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14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Kim, Jungho Jo, Hyunkyeong Seo, Seoktae Lee, Bonyoung Min, Hyungki Bien, Franklin Ulsan National Institute of Science and Technology School of Electrical and Computer Engineering Ulsan Korea Republic of Ulsan National Institute of Science and Technology Program in Information & Communication Technology Convergence Ulsan Korea Republic of

ISBN: (纸本)9798331516116

This paper proposed a novel landing platform with wireless power transfer (WPT) to charge multiple unmanned aerial vehicles (UAVs) without restrictions on landing locations or alignment. A transmitter is designed using wires to charge a wide area. To overcome the disadvantages of system made by wires, a grid pattern transmitter and double power line are proposed. These structures provide multiple charging with free positioning of receivers and excite the transmitter lines in wide area properly. The optimized system is composed of 0.15m square cells, providing a 0.9 m by 0.9 m charging area. By experiment, it can efficiently charge four 0.1 m square receivers located anywhere in transmitter. The overall efficiency of four receivers is 37.5%. Also, the experimental results verify that it is unnecessary to align the receiver within the cell, as it has a 2.62% error due to rotation and a 2.94 % error due to position within the cell. © 2025 IEEE.

关键词： Drones

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EDM10: A Polyphonic Stereo Dataset with Identical BGM for Musical Instrument Identification 27th

EDM10: A Polyphonic Stereo Dataset with Identical BGM for ...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Mukherjee, Himadri Marciano, Matteo Dhar, Ankita Roy, Kaushik TISA Lab Department of Computer Science West Bengal State University Barasat India Gazelien Records Lab Department of Arts and Humanities Music Program New York University Abu Dhabi Abu Dhabi United Arab Emirates Department of Computer Science and Engineering Sister Nivedita University New Town India

ISBN: (纸本)9783031784972

Music Signal Processing has significantly evolved in the past decades. One of the major areas of interest in this field has been automatic music transcription. It is a challenging task by itself that aggravates even more when the input audio is polyphonic (multiple instruments and timbres are played simultaneously). This requires the identification of musical instruments in the piece at the outset. The field of music signal processing that deals with this aspect is known as automatic music instrument identification. This field also has the potential of categorizing and recommending music based on instruments. Disparate datasets have been proposed to date for this task but none of them have interclass background similarity to the best of our knowledge. Further, the lead melody being played also varies from class to class in most cases. These aspects can introduce a possible bias for the machine learning models that can get manipulated unfairly by the additional variances in the classes other than the lead instrument itself. This sets the stage for a dataset where the classes are different only in terms of the tone of the lead instrument alone. In this paper, we introduce the first musical instrument dataset of 10 musical instruments with Electronic Dance Music melodies (EDM10) having identical background music (BGM) across instruments. This dataset is the first of its kind wherein synthetic tones have been used that have taken over the Globe. We introduce out-of-mood testing using exotic scales for musical instrument identification. The dataset is composed of 35800 polyphonic clips of 3 s each and a baseline result of 89.73% was obtained using a deep learning-based approach. The dataset is freely available for research purposes. https://***/yV5e36TK1jHMKjpC6. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Electronic musical instruments

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CNN-based multiplexed optical fiber sensors for multi-load mapping on 2D structures

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Optical Fiber Technology 2025年 93卷

作者： de Carvalho, Vinicius Martins, Victor Hugo Flores, Walter Oswaldo C. Muller, Marcia Fabris, José Luís Lazzaretti, André Eugenio UTFPR Graduate Program in Electrical and Computer Engineering Av. Sete de Setembro 3165 Paraná Curitiba80230-901 Brazil

