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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Junbin Gao Hao Ruan Bingrong Xu Zhigang Zeng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Automation Wuhan University of Technology Wuhan China

3D object detection plays a critical role in autonomous driving perception. Although multi-view-based perception solutions have made significant progress, their performance is still far from being ready for practical use. The estimation of pixel depth is dependent on camera intrinsic properties, which led us to explore a depth-aware model guided by camera parameters. Our contribution in this paper is the DAFormer, which incorporates camera parameters and position-aware image features to detect 3D objects. The depthaware module uses camera parameters to reweight image features and estimate depth, enhancing and offsetting the 3D position embedding. The object query uses depth information enhanced features for end-to-end 3D detection by Attention layers. DAFormer achieves impressive results on the standard nuScenes dataset without any additional embellishments.

关键词： Solid modeling Three-dimensional displays Estimation Object detection Detectors Cameras Feature extraction

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Analysis of Government-Taxation Methods and Maritime Companies’ Strategies Under Emission-Reduction Incentives

SSRN

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SSRN 2023年

作者： Wang, Jian Wenbo, Zhu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

The current emission-reduction trend in the shipping industry is inevitable. This study uses a multi-stage Stackelberg game to establish a low-carbon maritime supply chain model that includes a government, a carrier, and a port. The government can choose to impose carbon taxes only on the port or on both the port and carrier, while there are different power structures: port-led or carrier-led. Equilibrium solutions in different scenarios indicate that the leading port’s profit is not affected by the implementation of a carbon tax, while the carrier, surprisingly, hopes to join the carbon-tax policy. Both the government and the carrier prefer a bilateral carbon-tax scenario led by the carrier, while the port has the opposite preference. In the process of seeking coordination opportunities, we find that, driven by shippers’ low-carbon preferences, the maritime supply chain exhibits a "triple increasing" phenomenon, which means higher cargo volume, more emission reduction, and higher freight prices. The government and carrier can control the occurrence of this phenomenon and promote an all-win scenario through the use of carbon taxes and subsidies. We provide coordination strategies for unilateral carbon taxes in the maritime supply chain under different power structures and demonstrate the important role of the government in coordination. This provides a new direction for the implementation of carbon taxes in the maritime supply chain. © 2023, The Authors. All rights reserved.

关键词： Taxation

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Short-Term Residential Load Forecasting Via Pooling-Ensemble Model with Smoothing Clustering

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SSRN 2023年

作者： Fang, Hongliang Xiao, Jiang-Wen Wang, Yan-Wu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

Short-term residential load forecasting is essential to demand side response. However, the frequent spikes in the load and the volatile daily load patterns make it difficult to accurately forecast the load. To deal with these problems, this paper proposes a smoothing clustering method for daily load clustering and a pooling-ensemble model for one day ahead load forecasting. The whole shortterm load forecasting framework in this paper contains three steps. Specifically and firstly, the states of the residents are obtained by clustering the daily load curves with the proposed smoothing clustering method. Secondly, a weighted mixed Markov model is built to predict the probability distribution of the load state in the next day. Thirdly, multiple predictors in the pooling-ensemble model are selected for different states and the load is forecasted by weighing the results of the multiple predictors based on the predicted states. Results of the case studies and comparison studies on two public datasets verify the advantages of the smoothing clustering method and the pooling-ensemble model. © 2023, The Authors. All rights reserved.

关键词： Probability distributions

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Unequal Error Protection Rateless Codes for Spatial Audio Transmission 24

Unequal Error Protection Rateless Codes for Spatial Audio Tr...

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Yin, Junpeng Fu, Yusun Huang, Haobo Tang, Jinhui Shanghai Jiao Tong University Ningbo Artificial Intelligence Institute Ningbo China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai China Ministry of Education of China School of Electronic Information and Electrical Engineering The Key Laboratory of System Control and Information Processing Shanghai China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350363760

Spatial audio is an important component of the metaverse. With the rapid increase of the spatial resolution and the number of objects, the data volume of the spatial side information has grown larger. However, the low bit rate transmission of spatial side information in the object-based audio coding methods leads to the low-quality reconstruction of spatial side information with limited bandwidth. To address this issue, this paper constructs a cascade design of spatial audio coding and unequal error protection (UEP) rateless codes. Furthermore, the further protection of specific spatial side information is proposed for different scenarios, which effectively addresses the limitation of traditional spatial audio coding in side information protection. For the situation where the code length K of different importance levels is different, we propose an adaptive degree distribution (ADD), adding K to the selection probability as an influencing factor, which has better performance than other degree distribution for short code length. ADD is used to replace the multiple degree distribution strategy of the traditional unequal error protection scheme, and the block error rate (BER) is reduced nearly 10 times compared with the traditional scheme. © 2024 IEEE.

