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检索条件"任意字段=IEEE Conference on Control Technology and Applications"

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technology trends of automotive semiconductors for CASE application

Technology trends of automotive semiconductors for CASE appl...

引用

International Power Electronics conference (IPEC-Himeji - ECCE Asia)

作者： Eguchi, Hiroomi MIRISE Technol Corp Planning & Adm Div Nisshin Aichi Japan

CASE is a new word referred to "Connected", "Autonomous", "Shared & Service", "Electric". In the CASE era, technological advances in CASE are significantly changing the conc... 详细信息

ISBN: (纸本)9781665416313

CASE is a new word referred to "Connected", "Autonomous", "Shared & Service", "Electric". In the CASE era, technological advances in CASE are significantly changing the concept of the automobile and semiconductors play an important role. Regarding its technology for automotive applications, many specific requirements should be achieved to implement power devices onto EVs, peripheral monitoring sensors on autonomous driving, and SoCs for driving control. Due to the fact that, they should be developed by automobile makers or auto parts manufacturers themselves. In this paper, the technology trends of automotive semiconductors for CASE application will be reported, and the technology of power devices for electrification and peripheral detection sensors for autonomous driving will be focused on.

关键词： CASE SiC EV power device sensor

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SecGes: A Secure Biometric-Driven Hand Gesture Recognition System for Smart Wheelchair Movement 17

SecGes: A Secure Biometric-Driven Hand Gesture Recognition S...

引用

17th ieee International conference on Advanced Networks and Telecommunications Systems, ANTS 2023

作者： Kaur, Gurleen Gupta, Bakul Saini, Devanshi Mohindru, Kashika Nehra, Anushka Thapar Institute of Engineering and Technology Computer Science and Engineering Department Patiala India

ISBN: (纸本)9798350307672

In this paper, we present, SecGes, an innovative solution to enhance the mobility and accessibility of smart wheelchairs by integrating deep learning-based hand gesture recognition with the YOLO Version-8 DL model. The main objective is to create an intuitive and efficient control system for wheelchairs, allowing users to navigate their environment effortlessly. We incorporate contactless fingerprint biometric authentication using HSV and YCbCr based Image Segmentation and CNN classification to ensure secure and personalized access to the wheelchair. This dual system not only empowers users ability to control their mobility through intuitive hand gestures but also prioritizes safety and security through biometric authentication. We leverage deep learning techniques to design a robust and adaptable framework having potential to significantly improve the quality of life of an individual with mobility impairments. The results obtained demonstrate the feasibility and effectiveness of the proposed approach in smart wheelchair technology, with promising implications for broader assistive technology applications. © 2023 ieee.

关键词： Deep learning

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Improved Estimation Accuracy of HD-sEMG Decomposition via an Image K-means Clustering and Removal Strategy 50

Improved Estimation Accuracy of HD-sEMG Decomposition via an...

引用

50th Annual conference of the ieee Industrial Electronics Society, IECON 2024

作者： He, Jinbao Yang, Shenwu Huang, Kai School of Electronics and Information Engineering Ningbo University of Technology Ningbo China Ningbo First Hospital Ningbo University Ningbo China

ISBN: (纸本)9781665464543

Over the past few decades, several methods for decomposing electromyographic (EMG) signals into motor unit action potentials (MUAPs) have been reported, but there is still much room for improvement. Here, a new method for decomposing high-density surface EMG (HD-sEMG) signals is proposed. First, the firing time is extracted based on the linear minimum mean square error (LMMSE) algorithm. Second, the waveforms corresponding to the firing time are converted into images, and the images are spliced on the electrodes of the column in which the motor unit is located. Third, the images corresponding to the multiple firing times are clustered and averaged, and the motor unit action potential (MUAP) train is obtained iteratively. Finally, the extracted MUAPs are removed from the original signals, and the cycle further decomposes the residual signals. The simulation results show that the interval pulse trains can be reconstructed with a true positive rate (TPR) of greater than 91.32 ± 4.17%. According to the experimental results, 14-20 MUs were extracted, and the ratio of common discharges was determined to be 0.81 ± 0.03% via the two-source method. The simulation and experimental results show that the proposed method is accurate and efficient with potential applications in rehabilitation and motion control systems. © 2024 ieee.

关键词： Mean square error

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Power Quality assessment of Thyristor controlled Reactor supported inductively Coupled Hybrid DSTATCOM using Deep learning 3

Power Quality assessment of Thyristor controlled Reactor sup...

