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第41届中国控制会议

作者： Feng Liu Dongping Wang Kedong LYU School of electrical information engineering North Minzu University College of Computer and Information Engineering Tianjin Agricultural University Department of Automation Engineering Tianjin Electronic Information Technician College

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Single Gimbal Control Momentum Gyroscopes(SGCMG) are widely used with the ability of large torque output and high accuracy control of a *** singularity problem(especially the internal elliptical singularity) of SGCMG becoming a major obstacle in successful implementing the task of the attitude *** singularity can be effectively avoided by additional reaction wheel(RW) array in the field of the actual ***,the saturation problem is existed in the *** this paper,the hybrid actuators of the SGCMG with pyramid configuration and RW array with orthogonal configuration is *** new steering law is ***,the internal elliptical singularity and the saturation problem of the RW can be effectively avoided by the new steering law at the same time.

关键词： singularity avoidance new designed steering law hybrid actuators of SGCMG and RW array

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DPAL-BERT:A Faster and Lighter Question Answering Model

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computer Modeling in engineering & Sciences 2024年第10期141卷 771-786页

作者： Lirong Yin Lei Wang Zhuohang Cai Siyu Lu Ruiyang Wang Ahmed AlSanad Salman A.AlQahtani Xiaobing Chen Zhengtong Yin Xiaolu Li Wenfeng Zheng Department of Geography and Anthropology Louisiana State UniversityBaton RougeLA 70803USA School of Automation University of Electronic Science and Technology of ChinaChengdu610054China College of Computer and Information Sciences King Saud UniversityRiyadh11574Saudi Arabia School of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA 70803USA College of Resources and Environmental Engineering Guizhou UniversityGuiyang550025China School of Geographical Sciences Southwest UniversityChongqing400715China

Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering ***,with the constant evolution of algorithms,data,and computing power,the increasing size and complexity of these models have led to increased training costs and reduced *** study aims to minimize the inference time of such models while maintaining computational *** also proposes a novel Distillation model for PAL-BERT(DPAL-BERT),specifically,employs knowledge distillation,using the PAL-BERT model as the teacher model to train two student models:DPAL-BERT-Bi and *** research enhances the dataset through techniques such as masking,replacement,and n-gram sampling to optimize knowledge *** experimental results showed that the distilled models greatly outperform models trained from *** addition,although the distilled models exhibit a slight decrease in performance compared to PAL-BERT,they significantly reduce inference time to just 0.25%of the *** demonstrates the effectiveness of the proposed approach in balancing model performance and efficiency.

关键词： DPAL-BERT question answering systems knowledge distillation model compression BERT Bi-directional long short-term memory(BiLSTM) knowledge information transfer PAL-BERT training efficiency natural language processing

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Two-Operation Buffering based on Dynamic Optical RAM 17

Two-Operation Buffering based on Dynamic Optical RAM

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Semenov, Andriy Tsyrulnyk, Serhii Baraban, Serhii Semenova, Olena Rudyk, Andrii Khloba, Anton Vinnytsia National Technical University Faculty of Information Electronic Systems Vinnytsia Ukraine Vinnytsia National Agrarian University Department of Computer Sciences and Digital Economy Vinnytsia Ukraine Poznan University of Technology Faculty of Computing and Telecommunications Poznan Poland National University of Water and Environmental Engineering Department of Automation Electrical Engineering and Computer-Integrated Technologies Rivne Ukraine

ISBN: (纸本)9798331520564

The authors of this paper propose a block diagram for a dual-operating buffer on a dynamic optical RAM. The buffer consists of two dynamic optical RAMs, each controlled separately to allow for simultaneous writing and reading of data, thereby improving performance. This setup enables data to be read from the buffer while new data is being written to it. Implementing a dual-operating buffer on a dynamic optical RAM has the potential to enhance the performance of high-speed data transmission in telecommunications networks. The authors conducted numerical calculations to compare failure probabilities between single-operation and dual-operation buffers on dynamic optical RAM. The results indicated that using a dual-operating buffer significantly reduces the probability of failure with the same buffer memory capacity compared to a single-operating buffer. Additionally, the authors analyzed the effectiveness of the proposed dual-operating buffer. The analysis confirmed that exploiting dynamic optical memory for buffering enhances data transfer speed and efficiency due to the inherent properties of optical data transfer, such as high bandwidth and low latency. © 2024 IEEE.

