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arXiv 2022年

作者： Gong, Jibing Wan, Yao Liu, Ye Li, Xuewen Zhao, Yi Wang, Cheng Lin, Yuting Fang, Xiaohan Feng, Wenzheng Zhang, Jingyi Tang, Jie School of Information Science and Engineering The Key Lab for Computer Virtual Technology and System Integration The Key Laboratory for Software Engineering of Hebei Province Yanshan University No. 438 West Hebei Avenue Hebei Qinhuangdao066004 China School of Computer Science and Technology Huazhong University of Science and Technology Luoyu Road 1037 Hubei Wuhan430074 China Salesforce Research 556 Xixi Road Chicago United States School of Cyber Science and Technology Beihang University 37 Xueyuan Road Beijing100191 China Department of Computer Science Tsinghua University Beijing100084 China

Massive open online courses (MOOCs), which offer open access and widespread interactive participation through the internet, are quickly becoming the preferred method for online and remote learning. Several MOOC platforms offer the service of course recommendation to users, to improve the learning experience of users. Despite the usefulness of this service, we consider that recommending courses to users directly may neglect their varying degrees of expertise. To mitigate this gap, we examine an interesting problem © 2022, CC BY.

关键词： Information services

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Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning

arXiv

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arXiv 2024年

作者： Zhu, Hongze Xie, Guoyang Hou, Chengbin Dai, Tao Gao, Can Wang, Jinbao Shen, Linlin National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Department of Computer Science City University of Hong Kong Hong Kong Department of Intelligent Manufacturing CATL Ningde China Fuzhou Fuyao Institute for Advanced Study Fuyao University of Science and Technology Fuzhou China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen China Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

High-resolution point clouds (HRPCD) anomaly detection (AD) plays a critical role in precision machining and high-end equipment manufacturing. Despite considerable 3D-AD methods that have been proposed recently, they still cannot meet the requirements of the HRPCD-AD task. There are several challenges: i) It is difficult to directly capture HRPCD information due to large amounts of points at the sample level;ii) The advanced transformer-based methods usually obtain anisotropic features, leading to degradation of the representation;iii) The proportion of abnormal areas is very small, which makes it difficult to characterize. To address these challenges, we propose a novel group-level feature-based network, called Group3AD, which has a significantly efficient representation ability. First, we design an Intercluster Uniformity Network (IUN) to present the mapping of different groups in the feature space as several clusters, and obtain a more uniform distribution between clusters representing different parts of the point clouds in the feature space. Then, an Intracluster Alignment Network (IAN) is designed to encourage groups within the cluster to be distributed tightly in the feature space. In addition, we propose an Adaptive Group-Center Selection (AGCS) based on geometric information to improve the pixel density of potential anomalous regions during inference. The experimental results verify the effectiveness of our proposed Group3AD, which surpasses Reg3D-AD by the margin of 5% in terms of object-level AUROC on Real3DAD. We provide the code and supplementary information on our website: https://***/M-3LAB/Group3AD. Copyright © 2024, The Authors. All rights reserved.

关键词： Anomaly detection

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Calibration of a three-dimensional photodynamic therapy illumination system and its segmentation assessment for port-wine stains

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Photonics and Lasers in Medicine 2016年第3期5卷 195-202页

作者： Feng, Yun Hu, Xiaoming Zhou, Ya Wang, Yong School of Software Beijing Institute of Technology No. 5 Zhong Guan Cun South Street Haidian District Beijing China School of Life Science Key Laboratory of Convergence Medical Engineering System and Healthcare Technology Ministry of Industry and Information Technology Beijing Institute of Technology No. 5 Zhong Guan Cun South Street Haidian District Beijing China School of Optoelectronics Beijing Institute of Technology No. 5 Zhong Guan Cun South Street Haidian District Beijing China

The uniformity of light dosimetry is an important parameter that affects the efficacy of photodynamic therapy (PDT). Although this uniformity can be improved by a three-dimensional (3D) digital PDT illumination system, it has a low field-of-view (FOV) utilization rate. A checkerboard calibration method using color coding is proposed to calibrate both the projector and camera of the system with a broad common FOV. Experiments reveal that the proposed method increases the utilization rate by up to three times compared with noncolor-coding methods with almost the same accuracy. A fine distinction of phantom lesions in the 3D system can be obtained by clustering, which may be used to optimize the treatment and light-dosimetry evaluation. © 2016 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Calibration

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Designing and Application of Wearable Fatigue Detection system Based on Multimodal Physiological Signals