This paper reports the application of a Convolutional Neural Network specifically designed for one-dimensional optical signal processing to determine the magnitude and position of loads acting on a structure instrumented with multiplexed macrobend optical fiber sensors, offering a cost-effective and low complexity alternative for force monitoring solutions. The system effectively localized and quantified one, two, or three simultaneous loads within 16 distinct sensing areas, utilizing only five in-series optical fiber sensors, which were spectrally interrogated in transmission mode. The monitored loads ranged from 1000 to 2000 gf. The use of the Huber loss function allows the model to adaptively predict values associated with regions with or without loads. Experimental results showed an average mean absolute error of 224±65 gf during testing. By applying a straightforward post-processing method for load presence detection in each region, the system achieved average F1 scores ranging from 0.84 to 0.93 across the monitored regions, and an average Hamming score of 0.93. These findings demonstrate the system's effectiveness in monitoring multiple loads, underscoring the potential of optical fiber sensors and CNNs in sensing applications. © 2025 Elsevier Inc.

关键词： Convolutional neural network Load mapping Macrobend sensor Optical fiber sensor

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Performance Evaluation of Multi-ONU Customers Access Network using Spectrum Slicing and Duplication Techniques 5

Performance Evaluation of Multi-ONU Customers Access Network...

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5th International Conference on Emerging Electrical Energy, Electronics and Computing Technologies, ICE4CT 2024

作者： Rahman, Juwairiyyah Abdul Mugunthan, Sivaguru A.L. Hassan, Hasliza Abu Muslim, Norliana Ab-Rahman, Mohammad Syuhaimi Department of Electrical Engineering Faculty of Engineering and Life Sciences Universiti Selangor Selangor Bestari Jaya45600 Malaysia Department of Computer and Communication Technology Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Perak Kampar31900 Malaysia Department of Electrical Electronics and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Malaysia Electrical and Computer Engineering Program Faculty of Engineering Sohar University PC:311 Sohar Oman

This study aims to increase the number of access users by limiting the sample size to 30 users while ensuring that every Optical Network Unit (ONU) receives data from the Optical Line Terminal (OLT). The proposed solution allows for the determination of power requirements at each ONU based on bus-star topologies, facilitating an increase in user capacity. The power received by each ONU is a critical parameter that system designers must consider when planning the implementation of Fiber to the Home (FTTH), as it impacts the output data in terms of Bit Error Rate (BER) and Signal Quality Factor (QF) for each user. Various parameters were evaluated to ensure that the enhanced network improves scalability while adhering to standard specifications. These parameters included the Q-factor, BER, eye diagram, user count, and received power. The study employed slicing and duplication techniques, utilizing Arrayed Waveguide Grating (AWG) for signal duplication and Wavelength Division Multiplexing for signal slicing. The simulations were conducted using a transmitter operating at a frequency of 1491 nm with a power output of 0 dBm, utilizing the latest version of OptiSystem 20 software. The results highlighted the system's capability to support a total of 73,728 users, meeting stringent performance criteria. Specifically, the system achieved a Q-factor greater than 6, indicating high signal quality, and a bit error rate (BER) lower than 1 × 10-9, ensuring reliable data transmission. For the sampled 30 users, the average Q factor was 8.1527, and the average BER was 5.3648 × 10^-11, with an output power level of -54.278 dBm. Despite an increase in users, the quality of the data supplied to clients remained unchanged. These outcomes underscore the robustness and efficiency of the design in delivering high-capacity, error-resilient optical communication. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Q factor measurement

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A Design Study on Integrated Complex Coefficient Filters with Peripheral Circuits for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2025年第1期145卷 16-24页

作者： Shouno, Kazuhiro Sato, Lina Fukagawa, Kanta Tanimoto, Hiroshi Muto, Cosy Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan

This paper proposes a measurement technique for an integrated complex filter. The proposed method is based on two measurement methods with integrated circuitry for calibration. It is accomplished by applying square waves to an FUT (Filter Under Test) instead of sinusoidal waves or by superposing transfer characteristics obtained by applying a single sinusoidal wave to an FUT. In both of the above methods, the output signal connected to the external measurement equipment via a 50 Ω coaxial cable and so on. In this case, the output signal of the FUT should be amplified by internal or external amplifiers, which degrades the response. However, it is cancelled out by the proposed calibration circuitry with some analog switches. In addition to the above, for the RC polyphase filter, the source resistance and the load capacitance degrade the measurement results and their effect is discussed. The validity of the proposal is confirmed through computer simulation for a third-order RCPF whose passband is 8–40 MHz fabricated by Phenitec 0.6 µm CMOS process. It is shown that the measurement error is −1.10 dB for the square-wave method and −1.00 dB and −0.43 degrees for the superposition method at 40 MHz. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Capacitance

