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Title: Sense of Community and Virtual Community Among People with Autism Spectrum Conditions
Creator: Rafajko, Sean I
Date: 2020
Description: Individuals with autism spectrum conditions (ASC) face poorer quality of life (QOL) and psychological well-being. Sense of community (SOC) has...
Show moreIndividuals with autism spectrum conditions (ASC) face poorer quality of life (QOL) and psychological well-being. Sense of community (SOC) has been studied in the general population as well as in other disability populations and found to be associated with increased QOL outcomes. However, SOC has never been examined quantitatively in the ASC population. Additionally, a number of communities exist online, and there has been recent research showing that people may feel sense of virtual community (SOVC), which may be particularly important to the ASC population, as internet use is higher in the population, and people with ASC report positive experiences with online communication and relationships. The purpose of this study was to examine SOC and SOVC in the ASC population. A sample of 60 participants with ASC completed an online survey about their communities, SOC, SOVC, QOL, and psychological distress, and their results were compared with a sample of 60 general population participants (N = 120). Results indicated that people with ASC reported participating in a greater number of smaller relational communities compared to the general population sample. There were no significant differences between the ASC and general population samples on levels of SOC or SOVC, suggesting that the differential relationship of the ASC group with their communities does not reduce the experience of SOC. SOC significantly contributed to QOL but not psychological distress. Results indicated that the magnitude of the relationship between SOC and SOVC on QOL was not different between those with ASC and those in the comparisons sample. Findings from this study help frame the different ways in which people with ASC interact with their communities and inform individual and community-level interventions.
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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: Factor Analysis of the Neurobehavioral Symptom Inventory in Veterans with Posttraumatic Stress Disorder
Creator: Scimeca, Lauren
Date: 2020
Description: The Neurobehavioral Symptom Inventory (NSI) is a widely used measure of postconcussive symptoms in veteran populations. Previous psychometric...
Show moreThe Neurobehavioral Symptom Inventory (NSI) is a widely used measure of postconcussive symptoms in veteran populations. Previous psychometric studies used samples of veterans with mild Traumatic Brain Injury (mTBI) and high rates of comorbid Posttraumatic Stress Disorder (PTSD). The present study aims to determine the best-fitting factor structure of the NSI in veterans with PTSD and to evaluate the relationship between the best-fitting factor structure and the symptom clusters of PTSD. A confirmatory factor analysis (CFA) found that 4-factors had the best overall fit in veterans with PTSD. Correlational analyses found high rates of correspondence between the cognitive and affective factors of the NSI and the alterations in cognition and mood and hyperarousal symptom clusters of PTSD. The analyses reveal that symptoms of the NSI cluster in the same way in a sample of veterans with PTSD as they do in veterans with mTBI, suggesting that lingering postconcussive symptoms in veterans with PTSD are better characterized as non-specific generalized health symptoms on the NSI.
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Title: CONCEPTUAL COST ESTIMATION MODEL FOR BRIDGES WITH RESPECT TO ABC METHODS
Creator: Rajeei, Farshad
Date: 2020
Description: As the need for renovating and repairing structurally deficient and functionally obsolete bridges is increased, employing innovative methods...
Show moreAs the need for renovating and repairing structurally deficient and functionally obsolete bridges is increased, employing innovative methods which can lead to shorter construction time, better quality, longer durability, and less life-cycle costs become more popular in transportation agencies.Developing a model that has the capability of estimating the total construction cost of ABC projects and compare them with conventional methods costs [without using these methods] will help decision-makers at DOTs in understanding and assessing the benefits and costs of ABC methods at the planning phase of a project and in return, will lead to the elaboration in the use of ABC methods versus the conventional ones. But this decision making process is complicated since the number of executed ABC projects, especially those which done by SIBC and SPMT [two superstructure replacement method] is limited and as a result; there is a lack of historical knowledge to estimate the associated cost of these methods in future projects. Factors affecting this process include but are not limited to: construction costs, user costs, quality of work, impact on traffic, the safety of road users and construction workers, and the impact on surrounding communities and businesses. The main aim of this study is to make a model to estimate additional costs of using SIBC and SPMT methods and the saving in user costs.
