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1st IEEE International Conference on Medical Artificial Intelligence, MedAI 2023

作者： Xu, Xin Lu, Wenjing Lei, Jiahao Qiu, Peng Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Department of Vascular Surgery China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9798350358780

Interactive medical image segmentation methods have become increasingly popular in recent years. These methods combine manual labeling and automatic segmentation, reducing the workload of annotation while maintaining high accuracy. However, most current interactive segmentation frameworks are limited to 2D image data, and are not suitable for 3D image data due to the large size and high complexity of 3D data, as well as the challenges posed by information asymmetry and sparse annotation. In this paper, we propose SliceProp, an interactive segmentation framework that implements slice-wise Label Bidirectional Propagation (LBP) for 3D medical image segmentation. SliceProp extends the interactive 2D image segmentation algorithm to 3D image segmentation, and can handle 3D data with large size and high complexity. Moreover, equipped with a Backtracking Feedback Check (BFC) module, SliceProp effectively addresses the issues of information asymmetry and spatial sparse annotation in 3D medical image segmentation. Additionally, we adopt an uncertainty-based criterion to pri-oritize the slices to be refined interactively, which enhances the efficiency of the interaction process by enabling the model to focus on the regions with the most unreliable predictions. SliceProp is evaluated on two datasets and achieves promising results compared to state-of-the-art methods. © 2023 IEEE.

关键词： Medical imaging

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A Comparison of Large-Scale MOEAs with Informed Initialization for Voltage Transformer Ratio Error Estimation 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Li, Lianghao He, Cheng Li, Hongbin Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Large-scale multiobjective optimization problems (LSMOPs) exist widely in real-world applications. The large number of decision variables in LSMOP leads to a tremendous high-dimensional search space, which is still challenging for existing multiobjective evolutionary algorithms (MOEAs). The voltage transformer ratio error estimation (TREE) problem is a typical LSMOP in real-world applications. A number of large-scale multiobjective evolutionary algorithms (LSMOEAs) have been adopted for solving the TREE problem, but so far there is still considerable potential for improvement in their results. In this paper, we propose a informed initialization for solving the TREE problem. The physical properties of the TREE problem are used to construct an initial set of solutions with specific characteristics. The proposed initialization method is tested against the default initialization method on five TREE problems by being applied on six state-of-the-art LSMOEAs and a classical MOEA. The experimental results demonstrate that the initialization method has a significant effect on the performance of LSMOEAs in solving the TREE problems. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

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Spatial Dynamics of Chickenpox Outbreaks in Rapidly Developing Regions:Implications for Global Public Health

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Biomedical and Environmental Sciences 2024年第7期37卷 687-697页

作者： Li Wang Miaomiao Wang Chengdong Xu Peihan Wang Meiying You Zihan Li Xinmei Chen Xinyu Liu Xudong Li Yuanyuan Wang Yuehua Hu Dapeng Yin College of Geography and Environmental Science Henan UniversityKaifeng 475001HenanChina State Key Laboratory of Resources and Environmental Information System Institute of Geographic Science and Natural Resource ResearchChinese Academy of SciencesBeijing 100101BeijingChina Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions(Henan University) Ministry of EducationKaifeng 475001HenanChina Office of Epidemiology Chinese Center for Disease Control and PreventionBeijing 102206BeijingChina University of Chinese Academy of Sciences(UCAS) Beijing 100101BeijingChina Weifang Municipal Center for Disease Control and Prevention Weifang 261061ShandongChina Hainan Center for Disease Control and Prevention Haikou 570203HainanChina

Objective The occurrence of chickenpox in rapidly developing areas poses substantial seasonal risk to ***,certain factors influencing local chickenpox outbreaks have not been ***,we examined the relationship between spatial clustering,heterogeneity of chickenpox outbreaks,and socioeconomic factors in Southern *** We assessed chickenpox outbreak data from Southern China between 2006 and 2021,comprising both relatively fast-growing parts and slower sub-regions,and provides a representative sample of many developing *** analyzed the spatial clustering attributes associated with chickenpox outbreaks using Moran’s I and local indicators of spatial association and quantified their socioeconomic determinants using Geodetector q *** There were significant spatial heterogeneity in the risk of chickenpox outbreaks,with strong correlations between chickenpox risk and various factors,particularly demographics and living ***,interactive effects among specific are factors,such as population density and per capita residential building area,percentage of households with toilets,percentage of rental housing,exhibited q statistics of 0.28,0.25,and 0.24,*** This study provides valuable insights into the spatial dynamics of chickenpox outbreaks in rapidly developing regions,revealing the socioeconomic factors affecting disease *** implications extend the formulation of effective public health strategies and interventions to prevent and control chickenpox outbreaks in similar global contexts.

关键词： Chickenpox Spatial dynamics Socioeconomic factors

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Invariant Tensor Modeling and Functional Matrix Coding of Flight Dynamics for Nonlinear Aircraft control

Invariant Tensor Modeling and Functional Matrix Coding of Fl...