引用

3rd ieee International conference on Smart Technologies for Power, Energy and control, STPEC 2023

作者： Kundala, Praveen Kumar Yadav Mangaraj, Mrutyunjaya Vijaythakur, Rohan Sabat, Jogeswara Lendi Institute of Engineering and Technology Department of Eee Vizianagaram India Srm University Department of Eee Andhrapradesh Amaravati India Prof Ram Meghe College of Engineering & Management Department of Electrical Engineering Badnera India Outr Department of Electrical Engineering Odisha India

ISBN: (纸本)9798350304732

In this research paper, a Thyristor controlled reactor supported inductively coupled hybrid distributed static compensator (ICH-DSTATCOM) for three-phase three-wire (3P3W) distribution system (DS) is planned. The hybrid distributed static compensator (H-DSTATCOM) is a hot topic among scientists studying power quality (PQ) problems. The majority of published papers, however, avoid discussing H-DSTATCOM design. This paper proposes a design of a distributed static compensator (DSTATCOM) utilised to compensate for an uncontrolled rectifier load jointed to a 3P3W network. The filtering mechanism is performed by inductively coupled voltage source converter using the deep learning approach. The Thyristor controlled reactor (TCR) is incorporated in series with compensator inductance. The detailed design of TCR for the elimination of error caused by the system unbalance is discussed by using the mathematical equations. The MATLAB/ Simulation outcomes show that enhanced potential control & balancing, harmonic mitigation, and good power factor (pf) with the proposed topology as per the guidelines imposed by ieee-519-2017. © 2023 ieee.

关键词： Deep learning ICH-DSTATCOM TCR and PQ

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Mathematical Modelling of Slotted Circular Meta-atom for Holographic Meta-Surface applications 2

Mathematical Modelling of Slotted Circular Meta-atom for Hol...

引用

2nd International conference on Microwave, Optical and Communication Engineering, ICMOCE 2023

作者： Ghosh, Swarnadipto Saha, Dipankar Prahannathan, V. Saha, Chinmoy Indian Institute of Space Science & Technology Department of Avionics Thiruvananthapuram India

ISBN: (纸本)9798350321609

In this article, a systematic methodology and closed form mathematical modelling of circular center aligned single & cross-slotted holographic meta-atom structures have been proposed, to estimate the characteristics of the surface impedance variation based on the different slot parameters of the meta-atoms. This mathematical modelling provides the idea of the design considerations and regulations of the response of artificial impedance surface techniques to control the depth of modulation of the surface. © 2023 ieee.

关键词： Atoms

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Accuracy and cross-sensitivity analysis of the PMS5003 formaldehyde sensor 27

Accuracy and cross-sensitivity analysis of the PMS5003 forma...

引用

27th ieee Signal Processing: Algorithms, Architectures, Arrangements, and applications, SPA 2024

作者： Bronczyk, Karolina Adamski, Michal Dabrowska, Agata Konieczka, Adam Dabrowski, Adam Adam Mickiewicz University Faculty of Chemistry Department of Trace Analysis Poznań Poland Poznan University of Technology Division of Electronic Systems and Signal Processing Institute of Automatic Control and Robotics Poznań Poland

ISBN: (纸本)9788362065486

Measurement data produced with the PMS5003 electrochemical sensor, allegedly selective for formaldehyde, were analyzed. The amounts of formaldehyde released from heated standard solutions were measured. At the same time, samples were sorbed into sorption tubes with an XAD-2 cartridge, which enabled chromatographic analysis - gas chromatography coupled with an electron capture detector (GC-ECD). A susceptibility of the PMS5003 sensor to cross-sensitivity associated with the presence of other low-molecular-weight carbonyl compounds, such as acetaldehyde and acetone in the sample, was also tested. The conducted research clearly indicates poor selectivity/accuracy of the PMS5003 sensor in relation to formaldehyde and its sensitivity to the presence of other carbonyl compounds in the sample, with a structure similar to formaldehyde. © 2024 Division of Signal Processing and Electronic Systems, Poznan University of technology (DSPES PUT).

关键词： Acetone

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Multi-Modal Emotion and Gesture Recognition System for Humans and Animals Using Computer Vision and Deep Learning 5

Multi-Modal Emotion and Gesture Recognition System for Human...

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5th International conference on IoT Based control Networks and Intelligent Systems, ICICNIS 2024

作者： Nair, Rekha R Babu, Tina Kishore, S. Shivaswamy, Smitha Aruna, S. Bhargavi, Manchikalapudi Alliance School of Advanced Computing Alliance University Department of Computer Science and Engineering Bengaluru India Department of Computer Application Karnataka Mangaluru India Acharya Institute of Technology Department of Computer Applications Bengaluru India School of Science and Computer Studies CMR University Bangalore India Hyderabad India