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Title: PTSD Symptoms as a Potential Link Between Military Sexual Assault and Disordered Eating
Creator: Sandhu, Danielle
Date: 2020
Description: Despite increasing rates of sexual assault in the military and high rates of disordered eating and posttraumatic stress disorder (PTSD) among...
Show moreDespite increasing rates of sexual assault in the military and high rates of disordered eating and posttraumatic stress disorder (PTSD) among veterans, little is known about how these constructs are related. The present study examined whether PTSD symptoms mediate the relation between military sexual assault and disordered eating among female veterans. Prolific Academic was used to recruit 98 United States female veterans as participants for the study. Participants completed an online questionnaire of self-report measures assessing demographic characteristics, military sexual assault, PTSD symptoms, and disordered eating. Mediational analyses were conducted using the PROCESS v3 macro in IBM SPSS Statistics. Within the sample, 61% of female veterans reported being sexually assaulted while serving in the military. Military sexual assault was associated with higher levels of PTSD symptoms and disordered eating. Findings did not support the hypothesis that PTSD symptoms would mediate the relation between military sexual assault and disordered eating among women veterans. Given the heterogeneous nature of disordered eating, post-hoc mediational analyses were conducted to examine specific facets of eating pathology. Results indicated that PTSD symptoms fully mediated the relation between military sexual assault and bulimia and food preoccupation. Awareness of these psychopathological sequelae following military sexual assault may improve screening and intervention efforts at Veteran Affairs (VA) medical centers. The present study highlights the importance of future longitudinal studies that can establish temporal precedence in order to better understand the pathways leading to disordered eating in female veterans.
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Title: GROWTH KINETICS OF SALMONELLA ENTERICA DURING REHYDRATION OF DEHYDRATED PLANT FOODS AND SUBSEQUENT STORAGE
Creator: Ren, Yuying
Date: 2020
Description: Dehydrated plant foods have low water activities and do not support the growth of pathogenic bacteria like Salmonella enterica. Once...
Show moreDehydrated plant foods have low water activities and do not support the growth of pathogenic bacteria like Salmonella enterica. Once rehydration, the water activities will increase to > 0.92, and along with their neutral pHs, plant foods may be able to support the growth of S. enterica. Therefore, product assessments are required to determine the extent to which these products support growth of S. enterica. The purpose of this study was to determine the growth kinetics of S. enterica during rehydration with 5 or 25 °C water, and subsequent storage of dehydrated potatoes, carrots, and onions at 5, 10, and 25 °C. Fresh plant foods were dehydrated at 60°C (140°F) for 24 h. Dehydrated plant foods were inoculated with 4 log CFU/g of a 4-strain cocktail of S. enterica and dried for 24 h. Samples were rehydrated using 4-volumes of 5 or 25 °C water for 24 h. During rehydration, 30 g of sample was removed and drained for 10 min. Ninety mL of BPB was added to triplicate 10-g samples. Serial dilutions of the homogenate were plated onto TSA overlaid with XLD agar for enumeration of S. enterica. After 24 h rehydration, the remaining samples were drained and stored in containers at 5, 10, and 25°C for 7 d. S. enterica was enumerated at 1, 3, 5, and 7 d. Three independent trials were conducted. Growth kinetics were determined using DMFit and data were statistically analyzed using Student’s t-test (α=0.05). Overall, the growth rates of S. enterica when 5 °C water was used for rehydration were higher than when 25 °C water was used for potatoes and carrots. The highest growth rate of S. enterica was 3.74 log CFU/g per d on potatoes, leading to a 1 log CFU/g increase in S. enterica after only 0.27 d (16 h) which occurred during storage at 25 ℃ after 5℃ water rehydration. The highest growth rate on carrots was 1.98 log CFU/g per d (requiring only 0.51 d to increase 1 log CFU/g) when rehydrated with 5℃ water and stored at 25 ℃. The growth rates were the lowest during the storage of rehydrated onions. S. enterica required 12.5 d to increase 1 log CFU/g (the growth rate was 0.61 log CFU/g per d) when the onions were rehydrated with 25 ℃ water and stored at 25 ℃. The results of this study determined that S. enterica could survive and grow in dehydrated plant foods during rehydration and storage, highlighting the need for product assessments for these types of foods.