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Multiplexing B5G/6G Services Over Aerial VLC Networks: A Comprehensive Radio Resource Management Framework

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IEEE Internet of Things Journal 2025年第9期12卷 11600-11621页

作者： Zarini, Hosein Gholipoor, Narges Mili, Mohammad Robat Rasti, Mehdi Movaghar, Ali Choi, Jinho Chae, Chan-Byoung Sharif University of Technology Department of Computer Engineering Tehran11365-8639 Iran University of Oulu Center for Wireless Communications Oulu90570 Finland Pasargad Institute for Advanced Innovative Solutions Tehran1111111 Iran The University of Adelaide School of Electrical and Mechanical Engineering North Terrace AdelaideSA5005 Australia Yonsei University School of Integrated Technology BK21 Graduate Program in Intelligent Semiconductor Technology Seoul03722 Korea Republic of

Downlink transmission of a nonorthogonal visible light communication (VLC) system, empowered by autonomous aerial vehicles (AAVs), is studied for coexisting enhanced mobile broadband (eMBB), ultrareliable low-latency communication (URLLC), and massive machine-type communication (mMTC) services. A joint resource allocation problem involving user association, transmit power, and flight trajectory of AAVs is formulated, with the goal of characterizing a multiobjective tradeoff as a weighted sum of the power consumption of each AAV and the perceived Quality of Experience (QoE) of its associated eMBB users, while ensuring the service-specific requirements for eMBB, mMTC, and URLLC are met. Assuming the imperfection of channel state information (CSI), we invoke a generalized Benders decomposition (GBD) methodology, leveraging tools from convex optimization and multiagent deep reinforcement learning to address this problem. We further analytically derive the upper and lower bounds on the reward function for each AAV as a learning agent. Extensive simulations confirm that our proposed method outperforms the single-agent counterpart in the literature, with up to a 22% reduction in power consumption and a 13% gain in perceived QoE. Additionally, compared to the globally optimal brute-force method for AAV-user association, our proposed method experiences only a trivial performance loss in a small-scale scenario. © 2014 IEEE.

关键词： Convex optimization

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Comparative Analysis of Clusterization Methods Applied to a Solid-State LiDAR

Comparative Analysis of Clusterization Methods Applied to a ...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Henrique N. Poleselo Andre G. S. Conceicao Postgraduate Program in Electrical Engineering Federal University of Bahia Salvador Brazil Department of Electrical and Computer Engineering Federal University of Bahia Salvador Brazil

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Object segmentation is one of the main activities for the robot to create a sense of its environment. This task is a precursor to other activities, such as autonomous navigation in a given environment. Through sensors such as LiDAR, it's possible to generate high-resolution three-dimensional maps of the environment in which the robot is located, thus enabling their interpretation so that tasks such as object segmentation can be performed. In this article, the DBSCAN and HDBSCAN unsupervised clustering methods are explored. Results in a simulated environment in Gazebo together with Robot Operating System ROS framework for capturing sensory data from LiDAR Livox Mid-70 coupled to a mobile robot show the performance of such techniques through comparisons.

