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Articles 1381 - 1410 of 14333
Full-Text Articles in Entire DC Network
Smart Roadside Safety Vest, Nicholas Huttinger, Emily Stapleton, Susannah Smith
Smart Roadside Safety Vest, Nicholas Huttinger, Emily Stapleton, Susannah Smith
Williams Honors College, Honors Research Projects
The objective of this project is to design a vest to be worn by pedestrians and cyclists, or anyone who may be working near traffic. This vest will utilize an LED display on the back of the vest to increase the visibility of the wearer and convey information to nearby drivers. The vest will also be able to detect and alert the wearer to approaching vehicles. If it is detected that the wearer has been involved in an accident, the vest will send a message to the wearer’s designated emergency contact(s), which will include the GPS coordinates of the wearer …
Self-Watering Plant Device, Nick Sabetta
Self-Watering Plant Device, Nick Sabetta
Williams Honors College, Honors Research Projects
Many homeowners enjoy having plants around their homes. However, life can quickly become busy and stressful. This often makes it difficult to keep with their house plants. The goal of this project is to design a device that will be able to help take care of house plants. The device will be able to water the plant when the soil moisture is detected. The device will also monitor the air temperature as well as the sunlight levels that the plant is receiving. All of the collected data will then be sent via Bluetooth to a smartphone. The app will alert …
Smart Dog Door, Andrew Shetler, William Boissoneault, Jacob Stump, Benjamin Charlson
Smart Dog Door, Andrew Shetler, William Boissoneault, Jacob Stump, Benjamin Charlson
Williams Honors College, Honors Research Projects
With modern life getting busier and more complex, many have turned to autonomous assistance for taking care of pets. The objective of this project is to design and prototype a device and application that will allow only certain dogs to enter and exit through a dog door while making the owners aware of their dog's activity. The dog door will utilize wireless communication from the dog to the door to control the status of the door’s lock and update the database that will send updates to the application. The application will keep track of when the dog enters and exits …
Schaeffler Icvd Coating Machine, Louis Mcgrath
Schaeffler Icvd Coating Machine, Louis Mcgrath
Williams Honors College, Honors Research Projects
Chemical Vapor Deposition (CVD) is mutual technology used to deposit thin film through a gaseous phase by vaporizing the solid materials. This conventional process usually requires high thermal stability of the materials, which is not applicable for most of the polymeric materials. Therefore, a novel process, initiated Chemical Vapor Deposition (iCVD) is developed by introducing the gaseous monument and initiator to form the thin film in-situ. By adjusting the free-radical polymerization in the vapor phase, a variety of thin and uniform polymer films can be achieved. Depending on the chemistry, iCVD has many categories. This report explains the design …
Midi Recorder And Learning Tool, Caden Dees, Saikishore Gowrishankar, Cameron Johnson, Benjamin Bolyard
Midi Recorder And Learning Tool, Caden Dees, Saikishore Gowrishankar, Cameron Johnson, Benjamin Bolyard
Williams Honors College, Honors Research Projects
The project's goal is to create a device that can record MIDI files from any standard 88-key piano as well as teach piano learners how to play songs.