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Title: Analysis of High-Fidelity Experiments and Simulations of the Flow in Simplified Urban Environments
Creator: Stuck, Maxime
Date: 2020
Description: The mean ﬂow and turbulence statistics of the ﬂow through a simpliﬁed urban environment, which is an active research area in order to improve...
Show moreThe mean ﬂow and turbulence statistics of the ﬂow through a simpliﬁed urban environment, which is an active research area in order to improve the knowledge of turbulent ﬂow in cities, is investigated. This is useful for civil engineering, pedestrian comfort and for health concerns caused by pollutant spreading. In this work, we provide analysis of the turbulence statistics obtained both from highly-quality stereoscopic particle image-velocimetry (SPIV) measurements (from Monnier et al.) and well-resolved large eddy simulations (LES) by Torres et al. A detailed comparison of both databases reveals the impact of the geometry of the urban array on the ﬂow characteristics and provides for a good description of the turbulent features of the ﬂow around a simpliﬁed urban environment. The most prominent features of this complex ﬂow include coherent vortical structures such as the so-called arch vortex, the horseshoe vortex, or the roof vortex. These structures of the ﬂow have been identiﬁed by an analysis of the turbulence statistics. The inﬂuence of the geometry of the urban environment (and particularly the street width and the building height) on the overall ﬂow behavior has also been studied.
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Title: Predictive energy efficient control framework for connected and automated vehicles in heterogeneous traffic environments
Creator: Vellamattathil Baby, Tinu
Date: 2023
Description: Within the automotive industry, there is a significant emphasis on enhancing fuel efficiency and mobility, and reducing emissions. In this...
Show moreWithin the automotive industry, there is a significant emphasis on enhancing fuel efficiency and mobility, and reducing emissions. In this context, connected and automated vehicles (CAVs) represent a significant advancement, as they can optimize their acceleration pattern to improve their fuel efficiency. However, when CAVs coexist with human-driven vehicles (HDVs) on the road, suboptimal conditions arise, which adversely affect the performance of CAVs. This research analyzes the automation capabilities of production vehicles to identify scenarios where their performance is suboptimal, and proposes a merge-aware modification of adaptive cruise control (ACC) method for highway merging situations. The proposed algorithm addresses the issue of sudden gap and velocity changes in relation to the preceding vehicle, thereby reducing substantial braking during merging events, resulting in improved energy efficiency. This research also presents a data-driven model for predicting the velocity and position of the preceding vehicle, as well as a robust model predictive control (MPC) strategy that optimizes fuel consumption while considering prediction inaccuracies. Another focus of this research is a novel suggestion-based control framework in interactive mixed traffic environments leveraging the emerging connectivity between vehicles and with infrastructure. It is based on MPC to optimize the fuel efficiency of CAVs in heterogeneous or mixed traffic environments (i.e., including both CAVs and HDVs). In this suggestion-based control framework, the CAVs are considered to provide non-binding velocity and lane change suggestions to the HDVs to follow to improve the fuel efficiency of both the CAVs and the HDVs. To achieve this, the host CAV must devise its own fuel-efficient control solution and determine the recommendations to convey to its preceding HDV. It is assumed that the CAVs can communicate with the HDVs via Vehicle to Vehicle (V2V) communication, while the Signal Phase and Timing (SPaT) information is accessed via Vehicle-to- Infrastructure (V2I) communication. These velocity suggestions remain constant for a predefined period, allowing the driver to adjust their speed accordingly. It is also considered that the suggestions are non binding, i.e., a driver can choose not to follow the suggested velocity. For this control framework to function, we present a velocity prediction model based on experimental data that captures the response of a HDV to different suggested velocities, and a robust approach to ensure collision avoidance. The velocity prediction’s accuracy is also validated with the experimental data (on a table-top drive simulator), and the results are presented. In cases of low CAV penetration, a CAV needs to provide suggestions to multiple surrounding HDVs and incorporating the suggestions to all the HDVs as decision variables to the optimal control problem can be computationally expensive. Hence, a suggestion-based hierarchical energy efficient control framework is also proposed in which a CAV takes into account the interactive nature of the environment by jointly planning its own trajectory and evaluating the suggestions to the surrounding HDVs. Joint planning requires solving the problem in joint state- and action-space, and this research develops a Monte Carlo Tree Search (MCTS)-based trajectory planning approach for the CAV. Since the joint action- and state-space grows exponentially with the number of agents and can be computationally expensive, an adaptive action-space is proposed through pruning the action-space of each agent so that the actions resulting in unsafe trajectories are eliminated. The trajectory planning approach is followed by a low-level model predictive control (MPC)-based motion controller, which aims at tracking the reference trajectory in an optimal fashion. Simulation studies demonstrate the proposed control strategy’s efficacy compared to existing baseline methods.
