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28th International Conference on Neural Information Processing

作者： Li, Chenguang Yang, Hongjun Su, Shiying Cheng, Long Chinese Acad Sci Inst Automat State Key Lab Control & Management Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China

ISBN: (纸本)9783030923099;9783030923105

Assessment of hand motor function is crucial to stroke patients. However, the commonly used Fugl-Meyer assessment (FMA) scale requires 11 hand and wrist movements. To simplify these movements, this study proposes a hand motion classification framework based on deep learning to achieve the quantitative taxonomy of hand kinematics. To the best of our knowledge, this is the first study to use deep learning for the quantitative taxonomy of the hand kinematics. First, we use the Long Short-Term Memory (LSTM) neural network to extract deep features of 20 hand movements (including 11 FMA movements) from 37 healthy subjects, and rank the LSTM neural network output value (predicted probability) of each sample. The similarity between the movements obtained by the nonlinear transformation can be used to draw the confusion matrix. Then the confusion matrix is taken as the category feature to obtain the clustering dendrogram to show the similarity between different hand movements intuitively. Next, the 20 hand movements are divided into four groups by hierarchical clustering. The silhouette coefficient of the clustering results is 0.81, which is close to the ideal value of 1, indicating the validity of the clustering result. Finally, the clustering center is calculated to find the corresponding movement as the representative movement for motor function assessment. As a result, we reduced the 20 movements to 5 movements, allowing for a faster quantitative assessment of hand motor function than the FMA scale. This also lays the foundation of the assessment paradigm for our follow-up research on evaluation algorithm.

关键词： Hand kinematics Hand motor function assessment Deep learning LSTM Hierarchical clustering

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Quantitative analysis of the impact of various urban socioeconomic indicators on search-engine-based estimation of COVID-19 prevalence

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Infectious Disease Modelling 2022年第2期7卷 117-126页

作者： Ligui Wang Mengxuan Lin Jiaojiao Wang Hui Chen Mingjuan Yang Shaofu Qiu Tao Zheng Zhenjun Li Hongbin Song Department of Infectious Disease Prevention and Control Center for Disease Control and Prevention of Chinese People's Liberation ArmyBeijingChina Academy of Military Medical Sciences Academy of Military Science of Chinese PLABeijingChina The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina State Key Laboratory for Infectious Disease Prevention and Control National Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijingChina

Numerous studies have proposed search engine-based estimation of COVID-19 prevalence during the COVID-19 pandemic;however,their estimation models do not consider the impact of various urban socioeconomic indicators(USIs).This study quantitatively analysed the impact of various USIs on search engine-based estimation of COVID-19 prevalence using 15 USIs(including total population,gross regional product(GRP),and population density)from 369 cities in *** results suggested that 13 USIs affected either the correlation(SC-corr)or time lag(SC-lag)between search engine query volume and new COVID-19 cases(p<0.05).Total population and GRP impacted SC-corr considerably,with their correlation coefficients r for SC-corr being 0.65 and 0.59,*** population,GRP per capita,and proportion of the population with a high school diploma or higher had simultaneous positive impacts on SC-corr and SC-lag(p<0.05);these three indicators explained 37e50%of the total variation in SC-corr and *** for different urban agglomerations revealed that the goodness of fit,R2,for search engine-based estimation was more than 0.6 only when total urban population,GRP per capita,and proportion of the population with a high school diploma or higher exceeded 11.08 million,120,700,and 38.13%,respectively.A greater urban size indicated higher accuracy of search engine-based estimation of COVID-19 ***,the accuracy and time lag for search engine-based estimation of infectious disease prevalence can be improved only when the total urban population,GRP per capita,and proportion of the population with a high school diploma or higher are greater than the aforementioned thresholds.

关键词： Urban socioeconomic indicators Search engine-based estimation Effectiveness evaluation

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A Transformer-based Approach for Identifying Target-oriented Opinions from Travel Reviews

A Transformer-based Approach for Identifying Target-oriented...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE) / IEEE World Congress on Computational Intelligence (IEEE WCCI) / International Joint Conference on Neural Networks (IJCNN) / IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Qian, Haoda Tang, Zaichuan Ren, Yajun Li, Qiudan Zeng, Daniel Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China

ISBN: (数字)9781728186719

ISBN: (纸本)9781728186719

Performing target-oriented opinion word extraction (TOWE) from online travel reviews is a valuable reference for both tourists and attraction administration department. This paper formulates a novel research topic of identifying target-opinion pair from Chinese travel review corpus. Learning target-oriented representation accurately, locating the opinion word and extracting the complete opinion are three major challenges. Hence, we leverage aspect-based query, pos-tag and relative position and devise appropriate structure to fuse them in an encoder-decoder framework. Specifically, in the encoder, the target-fused (aspect, review) pair and the pos-tag label are encoded by transformers to model the global dependency, in the decoder, a BiLSTM is adopted to enhance contextual representation by incorporating relative position information. A real-world Chinese travel dataset for TOWE task is constructed, and the experimental results demonstrate the efficacy of the proposed model. Extensive ablation experiments are also conducted to study the effect of different components of the model.

