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Modeling Of Excitation In Skeletal Muscle, Sabrina Kinzie Metzger Jan 2021

Modeling Of Excitation In Skeletal Muscle, Sabrina Kinzie Metzger

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Recent experimental findings in the Rich lab suggest there are important gaps in our understanding of muscle excitability in various disease states. To generate and test hypotheses as well as to determine whether our current understanding of various aspects of muscle excitation can fully explain experimental findings, an accurate model of muscle excitation was needed. Previous studies have modeled excitation of muscle, but in each case, important aspects were omitted. One reason for this is that little effort has been made to accurately simulate muscle action potentials. In this thesis I present progress made towards generation of a model of …

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A Rebellion Framework With Learning For Goal-Driven Autonomy, Zahiduddin Mohammad Jan 2021

A Rebellion Framework With Learning For Goal-Driven Autonomy, Zahiduddin Mohammad

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Modeling an autonomous agent that decides for itself what actions to take to achieve its goals is a central objective of artificial intelligence. There are various approaches used to build autonomous agents including neural networks, state machines, utility functions, learning agents, and cognitive architectures. In this thesis, we focus on cognitive architectures. Our approach uses specific knowledge of the world, the goals they pursue, and the actions being performed. Most agents do what they are told (i.e., achieve the goals given to them by a human), but a genuinely autonomous agent does more. It can formulate its own goal or …

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The Course Scheduling Problem With Room Considerations, Lijian Xiao Jan 2021

The Course Scheduling Problem With Room Considerations, Lijian Xiao

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The course scheduling problem (CSP), more commonly referred to as the university timetabling problem, belongs to the larger family of general scheduling problems, where the aim is to assign students, faculties, exams, or lectures to a limited number of rooms over time in accordance under real-world constraints. Such problems are known to be NP-complete and have been the subject of study for the optimization society for many decades. This research extends the classical CSP to the CSP with Room Considerations (CSP-R) by incorporating two room-related considerations; cohort-to-room preference and topic-to-room preference. While the former refers to students in each cohort …

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Partial Facial Re-Imaging Using Generative Adversarial Networks, Derek Desentz Jan 2021

Partial Facial Re-Imaging Using Generative Adversarial Networks, Derek Desentz

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Existing facial recognition software relies heavily on using neural networks to extract key facial features to accurately classify known individuals. Some of these key features include the shape, size, and distance between an individual’s eyes, nose, and mouth. When these key features cannot be extracted due to facial coverings, existing applications become inaccurate and unreliable. The accuracy and reliability of these technologies are growing concerns as the facial recognition market continues to grow at an exponential rate. In this thesis, we have developed a web-based application service that is able to take in a partially covered face image and generate …

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Texture Evolution In Materials With Layered Crystal Structures, Vamsi Krishna Vempati Jan 2021

Texture Evolution In Materials With Layered Crystal Structures, Vamsi Krishna Vempati

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Materials with a layered structure consist of crystalline layers that are bonded to each other with secondary bonds (van der Waals interactions). The bonding between crystalline layers is relatively weak compared to the interatomic bonding within the crystalline layers. This research hypothesizes that under appropriate conditions, such as elevated temperature, the deformation of layered materials occurs like the classic “deck of cards” with no preferred direction of slip on the slip planes. The motivation for this study is from the experimental texture evolution of one such material, Bismuth Telluride ,(Bi2Te3), commonly used materials for thermoelectric applications in the range of …

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Sediment Nutrient Dynamics In Fondriest Agricultural Settling Pond, Marie Grace Bezold Jan 2021

Sediment Nutrient Dynamics In Fondriest Agricultural Settling Pond, Marie Grace Bezold

