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Articles 2071 - 2100 of 37177

Full-Text Articles in Electrical and Computer Engineering

3d Printing Metal Horn Antennas Using Periodic And Aperiodic Perforated Designs For Directed Energy Applications, Alexis Valencia Jan 2025

3d Printing Metal Horn Antennas Using Periodic And Aperiodic Perforated Designs For Directed Energy Applications, Alexis Valencia

Open Access Theses & Dissertations

In the past decade, Additive Manufacturing (AM) has proven to be groundbreaking yet reliable technology. Not only has it revolutionized the way we approach problems in research, design, and production but it has enabled burgeoning discoveries and methods due to the technologyâ??s efficiency, speed, and low manufacturing cost. One area that benefits greatly from this includes radio frequency (RF) devices like horn antennas. At the moment, most horn antennas produced by conventional manufacturing are expensive, heavy, and limited in customization, yet they are necessary for various systems like satellite communication, radar, radio astronomy, and more. 3D printing technology would alleviate …

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Flame Boundary Effects Of Hydrogen-Air Premixing, Alecson L. De Lima Junior Jan 2025

Flame Boundary Effects Of Hydrogen-Air Premixing, Alecson L. De Lima Junior

Honors Undergraduate Theses

The objective of this research was to investigate the reaction of hydrogen and heated air premixing when injected into a combusting ethylene-air crossflow, and to study the flame stabilization location with varying premixing levels. The main parameter of this investigation was the flame stabilization diagnosed through chemiluminescence, based on recorded equivalence ratio, temperature, and flame boundaries, and maintaining a constant air temperature, hydrogen and air mass flow, and momentum flux ratios. Testing was conducted at different ratios of hydrogen and air premixing achieved through alternating the distance between the point where hydrogen and air are mixed and the combusting crossflow. …

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Advanced Nanocomposite-Based Electrochemical Sensor For Ultra-Sensitive Dopamine Detection In Physiological Fluids, Megha Shinde, Gymama Slaughter Jan 2025

Advanced Nanocomposite-Based Electrochemical Sensor For Ultra-Sensitive Dopamine Detection In Physiological Fluids, Megha Shinde, Gymama Slaughter

Center for Bioelectronics Publications

This study presents a novel point-of-care electrochemical sensor for dopamine (DA) detection, featuring a flexible laser-induced graphene (LIG) modified with a unique nanocomposite comprising Nb4C3Tx MXene, polypyrrole (PPy), and iron nanoparticles (FeNPs). The LIG-Nb4C3Tx MXene-PPy-FeNPs is characterized by scanning electron microscopy to confirm the successful surface modification. The electrochemical performance of the fabricated sensor via cyclic voltammetry showed significant electrochemical activity upon Nb4C3Tx MXene-PPy-FeNPs nanocomposite modification of the LIG surface with an increased peak anodic current (Ipa) from 43 μA to 104 μA. The sensor …

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Laser-Induced Graphene For Early Disease Detection: A Review, Sri Ramulu Torati, Gymama Slaughter Jan 2025

Laser-Induced Graphene For Early Disease Detection: A Review, Sri Ramulu Torati, Gymama Slaughter

Center for Bioelectronics Publications

Electrochemical biosensors have been instrumental in early disease detection, facilitating effective monitoring and treatment. The emergence of graphene has significantly advanced sensor technology in various fields, including biomedicine, electronics, and energy. In this landscape, laser‐induced graphene (LIG) has emerged as a superior alternative to conventional graphene synthesis methods. Its straightforward fabrication process and compatibility with wearable devices boost its practicality and potential for real‐world applications. This review highlights the transformative potential of LIG in biosensing, showcasing its contributions to the development of next‐generation diagnostic tools for early disease detection. An overview of the LIG synthesis process and its applications in …

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Fabrication Of Thylakoid Membrane-Based Photo-Bioelectrochemical Bioanode For Self-Powered Light-Driven Electronics, Amit Sarode, Gymama Slaughter Jan 2025

Fabrication Of Thylakoid Membrane-Based Photo-Bioelectrochemical Bioanode For Self-Powered Light-Driven Electronics, Amit Sarode, Gymama Slaughter

