Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Missouri University of Science and Technology (5128)
- TÜBİTAK (3106)
- California Polytechnic State University, San Luis Obispo (1610)
- Air Force Institute of Technology (1334)
- Old Dominion University (1324)
-
- Chinese Chemical Society | Xiamen University (1277)
- Technological University Dublin (1240)
- New Jersey Institute of Technology (1156)
- University of Nebraska - Lincoln (1095)
- University of Central Florida (919)
- Portland State University (887)
- Brigham Young University (758)
- University of Kentucky (680)
- University of Texas at Arlington (656)
- University of Arkansas, Fayetteville (627)
- University of New Mexico (582)
- Embry-Riddle Aeronautical University (542)
- University of South Carolina (511)
- Marquette University (504)
- Purdue University (478)
- Utah State University (474)
- Universitas Indonesia (447)
- Louisiana State University (427)
- University of Nevada, Las Vegas (426)
- Tashkent State Technical University (416)
- Michigan Technological University (415)
- Florida Institute of Technology (376)
- Boise State University (366)
- Virginia Commonwealth University (364)
- Chulalongkorn University (358)
- Keyword
-
- Machine learning (412)
- Optimization (339)
- Deep learning (287)
- Department of Electrical Engineering (269)
- Applied sciences (260)
-
- Machine Learning (191)
- Simulation (184)
- FPGA (181)
- Image processing (180)
- Engineering (165)
- Electrical Engineering (164)
- Classification (157)
- Signal processing (153)
- Daniel Felix Ritchie School of Engineering and Computer Science (149)
- Algorithms (147)
- Electrical and Computer Engineering (145)
- Renewable energy (143)
- Computer vision (139)
- Reliability (137)
- Neural networks (135)
- Modeling (132)
- #antcenter (131)
- Microgrid (128)
- Security (123)
- Artificial intelligence (121)
- Power Electronics (118)
- Control (117)
- Photovoltaic (117)
- Power (117)
- Sensors (117)
- Publication Year
- Publication
-
- Electrical and Computer Engineering Faculty Research & Creative Works (3481)
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Theses and Dissertations (2204)
- Journal of Electrochemistry (1277)
- Electronic Theses and Dissertations (1170)
-
- Electrical Engineering (1054)
- Theses (916)
- Masters Theses (756)
- Department of Electrical and Computer Engineering: Faculty Publications (733)
- Electrical and Computer Engineering Faculty Publications and Presentations (726)
- Faculty Publications (695)
- Electrical and Computer Engineering Faculty Publications (692)
- Articles (564)
- Electrical and Computer Engineering ETDs (524)
- Electrical & Computer Engineering Theses & Dissertations (493)
- Dissertations (469)
- Master's Theses (462)
- Conference papers (438)
- Makara Journal of Technology (438)
- Electrical & Computer Engineering Faculty Publications (402)
- Dissertations and Theses (401)
- Electrical and Computer Engineering Faculty Research and Publications (391)
- Graduate Theses and Dissertations (388)
- Plant Identification in a Combined-Imbalanced Leaf Dataset -- Images (374)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (357)
- Doctoral Dissertations (351)
- Electrical Engineering Theses - Archive (336)
- Online Journal of Space Communication (336)
- Electrical and Computer Engineering Publications (302)
- Browse all Theses and Dissertations (299)
- Publication Type
- File Type
Articles 2941 - 2970 of 36787
Full-Text Articles in Engineering
The Impact Of N-Doped Carbon Quantum Dots On Dye-Sensitized Solar Cells Operating Under Diffused- And Low-Light Intensity, Mona Samir, Ahmed Agour, Zahraa Ismail, Hassan Nageh, Sameh O. Abdellatif
The Impact Of N-Doped Carbon Quantum Dots On Dye-Sensitized Solar Cells Operating Under Diffused- And Low-Light Intensity, Mona Samir, Ahmed Agour, Zahraa Ismail, Hassan Nageh, Sameh O. Abdellatif
Electrical Engineering
This study investigates the double role of N-doped carbon quantum dots (N-CQDs) in dye-sensitized solar cells (DSSCs) that operate under diffused- and low-light intensity conditions. We demonstrate that the incorporation of N-CQDs leads to a substantial improvement in the performance of DSSCs. Under standard one-sun illumination, the maximum power conversion efficiency (PCE) achieved with N-CQDs is 2% higher than that of the bare cell. Moreover, we introduce two new metrics, the diffused-light coefficient and the low-light intensity coefficient, to evaluate the performance of DSSCs under nonideal illumination conditions. The diffused-light coefficient is recorded at 1.55, which indicates a notable enhancement …