关键词： Dynamic random access storage

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Joint Class-Balanced Client Selection and Bandwidth Allocation for Cost-Efficient Federated Learning in Mobile Edge Computing Networks

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IEEE Transactions on Mobile Computing 2025年第7期24卷 5681-5698页

作者： Tang, Jian Li, Xiuhua Li, Hui Li, Penghua Wang, Xiaofei Leung, Victor C. M. Chongqing University School of Big Data & Software Engineering Chongqing400000 China Chongqing University of Posts and Telecommunications School of Automation Chongqing400065 China Tianjin University College of Intelligence and Computing Tianjin300072 China Shenzhen MSU-BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T1Z4 Canada

Federated Learning (FL) has significant potential to protect data privacy and mitigate network burden in mobile edge computing (MEC) networks. However, due to the system and data heterogeneity of mobile clients (MCs), client selection and bandwidth allocation is key for achieving cost-efficient FL in MEC networks with limited bandwidth. To address these challenges, we investigate the issue of joint client selection and bandwidth allocation for reducing the cost (i.e., latency and energy consumption) of FL training. We formulate the problem and decompose it into a holistic subproblem to reduce the number of rounds and a partial subproblem to reduce the costs of FL each round. We propose a joint class-balanced client selection and bandwidth allocation (CBCSBA) framework to address the whole problem. Specifically, for the holistic subproblem, CBCSBA combines MCs into groups, each having data distribution as close as possible to class-balanced distribution;For the partial subproblem, CBCSBA reduces costs by exploratively selecting a group and sequentially optimizing the latency and energy consumption of MCs within the group. Experimental results show that CBCSBA outperforms the baseline frameworks in reducing latency by 28.2% and energy consumption by 25.3% on average in the considered four datasets. © 2002-2012 IEEE.

关键词： Federated learning

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Robust Control of Feeding Speed in Coal Seam Drilling Process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

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2024 China automation Congress, CAC 2024

作者： Liu, Xiao Chen, Luefeng Lu, Chengda Fan, Haipeng Wu, Min Pedrycz, Witold School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey

ISBN: (纸本)9798350368604

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust H∞ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller’s effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction. © 2024 IEEE.

关键词： Coal deposits

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Optimization of Ethanol Production Using State-Space Modeling and Optimal Control Technology 13

Optimization of Ethanol Production Using State-Space Modelin...

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13th International Conference on Dependable Systems, Services and Technologies, DESSERT 2023

作者： Markina, Lyudmila Palchevskyi, Bogdan Hrudetskyi, Roman Smoliankin, Oleh Melnychuk, Yuliia Khrystynets, Nataliya Lutsk National Technical University Department of Automation and Computer-Integrated Technologies Lutsk Ukraine Lutsk National Technical University Department of Digital Educational Technologies Lutsk Ukraine Lutsk National Technical University Department of Computer Engineering and Cyber Security Lutsk Ukraine

ISBN: (纸本)9798350396119

in present paper we develop the automatic optimal control of the production process of dough mixture preparation, that can be used in the production of alcohol and fuel ethanol from grain raw materials. Known methods of automatic control of the dough preparation process are based on measuring a consumption of raw materials and a concentration of dough and regulating the water supply. We offer an improved method based on robust stabilization nonlinear process control that will ensure more stable operation of the system, smooth transitions of regimes and economy of used energy, improvement of a quality of the mixture dough, as well as final ethanol product. The optimal operating modes of experimental installation were investigated using state-space dynamical modelling technic and ethanol production process simulation. © 2023 IEEE.

关键词： Water supply

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Supply Chain Logistics Marine Simulator

Supply Chain Logistics Marine Simulator

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2024 International Conference Automatics and Informatics, ICAI 2024

作者： Dyakov, Bozhidar Karova, Milena Varbanova, Aneta Penev, Ivaylo Grigorov, Ivan Dimitrov, Danail Technical University of Varna Department of Navigation Varna Bulgaria Technical University of Varna Department of Computer Science and Engineering Varna Bulgaria Technical University of Varna Department of Industrial Automation Varna Bulgaria Technical University of Varna Department of Software and Internet Technologies Varna Bulgaria

ISBN: (纸本)9798350353907

The paper presents an implementation of a supply chain logistics marine simulator, which realizes document flow for processing of loads, carried by marine transport. The simulator is intended to be used in the educational process in specialties Navigation and Logistics. The main stages of the logistic process are discussed. The architecture of the software system is explained. The essential parts of the process are presented with screenshots from the system. © 2024 IEEE.

关键词： Ship simulators

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Covid-19 detection using chest X-rays: is lung segmentation important for generalization?

