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8th IEEE Data Driven control and Learning Systems Conference, DDCLS 2019

作者： Zhou, Kaibo Chen, Xudong Xu, Gaofeng Ge, Yaobao Zhang, Zhixin MOE Key Laboratory of Image Processing and Intelligence Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781728114545

The operation condition of aluminum electrolytic cells is critical to the stability of the aluminum electrolysis process. Under the tough working environment, there will be many abnormal states in the cells, detrimental to aluminum quality, aluminum electrolysis efficiency and electrolytic cells life. Therefore, it's of great significance to develop an effective process monitoring and multi-fault diagnosis method. The diagnosis accuracy and the speed of traditional multi-classification methods are limited. To solve these problems, a fault detection and multi-fault diagnosis framework based on wavelet packet decomposition (WPD) and directed acyclic graph support vector machine (DAG-SVM) is proposed. First, features are extracted from aluminum electrolytic cell voltage signals. Then, DAG-SVM is used to detect and diagnose abnormal states. The result shows that the proposed method can detect and diagnose three abnormal states, anode effect state, voltage instability and liquid aluminum fluctuation with a high precision. The accuracy can reach about 86.8%. © 2019 IEEE.

关键词： Failure analysis

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A novel method of constructing high-dimensional digital chaotic systems on finite-state automata

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Chinese Physics B 2020年第9期29卷 233-243页

作者： Jun Zheng Han-Ping Hu School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

When chaotic systems are implemented on finite precision machines, it will lead to the problem of dynamical degradation. Aiming at this problem, most previous related works have been proposed to improve the dynamical degradation of low-dimensional chaotic maps. This paper presents a novel method to construct high-dimensional digital chaotic systems in the domain of finite computing precision. The model is proposed by coupling a high-dimensional digital system with a continuous chaotic system. A rigorous proof is given that the controlled digital system is chaotic in the sense of Devaney's definition of chaos. Numerical experimental results for different high-dimensional digital systems indicate that the proposed method can overcome the degradation problem and construct high-dimensional digital chaos with complicated dynamical properties. Based on the construction method, a kind of pseudorandom number generator (PRNG) is also proposed as an application.

关键词： high-dimensional digital chaotic system dynamical degradation anti-control pseudorandom number generator

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

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial intelligence 2024年第7期5卷 3690-3702页

作者： Xiao, Jiang-Wen Fang, Hongliang Wang, Yan-Wu Huazhong University of Science and Technology Ministry of Education School of Artificial Intelligence and Automation The Key Laboratory of Image Processing and Intelligent Control 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 article proposes a smoothing clustering method for daily load clustering and a pooling-ensemble model for one day ahead load forecasting. The whole short-term load forecasting framework in this article contains three steps. Specifically and first, the states of the residents are obtained by clustering the daily load curves with the proposed smoothing clustering method. Second, a weighted mixed Markov model is built to predict the probability distribution of the load state in the next day. Third, 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. © 2020 IEEE.

关键词： Probability distributions

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Recent Patents Review in Three Dimensional Ultrasound Imaging

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Recent Patents on Biomedical Engineering 2011年第1期4卷 41-48页

作者： Chen, Yimin Li, He Zheng, Yaowu Yuchi, Ming Zhang, Xuming Ding, Mingyue College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of EducationMinistry of China Huazhong University of Science and Technology Wuhan 430074 China

Ultrasound is an inexpensive and widely used imaging modality for the diagnosis and staging of many *** the past several decades, it has benefited from major advances in technology and has become an indispensable imaging modality, due to its flexibility and non-invasive character. In the last decade, research investigators and commercial companieshave further advanced ultrasound imaging with the development of 3D ultrasound. Compared with two dimensional ultrasound imaging, it can provide a 3D image of the anatomy directly and localize the image plane much easier. This review focuses on three dimensional ultrasonic medical imaging patents filed in recent years between 2006 and 2010. The patents are classified into three classes: the hardware, software and applications. This paper will attempt to provide an appreciation of the recent advances in 3D ultrasound imaging research while glimpse the future development trend of 3D ultrasound imaging. © 2011 Bentham Science Publishers Ltd.

