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Articles 1081 - 1110 of 16936
Full-Text Articles in Entire DC Network
Exploring Smart Thermostat, Don P. Dang
Exploring Smart Thermostat, Don P. Dang
2024 Fall Honors Capstone Projects - Archive
This study examines the security, privacy, and compatibility challenges associated with smart thermostats in smart home systems. Smart thermostats, as part of the growing Internet of Things (IoT) ecosystem, face vulnerabilities such as unauthorized access, data breaches, and inconsistent security protocols. Using a mixed-methods approach, this research evaluates encryption techniques, communication protocols (Zigbee, Z-Wave, Wi Fi), and user behaviors that impact system security and efficiency. Key findings indicate that 35% of users are concerned about hacking risks, while 25% express data privacy concerns. Many users lack awareness of security measures, such as firmware updates and password management, which increases vulnerabilities. …
Co-Emulation Of Robotics And Software-Defined Radio Based 5g Wireless Communications., Bhaskara Venkata Raju Garuda
Co-Emulation Of Robotics And Software-Defined Radio Based 5g Wireless Communications., Bhaskara Venkata Raju Garuda
Electronic Theses and Dissertations
The convergence of robotics and 5G wireless communication technologies has opened new avenues for real-time, dynamic robotic applications. This dissertation introduces a novel framework that integrates the Robot Operating System (ROS), Software-Defined Radios (SDRs), and 5G wireless networks to achieve seamless coemulation of robotic systems. The research emphasizes the unique features of 5G, such as ultra-low latency and high throughput, which enable critical applications like remote surgery, industrial automation, and autonomous vehicles. The methodology combines ROS for robotic control, SDRs for programmable communication channels, and 5G testbeds for high-speed, reliable data transmission. The experimental evaluation focuses on both position-based and …
Development Of A Subsurface Water Velocity And Quality Measurement Payload For Suas, Mitchell Bailey
Development Of A Subsurface Water Velocity And Quality Measurement Payload For Suas, Mitchell Bailey
All Graduate Theses and Dissertations, Fall 2023 to Present
Aquaculture farms, like oyster farms, often use outdated techniques to measure the quality of their waters. These techniques are often stationary or are deployed by an operator who may struggle to reach a location depending on conditions like the presence of a storm or low tide. This creates data sets with gaps over time and across the area of the farm, meaning the data cannot be used to model the standard farm conditions. An Uncrewed Aerial System (UAS) payload is developed in this paper that is capable of measuring depth-velocity profiles through the use of a tethered velocity sensor. The …
Spectrum Optimization For Advanced Air Mobility Communications Using Deep Reinforcement Learning., Rafael D. Apaza
Spectrum Optimization For Advanced Air Mobility Communications Using Deep Reinforcement Learning., Rafael D. Apaza
Electronic Theses and Dissertations
As aviation operations expand and new participants enter the National Airspace System (NAS), the demand for aeronautical communications will experience a significant rise. This surge is propelled by increased air travel and the emergence of Urban Air Mobility (UAM) operations, a subset of Advanced Air Mobility (AAM). UAM aims to facilitate intra-city transportation of people and cargo utilizing remotely piloted aircraft capable of electric vertical takeoff and landing operations. The growing dependence on efficient wireless communication systems underscores the critical importance of intelligent spectrum allocation and effective airspace management to ensure safe, seamless, and technologically advanced air operations. However, the …
Open-Source Cubesat Flight Board, Braydon M. Burkhardt
Open-Source Cubesat Flight Board, Braydon M. Burkhardt
Electrical Engineering
The Helmsman Flight Board is an open-source main flight computer and electrical power system for educational and entry-level CubeSats. The board incorporates commercial off-the-shelf (COTS) components in conjunction with simplified monitoring and management circuitry, supporting easy adoption, modifiability, and affordability while crucially enabling the emerging aerospace industry’s rapid ‘design-build-test’ methodology in student satellite teams. Its design includes essential CubeSat subsystems such as battery management, command and data handling, attitude determination, on-board processing, and is built to support real-time embedded operating systems. Key features include an Arm Cortex-M7 based STM32, radiation-resistant memory for OS storage, bulk Flash memory, real-time clock, two …
