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Photonic Instrumentation engineering XI 2024

作者： Mazzo, Paulo H.R. Torelli, Gabriel A. Dreyer, Uilian J. Pelegrin, Jessé Stel, Henrique Da Silva, Luiz C.T. Romero, Gabriel A. Morales, Rigoberto E.M. da Silva, Jean C.C. Graduate Program in Electrical and Computer Engineering Federal University of Technology UTFPR Paraná PR Curitiba Brazil Graduate Program in Energy Systems Federal University of Technology UTFPR Paraná PR Curitiba Brazil Multiphase Flow Research Center - NUEM Federal University of Technology UTFPR Paraná PR Curitiba Brazil CENPES/PDIEP EE Petrobras Brazil Federal Institute Catarinense IFC Santa Catarina Brazil

ISBN: (纸本)9781510670464

This paper presents a study and development on the thermal mapping of a Three-phase Induction Motor for harsh environments application. These machines’ exceptional performance and precise speed control make them essential equipment in multiple industrial processes, such as Artificial Lift, which integrates with a multistage centrifugal pump to elevate fluids from the reservoirs to the surface. Increased motor speeds for higher production requirements can result in temperature rise, damaging the stator winding. Employing the Raman Distributed Temperature Sensing System (RDTS), we generate a comprehensive heat distribution map of the motor. ANSYS Motor-CAD was applied for computational simulations to perform steady-state thermal analysis, giving an overview of heat transfer among internal components and thermal limits for the instrumented motor. This preliminary study presents a series of experimental tests to evaluate the advantages of fiber optic temperature sensing in harsh environments, emphasizing its significance in improving electrical machines’ performance and reliability. © 2024 SPIE.

关键词： Centrifugal pumps

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Arabic text sentiment analysis and emotion classification using transformers

Arabic text sentiment analysis and emotion classification us...

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Electronics, Communications, and Computations (JAC-ECC), International Japan-Africa Conference on

作者： Nada Mossad Youssef Mohamed A Fares Ahmed B. Zaky Egypt-Japan University of Science and Technology (E-JUST) Alexandria Egypt The Department of Electrical Engineering The Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University

Sentiment analysis and emotion classification are two crucial components of natural language processing (NLP), which have been widely explored in recent years due to their broad applications. Sentiment analysis aims to identify the polarity of written texts, ranging from positive to negative. Meanwhile, emotion classification is focused on recognizing and categorizing the emotional states expressed in the text. To achieve a deeper understanding of sentiments and emotions, it's essential to utilize models like BERT transformers that can effectively interpret the context. The process begins with data preprocessing, including tokenization and noise removal, followed by fine-tuning techniques to adapt the BERT model to the proposed tasks. We employed the BERT model on four datasets obtained from various sources, including Twitter, news websites, and restaurant reviews, where each dataset represents a distinct Arabic dialect. Our proposed model outperforms commonly used techniques like LSTM and CNN, yielding superior results. Despite the progress made, there are still challenges to overcome, such as dealing with Arabic diacritics, the new Arabic Arabizi, which uses Latin characters, and handling Arabic idioms. Further research is required to address these challenges adequately.

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Comparison of Coherent and Incoherent Donut Beams for Deep Tissue STED Microscopy

Comparison of Coherent and Incoherent Donut Beams for Deep T...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Shanavas, Thariq McLeod, Robert R. Siemens, Mark E. Gopinath, Juliet T. Department of Physics University of Colorado BoulderCO80309 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States Department of Physics University of Denver DenverCO80204 United States Materials Science Engineering Program University of Colorado BoulderCO80309 United States

We numerically compare the null quality for STED microscopy generated by Laguerre-Gaussian beams with orbital angular momentum and donut beams generated by incoherent addition of orthogonal Hermite Gaussian beams when... 详细信息

ISBN: (纸本)9781957171258

关键词： Tissue

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Low-Cost CSRR-based Microwave Sensor for Evaluating Water Quality to Prevent Unwanted Sugar Contamination

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Journal of Microwaves, Optoelectronics and Electromagnetic Applications 2025年第2期24卷

作者： de Sousa, Bruno Matias Duarte, José Garibaldi da Silva Neto, Valdemir Praxedes Graduate Program in Electrical and Computer Engineering Federal University of Rio Grande do Norte RN Natal Brazil Department of Communication Engineering Federal University of Rio Grande do Norte RN Natal Brazil

