-trained using 4 in-vivo MR images. EPVS were segmented and quantified in a large longitudinal cohort where each participant was imaged at multiple timepoints. Factors that influenced segmentation performance across timepoints were evaluated, and linear mixed effects models controlling for these factors were used to investigate the associations of qEPVS with time.
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Title: Optimization of Large-Scale NOMA With Incidence Matrix Design and Physical Layer Security
Creator: Hwang, Eli W.
Date: 2024
Description: The Non-Orthogonal Multiple Access (NOMA) system is recognized for its capability to achieve higher spectral efficiency and massive...
Show moreThe Non-Orthogonal Multiple Access (NOMA) system is recognized for its capability to achieve higher spectral efficiency and massive connectivity. NOMA is intended to transmit massive user communications. The incidence matrix governs the relationship between users and resources for the Code domain NOMA (CD-NOMA). However, NOMA studies focus less on the design and optimization of the incidence matrix.Therefore, this thesis aims to investigate the development of a secure and large-scale NOMA system based on incidence matrix design. The main contributions are outlined as follows: Firstly, this research introduces a novel NOMA system. Distinct from existing studies, the NOMA system is based on combinatorial design. This innovative approach, coupled with a unique constellation design, eliminates the surjective mapping from the linear adding data of multiusers, reducing the complexity of constellation design and Multiuser Detection (MUD). The characteristics of the incidence matrix designs, Simple Orthogonal Multi-Arrays (SOMA), are explored, which display a distinct Latin Square pattern. The SOMA design's unique structure allows for the creation of a highly flexible and fair resource allocation matrix. The NOMA system's theoretical performance analysis equations are established, supporting dynamic adaptability and optimization. The design is validated by Monte Carlo simulation. Compared to other NOMA schemes, it offers higher degrees of freedom and lower complexity while maintaining graceful error rates to transmit a larger number of users. Secondly, a novel NOMA system utilizing incidence matrix information in the uplink is investigated. The incidence matrix pattern is exploited for MUD to achieve large-scale user connectivity. The incidence matrix is designed based on two critical mathematical concepts: parallel classes in hypergraph theory and orthogonal arrays (OAs) in combinatorial designs. Unlike other NOMA schemes, which require modification of their receiver and transmitter to decode superimposed multiuser signals, the unique pattern of the OA structure enables the use of conventional modulators. Consequently, the system load increases and the complexity and latency are reduced. The order of magnitude of the decoding complexity can be significantly reduced from O(N^3) to O(N) compared to the conventional minimum mean-square estimation (MMSE) decoder. Monte Carlo simulation validates that this novel NOMA system outperforms other NOMA designs in terms of error rate, data rate, and system size. Finally, a reconfigurable convolutional encoder design that integrates security and error correction based on physical layer security (PLS) and randomness is developed. This design addresses concerns over privacy, security, and reliability of Internet of Things devices in edge computing networks. The lightweight Convolutional encoders are designed to ensure security by updating the transfer function dynamically with user data. The reconfigurability of the design is achieved by replacing the fixed adder that represents the generator polynomials with the switch adder, enabling the use of 87 billion distinct updating structures, thereby enhancing the versatility of the design. BER-based PLS paradigms are demonstrated in the simulation. In the simulation, the robustness and randomness of this design are further validated through tests suggested by the National Institute of Standards and Technology for cryptographically secure pseudorandom number generators, such as the monobits, longest one, and run tests.
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Title: Cardiolipin Modulates the Insertion of Adsorbed Helical Amyloid Beta Peptide Into Model Mitochondrial Membranes
Creator: Kaczmarek, Julia A.
Date: 2023
Description: The loss of mitochondrial phospholipid cardiolipin (CL) may play a role in both the pathogenesis of Alzheimer's Disease (AD) and its treatment...
Show moreThe loss of mitochondrial phospholipid cardiolipin (CL) may play a role in both the pathogenesis of Alzheimer's Disease (AD) and its treatment. An effector molecule of the disease, amyloid-beta (Aβ), has been observed to interact with lipid membranes, but its relevance to mitochondrial membranes containing CL remained elusive. The present study investigated if the presence of CL modulated the insertion of adsorbed helical amyloid beta (Aβ14-40) into model mitochondrial membranes, and if this effect was more pronounced for its N-terminus or C-terminus. I conducted a coarse-grained computer simulation using well-tempered metadynamics to traverse the free energy landscape that maps the translocation of Aβ14-40. Insertion into CL-containing bilayers created larger local membrane deformations and modulated the location of the transition path but had an inconclusive impact on the free energy cost of translocation. Since the generation of toxic calcium-permeable pores depends on the insertion of Aβ into the bilayer, the loss of CL seen in AD may prime the inner mitochondrial membrane for pore formation, but more research is needed to pursue this hypothesis.
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Title: The Double-edged Sword of Executive Pay: How the CEO-TMT Pay Gap Influences Firm Performance
Creator: Haddadian Nekah, Pouya
Date: 2024
Description: This study examines the relationship between the chief executive officer (CEO) and top management team (TMT) pay gap and consequent firm...
Show moreThis study examines the relationship between the chief executive officer (CEO) and top management team (TMT) pay gap and consequent firm performance. Drawing on tournament theory and equity theory, I argue that the effect of the CEO-TMT pay gap on consequent firm performance is non-monotonic. Using data from 1995 to 2022 from S&P 1500 US firms, I explicate an inverted U-shaped relationship, such that an increase in the pay gap leads to an increase in firm performance up to a certain point, after which it declines. Additionally, multilevel analyses reveal that this curvilinear relationship is moderated by attributes of the TMT, and the industry in which the firm competes. My findings show that firms with higher TMT gender diversity suffer lower performance loss due to wider pay gaps. Furthermore, when firm executives are paid more compared to the industry norms, or when the firm has a long-tenured CEO, firm performance becomes less sensitive to larger CEO-TMT pay gaps. Lastly, when the firm competes in a masculine industry, firm performance is more negatively affected by larger CEO-TMT pay gaps. Contrary to my expectations, firm gender-diversity friendly policies failed to influence the CEO-TMT pay gap-firm performance relationship.
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