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Author Correction: Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

Nature cell biology 2024年第5期26卷 839页

作者： Sanjay Jain Liming Pei Jeffrey M Spraggins Michael Angelo James P Carson Nils Gehlenborg Fiona Ginty Joana P Gonçalves James S Hagood John W Hickey Neil L Kelleher Louise C Laurent Shin Lin Yiing Lin Huiping Liu Alexandra Naba Ernesto S Nakayasu Wei-Jun Qian Andrea Radtke Paul Robson Brent R Stockwell Raf Van de Plas Ioannis S Vlachos Mowei Zhou Katy Börner Michael P Snyder Department of Medicine Washington University School of Medicine St Louis MO USA. sanjayjain@wustl.edu. Department of Pediatrics Washington University School of Medicine St Louis MO USA. sanjayjain@wustl.edu. Department of Pathology and Immunology Washington University School of Medicine St. Louis MO USA. sanjayjain@wustl.edu. Center for Mitochondrial and Epigenomic Medicine Department of Pathology and Laboratory Medicine Children's Hospital of Philadelphia and Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. lpei@pennmedicine.upenn.edu. Department of Cell and Developmental Biology and the Mass Spectrometry Research Center Vanderbilt University School of Medicine Nashville TN USA. jeff.spraggins@vanderbilt.edu. Department of Pathology Stanford School of Medicine Stanford CA USA. Texas Advanced Computing Center University of Texas at Austin Austin TX USA. Department of Biomedical Informatics Harvard Medical School Boston MA USA. GE Research Center Niskayuna NY USA. Department of Intelligent Systems Delft University of Technology Delft Netherlands. Department of Pediatrics (Pulmonology) and Program for Rare and Interstitial Lung Disease University of North Carolina at Chapel Hill Chapel Hill NC USA. Department of Microbiology and Immunology Stanford University Stanford CA USA. Departments of Medicine Chemistry and Molecular Biosciences Northwestern University Evanston IL USA. Department of Obstetrics Gynecology and Reproductive Sciences University of California San Diego La Jolla CA USA. Division of Cardiology University of Washington School of Medicine Seattle WA USA. Department of Surgery Washington University School of Medicine St Louis MO USA. Departments of Pharmacology Medicine (Hematology and Oncology) Lurie Cancer Center Northwestern University Feinberg School of Medicine Chicago IL USA. Department of Physiology and Biophysics University of Illinois at Chicago Chicago IL USA. Biological Sciences Division

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Siamese-ResNet: Implementing Loop Closure Detection based on Siamese Network

Siamese-ResNet: Implementing Loop Closure Detection based on...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Qiu, Kai Ai, Yunfeng Tian, Bin Wang, Bin Cao, Dongpu School of Aritificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China School of Software Engineering University of Science and Technology of China HeFei230026 China Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada

ISBN: (纸本)9781538644522

Deep learning has made significant breakthroughs in the tasks of image classification, detection, segmentation, etc. However, the application of deep learning in robotics is still scarce. SLAM is a fundamental problem in robotics and loop closure detection is an important part of SLAM. This paper attempts to use supervised learning methods to solve the loop closure detection problem in vision SLAM. We proposed Siamese-ResNet network, which combines Siamese network with ResNet to detect loop closure. To show the effectiveness of Siamese-ResNet, we evaluate Siamese-ResNet and FabMap2.0 on several open published datasets, like TUM SLAM dataset and FabMap SLAM dataset. Compared with FabMap2.0, Siamese-ResNet shows higher accuracy, better robustness and shorter time-consuming. © 2018 IEEE.

关键词： Robotics

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Development of structure and behavioral model for screw driving in-pipe inspection robot based on adaptive mechanism on legs 8

Development of structure and behavioral model for screw driv...