Center for Bioelectronics Publications

The transition toward sustainable and decentralized energy solutions necessitates the development of innovative bioelectronic systems capable of harvesting and converting renewable energy. Here, we present a novel photo-bioelectrochemical fuel cell architecture based on a biohybrid anode integrating laser-induced graphene (LIG), poly(3,4-ethylenedioxythiophene) (PEDOT), and isolated thylakoid membranes. LIG provided a porous, conductive scaffold, while PEDOT enhanced electrode compatibility, electrical conductivity, and operational stability. Compared to MXene-based systems that involve complex, multi-step synthesis, PEDOT offers a cost-effective and scalable alternative for bioelectrode fabrication. Thylakoid membranes were immobilized onto the PEDOT-modified LIG surface to enable light-driven electron generation. Electrochemical characterization revealed enhanced redox …

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Safe Data-Enabled Control Of Human-In-The-Loop Robotic Manipulator Systems, Ritirupa Dey, Avimanyu Sahoo, Vignesh Narayanan Jan 2025

Safe Data-Enabled Control Of Human-In-The-Loop Robotic Manipulator Systems, Ritirupa Dey, Avimanyu Sahoo, Vignesh Narayanan

Publications

Safe control of human-in-the-loop (HIL) robotic manipulators is critical for applications such as assistive robotics, teleoperation in hazardous environments, and collaborative manufacturing. However, this remains challenging due to the lack of a unified framework that simultaneously addresses safety constraints, external disturbances, unmodeled dynamics, and dynamic role switching in the HIL setting. In this paper, we propose a novel NN-driven HIL control framework in which human–robot dyadic interaction occurs through the haptic channel. Using Lyapunov stability analysis, we theoretically show that the proposed NN-based controller ensures accurate joint trajectory tracking, compensates for system uncertainties, and adapts to human inputs modeled as …

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Ai-Generated Messaging For Life Events Using Structured Prompts: A Comparative Study Of Gpt With Human Experts And Machine Learning, Christopher Lynch, Erik Jensen, Ross Gore, Virginia Zamponi, Kevin O'Brien, Brandon Feldhaus, Katherine Smith, Joseph Martínez, Madison H. Munro, Timur E. Ozkose, Tugce B. Gundogdu, Ann Marie Reinhold, Hamdi Kavak, Barry Ezell Jan 2025

Ai-Generated Messaging For Life Events Using Structured Prompts: A Comparative Study Of Gpt With Human Experts And Machine Learning, Christopher Lynch, Erik Jensen, Ross Gore, Virginia Zamponi, Kevin O'Brien, Brandon Feldhaus, Katherine Smith, Joseph Martínez, Madison H. Munro, Timur E. Ozkose, Tugce B. Gundogdu, Ann Marie Reinhold, Hamdi Kavak, Barry Ezell

VMASC Publications

Large Language Models (LLMs) play an increasingly integrated and pivotal role in generating diverse types of texts, such as social media messages, emails, narratives, and technical reports, among other textual communication forms. As AI-generated messaging filters into human communication, a systematic exploration of their effectiveness for mimicking human-like communication of life events is needed. In this study, we employ a zero-shot structured narrative prompt to generate 24,000 life event messages for birth, death, hiring, and firing events using OpenAI's GPT-4. From this dataset, we manually classify 2880 messages and evaluate their validity in conveying these life events through the form …

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Electronics Hardware Assembly And Pcb Design For Lv3.1 Rocket And Cubesat Systems, Shaelin Olton Jan 2025

Electronics Hardware Assembly And Pcb Design For Lv3.1 Rocket And Cubesat Systems, Shaelin Olton

Maseeh Summer Undergraduate Research Experience

The Portland State Aerospace Society (PSAS) develops open-source rockets and CubeSats for research and education. This work involved electronics projects across multiple active systems, from assembling hardware for the LV3.1 rocket to redesigning PCBs for CubeSat testing equipment and lab instruments. The Roll Control System (RCS) boards for LV3.1 were populated using surface-mount technology (SMT) assembly techniques. The Card Debug Board was redesigned to troubleshoot various cards within the "flat-sat" engineering model of the most recent CubeSat iteration. This work involved assembling the electronics hardware for LV3.1, the most recent rocket model in development. Much of the initial work focused …

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Lv 3.1, Jacob Lutz Jan 2025

Lv 3.1, Jacob Lutz

Maseeh Summer Undergraduate Research Experience

The LV 3 rocket was designed over a number of years with a variety of different modules. There does not exhist a full integrated system. In this work, I worked to combine a number of the modules to have a more complete rocket.