Chatreview: A Chatgpt-Enabled Natural Language Processing Framework To Study Domain-Specific User Reviews, Brittany Ho, Ta'rhonda Mayberry, Khanh Linh Nguyen, Manohar Dhulipala, Vivek Krishnamani Pallipuram
Chatreview: A Chatgpt-Enabled Natural Language Processing Framework To Study Domain-Specific User Reviews, Brittany Ho, Ta'rhonda Mayberry, Khanh Linh Nguyen, Manohar Dhulipala, Vivek Krishnamani Pallipuram
All Faculty Articles - School of Engineering and Computer Science
We present ChatReview, a ChatGPT-enabled natural language processing framework that effectively studies domain-specific user reviews to offer relevant and personalized search results at multiple levels of granularity. The framework accomplishes this task using four phases including data collection, tokenization, query construction, and response generation. The data collection phase involves gathering domain-specific user reviews from public and private repositories. In the tokenization phase, ChatReview applies sentiment analysis to extract keywords and categorize them into various sentiment classes. This process creates a token repository that best describes the user sentiments for a given user-review data. In the query construction phase, the framework …
A Sindy Hardware Accelerator For Efficient System Identification On Edge Devices, Michael Sean Gallagher
A Sindy Hardware Accelerator For Efficient System Identification On Edge Devices, Michael Sean Gallagher
Master's Theses
The SINDy (Sparse Identification of Non-linear Dynamics) algorithm is a method of turning a set of data representing non-linear dynamics into a much smaller set of equations comprised of non-linear functions summed together. This provides a human readable system model the represents the dynamic system analyzed. The SINDy algorithm is important for a variety of applications, including high precision industrial and robotic applications. A Hardware Accelerator was designed to decrease the time spent doing calculations. This thesis proposes an efficient hardware accelerator approach for a broad range of applications that use SINDy and similar system identification algorithms. The accelerator is …
A Study Of Random Partitions Vs. Patient-Based Partitions In Breast Cancer Tumor Detection Using Convolutional Neural Networks, Joshua N. Ramos
A Study Of Random Partitions Vs. Patient-Based Partitions In Breast Cancer Tumor Detection Using Convolutional Neural Networks, Joshua N. Ramos
Master's Theses
Breast cancer is one of the deadliest cancers for women. In the US, 1 in 8 women will be diagnosed with breast cancer within their lifetimes. Detection and diagnosis play an important role in saving lives. To this end, many classifiers with varying structures have been designed to classify breast cancer histopathological images. However, randomly partitioning data, like many previous works have done, can lead to artificially inflated accuracies and classifiers that do not generalize. Data leakage occurs when researchers assume that every image in a dataset is independent of each other, which is often not the case for medical …
Numerical Back Analysis Of An Underground Bulk Mining Operation Using Distributed Optical Fiber Sensors For Model Calibration, Samuel Nowak, Taghi Sherizadeh, Mina Esmaeelpour, Paul Brooks, Dogukan Guner, Kutay Karadeniz
Numerical Back Analysis Of An Underground Bulk Mining Operation Using Distributed Optical Fiber Sensors For Model Calibration, Samuel Nowak, Taghi Sherizadeh, Mina Esmaeelpour, Paul Brooks, Dogukan Guner, Kutay Karadeniz
Mining Engineering Faculty Research & Creative Works
Numerical Modeling Of Complex Underground Engineering Projects Such As Caverns, Tunnels, And Bulk Mining Zones Is An Essential Part Of The Design Phase. Large-Scale Models Require Significant Reductions In Complexity From The Real-World Scenario, Which Often Leads To Low Confidence In The Model Output. In This Work, A Mine-Scale Numerical Model Is Developed To Simulate A Room And Pillar Extraction Mining Operation. The Model Inputs Are Calibrated Through The Comparison Of The Model Response To Pillar Extraction In An Analogous Mine Geometry With Measured Strain Values Collected Using A Novel Distributed Optical Fiber Strain Sensing Technique After Pillar Extraction. Calibration …