Dual-Channel Side Channel Attack: Improved Aes Key Decryption By Combining Power And Electromagnetic Side Channels With Convolutional Neural Networks, Sean P. O'Neill
Dual-Channel Side Channel Attack: Improved Aes Key Decryption By Combining Power And Electromagnetic Side Channels With Convolutional Neural Networks, Sean P. O'Neill
Theses and Dissertations
This research introduces a novel DL approach for SCA that combines power consumption and EM signals to enhance encryption key deduction by leveraging a dual-channel CNN architecture. A new dataset, consisting of simultaneous power and EM signal collections during 128-bitAES encryption, was developed to train and evaluate the model’s effectiveness. The combined approach achieved an 88% reduction in traces needed, from 50 traces to 6, for encryption key classification, outperforming traditional methods such as random forest, DPA, DEMA,and individual side channel CNN models. These findings highlight the potential of integrating multiple side channels in SCA to improve performance without the …
Nanostructured Silicon Meta-Waveguides And Surfaces For Enhanced Light-Matter Interaction, Saddam Gafsi
Nanostructured Silicon Meta-Waveguides And Surfaces For Enhanced Light-Matter Interaction, Saddam Gafsi
All Dissertations
In this study, we tackle the challenge of light-matter interaction engineering and local field enhancement using various silicon photonic platforms based on three different approaches. (i) The first approach is based on boundary condition engineering where we present and show through simulation and experimental results, a silicon nanodisk “diabolo” configuration able to support significant local field enhancement levels in the range ~102 to 104 in the high index medium through proper structural modifications at the nanoscale. We show that the presented optical behavior is consistent with the anapole modes characterized by the observed near-field enhancement and coinciding with far-field suppression. …
Security Of Mobile Radiological Sources: Overview Of Industry Applied Technologies, Ann M. Archer, Ashleigh Wickham
Security Of Mobile Radiological Sources: Overview Of Industry Applied Technologies, Ann M. Archer, Ashleigh Wickham
International Journal of Nuclear Security
Small radiological sources used in industrial settings recurrently require transit between job sites. Securing these sources, while stationary, can be addressed with standard security approaches and equipment. Transport of these sources increases the risk and complexity of managing and maintaining control of these sources. Implementing methodologies to securely monitor and locate sources improves response and resolution of anomalous events during transit. The Mobile Source Transit Security (MSTS) system was developed to improve security and provide situational awareness of these mobile sources throughout their job cycle. The MSTS development effort focused on creating a set of systems that could be successfully …
Enhancing Home Energy Efficiency: Web And Cloud Integration For Sustainable Electricity Monitoring, Kyle Aaron Coloma, King Harold A. Recto
Enhancing Home Energy Efficiency: Web And Cloud Integration For Sustainable Electricity Monitoring, Kyle Aaron Coloma, King Harold A. Recto
Electronics, Computer, and Communications Engineering Faculty Publications
This paper demonstrates how sustainability can be integrated to technology by developing a cloud-based web application that monitors the use of energy in a residential setting. In the development of the minimum viable product (MVP), frontend tools were utilized to ensure that the platform runs on most types of devices. Moreover, backend tools were also used to ascertain efficient handling of data while maintaining security for the users. The project which has guaranteed fundamental functionality and a measure of security has been deployed successfully for early users. For future improvements, it is recommended to prioritize the optimization of user interface …
Ellipticity-Controlled Exceptional Points From Nanoscale Metasurfaces, Benjamin Goldberg
Ellipticity-Controlled Exceptional Points From Nanoscale Metasurfaces, Benjamin Goldberg
McKelvey School of Engineering Graduate Student Theses & Dissertations