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Zephyr Rtos Integration On The Nxp Mcxn947 For Oresat Programming, Blen Ermias Jan 2025

Zephyr Rtos Integration On The Nxp Mcxn947 For Oresat Programming, Blen Ermias

Maseeh Summer Undergraduate Research Experience

The objective of this work is to implement and test the Zephyr RTOS on the NXP MCXN947 board with debugger support, then integrate the MCU into OreSat protocards to program and develop applications for OreSat1. Zephyr is a Soft real time operating system, open-source, designed for embedded devices. OreSat is a fully open-source CubeSat project. A CubeSat is a standardized, modular satellite with a compact box-shaped design. The basic unit, called a 1U CubeSat, measure 10 x 10 x 10 cm. Zephyr RTOS can be utilized to program and debug this board. A board directory for the breakout board has …

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Zephyr Rtos On Nxp Mcxn947 For Oresat Protocards: Bring-Up, Drivers, And Debug, Las Meman Jan 2025

Zephyr Rtos On Nxp Mcxn947 For Oresat Protocards: Bring-Up, Drivers, And Debug, Las Meman

Maseeh Summer Undergraduate Research Experience

OreSat Project: Oregon’s first student-built satellite, designed as a CubeSat (10×10×10 cm) to make space research more accessible and affordable. Why it matters: CubeSats let students and researchers test new technology in space at a fraction of the cost of traditional satellites. Our challenge: To prepare OreSat for future missions, we need reliable software and hardware that can run on small, low-power computers. Our solution: Use Zephyr RTOS (an open-source operating system for microcontrollers) with the new NXP MCXN947 board to test and build satellite applications. (Transitioning from the STM32F091 that has ChibiOS) Goal: Bring up and test the Zephyr …

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Modeling Residential Water Heater Usage With Ochre, Josephine Deline Jan 2025

Modeling Residential Water Heater Usage With Ochre, Josephine Deline

Maseeh Summer Undergraduate Research Experience

Energy Demand and Flexible Loads U.S. electricity use is projected to rise in 2025–2026 after years of little growth, according to the U.S. Energy Information Administration (EIA). Residential water heaters (WHs) can serve as flexible loads by shifting use to off-peak times. CTA-2045 The CTA-2045 protocol allows utilities to coordinate with WHs, signaling optimal operation without sacrificing comfort or performance. The OCHRE model, developed by NREL, simulates household energy use and appliance behavior. OCHRE shows how flexible WH loads can improve grid stability and lower consumer costs. The goal is to compare simulated results with field test data to validate …

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Development Of 2d Microfluidics Surface With Low-Frequency Electric Fields For Cell Separation Applications, Madushan Wickramasinghe, Dharmakeerthi Nawarathna Jan 2025

Development Of 2d Microfluidics Surface With Low-Frequency Electric Fields For Cell Separation Applications, Madushan Wickramasinghe, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell separation techniques are widely used in many biomedical and clinical applications for the development of screening, diagnosis and therapeutic tests. Current 3D microfluidics-based cell separation methods have limited applications in part due to low throughput and technical complexity. To address these critical needs, we have developed a 2D microfluidics surface which is the miniaturized version of a 3D microfluids cell separation device. Using low-frequency electric fields (1–10 Vpp and 1 kHz–20 MHz), we have first studied dielectrophoresis, AC electro-osmosis and capillary flow within a sessile drop, and finally utilized the results to develop the 2D cell separation surface. Our …

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Modeling Strain And Quantum Confinement In Gaas/GaXIn1-XP Superlattices For Spin-Polarized Electron Sources, A. Kachwala, G. Blume, S. Marsillac, J. Grames, M. Grau Jan 2025

