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检索条件"机构=Control and Computer Engineering"

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SS-DBSCAN: Epsilon Estimation with Stratified Sampling for Density-Based Spatial Clustering of Applications with Noise

SS-DBSCAN: Epsilon Estimation with Stratified Sampling for D...

引用

2023 International Conference on Automation, control and Electronics engineering, CACEE 2023

作者： Monko, Gloriana Joseph Kimura, Masaomi Shibaura Institute of Technology Graduate School Department of Functional Control Systems Tokyo Japan Shibaura Institute of Technology Department of Computer Science and Engineering Tokyo Japan

ISBN: (纸本)9798350309201

Clustering algorithms are crucial in uncovering hidden patterns and structures within datasets. Among the density-based clustering algorithms, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) has gained considerable attention for its effectiveness in various applications. However, determining appropriate parameter values for this algorithm remains a challenging task. This paper presents a novel methodology for eps parameter estimation for an improved DBSCAN, namely SS-DBSCAN. The experimental results across nine datasets demonstrate the efficacy of our proposed method in accurately determining clusters with eps value from SS-DBSCAN algorithm. The clusters identified using estimated eps values by SS-DBSCAN align well with the inherent structure of the datasets, yielding better cluster results than the manually set parameters and other methods used for automatic estimations of the eps for DBSCAN. Our approach adapted well to the peculiarities of each dataset, whether dealing with different scales, dimensions, or densities;it proved the versatility and robustness across various datasets, thereby emphasizing its generalizability and potential for broader applications. © 2023 IEEE.

关键词： Parameter estimation

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High-Precision UAV Micro-Motion Feature Extraction and Estimation Method Based on Local Maximum Synchroextracting Transform 6

High-Precision UAV Micro-Motion Feature Extraction and Estim...

引用

6th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2023

作者： Yuan, Wang Chen, Xiaolong Du, Xiaolin Yu, Gang He, Xiaoyang School of Computer and Control Engineering Yantai Unversity Yantai China Naval Aviation University Marine Target Detection Reaserch Group Yantai China School of Electrical Engineering Universiy of Jinan Jinan China

ISBN: (纸本)9798350399059

Accurately estimating the micro-motion parameters of unmanned aerial vehicles (UAVs) is of significant importance for UAV recognition and classification. Traditional time-frequency analysis methods have low resolution and suffer from severe cross-term interference, making it challenging to precisely estimate the micro-motion parameters of UAVs. In order to slove this problem, this paper proposes a high-resolution local maximum synchroextracting transform method(LSET). Firstly, echo data is collected using FMCW, and then the data is subjected to STFT. Next, an estimation of the instantaneous frequency is calculated, and finally, the value of the maximum energy in the time-frequency representation is extracted to retain useful information. The experimental results from the actual data testing show that compare with the traditional time-frequency analysis method, the proposed method reduces the average Renyi entropy by 4.7 dB. A smaller entropy value indicates higher time-frequency resolution and energy concentration. This method improves the average length estimation accuracy of rotating blades by 33.3%. © 2023 IEEE.

关键词： Extraction

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Multimodal Sentiment Recognition Based on Sentiment Fusion Transformer 5

Multimodal Sentiment Recognition Based on Sentiment Fusion T...

引用

5th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2023

作者： Guan, Xinyu Wang, Yuan College of Intelligent Equipment Shandong University of Science and Technology Tai'an China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798350310603

Multimodal emotion recognition (MER), which relies on its role in processing and analysing comments posted on social media and identifying the corresponding target emotion states, has a very important position in education, social media and especially in the field of HCI. In order to solve the problem of emotion recognition for video, text and other forms of data in social media, we propose a Transformer with feature. The Transformer is able to take into account the combination of different feature relations and extract global keys, so it is introduced for long-range sequential context extraction, and the residual connections are placed after the Transformer to prevent information collapse. In addition, this paper uses a multi-headed attention mechanism to combine the extracted different feature laws, and finally the fused feature vectors are fed into the classifier to classify the sentiment and output it to achieve multimodal sentiment recognition in a multimodal context. © 2023 IEEE.

关键词： Emotion Recognition

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Combining Global and Local Merges in Logic-based Entity Resolution 20

Combining Global and Local Merges in Logic-based Entity Reso...

