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arXiv 2018年

作者： Beste, Christian Kaping, Daniel Tzvetanov, Tzvetomir Cognitive Neurophysiology Department of Child and Adolescent Psychiatry Faculty of Medicine TU Dresden Germany National Institute of Mental Health Klecany Czech Republic CAS Key Laboratory of Brain Function and Disease School of Life Sciences University of Science and Technology of China Hefei Anhui230027 China Anhui Key Laboratory for Affective Computing and Advanced Intelligent Machines School of Computer and Information Hefei University of Technology Hefei Anhui230009 China

Oscillatory processes are central for the understanding of the neural bases of cognition and behaviour. To analyse these processes, time-frequency (TF) decomposition methods are applied and non-parametric cluster-based statistical procedure are used for comparing two or more conditions. While this combination is a powerful method, it has two drawbacks. One the unreliable estimation of signals outside the cone-of-influence and the second relates to the length of the time frequency window used for the analysis. Both impose constrains on the non-parametric statistical procedure for inferring an effect in the TF *** we extend the method to reliably infer oscillatory differences within the full TF mapand to test single *** show that it can be applied in small time windowsirrespective of the cone-of-influence and we further develop its application to single-condition case for testing the hypothesis of the presence or not of time-varying *** present tests of this new method on real EEG and behavioural data and show thatits sensitivity to single-condition testsis at least as good as classic Fourier *** inference in the full TF map is available and efficient in detecting differences between conditions as well as the presence of time-varying signal in single condition. Copyright © 2018, The Authors. All rights reserved.

关键词： Fourier analysis

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A prediction model of edge gas flow development state based on BP neural network 5

A prediction model of edge gas flow development state based ...

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Zhang, Jialiang An, Jianqi Wu, Min Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

The development and distribution states of the blast furnace (BF) gas flow determine whether the reaction in the furnace can proceed normally and decide the utilization efficiency of the carbon in the furnace and the stable smooth operation of the furnace. The internal environment of BF is closed with high temperature and high pressure, which causes that the relationship between the development situation of edge gas flow of the BF and the BF operation is uncertain. In this paper, a prediction model of edge gas flow development state based on BP neural network (BPNN) is proposed, clarifying the relationship between the development state of edge gas flow and the edge burden parameters. Firstly, this paper gets the relative operation factors of effecting the development situation of edge gas flow through analyzing the process mechanism of the BF ironmaking, and proposes the development index of edge gas flow and the heat load of cooling stave to measure the development state of the edge gas flow. Secondly, the intrinsic correlation between the data is verified, and the data are analyzed by Spearman's rank correlation coefficient (SRCC) analysis. Finally, according to the analysis results, combined with the burden mechanism, the edge gas flow prediction model is established to realize the prediction of the development state of the edge gas flow. The calculation of the data collected in the metallurgy scene of the BF suggested that this prediction model of the edge gas flow development state of the BF could describe the relationship between BF operation parameters and the developing state of the edge gas flow.

关键词： Flow of gases

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Passivity of Reaction–Diffusion Genetic Regulatory Networks with Time-Varying Delays

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Neural Processing Letters 2017年第3期47卷 1115-1132页

作者： Zou, Chengye Wei, Xiaopeng Zhang, Qiang Zhou, Changjun Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China Key Laboratory of Advanced and Intelligent Computing Dalian University Ministry of Education Dalian China

This article investigates the passivity of reaction–diffusion genetic regulatory networks (GRNs) with time-varying delays and uncertainty terms under Dirichlet, Neumann, and Robin boundary conditions. We provide delay-dependent stability criteria by constructing appropriate Lyapunov–Krasovskii functions and linear matrix inequalities, and offer conditions sufficient to ensure the passivity of GRNs. We conducted a comparative analysis of GRNs under these three conditions. Numerical examples of the proposed approaches are provided to illustrate its effectiveness, and represent the three-dimensional figures of the trajectories of the concentrations of mRNA and the proteins of GRNs under Dirichlet boundary conditions.