Precise control over light polarization is critical for advancing technologies in telecommunica- tions, quantum computing, and image sensing. However, existing methods for manipulating polarization around exceptional points in non-Hermitian systems, have exclusively focused on circular polarization and work with reflected light. To address this limitation, we de- velop a novel metasurface platform with high-Q resonators that enables tunable control of polarization exceptional points across arbitrary ellipticity for transmitted light. Our design uses orthogonally polarized guided mode resonators in a two-layer silicon metasurface, where careful tuning of the dipolar guided mode resonances (DGMRs) and layer spacing allows us to control the …
Constructing Qur’An Recitation Classification Using Alexnet Algorithm, Harits Ar Rosyid, Dzulkifli Abdullah, Mohammed S. Alqahtani
Constructing Qur’An Recitation Classification Using Alexnet Algorithm, Harits Ar Rosyid, Dzulkifli Abdullah, Mohammed S. Alqahtani
Knowledge Engineering and Data Science
The growing demands for accurate and efficient methods in the Qur'an recitation classification highlight the limitations of existing models, particularly in assisting the memorization process. This study aims to address these challenges by implementing the AlexNet Convolutional Neural Network architecture, widely recognized for its effectiveness in image classification, to classify the Qur'an recitations using the Mel Frequency Cepstral Coefficient (MFCC) as the feature extraction method. The research involves several stages, including data collection, preprocessing (audio segmentation by verse), data augmentation, feature extraction, and classification using the AlexNet architecture, followed by performance evaluation. Key results demonstrate that the combination of MFCC …
Low-Cost Vehicle Controller Testing System, Kevin R. Jung
Low-Cost Vehicle Controller Testing System, Kevin R. Jung
Electrical Engineering
This project aims to create a system to facilitate easier evaluation of PCBs designed for low-voltage vehicle applications with an emphasis on accessibility for student teams in collegiate design series' such as Formula SAE. Student teams or smaller vehicle electronics manufacturers often need to verify designs and validate functionality during both development and manufacturing. An inexpensive, small, and portable, yet capable, system for taking measurements and simulating inputs would allow designers to put their boards into vehicle-representative conditions and environments without needing to connect to actual vehicle hardware. Additionally, while systems exist off-the-shelf that could fulfill the requirements needed by …
Building Energy Management: A Data-Driven Approach Using Clustering And Load Forecasting, Aviral Kandel
Building Energy Management: A Data-Driven Approach Using Clustering And Load Forecasting, Aviral Kandel
LSU New Orleans Theses and Dissertations
The increase of smart meters in the grid has led to the generation of a vast amount of high dimensional energy data with improving temporal resolution. During analysis, relying on short samples like a day or week of data, could lead to wrong conclusion due to seasonal dynamics and customer behavior variations. To effectively utilize the vast amount of information, it must be compressed into a low-dimensional representation. This thesis explores the state-of-the-art dimensionality reduction techniques for a high-dimensional, non-linear energy dataset and proposes a novel deep learning based method to address the limitation of existing approaches. The proposed method …
Alteration Of Peripheral Cytokines In Alzheimer’S Disease, Zhengshi Yang
Alteration Of Peripheral Cytokines In Alzheimer’S Disease, Zhengshi Yang
UNLV Theses, Dissertations, Professional Papers, and Capstones
Alzheimer’s disease (AD) is a progressive neurodegenerative disease with the clinical symptoms of gradual cognitive decline and memory loss. Biologically, abnormal accumulation of Aβ (Aβ) plaque and tau tangles in the brain are the core pathological hallmarks in AD. Although inflammatory response is not specific to AD, emerging evidence suggests that the disrupted innate immune system within the central nervous system, particularly microglial activation, might act as the bridge linking Aβ aggregation to pathological phosphorylation and aggregation of tau. The inflammatory response was suggested to initially have a neuroprotective role of attempting to clear Aβ plaques, and then become neurotoxic …
Clusteredlog: Optimizing Log Structures For Efficient Data Recovery And Integrity Management In Database Systems, Mariha Siddika Ahmad, Brajendra Panda
Clusteredlog: Optimizing Log Structures For Efficient Data Recovery And Integrity Management In Database Systems, Mariha Siddika Ahmad, Brajendra Panda