关键词： Audio signal processing

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Joint Load Prediction of Multiple Buildings Using Multi-Task Learning with Selected-Shared-Private Mechanism

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SSRN 2023年

作者： Cao, Minghui Xiao, Jiang-Wen Fang, Hongliang Li, Yuan-Zheng Wang, Yan-Wu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

Short-term load forecasting for residential buildings is of great significance to ensure the safe and economic operation of power grid. However, most of the existing prediction methods focus on the temporal characteristics of individual buildings and ignore the importance of spatial characteristics between different buildings. To tackle this problem and realize joint prediction for multiple buildings, a novel multi-task learning model with the selected-shared-private mechanism is proposed in this paper. Firstly, the temporal and spatial characteristics hidden in electricity consumption patterns are analyzed and represented by auto-correlation and cross-correlation, respectively. Then, a correlation-oriented combination strategy considering the auto-correlation and time dependency is proposed to build input set for the prediction model, and the temporal convolutional network is adopted to extract features. Furthermore, this paper designs a novel selected-shared-private mechanism based on the cross-correlation, which can selectively utilize information from related tasks while focusing on private features to improve prediction accuracy. The proposed model is compared with other methods on the public dataset, and the results demonstrate the superiority of this model in load prediction for multiple buildings. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Fixed-time extended state observer-based trajectory tracking control for autonomous underwater vehicles

Fixed-time extended state observer-based trajectory tracking...

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作者： Zheng, Jiaqi Song, Lei Liu, Lingya Yu, Wenbin Zhu, Shanying Wang, Yiyin Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

In this paper, we investigate the trajectory tracking control problem for autonomous underwater vehicles (AUVs) with time-varying external disturbances of currents and waves in the sea. To solve the problem, a fixed-time extended state observer (FTESO)-based tracking controller is proposed. Firstly, by using the extended state observer, the FTESO is proposed for estimating the external disturbances and the velocities of the AUV within the fixed convergence time. Based on the FTESO, the fixed-time controller is proposed for reducing the tracking errors and improving robustness performance. Theoretical analysis is given, which shows that the unknown external disturbances can be compensated and tracking error can converge to zero within the fixed time. Simulation results show that the proposed FTESO controller not only guarantees the fixed-time convergence but also reduces the trajectory tracking errors of the AUV. © 2021 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Autonomous underwater vehicles

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Generation Maintenance Scheduling for Power Systems Considering the Risk Quantification of Hybrid Uncertainty

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IEEE Transactions on Power Systems 2025年

作者： Yang, Xiao Zhao, Yong Li, Yuanzheng Huang, Cheng Ding, Qiang Key Laboratory of Image Information Processing and Intelligent Control of Ministry of Education of China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China Power Science Research Institute of State Grid Jiangsu Electric Power Company China China Electric Power Research Institute Company China

The accurate quantification of risk caused by uncertainty forms a crucial foundation for formulating the generation maintenance scheduling (GMS) of power systems. However, the probability distribution functions (PDFs) of uncertain variables such as wind power and load are challenging to model accurately or are unknown, which makes it difficult to measure their economic risk and formulate appropriate GMS for power systems. To address this issue, we consider hybrid uncertainty from wind power and load, and propose a novel interval-probabilistic worst conditional value-at-risk (IP-WCVaR)-based generation maintenance scheduling method. Firstly, a novel IP-WCVaR method is proposed to measure the risk of the interval and probabilistic hybrid uncertainty, and the analytical mathematical model of the IP-WCVaR is derived through typical scenarios of probability correction. On this basis, the positive and negative spinning reserve models are established using the IP-WCVaR and then integrated into the GMS model, which enhances the resilience of the power system. Finally, the new risk-averse GMS model is formulated as the lower and upper boundary optimal models, which are transformed into tractable mixed integer linear programming problems based on the interval extreme value theory. The effectiveness and superiority of the proposed IP-WCVaR method are verified on the modified IEEE 24-bus and IEEE 118-bus power systems. © 1969-2012 IEEE.