An Impedance-Source-Based Soft-Switched High Step-Up Dc-Dc Converter With An Active Clamp, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi
An Impedance-Source-Based Soft-Switched High Step-Up Dc-Dc Converter With An Active Clamp, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi
Electrical and Computer Engineering Faculty Research & Creative Works
This article proposes a high step-up dc-dc converter based on a trans-inverse impedance-source structure, in which the voltage gain of the converter is increased by using a lower number of turns ratio of the coupled inductors (CI) windings. The proposed converter achieves a very high voltage gain and a very low voltage stress on the switches. An active clamp is incorporated into the topology of the proposed converter, helping to absorb the energy of the leakage inductances of the CI, and to recycle that energy to the output of the converter to further increase the voltage gain. Furthermore, the active …
Toward Smart And Sustainable Cement Manufacturing Process: Analysis And Optimization Of Cement Clinker Quality Using Thermodynamic And Data-Informed Approaches, Jardel P. Gonçalves, Taihao Han, Gaurav Sant, Narayanan Neithalath, Jie Huang, Aditya Kumar
Toward Smart And Sustainable Cement Manufacturing Process: Analysis And Optimization Of Cement Clinker Quality Using Thermodynamic And Data-Informed Approaches, Jardel P. Gonçalves, Taihao Han, Gaurav Sant, Narayanan Neithalath, Jie Huang, Aditya Kumar
Electrical and Computer Engineering Faculty Research & Creative Works
Cement manufacturing is widely recognized for its harmful impacts on the natural environment. In recent years, efforts have been made to improve the sustainability of cement manufacturing through the use of renewable energy, the capture of CO2 emissions, and partial replacement of cement with supplementary cementitious materials. To further enhance sustainability, optimizing the cement manufacturing process is essential. This can be achieved through the prediction and optimization of clinker phases in relation to chemical compositions of raw materials and manufacturing conditions. Cement clinkers are produced by heating raw materials in kilns, where both raw material compositions and processing conditions …
Advances In Growth, Doping, And Devices And Applications Of Zinc Oxide, Vishal Saravade, Zhe Chuan Feng, Manika Tun Nafisa, Chuanle Zhou, Na Lu, Benjamin Klein, Ian T. Ferguson
Advances In Growth, Doping, And Devices And Applications Of Zinc Oxide, Vishal Saravade, Zhe Chuan Feng, Manika Tun Nafisa, Chuanle Zhou, Na Lu, Benjamin Klein, Ian T. Ferguson
Electrical and Computer Engineering Faculty Research & Creative Works
Zinc oxide is a breakthrough multifunctional material of emerging interest applicable in the areas of electronics, computing, energy harvesting, sensing, optoelectronics, and biomedicine. Zno has a direct and wide bandgap and high exciton binding energy. It is nontoxic, earth-abundant, and biocompatible. However, the growth and characterization of high-quality zno has been a challenge and bottleneck in its development. Efforts have been made to synthesize device-quality zinc oxide and unleash its potential for multiple advanced applications. Zno could be grown as thin films, nanostructures, or bulk, and its properties could be optimized by tuning the growth techniques, conditions, and doping. Zinc …
Plc Course Development, Leonard Hernandez, Jacqueline Grace Radding
Plc Course Development, Leonard Hernandez, Jacqueline Grace Radding
Electrical Engineering
The goal of this project is to design and construct the first lab experiment for the newly developed EE435 laboratory course. The experiment entails PLC programming to automate LED lighting in a simulated building. Starting with why PLCs are used, how to use the interface of EcoStruxure Control Expert V15.0 and practice using logic to control the dimming of a Light Emitting Diode (LED) to sustain a certain number of lumens consistent in a zone. Through the lab manual developed in this project, students will gain experience of creating logic designs using Function Block Diagram (FBD) and learn the layout …
Improvements Of Hybrid Ac/Dc House Prototype, Arden Abude
Improvements Of Hybrid Ac/Dc House Prototype, Arden Abude