Electrical Engineering and Computer Science Faculty Publications and Presentations
In modern database systems, efficient log management is crucial for ensuring data integrity and facilitating swift recovery from potential data corruption or system failures. Traditional log structures, which store operations sequentially as they occur, often lead to significant delays in accessing and recovering specific data objects due to their scattered nature across the log. ClusteredLog addresses the limitations of traditional logging methods by implementing a novel logical organization of log entries. Instead of simply storing operations sequentially, it groups related operations for each data item into clusters. As a result, ClusteredLog enables faster identification and recovery of damaged data items …
Synthesis Of Binary-Input Multi-Valued Output Optical Cascades For Reversible And Quantum Technologies, Ishani Agarwal, Miroslav Saraivanov, Marek Perkowski
Synthesis Of Binary-Input Multi-Valued Output Optical Cascades For Reversible And Quantum Technologies, Ishani Agarwal, Miroslav Saraivanov, Marek Perkowski
Electrical and Computer Engineering Faculty Publications and Presentations
This paper extends the decomposition from the group theory based methods of Sasao and Saraivanov to design binary input multivalued output quantum cascades realized with optical NOT, SWAP, and Fredkin Gates. We present this method for 3, 5, and 7 valued outputs, but in general it can be used for odd prime valued outputs. The method can be extended to realize hybrid functions with different valued outputs. A class of local transformations is presented that can simplify the final cascade circuits. Using these simplifying transformations, we present an upper bound on the maximum number of gates in an arbitrary -variable …
Feasibility Study On Microwave Glucose Level Monitoring, Ricardo Cepeda
Feasibility Study On Microwave Glucose Level Monitoring, Ricardo Cepeda
Theses and Dissertations
Diabetes management heavily relies on regular blood glucose monitoring, which traditionally involves invasive techniques. In recent years, significant research has been directed towards developing non-invasive glucose monitoring methods, particularly using electromagnetic waves. This study explores the feasibility of detecting blood glucose levels non-invasively by measuring the resonant frequency shifts of an antenna, influenced by the dielectric properties of blood. Microwave measurement techniques have garnered attention due to their ability to safely penetrate human tissue and detect biochemical markers like glucose. While previous studies have established a link between glucose concentration and dielectric properties, many techniques suffer from poor sensitivity or …
Enhancing Webtas: From An Atam Simulator To A Developmental Environment, Elizabeth G. Schmidt
Enhancing Webtas: From An Atam Simulator To A Developmental Environment, Elizabeth G. Schmidt
Electrical Engineering and Computer Science Undergraduate Honors Theses
As interest in a niche research area, like the abstract Tile Assembly Model (aTAM), grows it is crucial to ensure that simulation tools are accessible and user-friendly for a broad audience. Existing resources can pose challenges for less experienced users, highlighting the need for enhancements that improve usability and functionality. To address these issues, key upgrades to the current online simulation platform, WebTAS, were implemented, including breakpoint functionality and nondeterminism checks, alongside features such as XML file integration, image capturing, and simulation view resets. These enhancements collectively elevate the platform from a basic learning tool to a comprehensive environment for …
Leveraging P4 Programmable-Hardware Switches For In-Network Pmu Packet Recovery, Evan Michael Bonar
Leveraging P4 Programmable-Hardware Switches For In-Network Pmu Packet Recovery, Evan Michael Bonar
Electrical Engineering and Computer Science Undergraduate Honors Theses
Phasor Measurement Unit (PMU) systems are essential for real-time power grid monitor- ing but often face data loss due to network delays, equipment malfunctions, or transmis- sion errors. Traditional centralized recovery solutions introduce significant latency and scalability challenges. This thesis presents a P4-based in-network recovery mechanism that embeds detection and recovery directly into the data plane of P4-enabled programmable switches, significantly reducing recovery time and infrastructure complexity. Using the Aurora 610 switch, the system detects missing packets via sequence number analysis and recovers magnitudes with an efficient register-based algorithm.
