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2024

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Articles 1201 - 1230 of 1326

Full-Text Articles in Electrical and Computer Engineering

Smart Longboard, Ben Rath Jan 2024

Smart Longboard, Ben Rath

Williams Honors College, Honors Research Projects

The proposed design project includes a motorized longboard, equipped with a wireless handheld remote to manage the speed of the board. An embedded system mounted underneath the board will gather data from an accelerometer and a GPS sensor. This information is sent through a Bluetooth connection to a compatible smartphone application where it will be displayed. The project also includes a custom battery and charging circuit for the board to ensure that all of the engineering requirements are met. The board will be easy to use and the smartphone application will be able to display ride statistics of the user …

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Zero-Shot Cross-Lingual Pos Tagging For Filipino, Jimson Paulo Layacan, Isaiah Edri W. Flores, Katrina Bernice M. Tan, Ma. Regina Justina Estuar, Jann Railey E. Montalan, Marlene M. De Leon Jan 2024

Zero-Shot Cross-Lingual Pos Tagging For Filipino, Jimson Paulo Layacan, Isaiah Edri W. Flores, Katrina Bernice M. Tan, Ma. Regina Justina Estuar, Jann Railey E. Montalan, Marlene M. De Leon

Department of Information Systems & Computer Science Faculty Publications

Supervised learning approaches in NLP, exemplified by POS tagging, rely heavily on the presence of large amounts of annotated data. However, acquiring such data often requires significant amount of resources and incurs high costs. In this work, we explore zero-shot cross-lingual transfer learning to address data scarcity issues in Filipino POS tagging, particularly focusing on optimizing source language selection. Our zero-shot approach demonstrates superior performance compared to previous studies, with top-performing fine-tuned PLMs achieving F1 scores as high as 79.10%. The analysis reveals moderate correlations between cross-lingual transfer performance and specific linguistic distances–featural, inventory, and syntactic–suggesting that source languages with …

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Datum–Wise Learning And Inference For Supervised Classification, Sachini Piyoni Ekanayake Ekanayake Mudiyanselage Jan 2024

Datum–Wise Learning And Inference For Supervised Classification, Sachini Piyoni Ekanayake Ekanayake Mudiyanselage

Electronic Theses & Dissertations (2024 - present)

Traditional supervised classification typically involves assigning a label to a single variable, considering a common subset of features for all the instances, and employing a single classifier. However, in many real–world applications like behavioral analysis or insurance recommendation, a data instance is described by a set of related variables such as physical activity and emotion, or driving quality and accident severity. At the same time, these variables are not directly observable but can be inferred via noisy but costly features. Specifically, access to all features is prohibitive due to cost, invasiveness, or limited resources. Finally, while using a single classifier …

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Sparse Representation Learning For Temporal Networks, Maxwell Mcneil Jan 2024

Sparse Representation Learning For Temporal Networks, Maxwell Mcneil

Electronic Theses & Dissertations (2024 - present)

Temporal networks arise in many domains including activity of social network users, sensor network readings over time, and time course gene expression within the interaction network of a model organism. Data of this type contains a wealth of prior information such as the connectivity among nodes (e.g., a friendship graph), and prior knowledge of expected temporal patterns (e.g., periodicity). Modeling these temporal and network patterns jointly is essential for state-of-the-art performance in temporal network data analysis and mining. Sparse dictionary encoding is one modeling approach for such underlying patterns. However, most classical approaches consider only one dimension of the data …

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Efficient Connectivity Management And Path Planning For Iot And Uav Networks, Amirahmad Chapnevis Jan 2024

Efficient Connectivity Management And Path Planning For Iot And Uav Networks, Amirahmad Chapnevis

Theses and Dissertations

This dissertation explores how to better manage resources in mobile networks, especially for enhancing the performance of Unmanned Aerial Vehicles (UAV)-supported IoT networks. We explored ways to set up a flexible communication architecture that can handle large IoT deployments by making good use of mobile core network resources like bearers and data paths. We developed strategies that meet the needs of IoT networks and enhance network performance. We also developed and tested a system that combines traffic from several mobile devices that use the same user identity and network resources within the core mobile network. We used everyday smartphones, SIM …

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Photoluminescence Of Beryllium-Related Defects In Gallium Nitride, Mykhailo Vorobiov, Mykhailo Vorobiov Jan 2024