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Excess loading of nitrogen (N) and phosphorus (P) is a serious global problem and has numerous negative impacts on water quality of aquatic ecosystems including eutrophication, harmful algal blooms, and hypoxia. Anthropogenic activities (such as the Haber-Bosch process, burning of fossil fuels, sewage treatment, and manure reuse) have led to excess N loading to aquatic systems. Sediment N dynamics were examined from Oct 2019 – Oct 2020 in an agricultural settling pond connected to a constructed wetland adjacent to an agricultural field. Intact sediment cores were amended with 15N for continuous-flow incubations to measure denitrification and N fixation rates, as …

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Finite Different Time-Domain Simulation Of Terahertz Waves Propagation Through Unmagnetized Plasma, Aditha Srikantha Senarath Jan 2021

Finite Different Time-Domain Simulation Of Terahertz Waves Propagation Through Unmagnetized Plasma, Aditha Srikantha Senarath

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In order to support ongoing terahertz time-domain spectroscopic experiments involving plasma characterization, it is beneficial to simulate the interaction of THz pulses with varying plasma configurations. In this approach, a 1-D Finite Difference Time Domain (FDTD) model was constructed to simulate the interaction of terahertz radiation with a plasma medium. In order to incorporate the plasma properties into the simulation, a Z-transformation was applied. This model is capable of simulating the following properties of plasmas including electron density, collision frequency, and the interaction length of the plasma medium. The simulated model was characterized using terahertz time-domain spectroscopy. The effects of …

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Understanding Human Decision Making With Automation Using Systems Factorial Technology, Cara M. Kneeland Jan 2021

Understanding Human Decision Making With Automation Using Systems Factorial Technology, Cara M. Kneeland

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While many researchers have investigated the performance consequences of automated recommender systems, little research that has explored how these systems impact the decision making process. The purpose of this dissertation is to examine how people process information from an automated recommender system and raw information from the en- vironment using Systems Factorial Technology (SFT). Participants completed a speeded length judgment task with a reliable but imperfect aid. Experiment 1 focused on whether people process all the available information or are selective in their information search under certain circumstances (e.g., with performance incentives and with more experience with automation failures in …

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Using Functionalized Benzylidene Oxindoles To Determine An Improved Monoamine Oxidase-B Inhibitor As A Therapeutic Agent For Parkinson's Disease, Christine Morgan Kinstedt Jan 2021

Using Functionalized Benzylidene Oxindoles To Determine An Improved Monoamine Oxidase-B Inhibitor As A Therapeutic Agent For Parkinson's Disease, Christine Morgan Kinstedt

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With the intent to create an optimized monoamine oxidase-B (MAO-B) inhibitor, researchers in this investigation synthesized derivatives of the benzylidene oxindole scaffold in order to determine a lead molecule for further drug development. Previous work in this laboratory group evaluated a similar scaffold, the chalcone structural unit. As this class of compounds was determined to possess the ability to permeate the blood brain barrier (BBB) and to act as potent MAO-B inhibitors, it was posited that scaffold hopping from this previously studied molecular skeleton to benzylidene oxindoles would provide analogous results. Benzylidene oxindoles are readily synthesized via the Claisen-Schmidt condensation …

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Pre-Stack Seismic Inversion And Amplitude Variation With Offset (Avo) Attributes As Hydrocarbon Indicators In Carbonate Rocks: A Case Study From The Illinois Basin, Jacob T. Murchek Jan 2021

Pre-Stack Seismic Inversion And Amplitude Variation With Offset (Avo) Attributes As Hydrocarbon Indicators In Carbonate Rocks: A Case Study From The Illinois Basin, Jacob T. Murchek

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Amplitude anomalies in pre-stack seismic data have widely been used in the oil and gas industry as a risk analysis tool when exploring for hydrocarbons. AVO analysis is most often applied to poorly consolidated Tertiary rocks due to the compressibility of these strata when natural gas and porosity are present. In contrast, well-lithified carbonate rocks are less prone to producing a pre-stack amplitude response due to the rigidity of their frame. Pre-stack seismic data of a 2-D seismic profile were conditioned and interpreted to identify amplitude variation with offset (AVO) attributes corresponding to the presence of hydrocarbons within the North …