Designing and Application of Wearable Fatigue Detection Syst...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiaoxuan Qiu Fuze Tian Qiuxia Shi Qinglin Zhao Bin Hu Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University Lanzhou China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Lanzhou China Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University Institute of Semiconductors Chinese Academy of Sciences Lanzhou China Engineering Research Center of Open Source Software and Real-Time System (Lanzhou University) Ministry of Education Lanzhou China

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Judging mental fatigue can be guided by acquiring and analyzing various physiological data. However, the existing equipment focuses on single physiological signals, such as electroencephalogram (EEG) and electrocardiogram (ECG), which ignores the preponderance of multimodal physiological signals in fatigue states. Alternatively, some equipment is difficult to operate and thus unsuitable for portable applications. To this end, this paper details the design of a miniaturized multi-physiological signal acquisition system. The system not only acquires EEG and ECG based on combining wavelet transform with Kalman filter, but also uses precise temperature sensors to synchronously acquire proximal skin temperature signals which are not easily interfered with by environmental noise or other physiological signals of human body. Through a fatigue assessment experiment on ten healthy subjects, it was verified that our equipment reliably detects mental fatigue states by monitoring and analyzing EEG, ECG, and proximal skin temperature data. In actual applications, this system appears to the traits of easy operation and good stability. It provides better hardware support for the pervasive applications and concrete implementation of mental health in multi-scene, and can popularize use.

关键词： Fatigue Electrocardiography Electroencephalography Skin Temperature measurement Temperature distribution Temperature sensors

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A Portable system of Mental Fatigue Detection and Mitigation based on Physiological Signals

A Portable System of Mental Fatigue Detection and Mitigation...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Chao Wu Fuze Tian Qiuxia Shi Qinglin Zhao Bin Hu Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University Lanzhou China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Lanzhou China Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors Chinese Academy of Sciences Lanzhou China Engineering Research Center of Open Source Software and Real-Time System(Lanzhou University) Ministry of Education Lanzhou China

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Mental fatigue of the brain will cause the weakening of the psychological and physiological functions of the human body, which increases the risk of mistakes and accidents. This paper designs a mental fatigue detection and mitigation system based on human physiological signals and classical music. Through the fatigue assessment and mitigation experiment on 20 healthy subjects, it is verified that the system is able to judge the mental fatigue state of the subjects and play classical music to mitigate fatigue via acquiring and analyzing (alpha+theta)/beta of electroencephalogram (EEG) and heart rate variability (HRV) of ballistocardiogram (BCG). The designed system realizes signal acquisition and fatigue analysis only through using portable device, this makes it have certain application value in office building, hospital, aircraft driving and other scenes.

关键词： Hospitals Buildings Psychology Fatigue Physiology Electroencephalography Multiple signal classification

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Classification of Cognitive Ability of Healthy Elderly Individuals Using Resting-State Functional Connectivity Magnetic Resonance Imaging and An Extreme Learning Machine

Research Square

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Research Square 2021年

作者： Yang, Zekun Ge, Manling Abdelkader, Nasreddine Belkacem Fu, Xiaoxuan Zhang, Qirui Chen, Shenghua Xie, Chong Song, Zibo Chen, Chao State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Hebei Province Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin300130 China Department of Computer and Network Engineering College of Information Technology United Arab Emirates University Al Ain15551 United Arab Emirates Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Harvard Medical School CharlestownMA02129 United States Department of Medical Imaging Jinling Hospital Nanjing University School of Medicine General Hospital of Eastern Theater Nanjing210002 China Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin300003 China

Purpose Quantitative determination of the correlation between cognitive ability and functional biomarkers in the elderly brain is essential. To identify biomarkers associated with cognitive performance in the elderly, this study combined an index model specific for resting-state functional connectivity (FC) magnetic resonance imaging (fcMRI) with a supervised machine learning method. Methods Performance scores on conventional cognitive test batteries and MRI data were obtained for 98 healthy elderly individuals and 90 healthy youth from two public databases. Based on the test scores, the elderly cohort was categorized into two groups: excellent and poor. An fcMRI index model was constructed for each elderly individual to determine the relative differences in FC among brain regions compared with that in the youth cohort. Brain areas sensitive to test scores could then be identified using the fcMRI indexes. To confirm the effectiveness of constructed model, the fcMRI indexes of these brain areas were used as feature matrix inputs for training an extreme learning machine. Classification accuracy was then tested in separate groups and confirmed by N-fold cross-validation. Results This learning study could effectively classify the cognitive status of healthy elderly individuals according to frontal lobe, temporal lobe, and parietal lobe FC values with a mean accuracy of 83.5%, which is substantially higher than that achieved using conventional correlation analysis. Conclusion This fcMRI classification study may facilitate early detection of age-related cognitive decline as well as help reveal the underlying pathological mechanisms. © 2021, CC BY.