Modeling Strain And Quantum Confinement In Gaas/GaXIn1-XP Superlattices For Spin-Polarized Electron Sources, A. Kachwala, G. Blume, S. Marsillac, J. Grames, M. Grau

Physics Faculty Publications

In this study, we systematically design and simulate a series of GaAs-based superlattice configurations aimed at enhancing heavy-hole–light-hole band splitting while simultaneously optimizing band alignment to reduce the conduction band barrier, thereby facilitating efficient electron transport. These combined effects are crucial for achieving high electron spin polarization and high quantum efficiency, the two key performance metrics of next-generation spin-polarized electron sources. We investigated three types of superlattice architectures: (1) compressively strained GaAs wells on GaInP barriers, yielding a maximum band splitting of 140 meV, (2) lattice-matched GaAs/GaInP structures, resulting in the maximum band splitting of 75 meV, and (3) tensile …

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A Framework For Fair And Trustworthy Multimodal Video Anomaly Detection: Fusion, Dataset Quality Auditing, Explainability, And Fairness, Omeshamisu Judith Anigala Jan 2025

A Framework For Fair And Trustworthy Multimodal Video Anomaly Detection: Fusion, Dataset Quality Auditing, Explainability, And Fairness, Omeshamisu Judith Anigala

Electronic Theses and Dissertations

No abstract provided.

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Largely Enhanced Out-Of-Plane Electromechanical Coupling Effects In Two-Dimensional Molybdenum-Disulfide/Boron-Nitride Heterostructures, Qiong Liu, Vijay Kumar Choyal, James E. Morris, Timon Rabczuk, Xiaoning Jiang, Xiaoying Zhuang Jan 2025

Largely Enhanced Out-Of-Plane Electromechanical Coupling Effects In Two-Dimensional Molybdenum-Disulfide/Boron-Nitride Heterostructures, Qiong Liu, Vijay Kumar Choyal, James E. Morris, Timon Rabczuk, Xiaoning Jiang, Xiaoying Zhuang

Electrical and Computer Engineering Faculty Publications and Presentations

The electromechanical coupling effects in two-dimensional (2D) transition metal dichalcogenides (TMDs) have attracted great interest. However, for 2D TMDs, piezoelectricity is confined to the basal plane, and the flexoelectricity-derived out-of-plane electromechanical response is usually faint, limiting the applications of this material family using the out-of-plane electromechanical effects. Here, this work reports a facile strategy to greatly enhance the out-of-plane electromechanical response of hexagonal molybdenum disulfide (2H-MoS2) nanoflakes by stacking monolayer hexagonal boron nitride (h-BN) on 2H-MoS2 nanoflakes to form MoS2/BN heterostructures. The deff/33 coefficient of MoS2/BN can reach a value comparable …

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Ecobuoys For Scalable Oceanography, Anuscheh Nawaz, Michael Steele, Ruth Branch, David Burnett, Kuotian Liao, Mallory Parker, Eleftheria Roumeli Jan 2025

Ecobuoys For Scalable Oceanography, Anuscheh Nawaz, Michael Steele, Ruth Branch, David Burnett, Kuotian Liao, Mallory Parker, Eleftheria Roumeli

Electrical and Computer Engineering Faculty Publications and Presentations

An approach to scalable surface-drifting buoys is needed to enable the high spatial and temporal resolution of oceanographic data that the science and meteorological communities are asking for. With the number of active buoys predicted to increase by a factor of 100 or more, the impact on the environment becomes even more important. Here, we present a pathway to a scalable and sustainable generation of buoys. We identify the main criteria to be used when developing such buoys to be low cost, with reliable data and neutral or even positive environmental impact. For each buoy subsystem—hull, electronics, energy generation and …

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An Offline Approach For Frequency Event Detection In Power Systems: Tkeo And Statistical Analysis, Hussain A. Alghamdi, Midrar Adham, Umar Farooq, Robert Bass Jan 2025

An Offline Approach For Frequency Event Detection In Power Systems: Tkeo And Statistical Analysis, Hussain A. Alghamdi, Midrar Adham, Umar Farooq, Robert Bass