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Title: Parking Demand Forecasting Using Asymmetric Discrete Choice Models with Applications
Creator: Zhang, Ji
Date: 2023
Description: Using discrete choice models to forecast travelers parking location choice has been a branch of parking demand research for many years. The...
Show moreUsing discrete choice models to forecast travelers parking location choice has been a branch of parking demand research for many years. The most used discrete choice models have fairly simple mathematical expressions, such as the probit and logit models. The application of simple models helps release the computational burdens brought by parameter estimation tasks in practice, but the cost is the unwanted properties of classic models such as the “symmetry property” that we argue is often undesirable in many fields. To some extent, the symmetry property of related models limits the shape of curves that makes the model fitting less flexible technically. This study addresses the following question: “Can discrete choice models with asymmetry property outperform classic models with symmetry property in forecasting travelers’ parking location choices?” The contributions of this study include: (1) providing a new perspective of using asymmetric discrete choice models to explain and forecast individual’s parking location choice; and (2) completing the travel demand forecasting process from choices of the destination zone centroid to the parking location, enabling parking choice forecasting. This provides a generalized framework to calibrate and validate asymmetric discrete choice models with the field observed parking facility-specific arrival profile data integrated into a large-scale, high-fidelity regional travel demand model. Further, an experimental study is conducted to compare the performance of the proposed asymmetric discrete choice models in the parking demand forecasting framework. The results suggest that asymmetric discrete choice models for individual’s parking choice modeling outperform the symmetric discrete choice models such as the logit models owing largely to their flexibility of parameter fitting and training using the available dataset.
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Title: Large-Signal Transient Stability and Control of Inverter-Based Resources
Creator: Wang, Duo
Date: 2024
Description: Renewable generation, including solar photovoltaic (PV) systems, type 3 and 4 wind turbine generation systems (WTG), battery energy storage...
Show moreRenewable generation, including solar photovoltaic (PV) systems, type 3 and 4 wind turbine generation systems (WTG), battery energy storage systems (BESS), as well as high voltage direct current (HVDC) and flexible alternating current (FACT) transmission system devices with increasing penetration level are being connected to the bulk power systems (BPS) via power electronic (PE) converters as the interface, referred to as the inverter-based resources (IBRs) on the transmission and sub-transmission levels or distributed energy resources (DERs) located on the distribution level. The IBR is almost entirely defined by the control algorithms and found to be more prone to experiencing large disturbances due to the lack of the conventional synchronous machine (SM) intrinsic synchronous characteristics and mechanical inertia, as well as being in smaller capacity sizes. Thus, these reasons motivate this dissertation to study the large-signal transient stability and control of IBRs for reliable grid integration and rapid grid transformation. For large-signal stability analysis methods, Lyapunov-based methods are the fundamental theory used to characterize the stability issues with analytical solutions, although other non-Lyapunov methods could also be very helpful. A main difficulty hindering the widespread adoption of the Lyapunov stability analysis method is the difficulty of finding the proper Lyapunov function candidate for a higher dimensional nonlinear system. The Port-Hamiltonian (PH) nonlinear control theory is explored in this dissertation as a promising theoretical framework solution addressing this challenging issue. A PH-based tracking and robust control method is proposed to facilitate the practical application of the PH framework in IBR controls. In addition, considering the typical grid-forming (GFM) IBR control with a first-order low pass filter (LPF) block is usually involved with control saturation function for protection purposes under abnormal operating conditions with anti-windup issue in practical implementation, a PH-based bounded LPF (PH-BLPF) control is proposed to incorporate this in the large-signal PH interconnection modeling framework while preserving the robust tracking Lyapunov stability with improved transient dynamic performance and stability margin.Moreover, specific real-world transient synchronization stability issues, such as the grid voltage large fault disturbance case, are studied. In addition, to meet the recent emerging IBR grid code requirements, such as the current magnitude limitation, grid support function, and fault recovery capability of GFM-VSCs, a virtual impedance-based current-limiting GFM control with enhanced transient stability and grid support is proposed.
