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CT perfusion parameter estimation in stroke using neural network with transformer and physical model priors

Computers in Biology and Medicine 2024年 182卷 109134-109134页

作者： Luo, Luyao Liu, Pan Ye, Wanxing Chen, Fengwei Liu, Yu Liu, Ziyang Jing, Jing Xiong, Yunyun Zhu, Wanlin Jiang, Yong Cheng, Jian Wang, Yongjun Liu, Tao Beijing Advanced Innovation Center for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing China Medical Big Data Research Center Chinese PLA General Hospital Beijing China China National Clinical Research Center for Neurological Diseases Beijing China Department of Neurology Beijing Tiantan Hospital Capital Medical University Beijing China School of Computer Science and Engineering Beihang University Beijing China

Objectives: CT perfusion (CTP) imaging is vital in treating acute ischemic stroke by identifying salvageable tissue and the infarcted core. CTP images allow quantitative estimation of CT perfusion parameters, which can provide information on the degree of tissue hypoperfusion and its salvage potential. Traditional methods for estimating perfusion parameters, such as singular value decomposition (SVD) and its variations, are known to be sensitive to noise and inaccuracies in the arterial input function. To our knowledge, there has been no implementation of deep learning methods for CT perfusion parameter estimation. Materials & methods: In this work, we propose a deep learning method based on the Transformer model, named CTPerformer-Net, for CT perfusion parameter estimation. In addition, our method incorporates some physical priors. We integrate physical consistency prior, smoothness prior and the physical model prior through the design of the loss function. We also generate a simulation dataset based on physical model prior for training the network model. Results: In the simulation dataset, CTPerformer-Net exhibits a 23.4 % increase in correlation coefficients, a 95.2 % decrease in system error, and a 90.7 % reduction in random error when contrasted with block-circulant SVD. CTPerformer-Net successfully identifies hypoperfused and infarcted lesions in 103 real CTP images from the ISLES 2018 challenge dataset. It achieves a mean dice score of 0.36 for the infarct core segmentation, which is slightly higher than the commercially available software (dice coefficient: 0.34) used as a reference level by the challenge. Conclusion: Experimental results on the simulation dataset demonstrate that CTPerformer-Net achieves better performance compared to block-circulant SVD. The real-world patient dataset confirms the validity of CTPerformer-Net. © 2024 Elsevier Ltd

关键词： Image segmentation

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data mining accelerated the design strategy of high-entropy alloys with the largest hardness based on genetic algorithm optimization

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Materials Genome engineering Advances 2024年第2期2卷 108-125页

作者： Xianzhe Jin Hong Luo Xuefei Wang Hongxu Cheng Chunhui Fan Xiaogang Li Xiongbo Yan Key Laboratory for Corrosion and Protection of The Ministry of Education(MOE) Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijingChina National Materials Corrosion and Protection Data Center Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijingChina Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijingChina

This article proposed a design strategy that integrated machine learning models based on random forest and genetic algorithm(GA)for the rapid screening of hardness in the AlCoCrCuFeMoNiTi high-entropy alloys *** feature engineering and modeling,valence electron concentration,atomic size difference(δr),Pauling electronegativity difference(Δχ),geometric parameters(Λ),and the Cr content were identified as the five key features in the *** GAwas employed to search for alloys with superior hardness and guided *** three itera-tions,the HEA Al_(18)Co_(21)Cr_(23)Fe_(23)Mo_(15)exhibiting the highest predicted hardness(868.8 HV)was *** alloy was predominantly composed of BCC,ordered B2,andσphases,with an experimental hardness of 899.8±9.9 HV,which as approximately 5.38%greater than the maximum hardness observed in the original *** design strategy can also solve other regression problems and pave the way for optimizing material performance in various engineering applications.