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Human motion data editing based on a convolutional automatic encoder and manifold learning

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Entertainment computing 2019年 30卷

作者： Dongsheng Zhou Xinzhu Feng Xin Yang Qiang Zhang Xiaopeng Wei Xiaoyong Fang Deyun Yang Key Laboratory of Advanced Design and Intelligent Computing (Dalian University) Ministry of Education Dalian 116622 China College of Computer Science and Technology Dalian University of Technology Dalian 116024 China Research Institute of Human Factors and Safety Engineering Hunan Institute of Technology Hengyang Hunan Province 421002 China School of Information Science and Technology Taishan University Tai’an Shandong Province 271000 China

Technology of human motion capture has been widely used in digital entertainment field. Editing the existing large amount of human motion capture data, correcting and eliminating motion distortion caused by noise and other defects have important value and significance for data reuse. In this paper, data processing is carried out based on convolutional automatic encoder and manifold learning. The popular structure of human motion data was learned by a one-dimensional time domain convolution automatic encoder, in which the hidden unit of the automatic encoder represents motion data. Three constraints were used to overcome the problem that the hidden unit has too much motion editing range. The data to be processed in this paper has no limit on the number of motions. The proposed method can process large data sets in parallel and automatically perform manifold learning without manual labelling and segmentation. In the final, comparative experiments based on a variety of damaged motion data have been carried out. The results showed that the proposed method can effectively reduce the error of the original motion data, and has achieved good results in both objective evaluation and subjective evaluation.

关键词： Human motion data Convolution automatic encoder Manifold learning Motion editing

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Method of Age Estimation Based on ML-GMM Feature and Double Layers Estimation Model

Method of Age Estimation Based on ML-GMM Feature and Double ...

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作者： Min Hu Wendi Teng Yaona Zheng Keke Zhang AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information He Fei University of Technology

Feature extraction and estimation method are two key components of age estimation. This paper proposes a novel age estimation method based on Multi Levels Gaussian Mixture Model(MLGMM) and double layers estimation model. In the feature extraction phase, ML-GMM is used to construct different GMMs for different level features, which can well reflect the global and local age feature of facial images. In the estimation phase, double layers estimation model based on SVM-KNN is proposed. The first layer roughly divides age groups by using SVM. The second layer adopts KNN theory to find K images of consecutive age which have minimum sum of distance with the testing sample. The specific age is obtained by weighting these K age values. This paper performs a lot of experiments on mixed age database of FG-NET and MORPH-II databases. The mean absolute errors of age estimation are 3.22 years. Experimental results show that the proposed method is more effective than other methods of state-of-the-art for age estimation of facial images. It can extract more rich and complete age feature, improve the generalization ability of age estimation and reduce the mean absolute errors.

关键词： Multi Levels Gaussian Mixture Model SVM KNN Age Estimation

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A Fusion Decision Method Based on the Dynamic Fuzzy Density Assignment

A Fusion Decision Method Based on the Dynamic Fuzzy Density ...

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作者： Yanqiu Li Fuji Ren Min Hu Xiaohua Wang AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information He Fei University of Technology

Fuzzy density is an important part of fuzzy integral, which is used to describe the reliability of classifiers in the process of fusion. Most of the fuzzy density assignment methods are based on the training priori knowledge of the classifier and ignore the difference of the testing samples themselves. To better describe the real-time reliability of the classifier in the fusion process, the dispersion of the classifier is calculated according to the decision information which outputted by the classifier. Then the divisibility of the classifier is obtained through the information entropy of the dispersion. Finally, the divisibility and the priori knowledge are combined to get the fuzzy density which can be dynamically adjusted. Experiments on JAFFE and CK databases show that, compared with traditional fuzzy integral methods, the proposed method can effectively improve the decision performance of fuzzy integral and reduce the interference of unreliable output information to decision. And it is an effective multi-classifier fusion method.

