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Articles 51571 - 51600 of 197043

Full-Text Articles in Engineering

Contact Fatigue Of Spur Gear Operating Under Starved Lubrication Condition, Aparna Udthala Jan 2021

Contact Fatigue Of Spur Gear Operating Under Starved Lubrication Condition, Aparna Udthala

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This study describes contact fatigue behavior of spur gear contacts operating under mixed elastohydrodynamic condition. The focus is placed on the starvation effect on fatigue crack initiation. With the model, parametric simulations are carried out with different contact parameters. In the process, the lubricant supply is varied to alter the lubrication condition from fully flooded to severely starved circumstance. Multi-axial stress fields induced by surface normal and tangential tractions are evaluated, whose amplitudes and means are used in a multi-axial fatigue criterion to determine the crack initiation life. It is found a lower lubricant viscosity elongates fatigue life when severe …

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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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Functionalizing Ceramic Matrix Composites By The Integration Of A Metallic Substructure With Comparable Feature Size, Elizabeth Pierce Heckman Jan 2021

Functionalizing Ceramic Matrix Composites By The Integration Of A Metallic Substructure With Comparable Feature Size, Elizabeth Pierce Heckman

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A metallic network has been embedded in a silicon carbide fiber– silicon carbide (SiC) matrix ceramic composite (CMC) in order to combine the functional properties of the metal and the structural properties of the CMC. The processing of the composite involves iterative pre-ceramic polymer infiltration and heating to temperatures at 1100°C. The metallic structure embedded in the CMC must retain its unique properties during processing and cannot convert to a silicide or carbide resulting from diffusion of Si and C species from the SiC matrix. To gain an understanding of the diffusion process, a fully processed CMC with tungsten, tantalum, …

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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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Fabrication And Analysis Of High-Performance Thermochemically Densified Wood, Victor Arulappan Pushparaj Jan 2021

Fabrication And Analysis Of High-Performance Thermochemically Densified Wood, Victor Arulappan Pushparaj

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While wood construction may be as ancient as humanity itself, wood remains one of the most utilized structural materials because of it’s availability, low cost, durability, surprisingly high specific mechanical properties, and renewability. Recent research into wood-based materials has focused on strategies for enhancing the strength and stiffness of as-grown materials. We fabricated densified wood by thermochemically treating raw white oak wood in Na2SO3 and NaOH solutions, followed by compressing the treated wood at 5MPa at high temperature. Treating the raw wood in NaOH and Na2SO3 cleaves the alpha-O-4 ether bond and beta-O-4 ether bonds, thus dissolving most of the …

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Unraveling The Etiologies Of Discrete Subaortic Stenosis: A Focus On Left Ventricular Outflow Tract Hemodynamics, Jason A. Shar Jan 2021

Unraveling The Etiologies Of Discrete Subaortic Stenosis: A Focus On Left Ventricular Outflow Tract Hemodynamics, Jason A. Shar

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Discrete subaortic stenosis (DSS) is an obstructive cardiac disease characterized by the formation of a thin fibromuscular ring of tissue in the left ventricular (LV) outflow tract (LVOT). Although its etiology is unknown, the association between DSS, pediatric age, and morphological LVOT abnormalities points to a potential hemodynamic etiology. Here, altered subaortic flow dynamics, stemming from deviated LVOT anatomy, may promote lesion formation through local fluid shear stress abnormalities triggering membrane formation. The assessment of this hypothetical pathway requires elucidation of the complex LV wall shear stress (WSS) environment. The central hypothesis of this dissertation is that altered LV hemodynamics, …

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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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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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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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Aqueous Fabrication Of Pristine And Oxide Coated Znse Nanoparticles, Nicholas L. Van Zandt Jan 2021

Aqueous Fabrication Of Pristine And Oxide Coated Znse Nanoparticles, Nicholas L. Van Zandt

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Semiconducting nanoparticles have received significant attention due to their unique optoelectronic properties. Quantum dots (QDs), a class of spherical nanoparticles, possess a size-dependent bandgap and photoluminescence at visible wavelengths. QDs have many applications including biological labelling, solar cells, chemical impurity detection, and optical glasses. Doping QDs into optical glasses is highly desirable. High-quality QDs can be synthesized via liquid solution methods. However, solution-synthesized QDs often degrade over time and they cannot survive incorporation into a glass melt without protection. In this work, the aqueous synthesis of ZnSe QDs and coating with nanometer silica and alumina protective shells are investigated. The …

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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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Development Of A Robust And Tunable Aircraft Guidance Algorithm, Jacob R. Spangenberg Jan 2021

Development Of A Robust And Tunable Aircraft Guidance Algorithm, Jacob R. Spangenberg

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A set of guidance control laws is developed for application to a reduced order dynamic aircraft model. A feedback control formulation utilizing a linear quadratic regulator (LQR) is developed, together with methods for easing the design burden associated with gain tuning. Metrics are developed to assess the stability margin of the controller over the full flight envelope of a notional unmanned aerial vehicle (UAV) model. A feedforward control path is then added to the architecture. The performance of the guidance control laws is assessed through time domain step response metrics as well as through execution of a design mission. The …