关键词： AlCoCrCuFeMoNiTi genetic algorithm hardness high-entropy alloys machine learning

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Models of Exchanged datasets and Interactions of Buyers in the data Market: Toward Multi-Agent Simulators for System Design 26

Models of Exchanged Datasets and Interactions of Buyers in t...

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26th International Conference on Knowledge-Based and Intelligent Information and engineering Systems, KES 2022

作者： Hayashi, Teruaki Matsushima, Hiroyasu Sakaji, Hiroki Fukami, Yoshiaki Shimizu, Takumi Department of Systems Innovation School of Engineering The University of Tokyo Tokyo Japan Center for Data Science Education and Research Shiga University Shiga Japan Department of International Digital and Design Management Tokyo University of Science Tokyo Japan Faculty of Policy Management Keio University Kanagawa Japan

Value creation by reusing data as exchangeable resources has been widely studied as a new source of innovation, resulting in the establishment of a data market and its ecosystem. However, owing to the nascent nature of the market, observable information on exchanged datasets and interactions among stakeholders, such as buyers and providers, in the market are limited. Therefore, a lack of observable information that contributes to designing the market system and formulating regulations to promote the sound growth of data markets exists. This study modeled exchanged datasets and data buyers as agents, the smallest units of the data market components, and prepared seven scenarios for four market sizes. We simulated the effects of datasets and agent models with different market sizes on the agents' data purchases and emergence of popular datasets and discussed the factors that affect the purchase frequency distribution of the datasets. We present the experimental results and new implications for developing a data market simulator. The development of this simulator is expected to significantly advance research on the market understanding and system design in data markets. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & engineering Systems (KES 2022)

关键词： Systems analysis

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Pre-training with asynchronous supervised learning for reinforcement learning based autonomous driving

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Frontiers of Information Technology & Electronic engineering 2021年第5期22卷 673-686页

作者： Yunpeng WANG Kunxian ZHENG Daxin TIAN Xuting DUAN Jianshan ZHOU Beijing Advanced.Innovation Center for Big Data and Brain Computing School of Transportation Science and EngineeringBeihang UniversityBeijing 100191China

Rule-based autonomous driving systems may suffer from increased complexity with large-scale intercoupled rules,so many researchers are exploring learning-based *** learning(RL)has been applied in designing autonomous driving systems because of its outstanding performance on a wide variety of sequential control ***,poor initial performance is a major challenge to the practical implementation of an RL-based autonomous driving *** training requires extensive training data before the model achieves reasonable performance,making an RL-based model inapplicable in a real-world setting,particularly when data are *** propose an asynchronous supervised learning(ASL)method for the RL-based end-to-end autonomous driving model to address the problem of poor initial performance before training this RL-based model in real-world ***,prior knowledge is introduced in the ASL pre-training stage by asynchronously executing multiple supervised learning processes in parallel,on multiple driving demonstration data *** pre-training,the model is deployed on a real vehicle to be further trained by RL to adapt to the real environment and continuously break the performance *** presented pre-training method is evaluated on the race car simulator,TORCS(The Open Racing Car Simulator),to verify that it can be sufficiently reliable in improving the initial performance and convergence speed of an end-to-end autonomous driving model in the RL training *** addition,a real-vehicle verification system is built to verify the feasibility of the proposed pre-training method in a real-vehicle *** results show that using some demonstrations during a supervised pre-training stage allows significant improvements in initial performance and convergence speed in the RL training stage.

关键词： Self-driving Autonomous vehicles Reinforcement learning Supervised learning

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Application of Bayes’ Theorem in an Expert System for Diagnosing Mangosteen Diseases and Pests 22

Application of Bayes’ Theorem in an Expert System for Diagn...