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第34届中国控制与决策会议

作者： Tangwen Yin Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education

Flight trajectory consistence is an important factor influencing mission performance and ***,the lack of in-situ flight dynamics with high fidelity remains a challenge to enhance stability and controllability for aircraft maneuver in space,because modeling and coding of predictive system response in control synthesis is difficult to be mathematically formulated and computationally *** we generalize the invariant tensor modeling of flight dynamics so that its functional matrix coding is adapted to the multivariable nonlinear control of aircraft with augmented stability and controllability;and we verify that the nonlinear functional parameters in control synthesis with unobservable external forces and moments can improve the consistence of flight *** demonstrate that the planned flight trajectory can be consistently fulfilled using the nonlinear control synthesized through tensor modeling and matrix *** conclusion,invariant tensor modeling facilitates the functional matrix coding of flight dynamics with six degrees of freedom,which can be applied to build the feedback through dimensional analysis for augmented stability and controllability,such that collaborative optimization of nonlinear functional parameters establishes the multivariable nonlinear control to improve the consistence of flight trajectory for sustained performance and continuing safety.

关键词： controllability Dimensional Analysis Flight Trajectory Consistence Nonlinear control Stability

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Modeling and Parameter Identification of Constant-Speed Centrifugal Chiller Based on Experiments

Modeling and Parameter Identification of Constant-Speed Cent...

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2023 International Conference on Power system Technology, PowerCon 2023

作者： Han, Xinchan Zhang, Wen Cheng, Dingyi Zhang, Tingting Liu, Meng Xie, Yuxin Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Shandong Electric Power Research Institute Jinan China JinXianDai Information Industry Co. Ltd. Jinan China

ISBN: (纸本)9798350300222

The expanding penetration of intermittent renewable energy resources is motivating the development of demand response (DR) services for balancing generation and load. Central air conditionings (CACs) are potential candidates due to their thermal energy storage capability. A suitable load model is the foundation for DR services. However, CACs contain multiple control subsystems whose parameters are difficult to obtain because of trade secrets. This paper focuses on the modeling and parameter identification of the constant-speed centrifugal chiller, which accounts for 60-70% of the power of CAC. A thermal-electrical model of a constant-speed centrifugal chiller is established to describe the dynamic operation process. In addition, the critical control parameters and the delay time of control systems are identified based on experimental data for a practical building chiller. The experimental results verified the effectiveness of the proposed model. © 2023 IEEE.

关键词： Air conditioning

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Isoform Function Prediction Based on Heterogeneous Graph Attention Networks

Isoform Function Prediction Based on Heterogeneous Graph Att...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Guo, Kuo Li, Yifan Chen, Hao Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Institute of Image Processing and Pattern Recognition Shanghai200240 China Carnegie Mellon University School of Computer Science Computational Biology Department PittsburghPA15213 United States

ISBN: (纸本)9798350337488

Isoforms refer to different mRNA molecules transcribed from the same gene, which can be translated into proteins with varying structures and functions. Predicting the functions of isoforms is an essential topic in bioinformatics as it can provide valuable insights into the intricate mechanisms of gene regulation and biological processes. Conventionally, gene function labels are standardized in Gene Ontology (GO) terms. However, traditional methods for predicting isoform function are largely limited by the absence of isoform-specific labels, sparse annotations, and the vast number of GO terms. To address these issues, we propose HANIso, a deep learning-based method for isoform function prediction. HANIso leverages a pretrained protein language model to extract features from protein sequences. It also integrates heterogeneous information, such as isoform sequence features, GO annotations, and isoform interaction data, using a Heterogeneous Graph Attention Network (HAN). This allows the model to learn the importance of different sources of information and their semantic relationships through the attention mechanism. Our method can predict function labels at both the gene level and isoform level. We conduct experiments on two species datasets, and the results demonstrate that our method outperforms existing methods on both AUROC and AUPRC. HANIso has the potential to overcome the limitations of traditional methods and provide a more accurate and comprehensive understanding of isoform function. © 2023 IEEE.

关键词： alternative splicing gene ontology heterogeneous graph attention network isoform function prediction protein language model

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Consensus of Linear Multi-agent systems with Pure Relative Output Through Fully Distributed Reduced-Order Protocols

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IFAC-PapersOnLine 2023年第2期56卷 10162-10167页

作者： Yuwen Ma Xianwei Li Shaoyuan Li Department of Automation Shanghai JiaoTong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China

This paper considers fully distributed adaptive control for linear multi-agent systems with pure relative output information only. Two reduced-order protocols, namely, an edge-based protocol and a node-based protocol, are derived. For the edge-based protocol, each edge is adapted by a coupling weight which depends only on relative output information of the associated two agents, while the coupling weight in the node-based protocol is based on the relative output information of all neighboring agents. Sufficient conditions for the solvability of the consensus problem under the two protocols are derived. Compared with most of the existing related protocols, the main merits of the protocols are that only relative output information is needed, which helps reduce the communication burdens and protect the multi-agent systems from network attacks, and that the protocols are fully distributed. A simulation example is finally presented to illustrate the effectiveness of the proposed protocols.