Evaluation demonstrates high accuracy and low latency, achieving a mean absolute …
Practical And Lightweight Defense Against Website Fingerprinting, Colman Mcguan, Chansu Yu, Kyoungwon Suh
Practical And Lightweight Defense Against Website Fingerprinting, Colman Mcguan, Chansu Yu, Kyoungwon Suh
Electrical and Computer Engineering Faculty Publications
Website fingerprinting is a passive network traffic analysis technique that enables an adversary to identify the website visited by a user despite encryption and the use of privacy services such as Tor. Several website fingerprinting defenses built on top of Tor have been proposed to guarantee a user's privacy by concealing trace features that are important to classification. However, some of the best defenses incur a high bandwidth and/or latency overhead. To combat this, new defenses have sought to be both lightweight - i.e., introduce a small amount of bandwidth overhead - and zero-delay to real network traffic. This work …
Three-Dimensional Environmentally Sustainable Neuromorphic Computing System Based On Natural Organic Memristor, Mohammed Rafeeq Khan
Three-Dimensional Environmentally Sustainable Neuromorphic Computing System Based On Natural Organic Memristor, Mohammed Rafeeq Khan
Graduate Theses and Dissertations (2019 - present)
A three-dimensional neuromorphic (3D) computing architecture based on environmentally sustainable natural organic honey memristors is proposed in this thesis. A set of comprehensive and experimental results indicate that the proposed systems exhibit remarkable inference accuracy, consistently surpassing the 90% threshold, even with different challenges such as device variations and nonlinearity. This study also considers four different conductance drift situations, the effects of analog-to-digital converter (ADC) quantization, and multiple algorithms, such as VGG8 and DenseNet-40. The deliverable of this thesis will test the stability of the proposed systems and explore their potential applications and scalability in real-world situations.
Uncovering The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Michelle Lara
Uncovering The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Michelle Lara
Open Access Theses & Dissertations
This thesis evaluates the effectiveness of the Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm under varying network load conditions. Repeated simulation experiments using Mininet were conducted for four different network-wide load levels: 100 Mbps, 500 Mbps, 1 Gbps, and 5 Gbps. Using statistical inference, our experimental results indicate that NLOF: MLL is ineffective under light load conditions (i.e., 100Mbps load) due to the limited network flow data available for its learning process. This limitation highlights a key challenge in applying the algorithm to lightly loaded networks. A preliminary algorithm was proposed to address this light-load performance …
Dynamic Optimization Of Directed Energy Deposition Build Conditions Using Real-Time Monitoring Via Closed-Loop Control, Callan Herberger
Dynamic Optimization Of Directed Energy Deposition Build Conditions Using Real-Time Monitoring Via Closed-Loop Control, Callan Herberger
Open Access Theses & Dissertations
Directed Energy Deposition (DED) is an additive manufacturing process that is being rapidly adopted by industry and is well suited for the fabrication of complex components in various metal alloys. DED provides unique benefits such as design flexibility, the potential for in-situ alloying, and an open environment that allows for unobstructed monitoring within the build chamber. Despite these benefits, fully exploiting additive manufacturing's (AM) potential remains a complex task for designers. This dissertation presents a framework for controlling Directed Energy Deposition process variables through in-situ monitoring. An exploration into modifying AM build conditions through the development and implementation of a …
Chipless 3d Microfluidic Rf Sensing, Sheikh Dobir Hossain
Chipless 3d Microfluidic Rf Sensing, Sheikh Dobir Hossain
Open Access Theses & Dissertations
Effective management of the cold chain is essential to uphold the quality and safety of products vulnerability to physical factors like temperature, humidity, pressure, etc., including perishable foods, pharmaceuticals, and vaccines. Chipless Radio Frequency Identification (RFID) sensors have become increasingly favored as a viable technology for tracking, inventory, and sensing industries due to their wireless and non-line of sight (NLOS) situations, straightforward fabrication, cost efficiency, and adaptability to challenging environmental conditions. However, there is still a need for advancements in RFID sensors to make them promise for cold chain applications. Integration of flexibility and non-volatile memory into the existing RFID …
An Overview Of Planning For Vehicle-To-Grid Systems With Large-Scale Adoption Of Electric Vehicles, Fazel Mohammadi, Mahmood Mirhashemi
An Overview Of Planning For Vehicle-To-Grid Systems With Large-Scale Adoption Of Electric Vehicles, Fazel Mohammadi, Mahmood Mirhashemi
Electrical & Computer Engineering and Computer Science Faculty Publications
The rapid adoption of Electric Vehicles (EVs) has the potential to transform energy infrastructure worldwide. Vehicle-to-Grid (V2G) systems, which enable bidirectional energy flow between EVs and power grids, offer a promising solution for balancing electricity demand, supporting renewable energy integration, and enhancing the resilience of power grids. This paper explores different strategic planning considerations necessary for the large-scale adoption of V2G-enabled EVs, aiming to support a more resilient and sustainable energy infrastructure.