Electrical and Computer Engineering Faculty Publications and Presentations

The increasing integration of renewable energy sources in power grids and the transition from conventional thermal-based generation to inverter-based resources for power generation have reduced power system inertia and increased the rate of change of frequency, which constitutes a challenge for frequency stability in modern power systems. These changes necessitate robust frequency event detection algorithms that can rapidly and accurately identify events, providing essential support to maintain stability. This paper proposes a frequency event detection algorithm with six tunable parameters for offline post-processing, leveraging the Teager-Kaiser Energy Operator method and statistical analysis. The algorithm is tested on a dataset comprised …

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Sogar: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition, Naga Venkata Sai Raviteja Chappa, Pha Nguyen, Alexander H. Nelson, Han-Seok Seo, Xin Li, Page Daniels Dobbs, Khoa Luu Jan 2025

Sogar: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition, Naga Venkata Sai Raviteja Chappa, Pha Nguyen, Alexander H. Nelson, Han-Seok Seo, Xin Li, Page Daniels Dobbs, Khoa Luu

Electrical Engineering and Computer Science Faculty Publications and Presentations

Social group activity recognition is crucial for various applications including surveillance, human-robot interaction, and behavioral analysis. Current approaches often require extensive manual annotations and rely heavily on pre-trained detectors, limiting their practical applications. Additionally, existing methods struggle to effectively model long-term spatiotemporal relationships in group activities. This paper introduces a novel approach to Social Group Activity Recognition (SoGAR) using Self-supervised Transformers network that can effectively utilize unlabeled video data. To extract spatio-temporal information, we create local and global views with varying frame rates. Our self-supervised objective ensures that features extracted from contrasting views of the same video are consistent across …

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Antennas For Emerging Satellite Services, Jakub Przepiorowski Jan 2025

Antennas For Emerging Satellite Services, Jakub Przepiorowski

Doctoral

The NewSpace era has revolutionized access to space, driving advancements in satellite communication (SATCOM) systems and creating demand for low-cost, compact, and high-performance user terminals. This thesis addresses these needs by developing innovative antenna solutions tailored for user terminals designed for emerging satellite constellations and satellite Internet-of-Things (S-IoT) applications.

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Power Utilization In Open Ran: Key Findings From A Usa Testbed, Saish Urumkar, Byrav Ramamurthy, Seshu Tirupathi, Sachin Sharma Jan 2025

Power Utilization In Open Ran: Key Findings From A Usa Testbed, Saish Urumkar, Byrav Ramamurthy, Seshu Tirupathi, Sachin Sharma

Articles

Open Radio Access Networks (Open RAN) provide flexible, scalable, and interoperable solutions to address the growing demands of mobile traffic while also aiming to reduce energy consumption. Most prior research on energy-efficient Open RAN has focused on switching techniques such as dynamic cell on/off strategies and adaptive resource allocation, primarily through simulations. This letter investigates Central Processing Unit (CPU) power utilization at the NodeB (base station) level, focusing on User Equipment (UE) connection states by making use of a USA testbed (i.e., POWDER testbed). Two scenarios are considered for the experimental setup: (1) a simulated virtual environment with a single …

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Multiphysics Modeling Of Solid Oxide Fuel Cells For Gradient Minimization And Inductive Loop Analysis In Impedance Spectroscopy Using Machine Learning-Based Microstructural Property Estimation, Muhammad Usman Khan Jan 2025

Multiphysics Modeling Of Solid Oxide Fuel Cells For Gradient Minimization And Inductive Loop Analysis In Impedance Spectroscopy Using Machine Learning-Based Microstructural Property Estimation, Muhammad Usman Khan

College of Graduate Studies: Theses & Dissertations

Solid oxide fuel cells have significant advantages in renewable energy utilization due to their high efficiency, fuel flexibility, and low emissions. However, despite the numerous efforts of technology, thermal and current density gradients and impedance behavior fluctuations are still causing performance degradation. A combined computational framework that integrates machine learning and three-dimensional Multiphysics modeling is needed to investigate and optimize the performance of solid oxide fuel cells. A machine learning model, trained on synthetic microstructure data by percolation analysis, is used to predict important microstructural parameters like triple phase boundary density and geometric tortuosity. These are then employed in a …

