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Improved IAMB with Expanded Markov Blanket for High-Dimensional Time Series Prediction

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Chinese Journal of Electronics 2016年第2期25卷 264-269页

作者： YANG Xianglin TONG Yunhai YANG Jianjun YAN Hong WANG Hongbo TAN Shaohua Key laboratory of machine perception (Ministry of Education) School of Electronics Engineering and Computer SciencePeking University State Key laboratory of Space Medicine Fundamentals and Application China Astronaut Research and Training Center

The classic regression model for multivariate time series prediction suffers from the curse of dimensionality because the least squares estimates become unreliable when the predictors of the time series are large and the number of samples is limited. The classic methods such as ridge regression, lasso regression, principal component regression are researched to solve the problem above. The ridge regression and principal component regression can not give the clear interpretation features for prediction,and lasso regression does not work well under collinearity, also the selections given by lasso regression are unstable and very sensitive to minor perturbations of the data.A practical method based on improved Incremental association Markov blanket(IAMB) with Expanded Markov blanket(EMB) was proposed for high-dimensional time series prediction. The EMB was constructed with simultaneous predictors and past predictors for time series. Since the faithfulness condition and reliable conditional independence test are not satisfied for high-dimensional time series with limited samples in practical applications. The symmetry of Markov blanket(MB) and the partial correlation coefficient criterion for conditional independent test were employed to learn the EMB, on which the regression was used for prediction. Empirical results show that our method based on EMB for macroeconomic prediction has less mean-square forecast error than other classic methods,especially when predicting the value with sharp fluctuation.

关键词： Expanded Markov blanket(EMB) High-dimensional time series Incremental association Markov blanket(IAMB) Prediction Regression

A versatile humanoid robot platform for dexterous manipulation and human-robot collaboration

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 526-540页

作者： Xin Shu Fenglei Ni Xinyang Fan Shuai Yang Changyuan Liu Baoxu Tu Yiwei Liu Hong Liu State Key laboratory of Robotics and System Harbin Institute of TechnologyHarbinChina

humanoid robots have attracted much attention by virtue of their compatibility with human ***,biped humanoids with immense promise still cannot function steadily and reliably in real-world settings in the current ***,rationally combining a humanoid robot with different stable mobile platforms is a favoured solution for diverse ***,a new versatile humanoid robot platform,aiming to provide a generic solution that can be flexibly deployed in diverse scenarios,for example,indoors and fields is *** humanoid robot platform incorporates multimodal perception,and extensible interfaces on hardware and software,allowing it to be rapidly integrated with different mobile platforms and end-effectors,only through easyto-assemble ***,the platform has achieved impressive integration,lightness,dexterity,and strength in its class,with human-like size and rich perception,targeted to have human-intelligent manipulation skills for human-engineered ***,this article elaborates on the reasoning behind the design choices,and outlines each ***,the essential performance of the platform is successfully demonstrated in a set of experiments with precise and dexterous manipulation,and human–robot collaboration requirements.

关键词： intelligent robots robotics

Diminishing the perception Bias in the Working Environment Using a Network Generation-Based Framework

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Tsinghua Science and Technology 2024年第3期29卷 671-683页

作者： Jun Qian Tongda Zhang Xiao Sun Yueting Chai Department of Automation Tsinghua UniversityBeijing 100084China Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhen 518055Chinaand with Systems Optimization LaboratoryStanford UniversityPalo AltoCA 94305USA

Income inequality is widespread in human society and has important implications for human ***’s perception of the environment bridges income inequality and individual behavioral *** research suggests that social income inequality is usually biased,either overestimated or ***,such phenomena have not been fully explored with quantitive prove,especially in the working environment based on performance data of actual *** fact,the correct perception of people is the basis of a fair environment for their production ***,the perception bias may weaken the adaptability and competitiveness of a company in the *** paper first confirms the prevalence of individual perception bias of income inequality within the working environment based on actual production *** results show that people tend to underestimate income inequity around them,and this underestimation grows with the real unfairness of the working ***,this paper proposes a network generation-based framework with a three-layer structure to correct perception bias using a cooperative network reengineering *** the framework,a homophily-based generative network model is proposed as the key *** simulation results show that our proposed framework effectively reduces individuals’perception bias of income inequality.

