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2024 International Conference on Electrical engineering and Photonics, EExPolytech 2024

作者： Bugakova, Anna V. Frolov, Ilya V. Ivanov, Yuri I. Dmitrienko, Nadezhda A. Don State Technical University Dept. Scientific Research Dept. Information Systems and Radio Engineering Rostov-on-Don Russia Ulyanovsk Branch of the Kotelnikov Institute of Radioengineering and Elecronics of Russian Academy of Science Lab. Solid-State Electronics Opto- and Nanoelectronics Ulyanovsk Russia Southern Federal University Dept. Automatic Control Systems Rostov-on-Don Russia Dstu in Shakhty Dept. Foreign Languages Shakhty Russia

ISBN: (纸本)9798350388879

This paper considers the circuit method for neutralizing the effect of parasitic components of the collector load in silicon-germanium (SiGe) and silicon-on-insulator (SOI) classical cascade amplifiers and common-base stages on their voltage gain (Gain). The article demonstrates that the incorporation of a dedicated compensating circuit into the original circuits enables the enhancement of their upper frequency limit or gain by a factor of 5 to 10. The conditions for mitigating the impact of resistor parasites, which contribute to losses in planar inductance, on the Q-factor of the RLC-circuit of the selective amplifier are established. It is recommended that the proposed circuit solutions be employed in practical applications involving SiGe and SOI analog chips operating at elevated temperatures. © 2024 IEEE.

关键词： Cascode amplifiers

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Fail-Safe Decision Architecture for Positioning Failures on Automated Vehicles 9

Fail-Safe Decision Architecture for Positioning Failures on ...

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9th IEEE Smart World Congress, SWC 2023

作者： Rodriguez-Arozamena, Mario Aranguren-Mendieta, Inigo Perez, Joshue Zubizarreta, Asier Tecnalia Basque Research and Technology Alliance Bilbao Derio Spain Basque Research and Technology Alliance Industry and Mobility Unit Tecnalia Derio Spain Dept. of Automatic Control and Systems Engineering Bilbao Spain

ISBN: (纸本)9798350319804

Precise localization is essential for the operation of Connected and Automated Vehicles (CAVs) in urban scenarios. Camera and LiDAR-based solutions are currently used in some of the CAVs around the world, but they entail an expensive performance in terms of computational time and economic cost. Due to this, Global Navigation Satellite system (GNSS) based solutions remains the preferred solution for positioning Automated Vehicles in different Operational Design Domains (ODDs). Although several improvements in system reliability have been made recently, in case of positioning failures most of the architectures rely on system redundancy or automation disengagements to achieve minimal risk conditions. This paper presents a fail-safe decision architecture for mitigating positioning failures of automated vehicles in urban scenarios. The proposed architecture utilizes a combination of sensor fusion localization and decision-making modules to ensure the safe and efficient operation of the vehicle in the event of a positioning failure. The proposed approach is evaluated through simulation in a representative urban scenario and is shown to effectively handle positioning failures, improving the localization accuracy provided by each information source. © 2023 IEEE.

关键词： automated driving fail-safe operation fallback strategy positioning failure safe state

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Mobile Application for Visualizing the Measurements 5

Mobile Application for Visualizing the Measurements

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5th IEEE International Conference on Modern Electrical and Energy system, MEES 2023

作者： Kiresova, Simona Guzan, Milan Sobota, Branislav Melnykov, Viacheslav Yatsiuk, Rostyslav Peryvertailo, Bohdan Technical University of Košice Dept. of Theoretical and Industrial Electrical Engineering Košice Slovakia Technical University of Košice Dept. of Computers and Informatics Košice Slovakia Kremenchuk Mykhailo Ostrohradskyi National University Dept. of Systems of Automatic Control and Electric Drive Kremenchuk Ukraine National University Dept. of Computer Engineering and Electronics Kremenchuk Mykhailo Ostrohradskyi Kremenchuk Ukraine

ISBN: (纸本)9798350359787

This paper deals with the design of an Android mobile application and visualization of the measured values of particulate matter and meteorological factors from the measurement stations. The application can in principle be effectively used in any field of data visualization. The architecture of the mobile application, the security, the use of AWS services to access the data in the InfluxDB databases, as well as the user interface and graphical visualizations of the measured data are described and illustrated. The application is user tested and the paper documents their first experiences using the mobile application. © 2023 IEEE.

关键词： Visualization

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A Review of Rotation Mechanical Fault Diagnosis Research Based on Deep Domain Adaptation 9

A Review of Rotation Mechanical Fault Diagnosis Research Bas...