关键词： Chinese Tourist Review Opinion Mining Transformers

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Design and Modeling of Elastic Variable Stiffness Robotic Fish Tail 19

Design and Modeling of Elastic Variable Stiffness Robotic Fi...

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19th IEEE International Conference on Mechatronics and Automation (IEEE ICMA)

作者： Zhu, Chunhui Deng, Liangwei Wang, Xiaofei Yin, Zhaoran Zhou, Chao Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China

ISBN: (数字)9781665408530

ISBN: (纸本)9781665408530;9781665408523

Fish have attracted a huge number of researchers in recent years due to their exceptional swimming abilities, and many imitation fish propulsion robots have been produced. Numerous studies have demonstrated that fish obtain the best swimming speed and efficiency by adjusting the stiffness of their bodies when the tail beats at different frequencies, yet most contemporary robotic fish neglect the stiffness of the fish body. In this article, we create a fishtail with elastic materials, which is combined with a hard silicone cylinder and several regularly arranged balls in the cylinder. We achieve changeable stiffness by squeezing the inner elastic balls to enhance total stiffness, which is controlled by a stepper motor, with the reason that second moments of cross section can influence the stiffness of beam. After modeling and analyzing the system, we build it into a composite cantilever beam made up of a hollow outer cylinder and a periodic heterogeneous core. The stiffness of this complicated beam is calculated using a explicitly formula. Finally, in order to achieve a considerable stiffness increase, we construct a test platform and undertake experimental verification.

关键词： Variable stiffness robotic fishtail cantilever beam composite beam

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Toward parallel intelligence: An interdisciplinary solution for complex systems

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The Innovation 2023年第6期4卷 152-164页

作者： Yong Zhao Zhengqiu Zhu Bin Chen Sihang Qiu Jincai Huang Xin Lu Weiyi Yang Chuan Ai Kuihua Huang Cheng He Yucheng Jin Zhong Liu Fei-Yue Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China Hunan Institute of Advanced Technology Changsha 410073China Shanghai Institute of Infectious Disease and Biosecurity Shanghai 200032China Institute of Epidemiology Helmholtz Zentrum Minchen-German Research Center for Environmental Health(GmbH)NeuherbergGermany Department of Computer Science Hong Kong Baptist UniversityHong KongChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling,analysis,management,and *** meet these demands,the parallel systems method rooted in the artificial systems,computational experiments,and parallel execution(ACP)approach has been *** method cultivates a cycle termed parallel intelligence,which iteratively creates data,acquires knowledge,and refines the actual *** the past two decades,the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines,offering vers atile interdisciplinary solutions for complex systems across diverse *** review explores the origins and fundamental concepts of the parallel systems method,showcasing its accomplishments as a diverse array of parallel technologies and applica-tions while also prognosticating potential *** posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.

关键词： execution artificial offering

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A BERT-based Heterogeneous Graph Convolution Approach for Mining Organization-Related Topics

A BERT-based Heterogeneous Graph Convolution Approach for Mi...

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作者： Qian, Haoda Yuan, Minjie Li, Qiudan Zeng, Daniel Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China

ISBN: (数字)9781728186719

ISBN: (纸本)9781728186719

Mining organization-related topics is helpful to analyze the information dissemination situation. Existing methods based on graph neural networks mainly consider the association between words and documents, they ignore the semantic interactions between documents, and do not consider the heterogeneity of edges which are difficult to solve the challenge of blurred topic boundaries in real scenarios, resulting in performance loss. This paper proposes a BERT-based Heterogeneous Graph Convolution Network (BERT-HGCN) approach for semi-supervised topic mining that comprehensively considers multi-semantic relations between words and documents. It deeply combines the advantages of transductive learning with pre-training models. We model documents as graph-structured data and capture multiple semantic dependencies among wordword, word-doc, and doc-doc via information propagation mechanism. During the model learning process, a two-stream encoding mechanism is used to learn the structural and semantic representations, which combines a hierarchical graph convolution network (HGCN) and a BERT-based auto-encoder. It considers both edges heterogeneity and semantics of original documents. Finally, a dual-supervision loss is used to train the classifier based on graph nodes and semantic representations for topic mining. We empirically evaluate the performance of the proposed model on a real-world organization-related dataset, and the experimental results demonstrate the efficacy of the model.