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Effect Of Activation Temperature On Quantum Efficiency And Lifetime Of Nea Truncated Nanocone Array Gaas Photocathode, Md. Aziz Arroyo Rahman, Md Abdullah Mamun, Shukui Zhang, Hani E. Elsayed-Ali Jan 2025

Effect Of Activation Temperature On Quantum Efficiency And Lifetime Of Nea Truncated Nanocone Array Gaas Photocathode, Md. Aziz Arroyo Rahman, Md Abdullah Mamun, Shukui Zhang, Hani E. Elsayed-Ali

Physics Faculty Publications

This study investigates the quantum efficiency (QE) and operational lifetime of a negative electron affinity GaAs truncated nanocone array (TNCA) photocathode benchmarked against a conventional flat GaAs photocathode under varying activation temperatures. The TNCA structure demonstrated a QE of up to 13.6% at 590 nm with room temperature (RT) activation—approximately 1.5 times higher than its flat counterpart. This enhancement is due to Mie resonance effects within the nanostructure, as confirmed by finite-difference time-domain simulations. Moreover, the TNCA photocathode exhibits significantly extended charge lifetime, with enhancement factors of ∼6.1 and ∼19.8 under RT and 50 °C activations, respectively. These gains are …

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Prediction Of Audit Findings Using Deep Learning With Financial And Non-Financial Data: A Case Study In Province X, Fery Yohan Setiawan, Eko Mulyanto Yuniarno, Reza Fuad Rachmadi Jan 2025

Prediction Of Audit Findings Using Deep Learning With Financial And Non-Financial Data: A Case Study In Province X, Fery Yohan Setiawan, Eko Mulyanto Yuniarno, Reza Fuad Rachmadi

Knowledge Engineering and Data Science

The implementation of the audit from the local government financial statements by The Audit Board of The Republic of Indonesia (BPK RI), especially for the Province X representative, are frequently faced by the various limitations, one of them being the required audit time. At this moment, the BPK RI representative of Province X doesn’t have the tools that are able to help the accurate of sample determination for the pick test, which resulted in this study proposing the application of multi-label classification to predict the findings of financial statement (Laporan Keuangan, LK) audits based on financial and non …

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Cognitive Eeg Differentiation With Hypnosis-Based Noise Reduction And K-Harmonic Means For Personalized Brainwave Modeling, Ahmad Azhari, Dimas Chaerul Ekty Saputra Jan 2025

Cognitive Eeg Differentiation With Hypnosis-Based Noise Reduction And K-Harmonic Means For Personalized Brainwave Modeling, Ahmad Azhari, Dimas Chaerul Ekty Saputra

Knowledge Engineering and Data Science

This study investigates the integration of hypnosis-based noise reduction and K-Harmonic Means (KHM) clustering for personalized brainwave modeling using Electroencephalography (EEG) data. EEG signals were collected from 100 participants using a Neurosky Mindset sensor at the FP1 (prefrontal) location, with each subject performing nine standardized cognitive tasks such as breathing, memory recall, and mathematical problem-solving. Hypnosis was applied not as a filtering method but as a behavioral protocol to standardize subject conditions and minimize physiological and environmental noise. The EEG signals were sampled at 128 Hz and analyzed using KHM clustering with K=4K = 4K=4, resulting in a Silhouette Score …

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Stable Numerical Solution Of An Elliptic Pde Inverse Problem Subject To Incomplete Boundary Conditions, Qasim Abd Ali Tayyeh Jan 2025

Stable Numerical Solution Of An Elliptic Pde Inverse Problem Subject To Incomplete Boundary Conditions, Qasim Abd Ali Tayyeh

Knowledge Engineering and Data Science

This study addresses the challenging problem of solving inverse elliptic Partial Differential Equations (PDE) with incomplete boundary data, data available only on a part of the domain boundary. The aim is to develop a robust, effective numerical framework that consistently recovers parameters and/or sources from incomplete, ill-posed data. In the case of a variational problem discretized by the Finite Element Method (FEM) and solved by an adjoint-based optimization strategy, the framework uses Tikhonov regularization. Morozov's Discrepancy Principle is used to determine regularization parameters that achieve the best balance between accuracy and stability. Even with 5% noise in the measurement data, …