关键词： Magnetic resonance imaging

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Real-time imaging of accelerated solid-liquid-gas reactions with nanobubbles

Research Square

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Research Square 2020年

作者： Wang, Wen Xu, Tao Chen, Jige Shangguan, Junyi Dong, Hui Ma, Huishu Zhang, Qiubo Bai, Tingting Guo, Zhirui Fang, Haiping Zheng, Haimei Sun, Litao SEU-FEI Nano-Pico Center Key Laboratory of MEMS of Ministry of Education Collaborative Innovation Center for Micro/Nano Fabrication Device and System Southeast University Nanjing210096 China Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Shanghai Synchrotron Radiation Facility Zhangjiang Laboratory Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai201204 China Department of Physics East China University of Science and Technology Shanghai200237 China Department of Materials Science and Engineering University of California BerkeleyCA94720 United States Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201800 China Key Laboratory of Welding Robot and Application Technology of Hunan Province Engineering Research Center of Complex Tracks Processing Technology Equipment of Ministry of Education Xiangtan University Xiangtan411105 China The Second Affiliated Hospital Key Laboratory for Aging & Disease Nanjing Medical University Nanjing210011 China

Solid-liquid-gas reactions are ubiquitous. An understanding of how gases influence the reactions at the nanoscale is significant for achieving the enhanced triple-phase reactions. Here, we report a real-time observation of the accelerated etching of gold nanorods with oxygen nanobubbles in aqueous hydrobromic acid using liquid cell transmission electron microscopy (TEM). Our observation reveals that when an oxygen nanobubble is close to a nanorod below the critical distance (~1nm), the local etching rate is significantly enhanced with over an order of magnitude faster. Molecular dynamics simulations results show that the strong attractive van der Waals interaction between the gold nanorod and oxygen molecules facilitates the transport of oxygen through the thin liquid layer to the gold surface and thus plays a crucial role in increasing the etching rate. This result sheds light on the rational design of solid-liquid-gas reactions for enhanced activities. © 2020, CC BY.

关键词： Molecular dynamics

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Covert channel mitigation method for secure real-time database using capacity metric

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Tongxin Xuebao/Journal on Communications 2008年第8期29卷 46-56页

作者： Zeng, Hai-Tao Wang, Yong-Ji Ruan, Li Zu, W. Cai, Jia-Yong Lab for Internet Software Technology Institute of Software Chinese Academy of Science Beijing 100190 China Key Laboratory for Computer Science Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China National Engineering Research Center for Fundamental Software Institute of Software Chinese Academy of Science Beijing 100190 China Integrate Information System Research Center Institute of Automation Chinese Academy of Science Beijing 100190 China

A capacity using covert channel mitigation method (CUCCMM) was proposed. This method uses capacity as metric for channel danger measure according to trusted computer system evaluation criteria (TCSEC) and multiple probabilities based protocol selection policy (MPBPSP) to guide die application of secure concurrency control protocol. The algorithms of channel's capacity measure and policy's parameter computing are also presented. Experimental results show that CUCCMM implements the restriction criterion on channel's capacity effectively and accurately, and the MPBPSP significantly decreases the influence of restriction operation on real-time performance.

关键词： Concurrency control

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Research on the Influence of Improved K-shell Algorithm on Commodity Profit

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Journal of Physics: Conference Series 2020年第1期1631卷

作者： Jing Chen Jincheng Huang College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China Key Laboratory for Computer Virtual Technology and system Integration of Hebei Province Qinhuangdao 066004 China Software Engineering Laboratory in Hebei Province Qinhuangdao 066004 China

In order to maximize the influence of commodity profits in e-commerce platforms, designing and improving the K-shell algorithm to select the more influential seed node sets in this paper. The new algorithm improves the number of active nodes by setting node threshold and edge weight attributes. To obtain more commodity profits, a strategy IRDSN (Strategy for Improving Repeat Degree of Seed Nodes) is proposed to select initial seed nodes and improve the repeat degree of seed nodes. The profit maximization based on linear threshold model is realized by setting different propagation modes. The improved algorithm and strategy IRDSN are analysed and verified in real data set and e-commerce platform. The results show that the algorithm effectively improves the profit of commodities.

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Correction to: Visual Servoing of Unknown Objects for Family Service Robots

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Journal of Intelligent & Robotic systems 2022年第4期106卷 1-1页

作者： Xin, Jing Dong, Caixia Zhang, Youmin Yao, Yumeng Gong, Ailing Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal Canada

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