关键词： Medical imaging

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New Insights on the Stability of Sampled-Data-Based LFC for Power Systems: A Delay-Interval-Dependent LKF Approach

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IEEE Transactions on Smart Grid 2025年

作者： Wang, Wei-Min Wang, Yan-Wu Wan, Qian Zeng, Hong-Bing Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Hunan University of Technology School of Electrical and Information Engineering Zhuzhou412007 China

This paper analyzes the stability problem of load frequency control (LFC) for power systems under uncertain transmission delays. First, an argumented LFC system model accounting for uncertainties in transmission delays is proposed. Then, a novel delay-interval-dependent Lyapunov-Krasovskii functional (LKF) that takes into account both the upper and lower bounds of the transmission delay is proposed. Several less conservative stability criteria are derived using the proposed LKF. Based on the stability criterion obtained, the sampling interval and the upper and lower bounds of the transmission delay are taken as the conditions to guide the controller design. Finally, case studies are conducted based on a one-area power system and a three-area power system, both integrated with wind and solar power generation. The simulation comparison results demonstrate that the proposed LFC scheme exhibits strong robustness against uncertain transmission delays, load fluctuations, and the intermittent generation of wind and solar power. © 2010-2012 IEEE.

关键词： Stability criteria

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Evolutionary attraction–repulsion algorithm embedded with LLM for UAV task allocation

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Advanced Engineering Informatics 2025年 66卷

作者： Bowen Wu Renbin Xiao School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China Institute of Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan 430074 China

Labor division provides an adaptive and scalable technique for unmanned systems. However, its designing process usually relies heavily on the manually crafted paradigms, leading to inefficiencies and insufficient performance. To overcome these challenges, this paper introduce an evolutionary approach to labor division algorithm design. Drawing inspiration from the regulatory behaviors observed in natural lion populations, we propose a bipolar feedback-guided attraction–repulsion mechanism. A formal model is developed to encapsulate this mechanism, and we provide an in-depth analysis of the algorithm’s evolution through the framework of systems science. In addition, we leverage prompt engineering techniques to integrate a large language model (LLM) with our proposed mechanism, facilitating a bidirectional enhancement between the two. This integration culminates in the development of the ARE-LLM framework, a robust and adaptive solution for designing labor division algorithms. To demonstrate the practical applicability of our approach, we apply the ARE-LLM framework to the UAV-based task allocation problem for enemy air defense suppression. The experimental results indicate that our method outperforms several advanced approaches. In a scenario involving 50 UAVs tasked with completing 300 assignments, the total distance traveled is only 9 % of that required by the ALPDA algorithm, while the processing time is reduced to 8 % of that used by ALPDA.

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Homotopy-based image reconstruction in breast ultrasound tomography

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Journal of Information and Computational Science 2013年第3期10卷 687-699页

作者： Gaddoura, Omer M. Wang, Longhui Ding, Mingyue School of Life Science and Engineering Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Engineering Wuhan 430074 China

To diagnose breast cancer, an alternative approach to X-ray mammography and B-mode ultrasound is the Breast Ultrasound Computed Tomography (UCT). Concerning breast cancer detection, mammographic techniques have been considered as gold standard modality but these methods suffer through high rate of false-positive results and radiations. In addition, the use of low resolution images in the conventional ultrasound techniques is another problem that makes it difficult to differentiate between breast tissues and tumor existence. In this particular study, we have used a full wave-based tomographic technique to diagnose the breast cancer. While taking into account the physical characteristics, full wave-based approach constructs non-linear operator that transforms it as a nonlinear inverse problem or a minimization problem. To solve the non-linear inverse problem, we have used Homotopoy Continuation Methods (HCM), which is globally convergent method and provides multiple solutions. In the subsequent steps, to reduce the computational complexity and the high usage of memory for finding out the Jacobian of the cost function, we have applied discrete adjoint method. In the last, the effect of the noise to the reconstructed image has been tested. In this preliminary analysis with the use of adjoint methods, obtained results have shown the robustness and visibility of our proposed approach. © 2013 by Binary Information Press.