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Silk Hydrogels Incorporated With Melanin, Anne Lutz Jan 2021

Silk Hydrogels Incorporated With Melanin, Anne Lutz

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Melanin is a naturally produced pigment found within the human body. Melanin is known for its ability to protect against Ultra Violet light, but also its ability to allow for mechanical protection. Making melanin a good addition to biomedical devices such as hydrogels. Silk hydrogels are weak in their load bearing capabilities but are known for their biocompatibility, biodegradability, and porosity. This makes the silk hydrogel a good material to incorporate melanin into in order to improve the mechanical properties. For the silk solution to form a solid, there must be a presence of both a catalyst and an oxidizer …

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Computer Modeling Of Solar Thermal System With Underground Storage Tank For Space Heating, Mohammad Yousef Mousa Naser Jan 2021

Computer Modeling Of Solar Thermal System With Underground Storage Tank For Space Heating, Mohammad Yousef Mousa Naser

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Space heating is required in almost every dwelling across the country for different periods of time. The thermal energy needed to meet a heating demand can be supplied using different conventional and/or renewable technologies. Solar energy is one example of a renewable resource that can be used for supplying heating needs. It can be utilized either by using photovoltaic panels to generate electricity, that in turn can be used to operate heaters, or by using solar thermal panels. Solar thermal panels obtain higher operating efficiencies than photovoltaic panels, but solar energy for heating purposes suffers from a mismatch between supply …

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Structural Analysis And Link Prediction Algorithm Comparison For A Local Scientific Collaboration Network, Denys Guriev Jan 2021

Structural Analysis And Link Prediction Algorithm Comparison For A Local Scientific Collaboration Network, Denys Guriev

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Scientific collaboration between researchers is very common and much influential and ground-breaking research is performed by teams comprised of scientist from different fields and organizations. In this thesis, we analyze and model a small scientific collaboration network limited to two organizations: Wright State University and the Air Force Research Laboratory. Research paper co-authorship is used for establishing the network structure. We analyze several network properties and compare them to past results from analysis of larger and more diverse collaboration networks. We show that the two-organization network we explored exhibits properties similar to those of larger networks. Guided by advances in …

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Bayesian Inspired Multi-Fidelity Optimization With Aerodynamic Design, Christopher Corey Fischer Jan 2021

Bayesian Inspired Multi-Fidelity Optimization With Aerodynamic Design, Christopher Corey Fischer

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In most engineering design problems, there exist multiple models of varying fidelities for use in predicting a single system response such as Computational Fluid Dynamics (CFD) models constructed using Potential Flow, Euler equations, or full physics Navier Stokes implementation. Engineering design is constantly pushing the forefront of the field through imposing stricter and more complex constraints on system performance, thus elevating the need for use of high-fidelity models in the design process. Increasing fidelity level often correlates to an increase in cost (financial, computational time, and computational resources). Traditional design processes rely upon low-fidelity models for expedience and resource savings. …

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Numerical Investigation Of Flow Around A Deformed Vacuum Lighter-Than-Air Vehicle, Jared N. Kerestes Jan 2021

Numerical Investigation Of Flow Around A Deformed Vacuum Lighter-Than-Air Vehicle, Jared N. Kerestes

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This study characterizes the functional dependence of drag on Reynolds number for a deformed vacuum lighter-than-air vehicle. The commercial computational fluid dynamics (CFD) code, FLUENT, is used to preform large eddy simulations (LES) over a range of Reynolds numbers; only Reynolds numbers less than 310,000 are considered. While the overarching goal is drag characterization, general flow-field physics are also discussed, including basic turbulence spectra. All large eddy simulations are preceded by a Reynolds-averaged Navier-Stokes (RANS) simulation using Menter’s shear stress transport (SST) model. The precursor RANS simulation serves to (1) provide realistic initial conditions, (2) decrease the time needed to …