Electrical Engineering
This is an iteration from previous designs of the Hybrid AC/DC House with a systematic addition of a portable AC power supply unit. This iteration for the Hybrid AC/DC House is an innovation of independence for sustainable housing solutions. It will serve as an alternative for rural communities needing power to rely on self-sustainable microgrids rather than large-scale AC electric grids. The addition of a portable AC power supply would allow the microgrid to remove its reliance on AC power from the larger grid and would elevate the system to complete energy independence. The microgrid has DC power generated from …
Small Unmanned Aircraft System Detection And Tracking With Audio, Computer Vision, And Deep Learning Techniques, Anthony C. Brunson
Small Unmanned Aircraft System Detection And Tracking With Audio, Computer Vision, And Deep Learning Techniques, Anthony C. Brunson
Theses and Dissertations
sUAS present significant risks to local and federal agencies when under the control of negligent, reckless, or criminal operators. In the face of an escalating presence of sUAS in shared airspace with traditional aircraft, and their deployment in protected airspace as potential weapons, safeguarding personnel, facilities, and assets becomes paramount. This research seeks to address this emerging threat by investigating the efficacy of integrating low-cost distributed sensors and Machine learning (ML) models to enhance battlespace awareness and complement existing sensing platforms for real-time sUAS detection, classification, and localization. The thesis introduces the conceptualization and development of a Drone Detection Command …
Assessing The Relationship Between The Quasi-Biennial Oscillation And D-Region Electron Density, Natalie R. Wirth
Assessing The Relationship Between The Quasi-Biennial Oscillation And D-Region Electron Density, Natalie R. Wirth
Theses and Dissertations
High frequency (HF) communication is a vital aspect of military communication and is highly reliant upon ionospheric conditions. The variation in electron density within the lowest echelon of the ionosphere, the D-region, can significantly impact HF signals, making communication inconsistent and unreliable for these wavelengths. Despite the D-region’s important, research in this area mainly focuses on understanding the impact of space weather anomalies on the upper ionosphere, particularly its higher layers, with relatively little exploration of the D-region. This region, situated closest to the troposphere and stratosphere, has been definitively linked to solar weather events like solar flares and geomagnetic …
The Effects Of A Non-Uniform Magnetic Field On Solar Cell Efficiency, Jason A. Burdette
The Effects Of A Non-Uniform Magnetic Field On Solar Cell Efficiency, Jason A. Burdette
Theses and Dissertations
Commercial-grade silicon-based solar cells have an efficiency in the 20-30% range. The addition of a non-uniform magnetic field manipulates the movement of charge carriers within the silicon of a solar cell. With this manipulation, one hypothesis is that the magnetic field increases the current produced by the solar cell which helps to increase the power and efficiency of the solar cell. Measuring a solar cell’s output current and voltage both with and without the presence of a non-uniform magnetic field tests this theory. Voltage multiplied by current gives output power, and to be calculated, efficiency needs maximum output power. The …
Reconstruction Of Radar Range Profiles Using Dropped Channel Polarimetric Compressive Sensing, Nat Thomason
Reconstruction Of Radar Range Profiles Using Dropped Channel Polarimetric Compressive Sensing, Nat Thomason
Theses and Dissertations
This thesis documents the design, construction and testing of a bench-top level measurement system and verifies previously established Dropped Channel Polarimetric Synthetic Aperture Radar Compressive Sensing (DCPCS) simulation results. Compressive Sensing is a mathematical technique which can capture and represent compressible signals at sampling rates significantly below the Nyquist rate. DCPCS is a technique which enhances Compressive Sensing techniques using known physical antenna crosstalk values. The DCPCS technique enables reconstruction of fully polarimetric signals whilst only measuring part of the signal, reducing data capture requirements.