Photoluminescence Of Beryllium-Related Defects In Gallium Nitride, Mykhailo Vorobiov, Mykhailo Vorobiov

Theses and Dissertations

This study explores the potential of beryllium (Be) as an alternative dopant to magnesium (Mg) for achieving higher hole concentrations in gallium nitride (GaN). Despite Mg prominence as an acceptor in optoelectronic and high-power devices, its deep acceptor level at 0.22 eV above the valence band limits its effectiveness. By examining Be, this research aims to pave the way to overcoming these limitations and extend the findings to aluminum nitride and aluminum gallium nitride (AlGaN) alloy. Key contributions of this work include. i)Identification of three Be-related luminescence bands in GaN through photoluminescence spectroscopy, improving the understanding needed for further material …

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Cross-Temporal Hierarchical Forecast Reconciliation Of Natural Gas Demand, Colin O. Quinn, George F. Corliss, Richard J. Povinelli Jan 2024

Cross-Temporal Hierarchical Forecast Reconciliation Of Natural Gas Demand, Colin O. Quinn, George F. Corliss, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Local natural gas distribution companies (LDCs) require accurate demand forecasts across various time periods, geographic regions, and customer class hierarchies. Achieving coherent forecasts across these hierarchies is challenging but crucial for optimal decision making, resource allocation, and operational efficiency. This work introduces a method that structures the gas distribution system into cross-temporal hierarchies to produce accurate and coherent forecasts. We apply our method to a case study involving three operational regions, forecasting at different geographical levels and analyzing both hourly and daily frequencies. Trained on five years of data and tested on one year, our model achieves a 10% reduction …

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Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick Jan 2024

Rf Steganography To Send High Security Messages Through Sdrs, Megan K. Patrick

Browse all Theses and Dissertations

This research illustrates a high-security wireless communication method using a joint radar/communication waveform, addressing the vulnerability of traditional low probability of detection (LPD) waveforms to hostile receiver detection via cyclostationary processing (CSP). To mitigate this risk, RF steganography is used, concealing communication signals within linear frequency modulation (LFM) radar signals. The method integrates reduced phase-shift keying (RPSK) modulation and variable symbol duration, ensuring secure transmission while evading detection. Implementation is validated through software-defined radios (SDRs), demonstrating effectiveness in covert communication scenarios. Results include analysis of message reception and cyclostationary features, highlighting the method's ability to conceal messages from hostile receivers. …

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Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer Jan 2024

Measured Phase History Data For Target Recognition Studies, Gregory A. Seltzer

Browse all Theses and Dissertations

Performing automatic target recognition (ATR) on full-size aircraft targets using inverse synthetic aperture radar (ISAR) data is challenging and expensive. The use of scale models and radar systems of such large targets saves time and reduces facility requirements. This study examines the feasibility of performing ATR on 1:144 scale model airplanes at Ka-band. The scale model and Ka-band radar simulate the collection of full-scale targets at VHF-band. The phase history measurement collections were completed in the Sensors and Signals Exploitation Laboratory (SSEL) at Wright State University. To ensure sufficient data for training and testing, the phase history data was augmented …

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Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich Jan 2024

Application Of Multiple Data Augmentation Techniques To Improve Training With Synthetic Sar Data In Common Cnn, Stephanie M.V. Saich

Browse all Theses and Dissertations

To address the issues of limited target data in the Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) problem set, synthetic data is often used to aid in filling the gap. This paper covers an in depth look at the use of colorization, dynamic range adjustment, and target extraction as data augmentation techniques to improve the accuracy of deep learning networks trained on synthetic SAR data. The use of multiple different data augmentations combine to dramatically improve the accuracy of a common Convolutional Neural Network (CNN) over the use of standard synthetic data. A comparison of increasing fraction of measured …

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Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi Jan 2024

Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi

Browse all Theses and Dissertations

Lithium-ion batteries are an integral component of energy storage systems for renewable energy applications owing to their high energy density. Extensive research has therefore been carried out, utilizing both experimental and computational methods, to aid in a deeper understanding of lithium-ion batteries. Challenges related to efficiency, safety and thermal management persist, particularly during high current draw, extreme temperature conditions and extreme dynamic current operation such as in electric vehicles. This thesis work presents an electrochemical-thermal model of a lithium-ion battery that simulates and analyzes the variation of electrical behavior, chemical behavior and thermal behavior. The electrochemical model is developed by …