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Interferometry Analysis Method For Colliding Plasma Generated With Exploded Wires, Michael D. Gruesbeck Jan 2021

Interferometry Analysis Method For Colliding Plasma Generated With Exploded Wires, Michael D. Gruesbeck

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Building upon recent work to estimate electron and ion densities from paired interferograms, the current work develops a model for the 2D interference phase function. Unlike the previous work that only estimated a radial plasma profile from images of a singly exploded straight Cu wire, we estimate 2D properties from a colliding plasma generated from two simultaneously exploded wires. First, a 2D phase model is proposed for the interference patterns of the images taken at 1064 nm and 532 nm. Then, the model parameters are estimated using Fourier analysis. Secondly, the plasma region in each image is partitioned into subregions …

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Diversity And Function Of Algal Biofilms In The Laurentian Great Lakes, Leon R. Katona Jan 2021

Diversity And Function Of Algal Biofilms In The Laurentian Great Lakes, Leon R. Katona

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Attached algae are ubiquitous components of lake benthic habitats wherever sufficient light reaches submerged surfaces. Attached algae interact with heterotrophic bacteria and fungi to form complex biofilms (“periphyton”) that provide a nutritious food source for consumers and influence biogeochemical cycling by regulating redox potential at the sediment-water interface. Despite their ecological importance, there are limited data on the role of periphyton in the Laurentian Great Lakes. I quantified wave exposure and light availability in rocky nearshore habitats in Lake Erie and Lake Huron. Periphyton biomass and productivity in nearshore Lake Erie was very high while algal biomass and productivity in …

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Development And Application Of A Computational Modeling Scheme For Periodic Lattice Structures, Abdalsalam Fadeel Jan 2021

Development And Application Of A Computational Modeling Scheme For Periodic Lattice Structures, Abdalsalam Fadeel

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Sandwich structures are widely used for aerospace, marines and other applications due to their light-weight, strength, and strain energy absorption capability. The cores of the sandwich structure are typically fabricated by using high strength cellular materials such as aluminum and titanium alloys, or polymer foams, and honeycombs. Lattice cell structures (LCS) of different configurations such as body centered cubic (BCC), tetrahedron and pyramidal are being investigated as core material due to their design freedom and periodic nature. Due to the recent advent of additive manufacturing (AM), new research is being sought in the areas of designing and developing application-specific LCS …

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Internal Loading Of Nitrogen (N) And Phosphorus (P), Reduced N Forms, And Periodic Mixing Support Cyanobacterial Harmful Algal Blooms (Habs) In Shallow, Eutrophic Honeoye Lake (New York, Usa), Justin Adam Myers Jan 2021

Internal Loading Of Nitrogen (N) And Phosphorus (P), Reduced N Forms, And Periodic Mixing Support Cyanobacterial Harmful Algal Blooms (Habs) In Shallow, Eutrophic Honeoye Lake (New York, Usa), Justin Adam Myers

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Cyanobacteria are important primary producers, but large cyanobacterial harmful algal blooms (HABs) have many negative ecological and health impacts and are becoming increasingly common. Honeoye Lake (New York, USA) is a shallow, eutrophic lake characterized by increasingly frequent HABs. Nitrogen (N) and phosphorus (P) loads often drive HABs in lakes, and sediment processes can contribute to N removal (e.g., denitrification) or loading (e.g., N fixation, remineralization). Sediment cores and lake water were collected during May–October (2016–2018) at two sites and incubated with no amendments (controls) or 15N stable isotopes to measure sediment nutrient fluxes and N cycling dynamics in Honeoye …

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Sediment-Water Fluxes Of Phosphorus And Trace Metals In The Maumee River, Northwest Ohio, Emily L. Holliday Jan 2021

Sediment-Water Fluxes Of Phosphorus And Trace Metals In The Maumee River, Northwest Ohio, Emily L. Holliday