Automated Flood Depth Estimation On Roadways, Kwame Ampofo, Megan A. Witherow, Alex Glandon, Monibor Rahman, Ahmed Temtam, Mecit Cetin, Khan M. Iftekharuddin
Automated Flood Depth Estimation On Roadways, Kwame Ampofo, Megan A. Witherow, Alex Glandon, Monibor Rahman, Ahmed Temtam, Mecit Cetin, Khan M. Iftekharuddin
Civil & Environmental Engineering Faculty Publications
Recurrent nuisance flooding is common across many parts of the globe and causes extensive challenges for drivers on the roadways. The prevailing monitoring methods for roadway flooding are costly and not automated or effective. The ubiquity of visual data from cameras and advancements in computing such as deep learning may offer cost-effective methods for automated flood depth estimation on roadways based on reference objects such as cars. However, flood depth estimation faces challenges due to the limited amount of data annotated with water levels and diverse scenes showing reference objects at various scales and perspectives. This study proposes a novel …
Distribution System Losses Allocation Based On Circuit Theory With Distributed Generation, Ahmed S. Abdelkader, Ibrahim I. Mansy, Abdelfattah A. Eladl
Distribution System Losses Allocation Based On Circuit Theory With Distributed Generation, Ahmed S. Abdelkader, Ibrahim I. Mansy, Abdelfattah A. Eladl
Mansoura Engineering Journal
Electricity energy is the most convenient and efficient form of energy transmission and conversion. Nonetheless, losses take place while electrical power is traveling from power stations through transmission and distribution networks to the loads. Despite the high efficiency of electrical transmission and distribution networks, the huge amounts of power moving through these networks make the financial loss due to the lost energy very high and its management becomes a critical consideration for both utility providers and regulatory bodies. The efficient management of losses encompasses two major functions: the first is running the system in a way that minimizes the losses; …
Extending Trailer, Alex Grove
Extending Trailer, Alex Grove
Williams Honors College, Honors Research Projects
The goal of this research project is to revolutionize the convenience in towable transportation. This innovative design aims to enhance the versatility of pull-behind trailers by incorporating an extendable feature, allowing users to effortlessly adjust the length according to their specific needs. Whether navigating tight spaces or accommodating extra cargo, our trailer adapts to diverse situations, providing unmatched flexibility. In addition to its adjustable length, the trailer is engineered to be compactable, addressing the storage constraints often faced by users with limited space. The collapsible design ensures easy storage without compromising on functionality, making it an ideal solution for individuals …
Autonomous Basketball Court Creation Robot, Bryce Haldeman, Tyler Gray, Dalon Vura
Autonomous Basketball Court Creation Robot, Bryce Haldeman, Tyler Gray, Dalon Vura
Williams Honors College, Honors Research Projects
The Autonomous Basketball Court Outlining System presents a comprehensive solution for precision court marking. Powered by a 24V lithium-ion battery and driven by a single ST microcontroller, the system autonomously marks the outline of a half basketball court using predefined algorithms. User-friendly features include easy loading of marking material, actuated by gravity or a small servo motor depending on material of choice, ensuring intuitive operation. Safety is prioritized, with the servo motor eliminating high-pressure concerns, and the system maintains a controlled speed accounting for user well-being. Two step and direction servo motors enable accurate linear displacement, facilitating straight lines, and …
Smart Longboard, Ben Rath
Smart Longboard, Ben Rath
Williams Honors College, Honors Research Projects
The proposed design project includes a motorized longboard, equipped with a wireless handheld remote to manage the speed of the board. An embedded system mounted underneath the board will gather data from an accelerometer and a GPS sensor. This information is sent through a Bluetooth connection to a compatible smartphone application where it will be displayed. The project also includes a custom battery and charging circuit for the board to ensure that all of the engineering requirements are met. The board will be easy to use and the smartphone application will be able to display ride statistics of the user …
Photoluminescence Of Beryllium-Related Defects In Gallium Nitride, Mykhailo Vorobiov, Mykhailo Vorobiov
Photoluminescence Of Beryllium-Related Defects In Gallium Nitride, Mykhailo Vorobiov, Mykhailo Vorobiov
Theses and Dissertations
This study explores the potential of beryllium (Be) as an alternative dopant to magnesium (Mg) for achieving higher hole concentrations in gallium nitride (GaN). Despite Mg prominence as an acceptor in optoelectronic and high-power devices, its deep acceptor level at 0.22 eV above the valence band limits its effectiveness. By examining Be, this research aims to pave the way to overcoming these limitations and extend the findings to aluminum nitride and aluminum gallium nitride (AlGaN) alloy. Key contributions of this work include. i)Identification of three Be-related luminescence bands in GaN through photoluminescence spectroscopy, improving the understanding needed for further material …
Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick
Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick
Browse all Theses and Dissertations
This research illustrates a high-security wireless communication method using a joint radar/communication waveform, addressing the vulnerability of traditional low probability of detection (LPD) waveforms to hostile receiver detection via cyclostationary processing (CSP). To mitigate this risk, RF steganography is used, concealing communication signals within linear frequency modulation (LFM) radar signals. The method integrates reduced phase-shift keying (RPSK) modulation and variable symbol duration, ensuring secure transmission while evading detection. Implementation is validated through software-defined radios (SDRs), demonstrating effectiveness in covert communication scenarios. Results include analysis of message reception and cyclostationary features, highlighting the method's ability to conceal messages from hostile receivers. …
Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer
Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer
Browse all Theses and Dissertations
Performing automatic target recognition (ATR) on full-size aircraft targets using inverse synthetic aperture radar (ISAR) data is challenging and expensive. The use of scale models and radar systems of such large targets saves time and reduces facility requirements. This study examines the feasibility of performing ATR on 1:144 scale model airplanes at Ka-band. The scale model and Ka-band radar simulate the collection of full-scale targets at VHF-band. The phase history measurement collections were completed in the Sensors and Signals Exploitation Laboratory (SSEL) at Wright State University. To ensure sufficient data for training and testing, the phase history data was augmented …
Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich
Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich
Browse all Theses and Dissertations
To address the issues of limited target data in the Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) problem set, synthetic data is often used to aid in filling the gap. This paper covers an in depth look at the use of colorization, dynamic range adjustment, and target extraction as data augmentation techniques to improve the accuracy of deep learning networks trained on synthetic SAR data. The use of multiple different data augmentations combine to dramatically improve the accuracy of a common Convolutional Neural Network (CNN) over the use of standard synthetic data. A comparison of increasing fraction of measured …
Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi
Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi
Browse all Theses and Dissertations
Lithium-ion batteries are an integral component of energy storage systems for renewable energy applications owing to their high energy density. Extensive research has therefore been carried out, utilizing both experimental and computational methods, to aid in a deeper understanding of lithium-ion batteries. Challenges related to efficiency, safety and thermal management persist, particularly during high current draw, extreme temperature conditions and extreme dynamic current operation such as in electric vehicles. This thesis work presents an electrochemical-thermal model of a lithium-ion battery that simulates and analyzes the variation of electrical behavior, chemical behavior and thermal behavior. The electrochemical model is developed by …
Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson
Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson
Browse all Theses and Dissertations
The uncertainty of the standard calibration procedure for radar cross-section (RCS) measurement is studied for different targets measured in the near-field from 550 to 700 GHz. Using common calibration spheres and squat cylinders mounted on a styrofoam pedestal at waterline (zero-degrees elevation), the calibration difference measure is determined for each target. Similarly, the difference metric is determined for square trihedral and tophat targets placed on a ground plane and measured at different elevation angles. The mean calibration measure is calculated using the dual calibration target method and repeated measurements in an anechoic chamber. The specific THz system is described and …
Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa
Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa
Dissertations, Master's Theses and Master's Reports
Reactivity Controlled Compression Ignition (RCCI) engines operates has capacity to provide higher thermal efficiency, lower particular matter (PM), and lower oxides of nitrogen (NOx) emissions compared to conventional diesel combustion (CDC) operation. Achieving these benefits is difficult since real-time optimal control of RCCI engines is challenging during transient operation. To overcome these challenges, data-driven machine learning based control-oriented models are developed in this study. These models are developed based on Linear Parameter-Varying (LPV) modeling approach and input-output based Kernelized Canonical Correlation Analysis (KCCA) approach. The developed dynamic models are used to predict combustion timing (CA50), indicated mean effective pressure (IMEP), …
Guarding The Grid: Exploring Iot And Iiot Security Vulnerabilities In Smart Power Systems, Nicole G. Parker
Guarding The Grid: Exploring Iot And Iiot Security Vulnerabilities In Smart Power Systems, Nicole G. Parker
Honors Undergraduate Theses
The Internet of Things (IoT) encompasses the collective network of electrical devices and the technology that enables them to send and receive data. The use of IoT technologies in industrial settings, such as transportation, manufacturing, and energy is referred to as the Industrial Internet of Things (IIoT). With the expansion of IoT in homes and IIoT in the energy sector has come an increase in the number of devices connected with each other. Engineers have utilized this network to develop sophisticated smart systems that combine sensing, processing, actuation, and control to produce smart environments. Along with the benefits of IoT …
Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk
Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk
Theses and Dissertations--Electrical and Computer Engineering