Improving Rogue Radio Emitter Detection Using Siamese Networks, Mason Wright
Improving Rogue Radio Emitter Detection Using Siamese Networks, Mason Wright
Theses and Dissertations
Radio Frequency Fingerprinting (RFF) is the process of creating discerning signatures of emitted radio signals, most often with the goal of identifying specific devices again in the future. The security benefits of this task are intended to build upon current software-based authentication by making use of multi-factor authentication (MFA), but the related task of being able to reject unwanted emitters is limited. This paper presents a Siamese network trained on two different extracted fingerprints of raw Wi-Fi signals, along with a verifier to perform classification and rogue device detection. It was found that fingerprints using the Distortion Reconstruction (DR) technique …
Machine Learning Predictions Of Electricity Transfers Between Balancing Authorities In The Carolinas, Victoria Groleau
Machine Learning Predictions Of Electricity Transfers Between Balancing Authorities In The Carolinas, Victoria Groleau
Theses and Dissertations
Climate change through reduced streamflow, increased temperatures, and other factors impacts the efficiency of energy generation systems. The United States electric grid is comprised of a large network of balancing authorities engaged in trading electricity to maintain balance between supply and demand. The generation of electricity, a pivotal component of this balance, is impacted by climate change and weather variability as well as the growing demand for energy. Several hydro climatological factors such as streamflow, air temperature, and wind speed significantly influence the efficiency of power plant electricity generation. Due to the exchange of electricity between balancing authorities, impacts to …
Modeling Recovery Of The Florida Electric Transmission Grid After Severe Weather Event, Wei B. Guan
Modeling Recovery Of The Florida Electric Transmission Grid After Severe Weather Event, Wei B. Guan
Theses and Dissertations
Predicted changes to the climate are expected to increase the frequency and severity of extreme weather events. The Florida electric grid is a critical infrastructure system susceptible to severe weather events, especially hurricanes, causing widespread damage and outages. A foundational concept of the electric grid’s resilience is its ability to recover after extreme weather events, such as hurricanes and flooding. The recovery of the electrical grid after an extreme event is predicated upon the electrical asset's remoteness and the component's level of damage. Using fragility analysis, previous models have assessed the mean time to recover for transmission towers and substations …
Estimating Stimulated Raman Scattering Noise In Cwdm O-Band Channels Induced By Two Classical Dwdm Sources In A Quantum Network Fiber Segment, Kurt T. Spranger Ii
Estimating Stimulated Raman Scattering Noise In Cwdm O-Band Channels Induced By Two Classical Dwdm Sources In A Quantum Network Fiber Segment, Kurt T. Spranger Ii
Theses and Dissertations
The purpose of this research is to estimate the stimulated Raman scattering noise induced in CWDM O-band channels by two DWDM classical sources in a terrestrial quantum optical network containing classical and quantum optical signal coexistence in the same fiber segment. A use case is defined and analyzed which extracts a single fiber segment from a notional Bell state measurement found in a notional terrestrial quantum network. A stimulated Raman scattering noise model is employed in a Python simulation to estimate and rank-order the five O-band channels with the least amount of relative induced stimulated Raman scattering noise when given …
Analyzing The Effects Of Atmospheric Turbulence On Polarization-Entangled Photon Pairs Using Quantum State Tomography, Noah S. Everett
Analyzing The Effects Of Atmospheric Turbulence On Polarization-Entangled Photon Pairs Using Quantum State Tomography, Noah S. Everett
Theses and Dissertations
To help in building a quantum-based communication link, we experimentally designed a system to simulate atmospheric turbulence and characterize its effects on a polarization-entangled photon-pair source. The simulated turbulence is constructed using two afocal optical systems with a phase plate inserted in each to mimic both weak and strong atmospheric turbulence respectively. After propagation, quantum state tomography (QST) is performed on each pair to reconstruct the density matrix of the pair’s overall polarization state. In characterization of the simulated turbulence, we were able to reach strengths up to a D/r0 of 18.2, which begins to approach the strong turbulent regime. …
Generalized Characterization Of Biaxial Media Using Ultra-Wideband Multi-Static Focused Beam System With Polarimetric Calibration, Jeffrey P. Massman
Generalized Characterization Of Biaxial Media Using Ultra-Wideband Multi-Static Focused Beam System With Polarimetric Calibration, Jeffrey P. Massman
Theses and Dissertations