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Excess phosphorus (P) and nitrogen (N) in the western basin of Lake Erie drive annual cyanobacteria blooms and associated hypoxia events. The Maumee River inputs ~5% of the water load into the western basin and ~50% of annual P loadings. I quantified seasonal variability of net P and metals fluxes from sediments in the Maumee River at four stations from Defiance, Ohio, to Maumee Bay. Upriver sediments were, on average, a total and filtered P sink throughout the year (−19 ± 7 and −6 ± 3, respectively; all fluxes represent `net flux’ reported in µmol m−2 h−1). At the river …

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Benzotriazole And Tolytriazole Analysis In Select Surface Waters Near Wilmington Air Park, Lee A. Raska Jan 2021

Benzotriazole And Tolytriazole Analysis In Select Surface Waters Near Wilmington Air Park, Lee A. Raska

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Previous investigations into the presence of benzotriazole (BTZ) and corresponding analogs done in early 2019 found elevated levels near the Wilmington Air Park in Wilmington, Ohio. The analogs detected were 4-methyl-1H-benzotriazole and 5-methyl-1H-benzotriazole: known together as tolytriazole (TTZ). BTZ and TTZ are emerging environmental contaminants of concern that are often found in aircraft de-icing solutions, anti-icing solutions and detergents. The Wilmington Air Park has two facilities used to pre-treat runoff water before its subsequent release into surrounding streams. Three sites were chosen: Lytle Creek, Indian Run, and Cowan Creek. For the 2019 and 2019/2020 investigative projects, Cowan Creek was designated …

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Computational Simulation And Analysis Of Neuroplasticity, Madison E. Yancey Jan 2021

Computational Simulation And Analysis Of Neuroplasticity, Madison E. Yancey

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Homeostatic synaptic plasticity is the process by which neurons alter their activity in response to changes in network activity. Neuroscientists attempting to understand homeostatic synaptic plasticity have developed three different mathematical methods to analyze collections of event recordings from neurons acting as a proxy for neuronal activity. These collections of events are from control data and treatment data, referring to the treatment of neuron cultures with pharmacological agents that augment or inhibit network activity. If the distribution of control events can be functionally mapped to the distribution of treatment events, a better understanding of the biological processes underlying homeostatic synaptic …

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Alterations In Cardiac Motions Of The Failing Heart During Direct Mechanical Ventricular Actuation, Benjamin Allyn Schmitt Jan 2021

Alterations In Cardiac Motions Of The Failing Heart During Direct Mechanical Ventricular Actuation, Benjamin Allyn Schmitt

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Objectives: Heart failure (HF) refractory to medical management can be effectively treated with mechanical support. However, available devices are frequently associated with complications due to blood contact. Direct cardiac compression (DCC) devices augment LV systolic pump function by externally compressing the heart surface. Direct Mechanical Ventricular Actuation (DMVA) is a unique DCC method providing not only systolic but, importantly, diastolic support. However, DCC in general remains a relatively poorly understood modality. The purpose of this study was to examine DMVA’s effect on restoration of physiologic function in the failing heart. Methods: Global ischemic HF was induced with 5 mins of …

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Deep Learning For Compressive Sar Imaging With Train-Test Discrepancy, Morgan R. Mccamey Jan 2021

Deep Learning For Compressive Sar Imaging With Train-Test Discrepancy, Morgan R. Mccamey

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We consider the problem of compressive synthetic aperture radar (SAR) imaging with the goal of reconstructing SAR imagery in the presence of under sampled phase history. While this problem is typically considered in compressive sensing (CS) literature, we consider a variety of deep learning approaches where a deep neural network (DNN) is trained to form SAR imagery from limited data. At the cost of computationally intensive offline training, on-line test-time DNN-SAR has demonstrated orders of magnitude faster reconstruction than standard CS algorithms. A limitation of the DNN approach is that any change to the operating conditions necessitates a costly retraining …