关键词： Laser radar Operating systems Clustering methods Object segmentation Robot sensing systems Sensors Mobile robots Autonomous robots

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Control of an Underactuated Quadrotor Using LQR and Visual Markers

Control of an Underactuated Quadrotor Using LQR and Visual M...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Gabriel Fernandes Andre G. S. Conceicao Humberto X. De Araújo Postgraduate Program in Electrical Engineering Federal University of Bahia Salvador Brazil Department of Electrical and Computer Engineering Federal University of Bahia Salvador Brazil

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

In this study, a robust Linear Quadratic Regulator (LQR) controller was developed and evaluated for the Bebop 2 quadrotor drone. Polytopic uncertainties in the dynamic model were taken into account in the control design, ensuring robustness. The drone's localization was achieved using fiducial markers and a Kalman Filter for state estimation, integrating visual and positional data. The controller design utilized Linear Matrix Inequalities (LMIs) to optimize performance while accounting for system constraints. A circular trajectory in three-dimensional space was employed to assess the controller's effectiveness in simulation. Results demonstrated precise trajectory tracking, stability, and robust performance despite parameter uncertainties. These findings highlight the applicability of the proposed framework for real-world scenarios involving underactuated UAVs.

关键词： Location awareness Visualization Uncertain systems Uncertainty Trajectory tracking Stability analysis Trajectory Vehicle dynamics Quadrotors Drones

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An Environmentally Friendly Fishing Android-Based Mobile Device App for Penghu Islands (Pescadores), Taiwan

An Environmentally Friendly Fishing Android-Based Mobile Dev...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Hung-Tu Lin Ke-Qing Yan Ying-Zun Fang Xiang-Rui Huang Liang-Bi Chen Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Electrical Engineering Master Program in Electrical Engineering and Computer Science National Penghu University of Science and Technology Penghu Taiwan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Penghu Islands (Pescadores), Taiwan's outlying islands surrounded by the sea, boast rich fishing resources that attract many anglers. However, successful fishing requires more than just gear: it involves understanding the varying fish species available in different locations, times, and climates, as well as adhering to relevant laws and regulations. To address these needs, this paper proposes an environmentally friendly fishing Android-based mobile device App specifically for the Penghu Islands. The proposed Android-based mobile device App aims to gather essential information, including local fishing regulations, aquatic safety tips, and important precautions. Its goal is to equip fishermen with the resources necessary to fish successfully and with peace of mind.

关键词： Sea measurements Length measurement Fish Regulation Mobile applications Tides Protection Smart phones Meteorology Lenses

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Hybrid Deep Learning Model for Accurate Short-Term Electricity Price Forecasting

Hybrid Deep Learning Model for Accurate Short-Term Electrici...

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Moradzadeh, Arash Mouhammadpourfard, Mostafa Weng, Yang Pol, Suhas Muyeen, S.M. Qatar University Department of Electrical Engineering Doha Qatar National Wind Institute Texas Tech University LubbockTX United States School of Electrical Computer and Energy Engineering Arizona State University TempeAZ United States Texas Tech University Renewable Energy Program LubbockTX United States

ISBN: (纸本)9798331541125

Accurate short-term electricity price forecasting (STEPF) is critical for efficient energy market operations, guiding investment strategies, resource allocation, and consumer behavior. This study introduces a hybrid deep learning approach specifically designed to improve STEPF accuracy by leveraging historical Hourly Ontario Energy Price (HOEP) data from 2017 to 2019. The model integrates advanced techniques, including data preprocessing and denoising through a Stacked Denoising Autoencoder (SDAE), along with enhanced temporal modeling via Bidirectional Long Short-Term Memory (BiLSTM) and Gated Recurrent Unit (GRU) networks. By capturing the complex dynamics inherent in electricity pricing data, the proposed hybrid model significantly enhances forecasting accuracy. Trained on data from 2017 and 2018, with 2019 used for testing, the model achieves a strong correlation coefficient (R = 99.86%) and substantially lowers forecasting errors. Comparative evaluations against established forecasting methods highlight the model's superior performance. This work demonstrates the practical value of deep learning techniques in the energy sector, particularly in responding to the volatility of demand and supply in real-time electricity markets. © 2025 IEEE.

关键词： Electricity market forecasting Energy management Hybrid deep learning models Short-term electricity price forecasting Temporal data analysis

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