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Assessing Deep Learning Models And Hyperparameter Optimization For Stable Time-Series Electricity Load Forecasting, Sukma Patrya, Aji Prasetya Wibawa, Aripriharta Aripriharta Jan 2025

Assessing Deep Learning Models And Hyperparameter Optimization For Stable Time-Series Electricity Load Forecasting, Sukma Patrya, Aji Prasetya Wibawa, Aripriharta Aripriharta

Knowledge Engineering and Data Science

Long-term electricity load forecasting plays an important role in ensuring system reliability, optimizing energy management, and making operational plans in face of continuously rising electricity demands. This study suggests a complete deep learning method for univariate forecasting of future electricity loads based on climatology and electricity consumption data for the period between 2019 and 2023. The initial dataset was cleaned, normalized, and partitioned chronologically into train/test datasets. Four train/test split cases (20/80, 40/60, 60/40, 80/20) were considered to explore the impact of different levels of historical data availability on the performance of the suggested framework from data-poor to data-rich situations. …

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Investigation Of Under-Frequency Load Shedding Prevention Of Isolated Medium-Sized Power Systems Using Energy Storage, Dilan Indoopa Manamperi Jan 2025

Investigation Of Under-Frequency Load Shedding Prevention Of Isolated Medium-Sized Power Systems Using Energy Storage, Dilan Indoopa Manamperi

Theses: Doctorates and Masters

Due to the rapid uptake of distributed photovoltaic generation, the visible load to transmission operators in distribution feeders is reducing. Traditional load-shedding schemes are facing challenges due to this low-load situation. The required amount of load reduction cannot be achieved with the same load-shedding scheme as before. In some situations, with reverse power flows, load shedding can further increase the generation reduction. On the other hand, increased Rate of Change of Frequency (RoCoF) due to low inertia can result in false activation of under-frequency load shedding (UFLS) relays. These challenges can cause a serious problem with the power system security. …

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Non-Line-Of-Sight Classification In Urban Areas Based On Machine Learning Algorithms, Mohamed Ali Ezzelarab, Mohamed Abdelazim Mohamed, Eman Abdelhalim, Ashraf Abosekeen Jan 2025

Non-Line-Of-Sight Classification In Urban Areas Based On Machine Learning Algorithms, Mohamed Ali Ezzelarab, Mohamed Abdelazim Mohamed, Eman Abdelhalim, Ashraf Abosekeen

Mansoura Engineering Journal

Non-Line-Of-Sight (NLOS) and multipath errors are significant causes of poor accuracy in Global Navigation Satellite Systems (GNSS). These errors occur when satellite signals are diffracted or reflected by obstacles instead of traveling directly along the Line-Of-Sight (LOS), particularly in urban environments. Such diffracted or reflected signals can reach GNSS receivers, skewing pseudorange measurements and posing challenges to accurate GNSS positioning. This study introduces an innovative approach using supervised Machine Learning (ML) models to detect and mitigate NLOS error. To develop and validate these models, GNSS data collected during the smartLoc project from Frankfurt and Berlin in Germany were leveraged, representing …

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High Voltage Circuit Breaker Arc Modelling State Of Art, Raghdaa I. Elbahy, Ahmed M. Abdelbaset, Ebrahim A. Badran, Mansour H. Abdel-Rahman Jan 2025

High Voltage Circuit Breaker Arc Modelling State Of Art, Raghdaa I. Elbahy, Ahmed M. Abdelbaset, Ebrahim A. Badran, Mansour H. Abdel-Rahman

Mansoura Engineering Journal

High-voltage (HV) circuit breakers (CBs) are critical for safe and reliable power system operation. However, electric arcs formed during current interruption pose a challenge due to their complex, non-linear behavior. These arcs can hinder CB efficiency and cause equipment damage. To address this, understanding and modeling arc properties are essential. This paper explores existing methods for modeling and simulating electric arcs in HV CBs, including physical, black box, and parameter models. By analyzing these approaches, the paper emphasizes the importance of arc modeling for CB optimization and outlines the physical, mathematical, and software requirements for effective modeling and simulation.

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