引用

20th International Conference on Principles of Knowledge Representation and Reasoning, KR 2023

作者： Bienvenu, Meghyn Cima, Gianluca Gutiérrez-Basulto, Víctor Ibáñez-García, Yazmín Univ. Bordeaux CNRS Bordeaux INP LaBRI UMR 5800 France Department of Computer Control and Management Engineering Sapienza University of Rome Italy School of Computer Science and Informatics Cardiff University United Kingdom

ISBN: (纸本)9781956792027

In the recently proposed LACE framework for collective entity resolution, logical rules and constraints are used to identify pairs of entity references (e.g. author or paper ids) that denote the same entity. This identification is global: all occurrences of those entity references (possibly across multiple database tuples) are deemed equal and can be merged. By contrast, a local form of merge is often more natural when identifying pairs of data values, e.g. some occurrences of 'J. Smith' may be equated with 'Joe Smith', while others should merge with 'Jane Smith'. This motivates us to extend LACE with local merges of values and explore the computational properties of the resulting formalism. © 2023 Proceedings of the International Conference on Knowledge Representation and Reasoning. All rights reserved

关键词： Knowledge representation

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Observer-Based control of Second-Order Multi-vehicle Systems in Bearing-Persistently Exciting Formations 63

Observer-Based Control of Second-Order Multi-vehicle Systems...

引用

63rd IEEE Conference on Decision and control, CDC 2024

作者： Tang, Zhiqi Fidan, Baris Johansson, Karl H. Martensson, Jonas Hamel, Tarek Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science StockholmSE-10044 Sweden University of Waterloo Mechanical and Mechatronics Engineering Department ON Canada I3S-UCA Cnrs France

ISBN: (纸本)9798350316339

This paper proposes an observer-based formation tracking control approach for multi-vehicle systems with second-order motion dynamics, assuming that vehicles' relative or global position and velocity measurements are unavailable. It is assumed that all vehicles are equipped with sensors capable of sensing the bearings relative to neighboring vehicles and only one leader vehicle has access to its global position. Each vehicle estimates its absolute position and velocity using relative bearing measurements and the estimates of neighboring vehicles received over a communication network. A distributed observer-based controller is designed, relying only on bearing and acceleration measurements. This work further explores the concept of the Bearing Persistently Exciting (BPE) formation by proposing new algorithms for bearing-based localization and state estimation of second-order systems in centralized and decentralized manners. It also examines conditions on the desired formation to guarantee the exponential stability of distributed observer-based formation tracking controllers. In support of our theoretical results, some simulation results are presented to illustrate the performance of the proposed observers as well as the observer-based tracking controllers. © 2024 IEEE.

关键词： Acceleration measurement

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Study on Landslide Susceptibility Evaluation Based on Improved Multivariable Weighted Model: A Case Study of Lushan County, China 3

Study on Landslide Susceptibility Evaluation Based on Improv...

引用

3rd IEEE International Conference on Software engineering and Artificial Intelligence, SEAI 2023

作者： Zhao, Li Duan, Gonghao Wuhan Institute of Technology School of Computer Science and Engineering Wuhan China Automation for Complex Systems Hubei Key Laboratory of Advanced Control and Intelligent Wuhan China

ISBN: (纸本)9798350337952

The evaluation of regional geological hazard susceptibility is of great significance to the prevention and control of geological hazard. In this paper, the "4-20"Lushan earthquake disaster area as the research area, combined with GIS and characteristics of the research area, through correlation analysis, selected 9 influencing factors as the evaluation factors. The study was conducted using a weighted information volume-logistic regression model (WI-LR). The results were classified into five sensitivity levels: very low, low, medium, high and very high. The results show that the landslide prone areas in Lushan County are concentrated in the area below the middle of the county seat, mostly near rivers, faults and areas with peak acceleration greater than 0.4. Among them, WI-LR model (AUC=0.918) > deterministic factor model (CF =0.908) > weighted information quantity model (WI) (AUC=0.896) > information quantity model I (AUC=0.853) > information quantity logistic regression model I-LR (AUC=0.799). It indicates that WI-LR model has high evaluation accuracy. © 2023 IEEE.

关键词： Hazards

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Multimodal Feature Fusion and Emotion Recognition Based on Variational Autoencoder 5

Multimodal Feature Fusion and Emotion Recognition Based on V...

引用

5th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2023

作者： Wang, Yuan Guan, Xinyu School of Control and Computer Engineering North China Electric Power University Beijing China College of Intelligent Equipment Shandong University of Science and Technology Tai'an China

ISBN: (纸本)9798350310603

Multimodal emotion recognition is one of the mainstream frontier directions in the field of AI, and has potential significant application value and wide application in related application scenarios involving intelligent science and human-computer interaction. Since the connection of semantic information features between contexts is a factor that needs to be focused on in multimodal emotion recognition (ER), although the CNN model can predict the information contained in the time series, it does not fully consider. The special relationship between semantic information has certain limitations. The CMN uses the semantic information that GRU can store in the memory unit. However, the practical application of this model is only to dynamically monitor the emotional changes of both parties over a period of time. There are deficiencies in the dialogue process involved. The recognition model based on variational autoencoder and multi-modal feature fusion constructed in this paper extracts rich contextual semantic information through Bi-LSTM, and uses the attention mechanism to analyze the multi-modal features extracted by multiple speakers. Features are fused to obtain important features, which effectively solves the problems mentioned above. The MFF-VAE recognition model proposed in this article effectively combines the extended feature extraction of horizontal multiple participants with the complementarity and connection of vertical semantic information, providing the next level of research direction for further improving recognition accuracy in the field of multimodal emotion recognition. © 2023 IEEE.