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Title: Retrospective Quantitative T1 Imaging to Examine Characteristics of Multiple Sclerosis Lesions
Creator: Young, Griffin James
Date: 2024
Description: Quantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1...
Show moreQuantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1 relaxometry is gaining popularity as elevated T1 values have been shown to correlate with increased inflammation, demyelination, and gliosis. The predominant issue is that relaxometry requires parametric mapping through advanced imaging techniques not commonly included in standard clinical protocols. This leaves an information gap in large clinical datasets from which quantitative mapping could have been performed. We introduce T1-REQUIRE, a retrospective T1 mapping method that approximates T1 values from a single T1-weighted MR image. This method has already been shown to be accurate within 10% of a clinically available reference standard in healthy controls but will be further validated in MS cohorts. We also further aim to determine T1-REQUIRE’s statistical significance as a unique biomarker for the assessment of MS lesions as they relate to clinical disability and disease burden. A 14-subject comparison between T1-REQUIRE maps derived from 3D T1 weighted turbo field echoes (3D T1w TFE) and an inversion-recovery fast field echo (IRFFE) revealed a whole-brain voxel-wise Pearson’s correlation of r = 0.89 (p < 0.001) and mean bias of 3.99%. In MS white matter lesions, r = 0.81, R2 = 0.65 (p < 0.001, N = 159), bias = 10.07%, and in normal appearing white matter (NAWM), r = 0.82, R 2 = 0.67 (p < 0.001), bias = 9.48%. Mean lesional T1-REQUIRE and MTR correlated significantly (r = -0.68, p < 0.001, N = 587) similar to previously published literature. Median lesional MTR correlated significantly with EDSS (rho = -0.34, p = 0.037), and lesional T1-REQUIRE exhibited xiii significant correlations with global brain tissue atrophy as measured by brain parenchymal fraction (BPF) (r = -0.41, p = 0.010, N = 38). Multivariate linear regressions between T1- REQUIRE NAWM provided meaningful statistical relationships with EDSS (β = 0.03, p = 0.027, N = 38), as well as did mean MTR values in the Thalamus (β = -0.27, p = 0.037, N = 38). A new spoiled gradient echo variation of T1-REQUIRE was assessed as a proof of concept in a small 5-subject MS cohort compared with IR-FFE T1 maps, with a whole brain voxel-wise correlation of r = 0.88, R2 = 0.77 (p < 0.001), and Bias = 0.19%. Lesional T1 comparisons reached a correlation of r = 0.75, R2 = 0.56 (p < 0.001, N = 42), and Bias = 10.81%. The significance of these findings means that there is the potential to provide supplementary quantitative information in clinical datasets where quantitative protocols were not implemented. Large MS data repositories previously only containing structural T1 weighted images now may be used in big data relaxometric studies with the potential to lead to new findings in newly uncovered datasets. Furthermore, T1-REQUIRE has the potential for immediate use in clinics where standard T1 mapping sequences aren’t able to be readily implemented.
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Title: Two Essays on Mergers and Acquisitions
Creator: Xu, Yang
Date: 2024
Description: This dissertation is composed of two self-contained chapters that both relate to mergers and acquisitions (M&A). In the first essay, we...