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Proceedings of the 2022 International Conference on Computer, Control, Informatics and Its Applications

作者： Foni Agus Setiawan Freza Riana Siti Aisyah Research Center for Data and Information Science National Research and Innovation Agency Indonesia and Department of Informatics Engineering Universitas Ibn Khaldun Indonesia Department of Informatics Engineering Universitas Ibn Khaldun Indonesia

ISBN: (纸本)9781450397902

Mangosteen is one of the typical fruits of Southeast Asia and Indonesia's flagship fruit with promising export prospects. However, the poor quality of the mangosteen fruit, which is caused by diseases and pest attacks, is an obstacle in increasing export targets. Disease and pest attacks can be immediately overcome if farmers can identify the types of pests and diseases quickly based on the symptoms that appear on the mangosteen plant. The lack of knowledge of farmers in identifying the symptoms that appear and the limited number of experts lead to the late process of handling pests and diseases of the mangosteen plant. Therefore, this study aimed to build an expert system for diagnosing mangosteen diseases and pests using Bayes’ theorem. The knowledge base contained data of 5 diseases, 5 pests, and 42 symptoms. The inference engine utilized the Bayes’ theorem to produce a probability value of a disease or pest attacking the mangosteen plant based on the symptoms that arise. This study yielded an accuracy value of 94% based on 50 test data. This expert system can help farmers in identifying the diseases and pests that attack mangosteen plants quickly as well as finding solutions to the problem.

关键词： mangosteen diseases expert system plant pests Bayes’ theorem

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Development of Automated Detection Methods for Calculating Blood Vessel Width and Stenosis Rate in Cardiac Catheterization Imaging 24

Development of Automated Detection Methods for Calculating B...

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8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Huang, Hsien-Cheng Chang, Hsiao-Huang Ke, Xiang-Wei Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Cardiovascular Surgery Department Taipei Veterans General Hospital Taipei City Taiwan Taipei Medical University Taipei City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Coronary artery disease is the most prevalent type of heart disease and has a considerable mortality rate. In diagnosing and assessing coronary artery disease, physicians must integrate a variety of clinical information and test results to evaluate the degree of coronary artery obstruction and continually learn and improve their skills in clinical practice to ensure the most accurate assessment of patients. Currently, the use of information technology to assist medical staff allows more effective and accurate analysis of symptoms. This approach not only serves as an auxiliary standard for physician diagnosis, thereby reducing the possibility of misdiagnosis, but also significantly improves patient treatment outcomes and medical quality while reducing the time burden on physicians for diagnosing patients. This study utilized image processing techniques and thinning algorithms to automate the detection of coronary artery width and, following the recommended methods of physicians in related fields, used specific vessel widths to calculate the degree of coronary artery narrowing. This provides a more accurate and efficient assessment method for evaluating the degree of vascular constriction in patients with coronary artery disease. © 2024 Copyright ACM.

关键词： Patient treatment

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Implications of Preference and Reference Effects on A Green Supply Chain Considering Subsidy Withdrawal 12

Implications of Preference and Reference Effects on A Green ...

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12th International Symposium on Project Management, ISPM 2024

作者： Chen, Shan Fang, Meiqi Wang, Linlin Su, Jiafu Chongqing Industrial Big Data Innovation Center Co. Ltd. Chongqing China National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University Chongqing China School of Management Science and Engineering Chongqing Technology and Business University Chongqing China Western Branch of China Academy of Information and Communications Technology Chongqing China International College Krirk University Bangkok Thailand

ISBN: (纸本)9798331302344

In order to examine the impact of the withdrawal of government green subsidies on the green market, this paper formulates a two-period model to examine a green supply chain composed of a government and two manufacturers. We construct a basic model of government green subsidies in the first period, and formulate four scenarios in the second period considering the market expansion effect, green preference effect, price reference effect, and quality reference effect. We examine the impacts of the above effects on equilibrium decision-making and profits of the green supply chain through comparing and numerical analysis. We find that: 1) Only the market size enlarges to a certain degree, the profit of green manufacturer would increase after subsidy withdrawal. 2) Both green and traditional manufacturers can benefit from the consumers’ green preference, but it will hinder some traditional manufacturers from investing in green production. 3) The consumer price reference effect will damage green manufacturers' profits and reduce the greenness of products, while the traditional manufacturer could benefit from it under certain conditions. 4) Appropriate consumer green quality preferences are beneficial to the green market and can increase the profits of green manufacturers, but they will also provide free-riding opportunities for traditional manufacturers. © 2024 ISPM. All Rights Reserved.