ISBN: (纸本)9798331518097

Emotion recognition through facial expressions and gesture analysis has emerged as a key area of research in computer vision and human-computer interaction. The ability to automatically detect and classify human emotions has wide-ranging applications, from enhancing user experiences to improving mental health monitoring and surveillance systems. This project builds on this background to develop a comprehensive system for recognizing emotions and gestures in both humans and animals. The system integrates facial emotion recognition, hand gesture interpretation, and animal emotion detection into a single platform. Using advanced deep learning models and computer vision libraries, the system classifies facial expressions into categories such as happiness, sadness, anger, fear, surprise, and neutral. The gesture recognition component interprets hand signals to convey messages like 'need help' or 'need water.' An innovative aspect of this work is the extension of emotion recognition to animals, particularly focusing on species like dogs and monkeys. Implemented primarily in Python, the system leverages libraries such as OpenCV and DeepFace. By combining these different modalities of nonverbal communication analysis, the project presents a versatile solution with potential applications in human-computer interaction, mental health monitoring, security, and animal welfare. © 2024 ieee.

关键词： Gesture recognition

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Dead-Beat Predictive control of DFIG-DC Based on Data-Driven Neural Network Predictor 14

Dead-Beat Predictive Control of DFIG-DC Based on Data-Driven...

引用

14th ieee International conference on Power Electronics and Drive Systems, PEDS 2023

作者： Liu, Lu Wang, Guangqiang Gu, Nan Wang, Dan Peng, Zhouhua Dalian Maritime University School of Marine Electrical Engineering Dalian116026 China

ISBN: (纸本)9798350399967

This paper is concerned with the dead-beat predictive control of a doubly fed induction generator in the presence of fully unknown motor parameters. Only the current and voltage values of the rotor are measured in the control system. Firstly, data-driven neural network predictors are proposed to approximate the model uncertainties as well as the unknown control gains. Based on the predictors, a dead-beat predictive controller is designed without any prior knowledge of model parameters. The input-to-state stability of the closed-loop system is proved by using the cascade theory. Simulation results show the effectiveness of the proposed dead-beat predictive control of a doubly fed induction generator based on data-driven neural network predictors. © 2023 ieee.

关键词： Closed loop systems

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Emotional Synchronization for Audio-Driven Talking-Head Generation 24

Emotional Synchronization for Audio-Driven Talking-Head Gene...

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24th ieee International conference on Data Mining, ICDM 2024

作者： Zhang, Zhao Luo, Yan Zuo, Zhichao Hong, Richang Yang, Yi Wang, Meng School of Computer Science and Information Engineering University of Technology Hefei China Yunnan Key Laboratory of Software Engineering Yunan China School of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (纸本)9798331506681

Audio-driven talking-head synthesis has become a significant focus in the field of virtual human applications. However, existing methodologies face challenges in effectively synchronizing audio and video, especially in maintaining emotional consistency. Additionally, there is a notable inefficiency in leveraging emotional prompts to guide expression generation. To address these limitations, this paper introduces an Emotion Synchronized audio-driven Talking-head synthesis (EST) approach. The EST approach aims to enhance the emotion-agnostic talking-head models by enabling emotion control, and it incorporates a diffusion module to learn diverse latent rep-resentations. Furthermore, EST utilizes null-text embedding to align the latent code with emotional prompts. Additionally, a novel Sync Attention Block (SAB) is developed to broaden the spatial perceptual field, thus preventing the loss of critical information. Extensive experiments demonstrate the effectiveness of the EST method, showcasing state-of-the-art performance across widely-adopted datasets. Moreover, the EST approach exhibits exceptional generalization capabilities, even in scenarios where emotional training videos are unavailable. © 2024 ieee.

关键词： Synchronization

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Incorporating Magnetic Saturation in the Modeling of Boost Converters

Incorporating Magnetic Saturation in the Modeling of Boost C...

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2024 International conference on Materials and Energy: Energy in Electrical Engineering, ICOME-EE 2024

作者： Poonnoy, Nitchamon Saksiri, Wiset Gavagsaz-Ghoachani, Roghayeh Phattanasak, Matheepot Pierfederici, Serge King Mongkut's University of Technology North Bangkok Faculty of Technical Education Department of Teacher Training in Electrical Engineering Bangkok Thailand Shahid Beheshti University Faculty of Mechanical and Energy Engineering Renewable Energy Department Tehran Iran Université de Lorraine CNRS LEMTA Nancy France

ISBN: (纸本)9798331531577

This paper presents a small-signal model for the boost DC-DC converter, considering the nonlinear magnetic characteristics of the inductor that affect system stability. The converter is designed with an optimized inductor core for space-constrained applications where output voltage quality is less critical, such as wind turbine kites and wave energy generators. Traditional linear controllers may underperform due to inductor nonlinearity. This study investigates the impact of magnetic saturation and shows that neglecting these effects degrades control performance. The simulation results align with the system's eigenvalues by explicitly incorporating the inductor's nonlinear characteristics, confirming the model's accuracy. © 2024 ieee.

关键词： Eigenvalues and eigenfunctions

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