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Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson Jan 2024

Empirical Investigation Of Calibration Targets In Thz In The Near Field From 550 To 700 Ghz, Anais Kypris L. Rawson

Browse all Theses and Dissertations

The uncertainty of the standard calibration procedure for radar cross-section (RCS) measurement is studied for different targets measured in the near-field from 550 to 700 GHz. Using common calibration spheres and squat cylinders mounted on a styrofoam pedestal at waterline (zero-degrees elevation), the calibration difference measure is determined for each target. Similarly, the difference metric is determined for square trihedral and tophat targets placed on a ground plane and measured at different elevation angles. The mean calibration measure is calculated using the dual calibration target method and repeated measurements in an anechoic chamber. The specific THz system is described and …

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Performance Degradation Of Gan Hemts Under Rf Aging: Implications For Wireless Communications Standards, Nathan Grant Jan 2024

Performance Degradation Of Gan Hemts Under Rf Aging: Implications For Wireless Communications Standards, Nathan Grant

Browse all Theses and Dissertations

This study examines the aging effects of GaN HEMTs, focusing on the CG2H40010 device under conditions that mimic the high-power, high-frequency environments of wireless communication systems. With the increasing adoption of GaN technology in RF applications, understanding its degradation mechanisms under CW stress and modulated signal characterization is essential for predicting device lifetime and ensuring performance standards for modern communication systems. RFALT was employed to stress the device using CW signals, while key performance metrics, such as gain compression, gate leakage, ACP, and EVM, were assessed using W-CDMA signals to replicate real-world dynamic stresses. The findings reveal that CW stress …

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Machine-Learning-Assisted Design Of Deep Eutectic Solvents Based On Uncovered Hydrogen Bond Patterns, Usman Lame Abbas, Yuxuan Zhang, Joseph Tapia, Md Selim, Jin Chen, Jian Shi, Qing Shao Jan 2024

Machine-Learning-Assisted Design Of Deep Eutectic Solvents Based On Uncovered Hydrogen Bond Patterns, Usman Lame Abbas, Yuxuan Zhang, Joseph Tapia, Md Selim, Jin Chen, Jian Shi, Qing Shao

Markey Cancer Center Faculty Publications

Non-ionic deep eutectic solvents (DESs) are non-ionic designer solvents with various applications in catalysis, extraction, carbon capture, and pharmaceuticals. However, discovering new DES candidates is challenging due to a lack of efficient tools that accurately predict DES formation. The search for DES relies heavily on intuition or trial-and-error processes, leading to low success rates or missed opportuni- ties. Recognizing that hydrogen bonds (HBs) play a central role in DES formation, we aim to identify HB features that distinguish DES from non-DES systems and use them to develop machine learning (ML) models to discover new DES systems. We first analyze the …

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Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk Jan 2024

Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk

Theses and Dissertations--Electrical and Computer Engineering

Refractory focal epilepsy is characterized by the presence of seizures that cannot be controlled via anti-seizure medications. For patients suffering from this form of epilepsy, accurate identification of the seizure onset zone is a crucial step for many modalities of treatment. Electrical source imaging (ESI) allows for estimation of the seizure onset zone from electroencephalography. EEG feature extraction is an important step that can impact the final accuracy of source estimates. This work provides a review of 23 ictal ESI studies and proposes a delta-focused ictal ESI methodology. Our proposed delta-focused ictal ESI is implemented across 33 refractory focal epilepsy …

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Electronics Design For Krepe Atmospheric Entry Capsule Avionics, Matt Ruffner Jan 2024

Electronics Design For Krepe Atmospheric Entry Capsule Avionics, Matt Ruffner

Theses and Dissertations--Electrical and Computer Engineering

This research documents the design, testing, and implementation of sensing, control, and communications subsystems for small atmospheric entry capsules. Atmospheric entry capsules pose a unique electronics design challenge given mission requirements, environmental constraints, and inherent risk involved in space based missions. Previous work on small satellites developed the CubeSat platform as a means of ensuring reliability after university-led small satellite missions experienced failures. The publication of the CubeSat platform allowed researchers to focus on the payload science utilizing a standardized form-factor and reusable electronics. Environmental and operational constraints of CubeSats and atmospheric entry capsules overlap and best-practices associated with building …