Hardware Applications Of High-Speed Fault Detection Algorithms, Daniel Zintsmaster
Hardware Applications Of High-Speed Fault Detection Algorithms, Daniel Zintsmaster
All Theses
The growing need for a sustainable electric energy infrastructure has driven research into control, protection, and optimization of power systems. A key challenge is that the changing grid must operate at increasingly higher speeds, but many current hardware devices cannot meet these demands. This thesis focuses on power system protection, aiming to design a hardware solution that can detect and isolate faults in microseconds, ensuring faster, more reliable grid operations. The first hardware developed was for a low-voltage direct current (LVdc) microgrid, which faces challenges due to a lack of protection schemes and novel speed requirements. This thesis presents protection …
Higher Order Bessel Beams Integrated In Time (Hobbit) With Engineered Light Frequencies And Applications In Computational Imaging, Tyler Cramer
All Theses
This thesis presents an adaptive optical system which leverages the frequency shifts from an acousto-optic deflector (AOD) form an array of uniformly spaced frequency diverse beamlets. These beamlets are then spatially transformed (wrapped) into a circular array forming a non-diffracting ring with an unprecedented orbital angular momentum (OAM) mode switching rate of 50Mhz with an OAM range of ±64. Along with frequency diversity, the non-diffracting range of the beams are analyzed 6 Rayleigh ranges of an equivalently sized gaussian beam. Inherent in the frequencies superposed on the AOD are associated relative phases which can be controlled to form sets of …
Control Of X-Delta Arm And Self-Leveling Robot Systems For Uav Applications, Prathibha Sobha
Control Of X-Delta Arm And Self-Leveling Robot Systems For Uav Applications, Prathibha Sobha
UNLV Theses, Dissertations, Professional Papers, and Capstones
The water droplet penetration test (WDPT) is an environmental assessment method for analyzing soil properties by measuring the penetration of water droplets into soil. This test provides insights into soil moisture retention and resilience, especially valuable in fire-prone or arid regions where soil recovery and erosion control are essential. Although this project does not conduct an actual WDPT, it investigates two key robotic systems designed to support such applications: an X-delta robot arm, which simulates precise droplet delivery patterns, and a self-leveling platform that ensures stability on uneven terrain, where the X-delta robot is mounted. Together, these systems examine the …
Mathematical Model For Helically Propagating Spatially Multiplexed Mimo Channels Inside Single Core Optical Fibers, Ibrahim Barka
Mathematical Model For Helically Propagating Spatially Multiplexed Mimo Channels Inside Single Core Optical Fibers, Ibrahim Barka
Theses and Dissertations
It all started when our curiosity was sparked by observing light beams from a Multi-Channel Laser Source precisely coupled into a single-core optical fiber positioned on an optical bench in the lab. The multiplexed light beams, characterized by different spatial azimuthal angles, were guided by the fiber, tracing helical paths and producing a bright central spot with concentric rings depending on the launched angles, a phenomenon we came to call Spatial Domain Multiplexing (SDM). Conventional concepts of hybrid and LP modes couldn’t fully explain the behavior of SDM modes, leading us to the question of the types of field configurations …
Debtor Eligibility Prediction Using Deep Learning With Chatbot-Based Testing, Reski Noviania, Enny Itje Sela, Luther Alexander Latumakulita, Steven R. Sentinuwo
Debtor Eligibility Prediction Using Deep Learning With Chatbot-Based Testing, Reski Noviania, Enny Itje Sela, Luther Alexander Latumakulita, Steven R. Sentinuwo
Knowledge Engineering and Data Science
Predicting debtor eligibility is essential for effective risk management and minimizing lousy credit risks. However, financial institutions face challenges such as imbalanced data, inefficient feature selection, and limited user accessibility. This study combines Recursive Feature Elimination (RFE) and Deep Learning (DL) to improve prediction accuracy. It integrates a chatbot interface for user-friendly testing. RFE effectively identifies critical features, while the DL model achieves a validation accuracy of 97.62%, surpassing previous studies with less comprehensive methodologies. The chatbot's novel design not only ensures accessibility but also enhances user engagement through flexible input options, such as approximate values, enabling non experts to …