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Research on Biomedical engineering 2022年第4期38卷 1121-1139页

作者： Bassi, Pedro R. A. S. Attux, Romis Department of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering University of Campinas - UNICAMP SP Campinas13083-970 Brazil Alma Mater Studiorum - University of Bologna BO Bologna40126 Italy Istituto Italiano Di Tecnologia GE Genoa16163 Italy

Purpose: We evaluated the generalization capability of deep neural networks (DNNs) in the task of classifying chest X-rays as Covid-19, normal or pneumonia, when trained in a relatively small and mixed datasets. Methods: We proposed a DNN to perform lung segmentation and classification, stacking a segmentation module (U-Net), an original intermediate module and a classification module (DenseNet201). To evaluate generalization capability, we tested the network with an external dataset (from distinct localities) and used Bayesian inference to estimate the probability distributions of performance metrics. Furthermore, we introduce a novel evaluation technique, which uses layer-wise relevance propagation (LRP) and Brixia scores to compare the DNN grounds for decision with radiologists. Results: The proposed DNN achieved 0.917 AUC (area under the ROC curve) on the external test dataset, surpassing a DenseNet without segmentation, which showed 0.906 AUC. Bayesian inference indicated mean accuracy of 76.1% and [0.695, 0.826] 95% HDI (high-density interval, which concentrates 95% of the metric’s probability mass) with segmentation and, without segmentation, 71.7% and [0.646, 0.786]. Conclusion: Employing an analysis based on LRP and Brixia scores, we discovered that areas where radiologists found strong Covid-19 symptoms are the most important for the stacked DNN classification. External validation showed smaller accuracies than internal, indicating difficulty in generalization, which is positively affected by lung segmentation. Finally, the performance on the external dataset and the analysis with LRP suggest that DNNs can successfully detect Covid-19 even when trained on small and mixed datasets. © 2022, The Author(s).

关键词： Deep neural networks

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Learning-based Green Workload Placement for Energy Internet in Smart Cities

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Journal of Modern Power Systems and Clean Energy 2022年第1期10卷 91-99页

作者： Qihua Zhou Yanfei Sun Haodong Lu Kun Wang School of Automation and School of Artificial Intelligence Nanjing University of Posts and TelecommunicationsNanjingChina School of Internet of Things Nanjing University of Posts and TelecommunicationsNanjingChina Department of Electrical and Computer Engineering University of CaliforniaLos AngelesUSA

The Energy Internet is a fundamental infrastructure for deploying green city applications, where energy saving and job acceleration are two critical issues to address. In contrast to existing approaches that focus on static metrics with the assumption of complete prior knowledge of resource information, both application-level properties and energy-level requirements are realized in this paper by jointly considering energy saving and job acceleration during job runtime. Considering the online environment of smart city applications, the main objective is transferred as an optimization problem with a model partition and function assignment. To minimize the energy cost and job completion time together, a green workload placement approach is proposed by using the multi-action deep reinforcement learning method. Evaluations with real-world applications demonstrate the superiority of this method over state-of-the-art methods.

关键词： Energy saving workload scheduling Energy Internet green city

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One-shot functional photoacoustic microscopy for monitoring traumatic brain injury 16

One-shot functional photoacoustic microscopy for monitoring ...

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16th International Conference on Photonics and Imaging in Biology and Medicine, PIBM 2023

作者： Zhang, Yameng Chen, Yang Qi, Xinping Li, Weitao Department of Computer Engineering Nanjing Institute of Technology No.1 Hongjing Avenue Nanjing Jiangsu211167 China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing Jiangsu211106 China

ISBN: (纸本)9781510667341

Photoacoustic microscopy (PAM) is a novel medical imaging technique developed rapidly in recent years with the advantages of high resolution, high contrast, and no ionizing radiation. In this study, we developed a one-shot functional photoacoustic microscopy (OS-fPAM) system for assessing traumatic brain injury (TBI). The OS-fPAM system only employed a single 532 nm nanosecond pulse laser with Raman delay optical path control, which can produce both 532 nm and 553 nm laser beams. The dual-wavelength beams were then coupled via a dichroic mirror and focused on the surface of the experimental sample. Then, the photoacoustic signal was collected and amplified in the ultrasonic signal acquisition module, and the blood oxygen saturation (sO2) image was calculated by two wavelength photoacoustic images. The feasibility of the OS-fPAM system was performed through the calibration experiments with different ratios of red ink and blue ink. Meanwhile, the OS-fPAM system can monitor microvascular structures and sO2 in the TBI model on mice for 96 hours in vivo with a spatial resolution of ∼40 μm, demonstrating the potential to evaluate rehabilitation and cerebral vascular damage. © 2023 SPIE.

关键词： Photoacoustic microscopy

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