Show moreThis dissertation is composed of two self-contained chapters that both relate to mergers and acquisitions (M&A). In the first essay, we examine the Delaware (DE) reincorporation effect on firms’ post-IPO behaviors on mergers and acquisitions. We find that firms’ DE reincorporation decisions enhance the likelihood of engaging in M&A as targets. However, as a tradeoff, DE reincorporated firms get lower takeover valuations compared to stay-at-home-state firms, and the acquisition of reincorporated firms is less likely to be successful. Our second essay aims to explore the role of the options market in price discovery for M&A. We find that the predictive power of the changes in implied volatility of the target firm stock for the takeover outcome is statistically and economically significant. The risk arbitrage portfolios incorporating filters derived from the options on stocks of the target firms generate annualized risk-adjusted abnormal returns between 2.6% and 5%, depending on the portfolio weighting method, the threshold of filters for the implied volatility change, and the asset pricing models applied for abnormal returns. The results are robust to different empirical setups and are not explained by traditional factors.
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Title: Heterogeneous Workloads Study towards Large-scale Interconnect Network Simulation
Creator: Wang, Xin
Date: 2023
Description: High-bandwidth, low-latency interconnect networks play a key role in the design of modern high- performance computing (HPC) systems. The ever...
Show moreHigh-bandwidth, low-latency interconnect networks play a key role in the design of modern high- performance computing (HPC) systems. The ever-increasing need for higher bandwidth and higher message rate has driven the design of low-diameter interconnect topologies like variants of dragonfly. As these hierarchical networks become increasingly dominant, interference caused by resource sharing can lead to significant network congestion and performance variability. Meanwhile, with the rapid growth of the machine learning applications, the workloads of future HPC systems are anticipated to be a mix of scientific simulation, big data analytics, and machine learning applications. However, little work has been conducted to understand performance implications of co-running heterogeneous workloads on large-scale dragonfly systems. There is a greater need to study how different interconnect technologies affect workload performance, and how conventional scientific applications interact with emerging big data applications at the underlying interconnect level. In this work, we firstly present a comparative analysis exploring the communication interference for traditional HPC applications by analyzing the trade-off between localizing communication and balancing network traffic. We conduct trace-based simulations for applications with different communication patterns, using multiple job placement policies and routing mechanisms. Then we develop a scalable workload manager that provides an automatic framework to facilitate hybrid workload simulation. We investigate various hybrid workloads and navigate various application-system configurations for a deeper understanding of performance implications of a diverse mix of workloads on current and future supercomputers. Finally, we propose a scalable framework, Union+, that enables simulation of communication and I/O simultaneously. By combining different levels of abstraction, Union+ is able to efficiently co-model the communication and I/O traffic on HPC systems that equipped with flash-based storage. We conduct experiments with different system configurations, showing how Union+ can help system designers to assess the usefulness of future technologies in next-generation HPC machines.
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Title: Empowering Visually Impaired Individuals With Holistic Assistance Using Real-Time Spatial Awareness System
Creator: Yu, Xinrui
Date: 2024
Description: The integration of artificial intelligence (AI) into daily life opens unprecedented avenues for enhancing the experiences of visually impaired...
Show moreThe integration of artificial intelligence (AI) into daily life opens unprecedented avenues for enhancing the experiences of visually impaired individuals, offering them greater autonomy and quality of life. This thesis introduces a Visually Impaired Spatial Awareness (VISA) system designed to assist visually impaired individuals holistically through a structured approach. At the foundational level, the VISA system incorporates several key technologies to interpret the surroundings and assist in basic navigation tasks. It utilizes Augmented Reality (AR) markers to facilitate recognition of places and aid in navigation, employs neural network models for advanced object detection and tracking, and leverages depth information for accurate object localization. Progressing to the intermediate level, the VISA system integrates the data obtained from object detection and depth sensing to assist in more complex navigational tasks such as obstacle avoidance and pathfinding toward a desired destination. At the advanced level, the VISA system synthesizes the capabilities developed at the foundational and intermediate levels to enhance the spatial awareness of visually impaired users, allowing them to undertake complex tasks, such as navigating complex environments and locating specific items. The VISA system also emphasizes efficient human-machine interaction, incorporating text-to-speech and speech-to-text technologies to facilitate natural and intuitive communication between the user and the system. The VISA system's performance was evaluated in different environments simulating real-world scenarios. The experimental results show that the user can interact with our system intuitively with minimal effort, and affirm that the VISA system can effectively assist the visually impaired user in locating and reaching for objects, navigating indoors, identifying merchandise, and recognizing both handwritten and printed texts.