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Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso Jan 2024

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso

Theses and Dissertations--Electrical and Computer Engineering

The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …

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Mitigation Of Reflected Overvoltage In Wind-Turbine Generator-Converter Systems With A Smart Coil Concept, Lulu Wei Jan 2024

Mitigation Of Reflected Overvoltage In Wind-Turbine Generator-Converter Systems With A Smart Coil Concept, Lulu Wei

Theses and Dissertations--Electrical and Computer Engineering

In the recent decade, ultra-fast wide bandgap switching devices such as Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) have been increasingly utilized in power electronic converters for renewable energy power generation systems due to their advantages of enabling high energy efficiency and high power density. However, the much higher voltage slew rate (i.e., dv/dt) with SiC power converters may induce voltage reflection and reliability concerns in machine-converter systems, especially for medium-voltage systems with long cable connections. In wind-turbine power generation systems, generators are typically located in the nacelles, and medium-voltage power converters are mostly placed at the bottom of the …

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Multi-Physics Modeling Of Immersion Cooled Electric Power Apparatuses, Reza Ilka Jan 2024

Multi-Physics Modeling Of Immersion Cooled Electric Power Apparatuses, Reza Ilka

Theses and Dissertations--Electrical and Computer Engineering

Electric power conversion apparatuses such as electromagnetic transformers and power electronic converters play a backbone role in the global power and energy industries, such as power transmission and distribution, electrified transportation vehicle systems, industry automation, and the like. To investigate the performance (efficiency, reliability, etc.) of such critical power conversion apparatuses, high-fidelity multi-physics modeling becomes critical which involves dedicated coupling among multiple physical domains, including electrical, magnetic, thermal, mechanical, and material engineering. Nevertheless, the majority of the existing models for these power conversion apparatuses focus only on one or two physical domains, and the modeling fidelity needs to be further …

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A Novel Processor Architecture Implementing The Stacked Error Diffusion Algorithm And Its Zynq-Based Realization, Qishi Hu Jan 2024

A Novel Processor Architecture Implementing The Stacked Error Diffusion Algorithm And Its Zynq-Based Realization, Qishi Hu

Theses and Dissertations--Electrical and Computer Engineering

Digital halftoning reproduces continuous-tone images using patterns of black and white dots, while multitoning extends this concept by incorporating inks with intermediate intensities. These techniques are extensively utilized in the printing industry to accommodate the limited range of inks available in printers. Stacked error diffusion is a high-quality multitoning algorithm that adheres to the blue-noise dithering standard. This thesis research studies the potential parallelism inherent in the algorithm and introduces the design of a novel processor architecture optimized for efficient execution. The architecture is realized on an FPGA development board featuring a Zynq SoC. Additionally, the hardware prototype can also …

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Information-Theoretic Learning Framework Based On Covariance Operators On Reproducing Kernel Hilbert Spaces, Jhoan Keider Hoyos Osorio Jan 2024

Information-Theoretic Learning Framework Based On Covariance Operators On Reproducing Kernel Hilbert Spaces, Jhoan Keider Hoyos Osorio

Theses and Dissertations--Electrical and Computer Engineering

Information theory provides tools to quantify uncertainty, dependence, and similarity between probability distributions, which are crucial for addressing various machine-learning problems. However, estimating these quantities is challenging because data distributions are usually unknown, and only observations are available for analysis. In this dissertation, we advance the field of information-theoretic learning by developing a comprehensive framework using kernel methods for analyzing probability distributions using reproducing kernel Hilbert spaces (RKHS). By leveraging covariance operators in this representation space, we propose approaches to estimate a set of fundamental information-theoretic quantities, that, because of their resemblance with conventional quantities in information theory, we call …

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Optimal Control And Evaluation Of Shipboard Power Systems, Musharrat Sabah Jan 2024

Optimal Control And Evaluation Of Shipboard Power Systems, Musharrat Sabah

Theses and Dissertations--Electrical and Computer Engineering

Electric warships are involved in complex missions consisting of multiple simultaneous operations. In order to ensure mission success, future ships must be designed in a way that optimizes their performance in the presence of complex mission loads. The focus of this research is an effort to optimally control the performance of shipboard systems during missions involving multiple scenarios or vignettes. The evaluation of the performance of mission-oriented power systems is based on the degree to which these systems deliver power to the loads required to perform the mission at hand. The performance of such systems involves a dynamic interplay between …