关键词： Emotion Recognition

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Development of a 5G-Enabled and AI-Powered Agricultural Picking Robot control Module

Development of a 5G-Enabled and AI-Powered Agricultural Pick...

引用

2023 International Conference on Applied Physics and Computing, ICAPC 2023

作者： Yu, Jianxiang Maalla, Maher Maalla, Allam School of Engineering Guangzhou College of Technology and Business Guangdong Guangzhou510850 China School of Computer Technologies and Control Itmo University Saint Petersburg197101 Russia

ISBN: (纸本)9798350359244

The escalating challenges faced by the agricultural industry, characterized by labor shortages, and rising costs, underscore the imperative for innovative solutions. This study explores the transformative potential of Intelligent Harvesting Systems in revolutionizing fruit harvesting, with a focus on assessing feasibility and understanding implications within the fruit industry. The integration of cutting-edge technologies, specifically 5G communication and artificial intelligence (AI), plays a pivotal role in the design and evaluation of a control module for an agricultural picking robot. The feasibility assessment encompasses an in-depth exploration of the technological, economic, operational, and environmental. Experimental evaluations conducted in controlled environments and real-world settings showcase the system's high picking speed, accuracy, and adaptability to diverse produce sizes. The outcomes of this research not only align with the initial objectives of enhancing harvesting efficiency and reducing labor costs but also hold promise for a sustainable and resource-efficient agricultural future. The positive synergy between 5G communication and AI technology emerges as a driving force behind the system's exceptional performance. This study not only contributes to the immediate advancements in intelligent harvesting but also lays a robust foundation for continued innovation, setting the stage for further exploration and refinement in this dynamic field. © 2023 IEEE.

关键词： 5G mobile communication systems

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Research on Preventing Commutation Failure in MMC and LCC Parallel DC Systems

Research on Preventing Commutation Failure in MMC and LCC Pa...

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International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Xiong, Lingfei Zheng, Kuan Wu, Yucheng Liu, Yiqi State Grid Economic and Technology Research Institute Co. Ltd. Beijing102209 China College of Mechanical and Electrical Engineering Northeast Forestry University Harbin150040 China College of Computer and Control Engineering Northeast Forestry University Harbin150040 China

ISBN: (纸本)9789819618675

Offshore wind power transmission systems require high capacity, and LCC-based HVDC transmission systems are well-suited to meet this demand. Nevertheless, LCCs are dependent on the grid to supply commutation voltage, and in the event of voltage dips or distortions in the grid, commutation failures can readily occur. This results in significant oscillations between the AC and DC sides, thereby compromising the system’s safe and stable operation. This paper introduces a method to enhance the system’s resilience to commutation failures by integrating an MMC-based VSC-HVDC system in parallel with an LCC-HVDC inverter station. The MMC offers the advantage of decoupled control of active and reactive power, enabling it to stabilize the AC bus voltage. By maintaining the stability of the AC bus voltage, the resilience of the parallel system to commutation failures is augmented, thereby improving the overall stability of the combined transmission system. Subsequently, a parallel hybrid HVDC system model was developed in PSCAD/EMTDC to simulate AC grid faults, and a coordinated control strategy was formulated. The simulation results demonstrate that the proposed control method significantly enhances the system’s capability to withstand commutation failures. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： HVDC power transmission

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High-Power LED Lamp Driver Modelling 7

High-Power LED Lamp Driver Modelling

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7th International Youth Conference on Radio Electronics, Electrical and Power engineering, REEPE 2025

作者： Chukhraev, Igor V. Sevastyanova, Marina A. Drach, Vladimir E. Torkunova, Julia V. Bauman Moscow State Technical University Computer Science and Control Department Moscow Russia Sochi State University Department of Innovative Engineering and Digital Technologies Sochi Russia Kazan State Power Engineering University Department of Information Technologies and Intelligent Systems Kazan Russia

ISBN: (纸本)9798331531836

The growing demand for energy-saving lamps highlights critical limitations in traditional LED secondary optics, which reduce energy efficiency and complicate heat dissipation - a key factor in LED lamp longevity. This study proposes an optimized circuit design for a 20-watt LED driver that addresses these issues. The proposed driver ensures effective LED control while improving thermal management and eliminating drawbacks of conventional designs. Key principles of modern LED lamp design and current challenges are identified. The electronic schematic of the high-power LED driver was simulated using LTSpice software in order to analyze and optimize the circuit's performance, resulting in a driver solution that enhances efficiency and reliability. © 2025 IEEE.

关键词： Energy efficiency

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