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Title: Utilizing Image Processing in Evaluation of Fibroblast Stimulation for Collagen Remodeling
Creator: Yoon, Shin Hae
Date: 2023
Description: This research delves into the realm of image processing as a pivotal component in the evaluation of fibroblast stimulation for collagen...
Show moreThis research delves into the realm of image processing as a pivotal component in the evaluation of fibroblast stimulation for collagen remodeling. The study focuses on unraveling the intricate synergy between electrospun silk fibroin-carbon nanotube (SF-CNT) fibers and electrical stimulation, working in harmony to enhance tissue regeneration. Building upon our previous work, we successfully engineered SF-CNT fibers through the electrospinning process, yielding highly aligned structures reminiscent of natural extracellular matrix proteins. These fibers were fortified with water stability through post-treatment with ethanol vapor, while subtle additions of carbon nanotubes (CNTs) significantly improved fiber alignment, strength, and conductivity without compromising biocompatibility. This innovative platform served as a cell culture matrix for fibroblasts harvested from pelvic organ prolapse (POP) patients, facilitating electrical stimulation that triggered a substantial increase in collagen production. In this study, we harnessed the power of various image-processing software tools, including ImageJ and Python, to analyze immunostained images of fibroblasts obtained from POP patients. Under carefully tailored electrical stimulation conditions, the stimulated cells exhibited an astonishing up to 11.97-fold increase in alpha-smooth muscle actin (α-SMA) expression, unequivocally signifying the successful activation of myofibroblasts. Additionally, in an animal model employing LOX-knockout mice to mimic collagen disorders associated with POP, the application of optimized electrical stimulation conditions for patient 003 led to a remarkable surge in collagen production and structural enhancement, underlining the potential of electrical stimulation in expediting tissue remodeling. Intriguingly, fibroblasts from patient 005 and patient 006 exhibited a distinct response, shedding light on the influence of POP severity on cellular behavior. This study firmly reinforces the imperative of personalized therapeutic approaches, emphasizing the need to customize treatment strategies to align with individual patient characteristics through innovative biological image analysis techniques.
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Title: Effect of organic acid treatment in reducing Salmonella on six types of sprout seeds
Creator: Yang, Dachuan
Date: 2023
Description: Fresh sprouts present a special food safety concern as their growing conditions also favor the growth of pathogens such as Salmonella....
Show moreFresh sprouts present a special food safety concern as their growing conditions also favor the growth of pathogens such as Salmonella. Contamination in sprouts often originates from the seeds used for sprouting. The Produce Safety Rule requires that seeds used to grow sprouts be treated to reduce pathogens. The treatments may be applied by sprout growers or by seed suppliers. Although 20,000 ppm calcium hypochlorite is the most used seed treatment method, the high chlorine level can be hazardous to workers and the environment. Alternative seed treatment methods that are safe and environmentally friendly are needed. In addition, a post-treatment drying step is needed when seed suppliers are using chemical seed treatment methods. This study evaluated the efficacy of an organic acid solution for reducing Salmonella on six types of seeds (alfalfa, clover, radish, mung bean, onion, and broccoli). The impact of treatment on seed germination and sprout yield was also examined. Ten grams of seeds inoculated with a five-serotype cocktail of Salmonella were pre-rinsed with 40 ml of water twice and treated with 75.7 ml of the organic acid solution for 1 hour. The treated seeds were either not rinsed or rinsed with 40 ml of water twice before being dried in the biological safety cabinet for 24 hours. The Salmonella level, germination percentage, and sprout yield of seeds treated with water, seeds treated with the organic acid solution, seeds treated with organic acid, dried, and rinsed, and seeds treated with organic acids, dried, and not rinsed were compared. Salmonella reductions that could be achieved with this organic acid solution treatment were less than 0.5 log CFU/g without drying, 0.6-2.0 log CFU/g with drying and rinse, or 1.6-2.9 log CFU/g with drying and no rinse. Drying significantly enhanced the treatment efficacy (p < 0.05 ) on alfalfa, radish, mung bean, and onion seeds. If seeds were not rinsed after treatment, the log reductions achieved on mung bean and onion seeds were significantly higher (p < 0.05). If seeds were treated and rinsed, the germination rates of six types of seeds were not affected (p > 0.05) regardless of whether the seeds were dried or not. All treatments significantly decreased the sprout yield of clover seeds by 13% (p < 0.05 ). If seeds were not rinsed after treatment, the germination rates of clover and broccoli seeds were reduced by 7 and 9%, respectively, and the sprout yield of alfalfa seeds was reduced by 35%. Overall, the organic acid solution was ineffective when compared with 20,000 ppm calcium hypochlorite in reducing Salmonella on sprout seeds, although the drying step after treatment could improve the treatment efficacy.