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High Reliability Motor-Drive Systems For Electric Aircraft Propulsion, Majid Tahmasbi Fard Jan 2024

High Reliability Motor-Drive Systems For Electric Aircraft Propulsion, Majid Tahmasbi Fard

Theses and Dissertations--Electrical and Computer Engineering

The transition towards electric propulsion in aircraft applications requires significant advancements in enhancing the efficiency and power density of power transmission and distribution systems. Among the critical power components in electric aircraft propulsion systems, power electronic converters hold paramount importance as they provide a pivotal interface between batteries and propulsion motors while providing a high degree of controllability and flexibility to the system. Integrating medium voltage DC (MVDC) and the emerging wide bandgap switching devices into power converters not only amplifies converter performance but also unlocks multifarious system-level benefits, including reduced power losses, weight savings, and the utilization of high-speed …

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Information Access For Infrastructurally-Challenged Environments And Beyond Through Mutually Aware Spectrum Sharing Technologies, Karyn Doke Jan 2024

Information Access For Infrastructurally-Challenged Environments And Beyond Through Mutually Aware Spectrum Sharing Technologies, Karyn Doke

Electronic Theses & Dissertations (2024 - present)

The Radio Frequency (RF) spectrum is scarce and to make it available for new mobile wireless services, regulators are forced to re-allocate spectrum from existing services or develop mechanisms to share spectrum with new entries. Television White Space (TVWS) and Citizen Broadband Radio Service (CBRS) are two examples of recently commercialized spectrum sharing technologies. TVWS enables sharing among fixed wireless broadband technologies (secondary users) and terrestrial TV broadcast services (primary users). CBRS enables spectrum sharing among 5G/LTE (secondary users) and naval radar (primary users). With both technologies, a central database determines when it is safe for secondary users to operate …

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Building Integration Of A Solar Air Heating System, Fernando Guerreiro Jan 2024

Building Integration Of A Solar Air Heating System, Fernando Guerreiro

Doctoral

In order to achieve the global carbon emission target, the high fraction of locally available renewable energy sources will become necessary to meet energy demand. Solar energy is one of the most important renewable sources locally available for use in space heating, cooling, hot water supply and power production. Building integrated solar thermal systems (BISTS) can be a potential solution towards the enhanced energy efficiency and reduced operational cost in built environment. The current research aimed at developing an active solar air heating collector for building integration. This system consisted of several asymmetric compound parabolic concentrating collectors with inverted transpired …

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Distribution System Losses Allocation Based On Circuit Theory With Distributed Generation, Ahmed S. Abdelkader, Ibrahim I. Mansy, Abdelfattah A. Eladl Jan 2024

Distribution System Losses Allocation Based On Circuit Theory With Distributed Generation, Ahmed S. Abdelkader, Ibrahim I. Mansy, Abdelfattah A. Eladl

Mansoura Engineering Journal

Electricity energy is the most convenient and efficient form of energy transmission and conversion. Nonetheless, losses take place while electrical power is traveling from power stations through transmission and distribution networks to the loads. Despite the high efficiency of electrical transmission and distribution networks, the huge amounts of power moving through these networks make the financial loss due to the lost energy very high and its management becomes a critical consideration for both utility providers and regulatory bodies. The efficient management of losses encompasses two major functions: the first is running the system in a way that minimizes the losses; …

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Experimental Investigation Of Self-Mixing Interferometric Technique For Displacement Assessment, Dulanjana Anuhas Egodagamage Jan 2024

Experimental Investigation Of Self-Mixing Interferometric Technique For Displacement Assessment, Dulanjana Anuhas Egodagamage

Chulalongkorn University Theses and Dissertations (Chula ETD)

The self-mixing interferometric (SMI) technique has proven effective for achieving precise, contactless measurements of submicron displacements. This study aims to further investigate and experimentally assess the capabilities of the SMI technique in displacement sensing. While extensive research has been conducted on the SMI technique for displacement sensing, its performance can still be further explored in scenarios where the target exhibits varying displacement amplitudes and oscillation frequencies. Understanding the limitations and ranges of the SMI technique is crucial for advancing laboratory-based setups into practical applications. An experimental optoelectronic setup was used in this work, employing a semiconductor laser diode module integrated …