This study proposes a low-cost microwave sensor for the monitoring of water quality contamination in irrigation systems. The sensor was employed for monitoring the concentration of specific compounds in mixtures of glucose and water, in order to prevent the accumulation of unwanted sugars in large plantations. The proposed sensor is an adaptation of a complementary split ring resonator (CSRR) fabricated on an FR4 substrate. A capillary tube constructed from polypropylene is inserted into the region of the CSRR microwave sensor exhibiting the maximum density surface current, wherein the liquid under test (LUT) is contained. The sensor was designed to operate at a resonance frequency of 2.45 GHz in the absence of a load. The maximum displacement observed at the resonance frequency is 275 MHz, with a normalization sensitivity of 0.844%. The simulations and experimental measurements are verified and their results compared, yielding a high level of concordance for the sensor’s intended purpose. The discrepancy between the measured permittivity values and the reference values of the samples under analysis is less than 5%. The proposed sensor is an effective solution for characterizing liquids, particularly mixtures of water and glucose, when compared to other sensors available for this application. © 2025 SBMO/SBMag.

关键词： Microwave sensors

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Evaluating the Impact of Data Cleaning for Improving Road Damage Detection Through Vision Transformer

Evaluating the Impact of Data Cleaning for Improving Road Da...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Andy Desman Kahlil Muchtar Maulisa Oktiana Maya Fitria Yuwaldi Away Fardian Fardian Hammam Riza Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia Dept. of Electrical and Computer Engineering Department of Informatics Universitas Syiah Kuala The Master Program in Artificial Intelligence Universitas Syiah Kuala (USK) Banda Aceh Indonesia Department of Informatics BRIN (National Research and Innovation Agency) Indonesia The Master Program in Artificial Intelligence Universitas Syiah Kuala Banda Aceh Indonesia

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

The WHO predicts that by 2030 road accidents will be the 5th leading cause of death. Globally, road accidents account for 1.25 million casualties each year, and road defects cause 34% of these casualties. The road survey process in many countries have several challenges, one of which is detection using cameras that do not have a recognition system. In this study, a model with YOLOS architecture based on Vision Transformer trained on the RDD2022 dataset successfully recognizes road damage well, as indicated by the number of objects detected, bounding box on accurate objects, and the ability to recognize objects with inconsistent shadow and light inference. This research uses assessment parameters such as Average Precision (AP) and Average Recall (AR) to determine the overall performance of the model. The model achieves the highest AP value at Intersection of Union (IoU) 0.5, 0.75, and 0.5-0.95, worth 62.1%, 37.1%, and 36.2% respectively, and the highest AR value in Large, Medium, and Small Areas, worth 42.1%, 60.3%, and 75.4% respectively. The supplementary material can be found through this link: https://***/watch?v=LzkI2e_IORE.

关键词： YOLO Surveys computer vision Road accidents Roads Manuals Transformers Cameras Cleaning Tuning

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Prior-Guided Parallel Residual Bi-Fusion Network in USV Obstacle Detection

Prior-Guided Parallel Residual Bi-Fusion Network in USV Obst...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Chih-Chung Hsu Sophia Yang Xiu-Yu Hou Yu-An Jhang Institute of Data Science National Cheng Kung University Interdisciplinary Program of Electrical Engineering and Computer Science National Tsing Hua University

In this paper, we propose a novel Prior-Guided Parallel Residual Bi-Fusion Feature Pyramid Network (PPRB-FPN) for accurate obstacle detection in unmanned surface vehicle (USV) sailing. Our method tackles the challenge of detecting small objects, which are prone to information vanishing. To the end, we leverage the PRB-FPN for small object detection and YOLOv7 as a single-stage object detector to effectively identify obstacles. Our experimental results on the Obstacle Detection Challenge dataset at the 1st Workshop on Maritime computer Vision (MaCVi) demonstrate that our method outperforms both Mask R-CNN (mrcnn) and YOLOv7, achieving an F_avg score of 0.514.

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Non-Hermitian selective thermal emitter for thermophotovoltaics

Non-Hermitian selective thermal emitter for thermophotovolta...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Prasad, Ciril S. Raphaelson, Samuel C. Naik, Gururaj V. Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Material Science and NanoEngineering Rice University HoustonTX United States

ISBN: (纸本)9781957171258

Selective thermal emitters can boost the efficiency of heat-to-electricity conversion in thermophotovoltaic systems only if their spectral selectivity is high. We demonstrate a non-Hermitian metasurface-based selective emitter operating at 1200 K in a GaSb-thermophotovoltaic cell. © Optica Publishing Group 2023 © 2023 The Author(s)

关键词： III-V semiconductors

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Balanced Spherical Grid for Egocentric View Synthesis