Novel metamaterial and metasurface realizations provide unique control of the electromagnetic wave dispersion but present many challenges for accurate constitutive parameter extraction. One measurement approach commonly employed is a freespace non-destructive focus beam system. Modern implementations are configured with multi-static dual-polarized capabilities for characterizing complex materials and offer many advantages by enabling ultra-wideband sampling, multiple measurement degrees of freedom and larger sample sizes. Practical electromagnetic material characterization of complex bianisotropic media requires the advancement of wave propagation analysis and calibration schemes. This research focuses on generalized biaxial media characterization and multi-static focused beam system metrology with polarimetric calibration schemes and …
Life Cycle Analysis Of Mobile Nuclear Reactor Compared To Other Alternative Fuels In Indopacom, Maria J. Hurtado
Life Cycle Analysis Of Mobile Nuclear Reactor Compared To Other Alternative Fuels In Indopacom, Maria J. Hurtado
Theses and Dissertations
Energy is an item that makes the military vulnerable as it is something that they depend on the most which can have negative impacts. Mobile nuclear reactors are gaining the interest of many leaders in the military as a viable option of a potential alternative fuel source. There are many positives in utilizing mobile nuclear reactors in terms of environmental impacts and feasibility of transport. Studies have shown that mobile nuclear reactors can produce very low or negligible carbon emissions during operations. The focus of this thesis is to determine the environmental impacts of nuclear reactors, logistical requirements, and determine …
Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen
Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen
Faculty Publications
It has been recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth’s anomaly magnetic field immersed in overwhelming complex signals for magnetic navigation in a GPS-denied environment. The accuracy of the detected anomaly field corresponds to a positioning accuracy in the range of 10–40 m. To increase the accuracy and reduce the uncertainty of weak signal detection as well as to directly obtain the position information, we exploit the machine-learning model of random forests that combines the output of multiple decision trees to give optimal values of the physical …
Deep Reinforcement Learning For Online Scheduling Of Photovoltaic Systems With Battery Energy Storage Systems, Yaze Li, Jingxian Wu, Yanjun Pan
Deep Reinforcement Learning For Online Scheduling Of Photovoltaic Systems With Battery Energy Storage Systems, Yaze Li, Jingxian Wu, Yanjun Pan
Electrical Engineering Faculty Publications and Presentations
A new online scheduling algorithm is proposed for photovoltaic (PV) systems with battery-assisted energy storage systems (BESS). The stochastic nature of renewable energy sources necessitates the employment of BESS to balance energy supplies and demands under uncertain weather conditions. The proposed online scheduling algorithm aims at minimizing the overall energy cost by performing actions such as load shifting and peak shaving through carefully scheduled BESS charging/discharging activities. The scheduling algorithm is developed by using deep deterministic policy gradient (DDPG), a deep reinforcement learning (DRL) algorithm that can deal with continuous state and action spaces. One of the main contributions of …
Electrical And Thermal Characterization Of (250 °C) Sic Power Module Integrated With Ltcc-Based Isolated Gate Driver, Salahaldein Ali Aboajila Ahmed, Pengyu Lai, Sudharsan Chinnaiyan, H. Alan Mantooth, Zhong Chen
Electrical And Thermal Characterization Of (250 °C) Sic Power Module Integrated With Ltcc-Based Isolated Gate Driver, Salahaldein Ali Aboajila Ahmed, Pengyu Lai, Sudharsan Chinnaiyan, H. Alan Mantooth, Zhong Chen
Electrical Engineering Faculty Publications and Presentations
The high-voltage SiC MOSFET power modules enable high-frequency and high-efficiency power conversion. The parasitic inductances induced by traditional packages of this device technology significantly deteriorate device switching performance, especially in high-temperature applications. In this paper, a novel low-cost discrete SMD component gate driver embedded in a SiC MOSFET power module is introduced. A newly integrated packaging structure has been introduced and proved to be efficient in reducing package-related turn-on loss and turn-off parasitic ringing. However, the gate propagation delay and optocoupler on-chip weak output signal in such a structure become limitations for further pushing the operating frequency and the output …
Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory, Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch
Analyzing Biomedical Datasets With Symbolic Tree Adaptive Resonance Theory, Sasha Petrenko, Daniel B. Hier, Mary A. Bone, Tayo Obafemi-Ajayi, Erik J. Timpson, William E. Marsh, Michael Speight, Donald C. Wunsch
Chemistry Faculty Research & Creative Works