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การพัฒนาแพลตฟอร์มเมตาเวิร์สแบบเว็บที่มีระบบสนับสนุนปัญญาประดิษฐ์, สืบพงศ์ น้อยศรี Jan 2024

การพัฒนาแพลตฟอร์มเมตาเวิร์สแบบเว็บที่มีระบบสนับสนุนปัญญาประดิษฐ์, สืบพงศ์ น้อยศรี

Chulalongkorn University Theses and Dissertations (Chula ETD)

วิทยานิพนธ์ฉบับนี้นำเสนอการพัฒนาต้นแบบแพลตฟอร์มเมตาเวิร์สที่มีขีดความสามารถขั้นพื้นฐานครอบคลุมระบบอวาทาร์ ระบบผู้ใช้หลายราย ระบบสื่อสารตามเวลา ระบบการเชื่อมต่อแชตบอต และฉากโลกเสมือนจริงสามมิติที่เหมือนจริง แพลตฟอร์มที่พัฒนาขึ้นนี้ถูกนำไปใช้ประโยชน์กับหน่วยงานภาคการศึกษาและภาคธุรกิจ ทั้งหน่วยงานภายในจุฬาลงกรณ์มหาวิทยาลัยและสถาบันการศึกษาทั้งในประเทศและระดับนานาชาติ ผลการทดสอบพบว่าระบบทำงานได้ให้ผลสัมฤทธิ์ที่ดีและมีคุณภาพตามความต้องการใช้งานในทางปฏิบัติ สามารถประยุกต์ใช้กับการสร้างห้องเรียนเสมือนออนไลน์ในโลกเสมือนจริง รองรับระบบการสื่อสารระหว่างผู้ใช้ทั้งภาพ เสียง และข้อความ อีกทั้งยังสามารถใช้งานร่วมกับระบบแชตบอตจากภายนอกได้ผ่านระบบเอพีไอที่พัฒนาขึ้น ผลการทดสอบบนระบบคลาวด์ของบริษัท โทรคมนาคมแห่งชาติ จำกัด แสดงให้เห็นว่าระบบสามารถรองรับปริมาณผู้ใช้งานได้ไม่น้อยกว่า 30 รายพร้อมกัน ผลการทดสอบในเชิงประสบการณ์การใช้งานมีระดับความพึงพอใจในเชิงบวก งานวิจัยและพัฒนาจึงให้ประโยชน์และเป็นจุดเริ่มต้นของการประยุกต์ใช้เทคโนโลยีเมตาเวิร์สในวงกว้าง

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Detecting Bearing Race Defects With Inductive Magnetic Reluctance Sensors And Artificial Neural Networks, Collin Daly Jan 2024

Detecting Bearing Race Defects With Inductive Magnetic Reluctance Sensors And Artificial Neural Networks, Collin Daly

College of Graduate Studies: Theses & Dissertations

This work proposes a method of detecting physical damage to bearing races in a rotational assembly by means of magnetic reluctance sensors generating a signal from a rotating gear-tooth wheel. A nominally sinusoidal signal is generated based on the rotation of a gearwheel with regularly spaced voids and lands. Detection is based on the time variance of the signal periodically in relation to the gearwheel and the bearing damage. The purpose of this work is to propose a process to detect and classify bearing race defects using existing sensors and neural networks for hazardous area equipment applications.

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Cross-Layer Performance Evaluation Of C-V2x, Dhruba Sunuwar Jan 2024

Cross-Layer Performance Evaluation Of C-V2x, Dhruba Sunuwar

College of Graduate Studies: Theses & Dissertations

The evolution of connected vehicles from a distant futuristic concept to an integral part of daily life is indisputable. Vehicle-to-everything communication (V2X) serves as the cornerstone of this transformation, facilitating seamless interaction among vehicles, infrastructure, pedestrians, and networks. However, evaluating V2X system performance proves intricate due to the dynamic nature of vehicles influenced by mobility factors. To address this complexity, we have developed a specialized system-level simulator expressly for evaluating V2X communication performance. Notably, the simulator encompasses (i) intelligent transportation system (ITS) scenarios integrated into a geographical framework and (ii) the capability to assess cross-layer performance spanning physical (PHY) and …

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