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9th IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2023

作者： Zhang, Shun Xie, Gang Tian, Juan Shi, Hui Zhang, Xiaohong Nie, Xiaoyin Xie, Xinlin Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan China Taiyuan University of Science and Technology Dept. of Electronic and Information Engineering Taiyuan China Division of Industrial and System Engineering Taiyuan China

ISBN: (纸本)9798350333794

With the rapid development of computer technology and the Internet of Things (IoT), a large amount of data containing both healthy and faulty states can be collected from existing devices in factories. However, the usable faulty state data is scarce. Transfer learning makes it possible to train efficient and reliable neural networks with a small number of samples. Domain adaptation, as a branch of transfer learning, can effectively realize knowledge transfer between small sample data. Starting from three subcategories of deep learning-based domain adaptation methods, this article summarizes the latest research achievements and provides insights into future research directions. © 2023 IEEE.

关键词： Failure analysis

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Efficient Deep Learning Models Based on Tension Techniques for Sign Language Recognition

SSRN

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SSRN 2023年

作者： Attia, Nehal F. Faheem Said Ahmed, Mohamed T. Alshewimy, Mahmoud A.M. Computer and Automatic Control Dept. Faculty of Engineering Tanta University Tanta Egypt

Among the various ways of self-expression and communication between people, communication by speaking prevails. Speech presents a significant challenge for some disabled people, such as the deaf, hearing impaired, wordless, and dumb persons. Therefore, these people rely on the use of sign language to interact with others. Sign language is a system of movements and visual messages that ensure the integration of these individuals into groups that communicate vocally. On the other side, it is necessary to understand the gestures and linguistic semantics of these individuals. The main objective of this study is to establish a new model that enhances the performance of the existing paradigms in use for the recognition of American Sign Language (ASL). Therefore, three enhanced deep-learning models of YOLOv5 for recognizing the alphabetic and numeric information conveyed by hand motions are presented in this paper. These models depend on using different attention approaches. The suggested models were evaluated using the MU HandImages ASL dataset. The proposed models yielded superior results compared to those achieved by the initial version of YOLOv5. The modified models have reached their maximum accuracy of 98.9%, maximum recall of 97.5%, maximum mAP 0.5 of 99.2%, and maximum mAP 0.5:0.95 of 98.9%. © 2023, The Authors. All rights reserved.

关键词： Computer vision

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PIDDNet: RGB-dept. Fusion Network for Real-time Semantic Segmentation 14

PIDDNet: RGB-Depth Fusion Network for Real-time Semantic Seg...

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14th International Conference on Information and Communication Technology Convergence, ICTC 2023

作者： Shin, Yunsik Lee, Chaehyun Son, Yongho Kim, YangGon Park, Junghee Choi, Jun Won Hanyang University Dept. Electrical Engineering Seoul Korea Republic of Lig Nex1 Co. Ltd. Dept. Ground Control System S/W Seongnam Korea Republic of Hanyang University Dept. Artificial Intelligence Seoul Korea Republic of

ISBN: (纸本)9798350313277

For RGB semantic segmentation, a two-branch network was proposed to effectively utilize both local detail information and global contextual information within an RGB image. This architecture combines a shallow spatial path with a deeper context path, resulting in high performance and FPS. Research on RGB-dept. segmentation has shown the performance gain that the dept. map could provide complementary information to the RGB model. However, the advantage of fusing RGB and dept. map within a two-branch network framework is unclear due to the distinct characteristics of these modalities. To address this, we present a novel fusion RGB-dept. architecture that takes into account the attributes of local context, global context, RGB, and dept. map. Through the bidirectional image dept. fusion technique, we effectively leverage each of the modalities, achieving a performance of 81.23 mIoU. This marks a gain of 1.27% when compared to the RGB-only model and 0.45% when contrasted with the element-wise feature addition fusion baseline. © 2023 IEEE.

关键词： Deep Learning RGB-dept. Fusion Semantic Segmentation

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A latent representation of brain networks based on EEG ⁎

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IFAC-PapersOnLine 2024年第15期58卷 414-419页

作者： Lucia Falconi Giulia Cisotto Mattia Zorzi Automatic Control Laboratory ETH Zurich Physikstrasse 3 8092 Zurich Switzerland Dept. of Informatics Systems and Communication University of Milano-Bicocca Milan Italy Dept. of Information Engineering University of Padova Italy Dept. of Information Engineering University of Padova Italy

Electroencephalography (EEG) is one of the most popular techniques to investigate normal as well as pathological cerebral mechanisms, as it allows to measure, non-invasively and in real-time, the brain activity. However, modeling EEG is still extremely challenging, because of its high-dimensionality, low signal-to-noise ratio, and high individual variability. This paper proposes a novel latent representation to study brain networks using EEG by means of a robust dynamic factor analysis (RDFA) approach. We investigate the ability of this latent representation to discriminate between two groups of subjects, i.e. alcoholic and healthy. By RDFA, we can extract a limited number of highly explanatory factors, as low as 8, significantly discriminating between the two groups. Also, we show that different brain patterns can be identified across different stimulation scenarios and EEG locations. Although preliminary, this work could give support to domain experts while providing some clinically-meaningful insights to identify common patterns as well as individual characteristics in different groups of healthy and pathological subjects.