关键词： image reconstruction

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TSPT: Two-Step Prompt Tuning for class-incremental novel class discovery

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Knowledge-Based Systems 2025年 319卷

作者： An, Jiayu Du, Zhenbang Zhang, Herui Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518063 China

In real-world applications, models often encounter a sequence of unlabeled new tasks, each containing unknown classes. This paper explores class-incremental novel class discovery (class-iNCD), which requires maintaining previously learned knowledge while discovering novel classes. We consider a more realistic and also more challenging scenario, which has a small number of initial known classes and a large number of unlabeled tasks, with the additional requirement of data privacy protection. A simple yet effective approach, Two-Step Prompt Tuning (TSPT), is proposed. TSPT tackles class-iNCD through prompt tuning, which is rehearsal-free and plug-and-play, protecting data privacy and significantly reducing the number of trainable parameters. TSPT consists of two main steps: (1) novel class discovery, which initializes the classifier using uniform clustering, and uses intra- and inter-sample consistency learning to discover novel classes;and, (2) knowledge fusion, where the prompt learned in the previous step is adapted as task-specific prompt, and additional optimal prompts are selected from a prompt pool to integrate knowledge from both old and new classes. Experiments on three datasets demonstrated the effectiveness of TSPT. © 2025 Elsevier B.V.

关键词： Sensitive data

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Fast DCT-I, DCT-III, and DCT-IV via Moments

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Eurasip Journal on Applied Signal processing 2005年第12期2005卷 1902-1909页

作者： Liu, J.G. Liu, Y.Z. Wang, G.Y. Key Laboratory of Education Huazhong University of Science and Technology Ministry for Image Processing and Intelligence Control Wuhan 430074 China Department of Computer Science and Engineering China University of Geosciences Wuhan 430074 China Key Laboratory of State Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

This paper presents a novel approach to compute DCT-I, DCT-III, and DCT-IV. By using a modular mapping and truncating, DCTs are approximated by linear sums of discrete moments computed fast only through additions. This enables us to use computational techniques developed for computing moments to compute DCTs efficiently. We demonstrate this by applying our earlier systolic solution to this problem. The method can also be applied to multidimensional DCTs as well as their inverses. © 2005 Hindawi Publishing Corporation.

关键词： Method of moments

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A REVIEW ON ARTERY WALL SEGMENTATION TECHNIQUES AND INTIMA-MEDIA THICKNESS MEASUREMENT FOR CAROTID ULTRASOUND imageS

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Journal of Innovative Optical Health Sciences 2012年第1期5卷 75-84页

作者： XIN YANG WANJI HE KAITONG LI JIAOYING JIN XUMING ZHANG MING YUCHI MINGYUE DING State Key Laboratory for Multi-Spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI)Huazhong University of Science and Technology Wuhan 430074HubeiChina Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074HubeiChina

Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and *** is important for the early stage diagnosis and monitoring medical intervention of the *** stenosis is a classical atherosclerotic lesion with vessel wall narrowing down and accumulating plaques *** carotid artery of intima-media thickness(IMT)is a key indicator to the *** the development of computer assisted diagnosis technology,the imaging techniques,segmentation algorithms,measurement methods,and evaluation tools have made considerable *** imaging,being real-time,economic,reliable,and safe,now seems to become a standard in vascular assessment methodology especially for the measurement of *** review firstly attempts to discuss the clinical relevance of measurements in clinical practice at first,and then followed by the challenges that one has to face when approaching the segmentation of ultrasound ***,the commonly used methods for the IMT segmentation and measurement are ***,discussion and evaluation of different segmentation techniques are *** overview of summary and future perspectives is given finally.

关键词： Ultrasound(US)images carotid artery intima-media thickness(IMT) atherosclerosis image segmentation computer assisted diagnosis(CAD)

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