Biomedical Datasets Distill Many Mechanisms Of Human Diseases, Linking Diseases To Genes And Phenotypes (Signs And Symptoms Of Disease), Genetic Mutations To Altered Protein Structures, And Altered Proteins To Changes In Molecular Functions And Biological Processes. It Is Desirable To Gain New Insights From These Data, Especially With Regard To The Uncovering Of Hierarchical Structures Relating Disease Variants. However, Analysis To This End Has Proven Difficult Due To The Complexity Of The Connections Between Multi-Categorical Symbolic Data. This Article Proposes Symbolic Tree Adaptive Resonance Theory (START), With Additional Supervised, Dual-Vigilance (DV-START), And Distributed Dual-Vigilance (DDV-START) Formulations, For The Clustering Of …
Pa2blo: Low-Power, Personalized Audio Badge, Hemanth Sabbella, Dulaj Sanjaya Weerakoon, Manoj Gulati, Archan Misra
Pa2blo: Low-Power, Personalized Audio Badge, Hemanth Sabbella, Dulaj Sanjaya Weerakoon, Manoj Gulati, Archan Misra
Research Collection School Of Computing and Information Systems
We present the hardware design and software pipeline for an ultra-low power device, in the form factor of a wearable badge, that supports energy efficient sensing, processing and wireless transfer of human voice commands and interactions. The proposed system, called PA2BLO, is envisioned to support both: (a) real-time, scalable, authorized voice based interaction and control of devices and appliances, and (b) longitudinal, low-power logging of natural voice interactions. PA2BLO in-troduces two key novel capabilities. First, it includes a low power, low-complexity voice authentication module that is able to reliably authenticate an authorized user only using low sampling rate (500 Hz) …
Investigation Of High-Latitude Gnss Radio Occulation Sporadic-E And Auroral-E Measurements, Kyle D. Roberts
Investigation Of High-Latitude Gnss Radio Occulation Sporadic-E And Auroral-E Measurements, Kyle D. Roberts
Theses and Dissertations
Abnormal sporadic-E (Es) occurrences were found in the high latitude regions during a recent climatology study by (Hodos, 2022), that calculated sporadic-E occurrence rates derived from a data set of GPS radio occultation (GPS-RO) and ionosondes. In this study, sporadic-E GNSS-RO techniques are shown to falsely attribute sporadic-E events to auroral-E (Ea) events. A comparative study is conducted on GPS-RO measurement techniques to find false occurrence rates for various RO techniques using a single ionosonde site in Gakona, Alaska. Phase-based RO techniques were found to be more likely to falsely attribute sporadic-E as auroral-E, while amplitude …
Accelerating Homomorphic Encryption In Risc-V Architectures With Hardware Based Number Theory Transform, Zachary Legg
Accelerating Homomorphic Encryption In Risc-V Architectures With Hardware Based Number Theory Transform, Zachary Legg
Theses and Dissertations
Fully Homomorphic Encryption is an encryption paradigm enabling computations on encrypted data without the need for decryption. Such behavior is promising for securing DoD cloud computing but is also computationally demanding. To alleviate some of the computational load and accelerate FHE schemes, this research proposes adding a hardware accelerator, for the Number Theory Transform (NTT) operation, to a RISC-V processor. Thus enhancing FHE capabilities for potentially resource-constrained devices.
Source Level Of Wind-Generated Ambient Sound In The Oceana, N. Ross Chapman, Michael Ainslie, Martin Siderius
Source Level Of Wind-Generated Ambient Sound In The Oceana, N. Ross Chapman, Michael Ainslie, Martin Siderius
Electrical and Computer Engineering Faculty Publications and Presentations
Inference of source levels for ambient ocean sound from local wind at the sea surface requires an assumption about the nature of the sound source. Depending upon the assumptions made about the nature of the sound source, whether monopole or dipole distributions, the estimated source levels from different research groups are different by several decibels over the frequency band 10–350 Hz. This paper revisits the research issues of source level of local wind-generated sound and shows that the differences in estimated source levels can be understood through a simple analysis of the source assumptions.
Analysis Of Countermeasures Against Remote And Local Power Side Channel Attacks Using Correlation Power Analysis, Aurelien Tchoupou Mozipo, John M. Acken
Analysis Of Countermeasures Against Remote And Local Power Side Channel Attacks Using Correlation Power Analysis, Aurelien Tchoupou Mozipo, John M. Acken
Electrical and Computer Engineering Faculty Publications and Presentations
Countermeasures and deterrents to power side-channel attacks targeting the alteration or scrambling of the power delivery network have been shown to be effective against local attacks where the malicious agent has physical access to the target system. However, remote attacks that capture the leaked information from within the IC power grid are shown herein to be nonetheless effective at uncovering the secret key in the presence of these countermeasures/deterrents. Theoretical studies and experimental analysis are carried out to define and quantify the impact of integrated voltage regulators, voltage noise injection, and integration of on-package decoupling capacitors for both remote and …