关键词： Green manufacturing

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Lower Limb Muscle State Transition Control Based on Complex Network

Lower Limb Muscle State Transition Control Based on Complex ...

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第42届中国控制会议

作者： Junjie Geng Lingling Chen Xin Guo Rui Chen Mengge Wang School of Artificial Intelligence and Data Science Hebei University of Technology Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology School of Electrical Engineering Hebei University of Technology

Muscle activation cannot achieve the activation state experienced during normal activity throughout the rehabilitation process,and effectiveness of rehabilitation will be enhanced if the muscle state can be controlled from the "zero EMG" state to the normal motion *** is challenging to precisely regulate the muscle state during the model establishment process because the lower limb muscle group is a highly interconnected complicated ***,this study provides a muscle state transfer control method based on complex network control theory.A linear time-invariant functional myoelectric network model is modeled,and the structural controllability of the network is demonstrated using the PBH rank criterion to determine the optimal set of control *** Electrical Stimulation is used as an exogenous input to drive state transfer between *** results suggest that the method we propose is effective in controlling muscle state transitions.

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Optimization of Fracture Reduction Robot Controller

Optimization of Fracture Reduction Robot Controller

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International Symposium on Computer science and Intelligent Controls (ISCSIC)

作者： Baichuan An Jianwen Chen Minghe Liu Minghuan Yin Zicheng Song Chao Zhuang Cheng Chang Hao Sun School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China Limb Deformity Correction and Function Reconstruction Department Southern University of Science and Technology Hospital Shenzhen China School of Artificial Intelligence and Data Science Engineering Research Center of Intelligent Rehabilitation Device and Detection Technology Ministry of Education Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology Tianjin China

ISBN: (数字)9798350380286

ISBN: (纸本)9798350380293

To improve the accuracy of fracture reduction, combining inverse kinematic analysis with robot dynamics modelling might lead to a more effective controller for the fracture reduction process. The trajectory of the actuator driving rod’s motion and any deviations from it are calculated using Simulink simulation. The Levy-SSA-optimized fracture reduction robot’s positioning inaccuracy is two orders of magnitude lower than the PID adjustment approach. Using this method also improves the reduction trajectory’s accuracy and speeds up the convergence of the fracture-resetting robot control system to the ideal solution.

关键词： Actuators Accuracy Torque Software packages Robot control Process control Muscles Reliability engineering Trajectory Optimization

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An overview on the designs of distributed observers in LTI multi-agent systems

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science China(Technological sciences) 2021年第11期64卷 2337-2346页

作者： PEI YingQing GU HaiBo LIU KeXin LU JinHu Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China

With the rapid development of information technologies and cloud computing, sensor networks play an increasingly important role in our society. Over the past few decades, distributed observer theory has attracted unprecedented attention due to its wide potential applications in different areas. Meanwhile, various approaches and algorithms have been proposed and investigated. The design of distributed observers is one of the frontier topics of system and control research, which has the significant theoretical values and broad application prospects. This paper attempts to review the representative models and the corresponding approaches for distributed observer design in linear time-invariant(LTI) systems. Firstly, the research backgrounds and main advances of distributed observer designs are briefly reviewed. Then, recent results of distributed observer designs for discrete-time and continuous-time LTI multi-agent systems(MASs) are introduced in detail, respectively. Finally, the prospects and the future work directions of the design of distributed observers are put forward. The main purpose of this paper is to promote the emerging topic on the designs of distributed observers, with focuses on the interdisciplinary interest from technological sciences.

关键词： multi-agent system linear time-invarient system distributed observer consensus

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