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Title: New Object
Creator: Zhang, He

Title: An architectural and structural study of multi-storied skeleton building
Creator: Lempp Kerbis, Gertrude 1926-2016
Date: 1954

Title: LOCAL VISCOELASTIC PROPERTIES OF SOFT ANISOTROPIC FIBROUS TISSUE
Creator: Gallo, Nicolas Remy
Date: 2020
Description: The current aging population, with more than 80 million "baby boomers", will present a steep medical challenge for our society in a...
Show moreThe current aging population, with more than 80 million "baby boomers", will present a steep medical challenge for our society in a foreseeable future. Half of the adults over 85 years old are predicted to be diagnosed with Alzheimer's disease by 2050. With healthcare cost reaching over 700 billion dollars in the United States, early detection of Alzheimer's disease (AD) and other co-existing neurodegenerative diseases is crucial to improve the recovery odds in patients and to decrease individual care cost. This work seeks to tackle this problem by proposing a novel computational framework toward improving the measurement of shear visco-elastic properties of brain white matter (WM), which vary with age. These measurements practically represent the effective (average) response of many cells and are typically obtained by using rheology or elastography. Although the former is direct, the latter requires the solution of an inverse problem based on a priori mechanical tissue model. The mechanical anisotropy of WM has previously not been fully explored although many inconsistencies have been reported in brain MRE experiments. To account for these inconsistencies a transversely isotropic constitutive model for the brain WM is proposed to interpret prior experiments involving 7 young and 4 older healthy men. By employing a novel inversion scheme, we report the local variation of the effective transverse and axial shear moduli in two well aligned WM structures (corpus callosum: CC; and cortical spinal tract: CST) for both the young and old cohort of healthy subjects part of the study. This work reports statistically significant changes in local regional variation of the transverse modulus across the CC for the young cohort. In the older cohort, the trend was similar yet not statistically significant. A novel candidate biomarker, the shear anisotropy metric, defined as the ratio of the transverse and axial shear moduli, found statistically significant local regional variation across the CC but not in the CST. Healthy aging was observed to decrease both transverse and axial in both CC and CST, although the variation was significant only for the CC. Finally, in an effort to understand the cause of effective transverse mechanical properties variation in WM with aging, the connection between effective and intrinsic contribution of WM cellular constituents is established. The intrinsic mechanical contributions of axons and glial matrix are separated by fitting the estimates of the effective shear moduli to a microscopic composite fiber model of myelinated axons embedded in the glial matrix. This work provides a method to establish a baseline for healthy brain mechanical properties thus promising to increase the specificity of MRE toward early diagnosis of neurodegenerative diseases. Additional oscillating disc rheology experiments with decellularized porcine myocardium, and the fabrication of a stable heterogeneous phantom matching the mechanical, diffusional and electrical properties of the WM provide foundational knowledge for due development and validation of MRE methodologies employed in other tissues.
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Title: My IIT
Creator: Namburi, Kartheeka
Date: 2024
Description: Master's Project focused on developing a user-friendly mobile application for Illinois Institute of Technology (IIT).

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