关键词： Multi-agent systems consensus pure relative output fully distributed design

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Lightweight Vision Transformer for Small Data Sets 38

Lightweight Vision Transformer for Small Data Sets

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Fang, Wenxing Su, Yanxu Institutes of Physical Science and Information Technology Anhui University Hefei China School of Artificial Intelligence Anhui University Hefei230601 China Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350303636

With the rapid development of Transformers in the field of computer vision, models based on Transformers have become highly competitive architectures in the area. Although variants of Transformer models have achieved increasing accuracy on image classification tasks, the size of the training set and the number of parameters required by the models have increased dramatically. When dealing with small datasets, such models face problems such as overfitting and undergeneralization, leading to poor accuracy on the test set. We propose a new lightweight vision transformer (LVT) to address these issues. We reconstructed the backbone network, which learns the relationship between pixels through local window self-attention and global self-attention computation. We also use the attention pooling approach to fuse the token sequences generated by the backbone network more meticulously. We trained on the CIFAR-10 and CIFAR-100 datasets from scratch and compared them with a modern convolutional neural network. The experimental results show that LVT outperforms the modern convolutional neural network in terms of accuracy and efficiency. On the test set of CIFAR-10, we have obtained an accuracy of 96.83%, which indicates that our model can effectively solve the problems facing the training of small datasets and has a wide range of application prospects. © 2023 IEEE.

关键词： lightweight pooling self-attention windows

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Oxidation Mechanism and Toxicity Evolution of Linalool,a Typical Indoor Volatile Chemical Product

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Environment & Health 2024年第7期2卷 486-498页

作者： Zihao Fu Song Guo Ying Yu Hong-Bin Xie Shiyu Li Daqi Lv Putian Zhou Kai Song Zheng Chen Rui Tan Kun Hu Ruizhe Shen Maosheng Yao Min Hu State Key Joint Laboratory of Environmental Simulation and Pollution Control International Joint Laboratory for Regional Pollution ControlMinistry of Education(IJRC)College of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing 210044China Key Laboratory of Industrial Ecology and Environmental Engineering(Ministry of Education) School of Environmental Science and TechnologyDalian University of TechnologyDalian 116024China Institute for Atmospheric and Earth System Research/Physics Faculty of ScienceUniversity of HelsinkiP.O.Box 64FIN-00014 HelsinkiFinland

Linalool,a high-reactivity volatile chemical product(VCP)commonly found in cleaning products and disinfectants,is increasingly recognized as an emerging contaminant,especially in indoor *** the gas-phase oxidation mechanism of linalool is crucial for assessing its impact on atmospheric chemistry and human *** quantum chemical calculations and computational toxicology simulations,we investigated the atmospheric transformation and toxicity evolution of linalool under low and high NO/HO_(2)·levels,representing indoor and outdoor *** findings reveal that linalool can undergo the novel mechanisms involving concerted peroxy(RO_(2)·)and alkoxy radical(RO·)modulated autoxidation,particularly emphasizing the importance of cyclization reactions *** expands the widely known RO_(2)·-dominated H-shift-driven autoxidation and proposes a generalized autoxidation mechanism that leads to the formation of low-volatility secondary organic aerosol(SOA)*** analysis shows that over half of transformation products(TPs)exhibited higher carcinogenicity and respiratory toxicity compared to *** also propose time-dependent toxic effects of TPs to assess their long-term *** results indicate that the strong indoor emission coupled with slow consumption rates lead to significant health risks under an indoor *** results highlight complex indoor air chemistry and health concerns regarding persistent toxic products during indoor cleaning,which involves the use of linalool or other VCPs.

关键词： volatile chemical products(VCPs) peroxy radicals(RO_(2)·) atmospheric autoxidation secondary organic aerosol(SOA) computational toxicology

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Edge-assisted Prediction and Predictive control for Flexible Platooning under Mixed Traffic Flow

Edge-assisted Prediction and Predictive Control for Flexible...

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IEEE Conference on Vehicular Technology (VTC)

作者： Fengkun Gao Bo Yang Jiahang Li Cailian Chen Xinping Guan Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China

The uncertainty of human-driven vehicles (HDVs) has a significant impact on the movement of connected and automated vehicles (CAVs), especially on the CAV platoon. In this regard, the future trajectory information of the preceding HDV is essential for CAV platoon to develop a safe and smooth speed control strategy. However, constrained by computation and energy resources, on-board unit can not provide accurate predictions, which results in inefficient control strategy and even safety issues. Hence, we propose an edge-assisted prediction and a flexible cooperative adaptive cruise control (CACC) strategy in this paper. The challenges mainly lie in the design of coordination mechanism and control strategy. Considering the inaccuracy of prediction, an error-aware communication trigger scheme is first designed to decide whether to request the roadside unit (RSU) for performing accurate prediction with the aid of mobile edge computing (MEC). Further, a novel flexible tracking policy is proposed to deal with prediction error, which is integrated with model predictive control method to determine control inputs. Simulations based on real data, collected in Shanghai, China, demonstrate that our proposed method can significantly improve driving safety and speed smoothness.

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