关键词： EEG system identification dynamic factor analysis

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Optimization Scheduling of Multi-Energy Microgrid Based on the QUBO Quantum Computing Model 19th

Optimization Scheduling of Multi-Energy Microgrid Based on t...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Wang, Baonan Wang, Hui Zhang, Dan College of Computer Science and Technology Shanghai University of Electric Power Shanghai China State Key Laboratory of Power System Operation and Control Dept. of Electrical Engineering Tsinghua University Beijing China Institute of Logistic Science and Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9789819608966

Current optimization methods for microgrid scheduling face issues such as insufficient precision in energy distribution, high operational costs, and inefficiency. In response to these challenges, an optimization scheduling method for multi-energy microgrids based on the QUBO (Quadratic Unconstrained Binary Optimization) quantum computing model is proposed in this paper, alongside a discretization approach based on a grid partitioning strategy. To validate the feasibility of addressing microgrid optimization scheduling problems in a quantum computing environment, a QUBO model is constructed and simulation studies are conducted in the qbsolv environment provided by D-Wave. The results indicate that operational costs are significantly reduced with an increase in the number of grids, particularly a reduction of 4.52% when the number of grids increases from five to ten. This method not only effectively enhances the precision of electricity supply and energy utilization efficiency but also reduces unnecessary electrical waste and economic costs. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Microgrids

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MMC Based D-STATCOM control by Using a Modified ADRC Strategy 8

MMC Based D-STATCOM Control by Using a Modified ADRC Strateg...

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8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023

作者： Neto, João A. Moor Zachi, Alessando R. Paucar, Braulio Chuco Do Brasil, Thiago Americano Mussa, Samir Ahmad CEFET-RJ Department of Electrical Engineering Rio de Janeiro Brazil CEFET-RJ Department of Control System and Automation Engineering Rio de Janeiro Brazil UFSC - Sc Dept. of Electrical and Electronic Engineering Florianopolis Brazil

ISBN: (纸本)9798350321128

This paper presents investigations of a transformerless half bridge sub-module (HBSM) modular multilevel converter based distribution static synchronous compensator (MMC D-STATCOM) performance in reactive power compensation considering the application of the modified ADRC controllers in the inner current loop and in the outer DC voltage loop using Synchronous Reference Frame control. Simulation results with the imposition of severe variations in reactive loads were obtained on a 5 km medium voltage feeder and will demonstrate that the modified ADRC controller enables superior performance for flexible operation with fast and efficient response of the MMC D-STATCOM in reactive power compensation. © 2023 IEEE.

关键词： ADRC controller D-STATCOM PI controller PSCAD/EMTDC Reactive Power Compensation

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Influence of Specimen Selection on Lifetime Prediction of Low Voltage Electrical Machines Under Variable Temperature Aging

Influence of Specimen Selection on Lifetime Prediction of Lo...

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2024 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2024

作者： Zhou, Xuanming Ji, Yatai Giangrande, Paolo Zhao, Weiduo Galea, Michael Ijaz, Salman University Of Nottingham Ningbo China Key Laboratory Of More Electric Aircraft Technology Of Zhejiang Province Ningbo China Tsinghua University Department Of Electrical Engineering Beijing China University Of Bergamo Dept. Of Engineering And Applied Sciences Dalmine Italy University Of Malta Dept. Of Electrical Engineering Msida Malta University Of Nottingham Ningbo China Control System Labrotary Ningbo China

ISBN: (纸本)9798331529277

To a great extent, electric machine (EM) lifetime is affected by electrical failures that compromise the integrity of the windings electrical insulation system (EIS). During EMs operation, the EIS suffered various stresses, such as, thermal, electrical, mechanical and ambient (TEAM), which lead the deterioration and decrease the dielectric property of EIS. However, under rated operating conditions, the entire degradation process can take several years before insulation breakdown occurs. Thus, accelerated lifetime tests (ALT) are conventionally performed on various high stress level. Furthermore, the suitable specimen topology should be chosen according to the ALT task objectives, which is also crucial to the resulted lifetime values. In this paper, ALTs at variable temperature profile are performed using two types of specimens (i.e., coils and motorettes). Then, the collected lifetime data are analyzed by statistical tools and the underlying stress mechanism is discussed. Finally, the thermal-mechanical stress is pointed out as the primary factor contributing to lifetime prediction mismatch. © 2024 IEEE.

关键词： Machine windings

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