关键词： Fuzzy Density Facial expression recognition (FER) Fuzzy integral Divisibility

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Dynamic Analysis of a New Type of Asymmetrical Parallel Mechanism Based on Lagrange Method

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IOP Conference Series: Materials Science and Engineering 2018年第1期428卷

作者： Quan Li Bin Li Xinhua Zhao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin 300191 China

In this article, a novel over constrained 2-RRU&RSR parallel manipulator is proposed and analyzed. This mechanism is composed of a moving platform and a base, which connected by two same configuration RRU legs and one RSR leg. The article uses the 2RRU&RSR parallel mechanism that can achieve 2R1T (two rotations and one translational motion) as the object. Based on the known kinematics forward solutions, the dynamics study was carried out. The dynamic model of the parallel mechanism was established using the Lagrange method and then it can be obtained that the dynamic inverse solution. Then ADAMS software was used to build a virtual prototype of this mechanism and the dynamics simulation was performed by using Lagrange method. Under the trend of a certain trajectory, the law of driving torque changes with time, paving the way for subsequent trajectory planning and control.

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Four-Analog Computation Based on DNA Strand Displacement

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ACS omega 2017年第8期2卷 4143-4160页

作者： Chengye Zou Xiaopeng Wei Qiang Zhang Chanjuan Liu Changjun Zhou Yuan Liu Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian 116024 China. Key Laboratory of Advanced and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China.

DNA strand displacement plays an important role in biological computations. The inherent advantages of parallelism, high storability, and cascading have resulted in increased functional circuit realization of DNA strand displacement on the nanoscale. Herein, we propose an analog computation with minus based on DNA strand displacement. The addition, subtraction, multiplication, and division gates as elementary gates could realize analog computation with minus. The advantages of this proposal are the analog computation with negative value and division computation. In this article, we provide the designs and principles of these elementary gates and demonstrate gate performance by simulation. Furthermore, to show the cascade property of gates, we computed a polynomial as an example by these gates.

关键词： Equilibrium Genetics Circuits Addition reactions Reaction rates

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Author Correction: Mapping global lake dynamics reveals the emerging roles of small lakes

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Nature communications 2022年第1期13卷 6337页

作者： Xuehui Pi Qiuqi Luo Lian Feng Yang Xu Jing Tang Xiuyu Liang Enze Ma Ran Cheng Rasmus Fensholt Martin Brandt Xiaobin Cai Luke Gibson Junguo Liu Chunmiao Zheng Weifeng Li Brett A Bryan School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen China. Department of Urban Planning and Design The University of Hong Kong Hong Kong SAR China. Urban Systems Institute The University of Hong Kong Hong Kong SAR China. School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen China. fengl@***. Department of Geosciences and Natural Resource Management University of Copenhagen Copenhagen Denmark. Department of Biology University of Copenhagen Copenhagen Denmark. Department of Physical Geography and Ecosystem Science Lund University Lund Sweden. Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China. Institute of Geodesy and Geophysics Chinese Academy of Sciences Wuhan China. School of Water Conservancy North China University of Water Resources and Electric Power 450046 Zhengzhou China. EIT Institute for Advanced Study Ningbo China. Institute for Climate and Carbon Neutrality The University of Hong Kong Hong Kong SAR China. Centre for Integrative Ecology School of Life and Environmental Sciences Deakin University Burwood Victoria Australia.

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Study on the influence of parameters of medical drill on bone drilling temperature

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IOP Conference Series: Materials Science and Engineering 2018年第1期339卷

作者： Xianchun XU Yahui Hu Jingwang Han Lin Yue Wangbiao Jiang Tianjin Key Laboratory of Design and Intelligent Control of Advanced Mechatronical System Tianjin 300384 China Tianjin University of Technology 300384 China.

During surgical interventions, the temperature generated during cortical bone drilling can affect the activity of bone material, which may lead to necrosis. In this paper, with the purpose of reducing the temperature during cortical bone drilling, the influence of the parameters of medical drill were analyzed. The finite element model of the drilling process was established based on the parametric design of the dril. The relationship between the drill bit diameter, the point angle, and the helix angle to the drilling temperature was studied by the center composite experiment. The results showed that the drilling temperature is increased with the increase of drill diameter, vertex angle and helix angle in the range of certain research.

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