关键词： income inequality perception bias Gini coefficient factory production cooperative networkreengineering homophily-based generative network model

Multistage Microstructured Ionic Skin for Real-Time Vital Signs Monitoring and human-machine Interaction

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Energy & Environmental Materials 2024年第6期7卷 218-229页

作者： Xueke Wang Jinyu Zi Yi Chen Qiang Wu Zhimin Xiang Yongqiang Tu Peng Yang Yanfen Wan National Center for International Research on Photoelectric and Energy Materials Yunnan Key Laboratory for Micro/Nano Materials&TechnologyYunnan Key Laboratory of Electromagnetic Materials and DevicesSchool of Materials and EnergyYunnan UniversityKunming 650091China

Skin-like electronics research aiming to mimic even surpass human-like specific tactile cognition by operating perception-to-cognition-to-feedback of stimulus to build intelligent cognition systems for certain imperceptible or inappreciable signals was so ***,we constructed an all-in-one tri-modal pressure sensing wearable device to address the issue of power supply by integrating multistage microstructured ionic skin(MM i-skin)and thermoelectric self-power staffs,which exhibits high sensitivity *** MM i-skin with multi-stage“interlocked”configurations achieved precise recognition of subtle signals,where the sensitivity reached up to 3.95 kPa^(−1),as well as response time of 46 ms,cyclic stability(over 1500 cycles),a wide detection range of 0–200 ***,we developed the thermoelectricity nanogenerator,piezoelectricity nanogenerator,and piezocapacitive sensing as an integrated tri-modal pressure sensing,denoted as P-iskin,T-iskin,and C-iskin,*** multifunctional ionic skin enables real-time monitoring of weak body signals,rehab guidance,and robotic motion recognition,demonstrating potential for Internet of things(IoT)applications involving the artificial intelligence-motivated sapiential healthcare Internet(SHI)and widely distributed human-machine interaction(HMI).

关键词： bio-template method integrated device ionic skin skin-like microstructure tri-modal pressure sensing

Further results on the margin explanation of boosting:new algorithm and experiments

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Science China(Information Sciences) 2012年第7期55卷 1551-1562页

作者： WANG LiWei 1,DENG XiaoCheng 2 ,JING ZhaoXiang 1 & FENG JuFu 1 1 Key laboratory of machine perception,MOE,Peking University,Beijing 100871,China 2 Microsoft Search Technology Center Asia,Beijing 100080,China Key laboratory of machine perception MOE Peking University Beijing China Microsoft Search Technology Center Asia Beijing China

Understanding the empirical success of boosting algorithms is an important theoretical problem in machine *** of the most influential works is the margin theory,which provides a series of upper bounds for the generalization error of any voting classifier in terms of the margins of the training *** an equilibrium margin (Emargin) bound which is sharper than previously well-known margin bounds is *** this paper,we conduct extensive experiments to test the Emargin ***,we develop an efficient algorithm that,given a boosting classifier (or a voting classifier in general),learns a new voting classifier which usually has a smaller Emargin *** then compare the performances of the two classifiers and find that the new classifier often has smaller test errors,which agrees with what the Emargin theory predicts.

关键词： boosting margin Emargin theory

A blind video watermarking scheme based on ICA and shot segmentation

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Science in China(Series F) 2006年第3期49卷 302-312页

作者： SUN Jiande LIU Ju School of Information Science and Engineering Shandong University Jinan 250100 China National laboratory on machine perception Beijing 100871 China

Video watermark is the main method to protect the copyright of digital video. In this paper, a blind video watermarking scheme based on independent component analysis （ICA） and shot segmentation is presented. In this scheme, the global histogram comparison approach is used to segment the video, and ICA is performed on each obtained segment to get its independent component frames （ICFs）. The copyright information is embedded into the principal independent component frames （PICFs） according to the single watermark embedding （SWE） scheme. The content-based shot segmentation for video sequences is used here to improve the robustness to temporal desynchronization. The watermark embedded in PICFs provides better robustness to intra-video collusion attack. And blind detection is achieved by using the SWE scheme. The simulations show the feasibility and validity of this scheme. It can resist most of the common frame-based and video-based attacks. The watermark can be detected blindly. And it is robust to temporal desynchronization and intra-video collusion.

关键词： digital watermark video watermark copyright protection independent component analysis shot segmentation.