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Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani Jan 2021

Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani

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People in today's world seek things that are simple to use. Learning is one of the most crucial aspects of the ongoing digital transformation. Everything is now accessible with a single click on mobile devices, making access to instructional materials faster, easier, and more comfortable. It takes time and effort to build abilities and become an expert in the fields of learning, training, and teaching; and music learning demands a great deal of both practice and mentoring. Initially, music teachers and band directors must maintain a steady attention and devote a significant amount of time to manually teaching materials. This …

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Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents, Elisavet Elli Kostalia Jan 2021

Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents, Elisavet Elli Kostalia

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A great percentage of documents in scientific and engineering disciplines include mathematical formulas and/or algorithms. Exploring the mathematical formulas in the technical documents, we focused on the mathematical operations associations, their syntactical correctness, and the association of these components into attributed graphs and Stochastic Petri Nets (SPN). We also introduce a formal language to generate mathematical formulas and evaluate their syntactical correctness. The main contribution of this work focuses on the automatic segmentation of mathematical documents for the parsing and analysis of detected algorithmic components. To achieve this, we present a synergy of methods, such as string parsing according to …

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Utilizing Rotational Energy In Wind Turbine Blades With The Flywheel Mechanism And Predicting The Power Output By Neural Networking, Anamika Mishra Jan 2021

Utilizing Rotational Energy In Wind Turbine Blades With The Flywheel Mechanism And Predicting The Power Output By Neural Networking, Anamika Mishra

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As we expand and innovate for better and safer living, there will always be a need for new energy sources. By replacing fossil fuels, renewable energy is becoming a viable option for primary power generation. That is why researchers are turning their attention to renewable energy sources and ways of making the most of them. WIND ENERGY is a promising renewable and clean energy source harvested from the wind which is plentiful on the planet. We already have the technology to harvest it, but the efficiency and power output are not optimal. In this thesis, to enhance the energy harvesting …

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Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta Jan 2021

Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta

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Development of professional communication skills, such as motivational interviewing, often requires experiential learning through expert instructor-guided role-plays between the trainee and a standard patient/actor. Due to the growing demand for such skills in practices, e.g., for health care providers in the management of mental health challenges, chronic conditions, substance misuse disorders, etc., there is an urgent need to improve the efficacy and scalability of such role-play based experiential learning, which are often bottlenecked by the time-consuming performance assessment process. WSU is developing ReadMI (Real-time Assessment of Dialogue in Motivational Interviewing) to address this challenge, a mobile AI solution aiming to …

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Goal Management In Multi-Agent Systems, Venkatsampath Raja Gogineni Jan 2021

Goal Management In Multi-Agent Systems, Venkatsampath Raja Gogineni

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Autonomous agents in a multi-agent system coordinate to achieve their goals. However, in a partially observable world, current multi-agent systems are often less effective in achieving their goals. In much part, this limitation is due to an agent's lack of reasoning about other agents and their mental states. Another factor is the agent's inability to share required knowledge with other agents and the lack of explanations in justifying the reasons behind the goal. This research addresses these problems by presenting a general approach for agent goal management in unexpected situations. In this approach, an agent applies three main concepts: goal …

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Applying Cognitive Measures In Counterfactual Prediction, Lori A. Mahoney Jan 2021

Applying Cognitive Measures In Counterfactual Prediction, Lori A. Mahoney

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Counterfactual reasoning can be used in task-switching scenarios, such as design and planning tasks, to learn from past behavior, predict future performance, and customize interventions leading to enhanced performance. Previous research has focused on external factors and personality traits; there is a lack of research exploring how the decision-making process relates to both task-switching and counterfactual predictions. The purpose of this dissertation is to describe and explain individual differences in task-switching strategy and cognitive processes using machine learning techniques and linear ballistic accumulator (LBA) models, respectively, and apply those results in counterfactual models to predict behavior. Applying machine learning techniques …

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