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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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Altered Skeletal Muscle Excitation-Contraction Coupling In The R6/2 Transgenic Mouse Model For Huntington's Disease, Daniel R. Miranda Jan 2021

Altered Skeletal Muscle Excitation-Contraction Coupling In The R6/2 Transgenic Mouse Model For Huntington's Disease, Daniel R. Miranda

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Huntington’s disease (HD) has classically been categorized as a neurodegenerative disorder. However, the expression of the disease-causing mutated huntingtin gene in skeletal muscle may contribute to the symptoms of HD, namely those that involve involuntary muscle contraction. In the R6/2 transgenic mouse model of HD, we previously observed ion channel defects that could contribute to involuntary muscle contraction. Here, in R6/2 muscle we investigated the consequence of these ion channel defects on action potentials (APs), the first step in excitation-contraction (EC) coupling. We found that the ion channel defects were associated with depolarizing the baseline membrane potential during AP trains. …

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Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger Jan 2021

Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger

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The additive manufacturing (AM) field is striving to identify anomalies in laser powder bed fusion (LPBF) using multi-sensor in-process monitoring paired with machine learning (ML). In-process monitoring can reveal the presence of anomalies but creating a ML classifier requires labeled data. The present work approaches this problem by printing hundreds of Inconel-718 coupons with different processing parameters to capture a wide range of process monitoring imagery with multiple sensor types. Afterwards, the process monitoring images are encoded into feature vectors and clustered to isolate groups in each sensor modality. Four texture representations were learned by training two convolutional neural network …

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Reconfigurable Antenna Array Using The Pin-Diode-Switched Printed Square Spiral Element, Corey M. Stamper Jan 2021

Reconfigurable Antenna Array Using The Pin-Diode-Switched Printed Square Spiral Element, Corey M. Stamper

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A dual-band array of reconfigurable elements is modeled and simulated. The array consists of four single square spiral microstrip antennas that are corporately fed and are used as a unit cell. The single square spiral uses two PIN diodes as switching elements to achieve reconfiguration. The array has four switch states that can operate over four discrete frequencies in the S and C bands. The unit cell radiation pattern is used with the pattern multiplication model to quickly simulate the array pattern of larger arrays. A 3 x 3 array of the unit cells is modeled with only the center …

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Development Of A Robust And Tunable Aircraft Guidance Algorithm, Jacob R. Spangenberg Jan 2021

Development Of A Robust And Tunable Aircraft Guidance Algorithm, Jacob R. Spangenberg

Browse all Theses and Dissertations

A set of guidance control laws is developed for application to a reduced order dynamic aircraft model. A feedback control formulation utilizing a linear quadratic regulator (LQR) is developed, together with methods for easing the design burden associated with gain tuning. Metrics are developed to assess the stability margin of the controller over the full flight envelope of a notional unmanned aerial vehicle (UAV) model. A feedforward control path is then added to the architecture. The performance of the guidance control laws is assessed through time domain step response metrics as well as through execution of a design mission. The …

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Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger Jan 2021

Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger

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The additive manufacturing (AM) field is striving to identify anomalies in laser powder bed fusion (LPBF) using multi-sensor in-process monitoring paired with machine learning (ML). In-process monitoring can reveal the presence of anomalies but creating a ML classifier requires labeled data. The present work approaches this problem by printing hundreds of Inconel-718 coupons with different processing parameters to capture a wide range of process monitoring imagery with multiple sensor types. Afterwards, the process monitoring images are encoded into feature vectors and clustered to isolate groups in each sensor modality. Four texture representations were learned by training two convolutional neural network …

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Augmenting Structure/Function Relationship Analysis With Deep Learning For The Classification Of Psychoactive Drug Activity At Class A G Protein-Coupled Receptors, Hannah Willow Shows Jan 2021

Augmenting Structure/Function Relationship Analysis With Deep Learning For The Classification Of Psychoactive Drug Activity At Class A G Protein-Coupled Receptors, Hannah Willow Shows

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G protein-coupled receptors (GPCRs) initiate intracellular signaling pathways via interaction with external stimuli. [1-5] Despite sharing similar structure and cellular mechanism, GPCRs participate in a uniquely broad range of physiological functions. [6] Due to the size and functional diversity of the GPCR family, these receptors are a major focus for pharmacological applications. [1,7] Current state-of-the-art pharmacology and toxicology research strategies rely on computational methods to efficiently design highly selective, low toxicity compounds. [9], [10] GPCR-targeting therapeutics are associated with low selectivity resulting in increased risk of adverse effects and toxicity. Psychoactive drugs that are active at Class A GPCRs used …

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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

Browse all Theses and Dissertations

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 …

Go to article

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

Browse all Theses and Dissertations

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 …

Go to article

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

Browse all Theses and Dissertations

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 …

Go to article

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