Refractory focal epilepsy is characterized by the presence of seizures that cannot be controlled via anti-seizure medications. For patients suffering from this form of epilepsy, accurate identification of the seizure onset zone is a crucial step for many modalities of treatment. Electrical source imaging (ESI) allows for estimation of the seizure onset zone from electroencephalography. EEG feature extraction is an important step that can impact the final accuracy of source estimates. This work provides a review of 23 ictal ESI studies and proposes a delta-focused ictal ESI methodology. Our proposed delta-focused ictal ESI is implemented across 33 refractory focal epilepsy …
Multi-Physics Modeling Of Immersion Cooled Electric Power Apparatuses, Reza Ilka
Multi-Physics Modeling Of Immersion Cooled Electric Power Apparatuses, Reza Ilka
Theses and Dissertations--Electrical and Computer Engineering
Electric power conversion apparatuses such as electromagnetic transformers and power electronic converters play a backbone role in the global power and energy industries, such as power transmission and distribution, electrified transportation vehicle systems, industry automation, and the like. To investigate the performance (efficiency, reliability, etc.) of such critical power conversion apparatuses, high-fidelity multi-physics modeling becomes critical which involves dedicated coupling among multiple physical domains, including electrical, magnetic, thermal, mechanical, and material engineering. Nevertheless, the majority of the existing models for these power conversion apparatuses focus only on one or two physical domains, and the modeling fidelity needs to be further …
A Novel Processor Architecture Implementing The Stacked Error Diffusion Algorithm And Its Zynq-Based Realization, Qishi Hu
Theses and Dissertations--Electrical and Computer Engineering
Digital halftoning reproduces continuous-tone images using patterns of black and white dots, while multitoning extends this concept by incorporating inks with intermediate intensities. These techniques are extensively utilized in the printing industry to accommodate the limited range of inks available in printers. Stacked error diffusion is a high-quality multitoning algorithm that adheres to the blue-noise dithering standard. This thesis research studies the potential parallelism inherent in the algorithm and introduces the design of a novel processor architecture optimized for efficient execution. The architecture is realized on an FPGA development board featuring a Zynq SoC. Additionally, the hardware prototype can also …
Experimental Investigation Of Self-Mixing Interferometric Technique For Displacement Assessment, Dulanjana Anuhas Egodagamage
Experimental Investigation Of Self-Mixing Interferometric Technique For Displacement Assessment, Dulanjana Anuhas Egodagamage
Chulalongkorn University Theses and Dissertations (Chula ETD)
The self-mixing interferometric (SMI) technique has proven effective for achieving precise, contactless measurements of submicron displacements. This study aims to further investigate and experimentally assess the capabilities of the SMI technique in displacement sensing. While extensive research has been conducted on the SMI technique for displacement sensing, its performance can still be further explored in scenarios where the target exhibits varying displacement amplitudes and oscillation frequencies. Understanding the limitations and ranges of the SMI technique is crucial for advancing laboratory-based setups into practical applications. An experimental optoelectronic setup was used in this work, employing a semiconductor laser diode module integrated …
Hyperspectral And Polarimetric Imaging Of The Ocean For The Characterization Of The Surface Effects And Measurement Uncertainties, Mateusz Malinowski
Hyperspectral And Polarimetric Imaging Of The Ocean For The Characterization Of The Surface Effects And Measurement Uncertainties, Mateusz Malinowski
Dissertations and Theses
Ocean and coastal waters are monitored by Ocean Color satellite sensors to determine concentrations of chlorophyll and water properties and identify areas of algal blooms and other events. The light radiance from the ocean is weak in comparison with the sky radiance, which requires very accurate atmospheric correction of the radiance measured at the top of the atmosphere (TOA) on the satellite and heavy validation of the derived water leaving radiance by field measurements from the ships and ocean platforms. For TOA and especially above water radiance the skylight reflected from the ocean surface represents one of the main sources …
Generalized Conditional Feedback System With Model Uncertainty, Chengbo Dai, Zhiqiang Gao, Yangquan Chen, Donghai Li
Generalized Conditional Feedback System With Model Uncertainty, Chengbo Dai, Zhiqiang Gao, Yangquan Chen, Donghai Li
Electrical and Computer Engineering Faculty Publications
Model uncertainty creates a largely open challenge for industrial process control, which causes a trade-off between robustness and performance optimality. In such a case, we propose a generalized conditional feedback (GCF) system to largely eliminate conflicts between robustness and performance optimality. This approach leverages a nominal model to design an optimal control in the virtual domain and defines an ancillary feedback controller to drive the physical process to track the trajectory of the virtual domain. The effectiveness of the proposed GCF scheme is demonstrated in a simulation for six typical industrial processes and three model-based control methods, and in a …
Machine Learning Assisted Optimization For Calculation And Automated Tuning Of Antennas, Lauren Linkous
Machine Learning Assisted Optimization For Calculation And Automated Tuning Of Antennas, Lauren Linkous
Theses and Dissertations
The Antenna Calculation and Autotuning Tool (AntennaCAT) software suite represents a significant advancement in the field of antenna design by automating the entire design, CAD, simulation, and optimization process compatible with several EM simulation software suites. It is the first comprehensive implementation of machine learning in this context. In particular, this work includes the capability to create and export structured datasets from the aforementioned EM software for iterative improvement and includes an expandable selection of optimizers.
Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber
Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber
Theses and Dissertations
As cyber-physical systems (CPS) become more integrated into everyday life, the security of these systems must also be considered during their development due to their ever-increasing importance. With the growth of physical components in the system, more autonomous control requirements, and increased dependence on proper functionality, verifying system safety and correct operation becomes increasingly difficult. CPS have become more complex through the combination of additional hardware and the resulting interconnected software in many layers, each requiring unique security solutions. One example of such a safety-critical CPS embedded system is the Flight Control System (FCS) of an Unmanned Aerial System (UAS). …
Towards The Automation Of Post-Processing Of Additive Manufacturing Using Collaborative Robots, Logan Schorr
Towards The Automation Of Post-Processing Of Additive Manufacturing Using Collaborative Robots, Logan Schorr
Theses and Dissertations
Despite the incredible potential that collaborative robots have, they are underutilized in several industries that could benefit greatly. These specialized fields, such as additive manufacturing, face challenges that can be solved with the use of robotics, including advanced computer vision, end-effector tooling, and process refinement. My research aims to utilize collaborative robots in an effort to solve the above stated problems, for the specific fields of additive manufacturing. Specifically within this field is the automation of post-processing; this is normally completely manual, as the tools for automation are not sufficiently developed to handle the flexibility required for additive manufacturing. This …
Evaluating The Impact Of Perceptual Loss In Generative Adversarial Models And Diffusion Models For Document Image Enhancement, Farzaneh Karimpour
Evaluating The Impact Of Perceptual Loss In Generative Adversarial Models And Diffusion Models For Document Image Enhancement, Farzaneh Karimpour
Electronic Theses and Dissertations
Documents often suffer from various types of degradation which make them difficult to read and restrict OCR performance. This study investigates the effectiveness of perceptual loss in enhancing document image cleanup by comparing a GAN-based model and a diffusion model. In our experiments, we utilized the DE-GAN model as a GAN-based model and the NAF-DPM model as a diffusion model, both enhanced by incorporating perceptual loss. We then compared the results of both models and evaluated them by using the DIBCO 2013, DIBCO 2017, and H-DIBCO 2018 datasets revealed that our approach consistently outperforms existing state-of-the-art methods. Results showed that …
Comparative Analysis Of Deep Learning-Based Anomaly Detection Models For Gps Spoofing Detection, Hasan Mirzakhaninafchi
Comparative Analysis Of Deep Learning-Based Anomaly Detection Models For Gps Spoofing Detection, Hasan Mirzakhaninafchi
Electronic Theses and Dissertations
As autonomous vehicles (AVs) become integral to modern transportation, their susceptibility to cyber-attacks, particularly GPS spoofing, presents a serious security threat. This study addresses these challenges by applying a suite of deep learning models to enhance the detection of anomalous GPS signals. Focusing on autoencoder-based architectures, the proposed models such as long short-term memory-based variational autoencoder (LSTM-VAE), LSTM-based autoencoder (LSTM-AE), multilayer perceptron-based variational autoencoder (MLP-VAE), MLP-based Autoencoder (MLPAE), Stacked LSTM-based variational autoencoder (Stacked-LSTM-VAE), stacked LSTM-based autoencoder (Stacked-LSTM-AE), memory-augmented-LSTM-VAE (Mem-LSTM-VAE), and time-series-anomaly-detection-generative-adversarial-networks (TadGAN) were trained exclusively on authentic GPS data. This unsupervised learning approach which used for the above-mentioned models enables …
K-Perm: Personalized Response Generation Using Dynamic Knowledge Retrieval And Persona-Adaptive Queries, Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur
K-Perm: Personalized Response Generation Using Dynamic Knowledge Retrieval And Persona-Adaptive Queries, Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur
Publications
Personalizing conversational agents can enhance the quality of conversations and increase user engagement. However, they often lack external knowledge to tend to a user’s persona appropriately. This is particularly crucial for practical applications like mental health support, nutrition planning, culturally sensitive conversations, or reducing toxic behavior in conversational agents. To enhance the relevance and comprehensiveness of personalized responses, we propose using a two-step approach that involves (1) selectively integrating user personas and (2) contextualizing the response with supplementing information from a background knowledge source. We develop K-PERM (Knowledge-guided PErsonalization with Reward Modulation), a dynamic conversational agent that combines these elements. …