关键词： Mixed-integer linear programming

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Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples

arXiv

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arXiv 2024年

作者： Ma, Mingrui Han, Lansheng Zhou, Chunjie School of Cyber Science and Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China

The frequent occurrence of cyber-attacks has made webshell attacks and defense gradually become a research hotspot in the field of network security. However, the lack of publicly available benchmark datasets and the over-reliance on manually defined rules for webshell escape sample generation have slowed down the progress of research related to webshell escape sample generation and artificial intelligence (AI)-based webshell detection. To address the drawbacks of weak webshell sample escape capabilities, the lack of webshell datasets with complex malicious features, and to promote the development of webshell detection, we propose the Hybrid Prompt algorithm for webshell escape sample generation with the help of large language models. As a prompt algorithm specifically developed for webshell sample generation, the Hybrid Prompt algorithm not only combines various prompt ideas including Chain of Thought, Tree of Thought, but also incorporates various components such as webshell hierarchical module and few-shot example to facilitate the LLM in learning and reasoning webshell escape strategies. Experimental results show that the Hybrid Prompt algorithm can work with multiple LLMs with excellent code reasoning ability to generate high-quality webshell samples with high Escape Rate (88.61% with GPT-4 model on VirusTotal detection engine) and Survival Rate (54.98% with GPT-4 model). Copyright © 2024, The Authors. All rights reserved.

关键词： Network security

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Optimizing Parameter Design with Frequency and Clock Drift Constraints in Microgrids⋆

Optimizing Parameter Design with Frequency and Clock Drift C...

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IEEE Conference on Decision and control

作者： Chang Yu Xiaoqing Lu School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan China School of Electrical Engineering and Automation Wuhan University Wuhan China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Microgrids subjected to secondary cooperative control encounter significant challenges, including operational constraints and clock drifts, adversely affecting their stability and efficiency. This paper provides conditions that assure optimal microgrid performance in both transient and steady-state scenarios, focusing on the effects of clock drifts and fluctuations in load. Furthermore, we introduce a novel approach for designing secondary control parameters, specifically engineered to minimize steady-state discrepancies attributable to clock drifts while ensuring adherence to standards for transient operations. Comprehensive experimental validations corroborate the effectiveness of our proposed solutions.

关键词： Fluctuations Stability criteria Focusing Microgrids Steady-state Transient analysis Standards Frequency control Clocks Load modeling

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Non-contact Detection of Vital Sign Based on ICCEMDAN-SpEn Combined with Wavelet Threshold Denoising

Non-contact Detection of Vital Sign Based on ICCEMDAN-SpEn C...

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International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Wan Li Binkun Liu Chunhua Zhu Key Laboratory of Grain Information Processing and Control Henan University of Technology Ministry of Education Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Henan Engineering Laboratory of Grain Condition Intelligent Detection and Application Henan University of Technology Zhengzhou China

ISBN: (数字)9798350389968

ISBN: (纸本)9798350389975

The detection of vital signs, especially respiratory rate and heartbeat rate, is of great significance for clinical diagnosis, daily health assessment and disaster rescue. In recent years, millimeter wave based non-contact vital sign detection has become a research hotspot. Aiming to overcome the noise influence of the target signal on the detection accuracy, one improved ICEEMDAN based on sample entropy (ICCEMDAN-SpEn) combined with wavelet threshold denoising is proposed. Firstly, the adaptive noise extraction ability of ICEEMDAN is analyzed to isolate all intrinsic mode function (IMF) components of the noisy target signals, and the sample entropy is introduced as the threshold to select the main IMFs; then wavelet threshold denoising is proposed to relieve the noise adaptively, which can better deal with the nonlinear and non-stationary signal; finally, IMFs after wavelet threshold denoising are reconstructed to attain target signals. The experimental results show that the proposed method can effectively relieve the noise contained in the vital sign signals and estimate the respiratory rate and heartbeat rate of human body accurately.

关键词： Heart beat Noise reduction Noise Millimeter wave technology Millimeter wave measurements Wavelet analysis Entropy

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