Balanced Spherical Grid for Egocentric View Synthesis

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Changwoon Choi Sang Min Kim Young Min Kim Dept. of Electrical and Computer Engineering Seoul National University Korea Interdisciplinary Program in Artificial Intelligence and INMC Seoul National University

We present EgoNeRF, a practical solution to reconstruct large-scale real-world environments for VR assets. Given a few seconds of casually captured 360 video, EgoNeRF can efficiently build neural radiance fields. Motivated by the recent acceleration of NeRF using feature grids, we adopt spherical coordinate instead of conventional Cartesian coordinate. Cartesian feature grid is inefficient to represent large-scale unbounded scenes because it has a spatially uniform resolution, regardless of distance from viewers. The spherical parameterization better aligns with the rays of egocentric images, and yet enables factorization for performance enhancement. However, the naive spherical grid suffers from singularities at two poles, and also cannot represent unbounded scenes. To avoid singularities near poles, we combine two balanced grids, which results in a quasi-uniform angular grid. We also partition the radial grid exponentially and place an environment map at infinity to represent unbounded scenes. Furthermore, with our resampling technique for grid-based methods, we can increase the number of valid samples to train NeRF volume. We extensively evaluate our method in our newly introduced synthetic and real-world egocentric 360 video datasets, and it consistently achieves state-of-the-art performance.

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Review on Determinant Parameters of Genetic Algorithm for the Optimized Closed Loop Control

Review on Determinant Parameters of Genetic Algorithm for th...

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Green Energy, Computing and Sustainable Technology (GECOST), International Conference on

作者： Ing Ming Chew W. K. Wong Filbert H. Juwono Teck Chai Tiong Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Computer Science Program University of Southampton Malaysia Nusajaya Malaysia Department of Electrical and Computer Engineering Curtin University Malaysia Miri Sarawak Malaysia

ISBN: (纸本)9781665486644

This paper aims to analyze the determinant parameters of Genetic Algorithm (GA) analysis for the optimized control performance of a closed control loop. The determinant parameters of GA optimization analysis cover population size (nPop), mutation rate (mu) and iteration (iter.) are analyzed and justified. The control terminology covers the Proportional-Integral-Derivative (PID) controller, a prestigious solution for industrial control applications. Besides, the research proposed stability analysis to determine the upper and lower limit settings for the optimization analysis. The research has begun with model identification, stability analysis and is followed by determining the controller tunings. The performance indexes are applied to compare the response performance of GA with deterministic controller tunings. Analysis results and discussion shows that GA with proper determinant parameters’ settings are performing better than other tuning methods in the closed loop control performance.

关键词： Analytical models Terminology Sociology Process control Stability analysis Performance analysis Statistics

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Study of the Bus Voltage Magnitude to Monitor Power Quality in the Distribution System

Study of the Bus Voltage Magnitude to Monitor Power Quality ...

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IEEE Canada Electric Power Conference, EPEC

作者： Christopher R. Men Douglas E. Dow Afsaneh Ghanavati Electrical and Computer Engineering Program School of Enginnering Wentworth Institue of Technology Boston MA

ISBN: (纸本)9781665463195

Power quality disturbances can be observed as sags, swells, transients, and harmonics, and can affect customers at varying levels of intensity. It is the responsibility of the utility to supply customers with power, however power quality disruptions can occur during distribution. Traditionally, only voltage information is used to conduct power quality monitoring at the distribution level. It is common to record the RMS values of the bus voltages and to identify abnormal operations based on when a sag or swell occurs. This paper proposes a tool consisting of an algorithm and an accompanying graphical user interface (GUI) that can display historical voltage bus data, analyze the data, and provide the user with information that details voltage behavior outside of a user-defined threshold. The GUI gives the user the interactive ability to import data and set the desired threshold. The algorithm then detects events in the imported data outside of the chosen threshold. It also provides the user with event durations, magnitudes, local maximums, and area. The efficacy of the algorithm was verified by comparing the output determined by the algorithm versus the conclusion drawn by a human observer. Additionally, this paper provides a brief overview of two power quality curves: the computer and Business Equipment Manufacturers' Association (CBEMA) curve, and the Information Technology Industry Council (ITIC) curve. These curves have been utilized in past decades as the common mechanisms to identify voltage variations and the duration of disturbances. Although these curves have proven to have great merit for use as tolerance curves, they may not capture all the necessary details of the events for power quality characterization.

关键词： Measurement Power quality Power system harmonics Observers Threshold voltage Classification algorithms Transient analysis

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