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New stability results of generalized impulsive functional differential equations

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Science China(Information Sciences) 2022年第2期65卷 248-250页

作者： Chao LIU Xiaoyang LIU Zheng YANG Hongyu YANG Junjian HUANG School of Computer Science and Engineering Chongqing University of Technology Key laboratory of machine perception and Children's Intelligence Development Chongqing University of Education

Dear editor,An impulsive functional differential equation (IFDE) is a hybrid dynamical system including both continuous-time dynamics exhibited via a functional differential equation and discrete-time dynamics which are shown by *** the best of our knowledge,impulsive phenomena,which are presented in the form of instantaneous jump,exist in the fields of engineering and *** recent years,

关键词： Stability Impulsive functional differential equation Uniformly stable function Razumikhin technique Lyapunov function

A malware detection model based on a negative selection algorithm with penalty factor

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Science China(Information Sciences) 2010年第12期53卷 2461-2471页

作者： ZHANG PengTao 1,2 , WANG Wei 1,2 & TAN Ying 1,2 1 Department of machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China 2 Key laboratory of machine perception, Ministry of Education, Peking University, Beijing 100871, China Department of machine Intelligence School of Electronics Engineering and Computer Science Peking University Beijing China Key laboratory of machine perception Ministry of Education Peking University Beijing China

A malware detection model based on a negative selection algorithm with penalty factor (NSAPF) is proposed in this paper. This model extracts a malware instruction library (MIL), containing instructions that tend to appear in malware, through deep instruction analysis with respect to instruction frequency and file frequency. From the MIL, the proposed model creates a malware candidate signature library (MCSL) and a benign program malware-like signature library (BPMSL) by splitting programs orderly into various short bit strings. Depending on whether a signature matches "self", the NSAPF further divides the MCSL into two malware detection signature libraries (MDSL1 and MDSL2), and uses these as a two-dimensional reference for detecting suspicious programs. The model classifies suspicious programs as malware and benign programs by matching values of the suspicious programs with MDSL1 and MDSL2. Introduction of a penalty factor C in the negative selection algorithm enables this model to overcome the drawback of traditional negative selection algorithms in defining the harmfulness of "self" and "nonself", and focus on the harmfulness of the code, thus greatly improving the effectiveness of the model and also enabling the model to satisfy the different requirements of users in terms of true positive and false positive rates. Experimental results confirm that the proposed model achieves a better true positive rate on completely unknown malware and a better generalization ability while keeping a low false positive rate. The model can balance and adjust the true positive and false positive rates by adjusting the penalty factor C to achieve better performance.

关键词： penalty factor negative selection algorithm signature extraction artificial immune system mal- ware detection

perception Enhanced Deep Deterministic Policy Gradient for Autonomous Driving in Complex Scenarios

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 557-576页

作者： Lyuchao Liao Hankun Xiao Pengqi Xing Zhenhua Gan Youpeng He Jiajun Wang Fujian Provincial Key laboratory of Automotive Electronics and Electric Drive Fujian University of TechnologyFuzhou350118China Fujian Provincial Universities Engineering Research Center for Intelligent Driving Technology Fuzhou350118China

Autonomous driving has witnessed rapid advancement;however,ensuring safe and efficient driving in intricate scenarios remains a critical *** particular,traffic roundabouts bring a set of challenges to autonomous driving due to the unpredictable entry and exit of vehicles,susceptibility to traffic flow bottlenecks,and imperfect data in perceiving environmental information,rendering them a vital issue in the practical application of autonomous *** address the traffic challenges,this work focused on complex roundabouts with multi-lane and proposed a perception EnhancedDeepDeterministic Policy Gradient(PE-DDPG)for AutonomousDriving in the ***,themodel incorporates an enhanced variational autoencoder featuring an integrated spatial attention mechanism alongside the Deep Deterministic Policy Gradient framework,enhancing the vehicle’s capability to comprehend complex roundabout environments and make ***,the PE-DDPG model combines a dynamic path optimization strategy for roundabout scenarios,effectively mitigating traffic bottlenecks and augmenting throughput *** experiments were conducted with the collaborative simulation platform of CARLA and SUMO,and the experimental results show that the proposed PE-DDPG outperforms the baseline methods in terms of the convergence capacity of the training process,the smoothness of driving and the traffic efficiency with diverse traffic flow patterns and penetration rates of autonomous vehicles(AVs).Generally,the proposed PE-DDPGmodel could be employed for autonomous driving in complex scenarios with imperfect data.

关键词： Autonomous driving traffic roundabouts deep deterministic policy gradient spatial attention mechanisms