关键词： topic mining multi-level semantic heterogeneous graph neural network pre-training model

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Sora for foundation robots with parallel intelligence:three world models,three robotic systems

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Frontiers of Information Technology & Electronic Engineering 2024年第7期25卷 917-923页

作者： Lili FAN Chao GUO Yonglin TIAN Hui ZHANG Jun ZHANG Fei-Yue WANG School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100044China School of Electrical Engineering Wuhan UniversityWuhan 430072China

This paper outlines the initial steps and basic framework for developing foundation/infrastructure robots/robotics based on foundation models and parallel intelligence,as well as the potential applications of new art... 详细信息

关键词： artificial foundation intelligence

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Adversarial Binary Mutual Learning for Semi-Supervised Deep Hashing

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING systems 2022年第8期33卷 4110-4124页

作者： Wang, Guanan Hu, Qinghao Yang, Yang Cheng, Jian Hou, Zeng-Guang Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing 100190 Peoples R China Macau Univ Sci & Technol Joint Lab Intelligence Sci & Technol Inst Syst Engn Macau 999078 Peoples R China

Hashing is a popular search algorithm for its compact binary representation and efficient Hamming distance calculation. Benefited from the advance of deep learning, deep hashing methods have achieved promising performance. However, those methods usually learn with expensive labeled data but fail to utilize unlabeled data. Furthermore, the traditional pairwise loss used by those methods cannot explicitly force similar/dissimilar pairs to small/large distances. Both weaknesses limit existing methods' performance. To solve the first problem, we propose a novel semi-supervised deep hashing model named adversarial binary mutual learning (ABML). Specifically, our ABML consists of a generative model GH and a discriminative model DH, where DH learns labeled data in a supervised way and GH learns unlabeled data by synthesizing real images. We adopt an adversarial learning (AL) strategy to transfer the knowledge of unlabeled data to DH by making GH and DH mutually learn from each other. To solve the second problem, we propose a novel Weibull cross-entropy loss (WCE) by using the Weibull distribution, which can distinguish tiny differences of distances and explicitly force similar/dissimilar distances as small/large as possible. Thus, the learned features are more discriminative. Finally, by incorporating ABML with WCE loss, our model can acquire more semantic and discriminative features. Extensive experiments on four common data sets (CIFAR-10, large database of handwritten digits (MNIST), ImageNet-10, and NUS-WIDE) and a large-scale data set ImageNet demonstrate that our approach successfully overcomes the two difficulties above and significantly outperforms state-of-the-art hashing methods.

关键词： Data models Semantics Force Computational modeling Hash functions Binary codes Training data Adversarial learning (AL) deep learning hashing

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Design, manipulability analysis and optimization of an index finger exoskeleton for stroke rehabilitation

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MECHANISM AND MACHINE THEORY 2022年 167卷 104526-104526页

作者： Li, Guotao Cheng, Long Sun, Ning Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Rehabilitation medicine studies have indicated that occupational therapy has a positive effect on the recovery of hand function. However, few wearable hand exoskeletons can assist in performing the adduction and abduction exercises of occupational therapy. Therefore, the wearable index finger rehabilitation exoskeleton (WIFRE) is studied in this paper. First, a WIFRE is proposed to realize the index joint's independent actuation, including adduction and abduction movements. Second, the local/global kinematic and dynamic manipulability measures are proposed and analyzed to evaluate the performance of the WIFRE. The analysis results show that the dimensional parameters of the WIFRE have a significant effect on its global manipulability measures. The global kinematic and dynamic manipulability measures can be improved by 13%-15% compared with the corresponding minimums. Third, a multi-parameter multi-objective optimization method is proposed to simultaneously enhance the three global manipulability measures. Finally, experiments are performed to verify the effectiveness of the index finger exoskeleton and the global manipulability measures.

关键词： Wearable exoskeleton Kinematics Manipulability Optimization

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Optimization of Sucker Rod Pump Operations Using Parallel systems

IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION

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IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION 2022年 6卷 977-981页

作者： Cheng, Xiang Wang, Xingxia Liu, Shuliang Lu, Jingwei Zhang, Zhixue Liu, Zhaohai Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macau Inst Syst Engn Macau Peoples R China Beijing Mot G Intelligent Technol Co Ltd Prod Management Dept Beijing Peoples R China Tangshan Jidong Petr Machinery Co Ltd Tangshan Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 101408 Peoples R China

With the exploitation of oil, oil pumping units are facing with the challenges such as low efficiency, increased mining difficulties and old infrastructures. The requirement of digital construction on oilfields is emerging, especially to these sucker sod pump (SRP) units built in last century. In this article, to facilitate the intelligent development of SRP systems, the concept of the parallel digital sucker rod pump systems (PDSRPS) was presented first, and their optimization framework was designed to efficiently improve the design and balance by data interactions. The real oil pump systems were integrated with their customized digital twins to establish the cyber-physical systems. The adaptive optimization on pumping processes was continuously developing with the interaction between physical pump units and their digital versions. The feasibility of the proposed framework has been demonstrated through the computational experiments on conventional beam-pumping units.

关键词： Parallel systems digital twins sucker rod pump operation optimization intelligent oilfields

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