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8th ECCOMAS Thematic Conference on MULTIBODY DYNAMICS, MBD 2017

作者： Osman, Krešimir Kovačić, Zdenko Sales and Technical Department Termo Servis Ltd Ul. grada Vukovara 72 Zagreb10000 Croatia Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 Zagreb10000 Croatia

ISBN: (纸本)9788001061749

This paper presents the beginning of research in connection with the development of a pipeline inspection robot. The authors aimed to describe and present a structure and behavior model of a robot designed for inspecting the interior of pipelines to be used for gas distribution. The robot structure comprises a driving section and a driven section, where each has three legs with two ankles. The driven section contains a group of wheel sets adaptable by pressing against the interior wall of the pipeline, thus maintaining balance and stability of the robot, especially when passing through brackets and T-branches in the pipeline. The driven section of the robot is powered by an electric motor and a planetary gearbox where torque is transmitted to the legs with wheels, thus moving the robot based on the screw principle through the interior of the pipeline. In addition, a robot behavior model (mathematical model) was made for the structure presented, including its kinematic and dynamic models. © 2017 National Technical University of Athens. All rights reserved.

关键词： Robots

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Lom： Discovering Logic Flaws Within MongoDB-based Web Applications

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International Journal of Automation and computing 2017年第1期14卷 106-118页

作者： Shuo Wen Yuan Xue Jing Xu Li-Ying Yuan Wen-Li Song Hong-Ji Yang Guan-Nan Si Institute of Machine Intelligence College of Computer and Control Engineering Nankai University Tianjin 300350 China Department of Electrical Engineering and Computer Science Vanderbilt University Nashville Tennessee 37212 USA Centre for Creative Computing Bath Spa University Bath BA2 9BN UK School of Information Science and Electrical Engineering Shandong Jiaotong University Ji'nan 250357 China

Logic flaws within web applications will allow malicious operations to be triggered towards back-end database. Existing approaches to identifying logic flaws of database accesses are strongly tied to structured query language （SQL） statement construction and cannot be applied to the new generation of web applications that use not only structured query language （NoSQL） databases as the storage tier. In this paper, we present Lom, a black-box approach for discovering many categories of logic flaws within MongoDB- based web applications. Our approach introduces a MongoDB operation model to support new features of MongoDB and models the application logic as a mealy finite state machine. During the testing phase, test inputs which emulate state violation attacks are constructed for identifying logic flaws at each application state. We apply Lom to several MongoDB-based web applications and demonstrate its effectiveness.

关键词： Logic flaw web application security not only structured query language （NoSQL） database black-box MougoDB.

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Plenary Lectures

Plenary Lectures

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Mediterranean Conference on control and Automation (MED)

作者： Bart De Moor Yasamin Mostofi Maryam Kamgarpour Zdenko Kovačić Maja Cepanec Airlie Chapmar Mehran Mesbahi Department of Electrical Engineering (ESAT-STADIUS) KU Leuven Leuven Belgium Department of Electrical & Computer Engineering University of of California Santa Barbara CA USA Automatic Control Laboratory Swiss Federal Institute of Technology Zurich Zurich Switzerland University of Zagreb Faculty of Electrical Engineering and Computing University of Zagreb Faculty of Education and Rehabilitation Sciences University of Melbourne Australia University of Washington USA

The following topics are dealt with: control system synthesis; stability; nonlinear control systems; closed loop systems; robust control; feedback; Lyapunov methods; mobile robots; uncertain systems; and position cont... 详细信息

ISBN: (纸本)9781538674994;9781538678909

关键词： Robot sensing systems Electrical engineering Education Autism Robot kinematics Decision making

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A Parametric Time Frequency-Conditional Granger Causality Method Using Ultra-regularized Orthogonal Least Squares and Multiwavelets for Dynamic Connectivity Analysis in EEGs

arXiv

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arXiv 2018年

作者： Li, Yang Lei, Mengying Cui, Weigang Guo, Yuzhu Wei, Hua-Liang Department of Automation Sciences and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing Advanced Innovation Center for Big Date-based Precision Medicine Beihang University Beijing China Department of Automation Sciences and Electrical Engineering Beihang University Beijing China Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3DJ United Kingdom

— Objective: This study proposes a new parametric TF (time-frequency)-CGC (conditional Granger causality) method for high-precision connectivity analysis over time and frequency in multivariate coupling nonstationary systems, and applies it to scalp and source EEG signals to reveal dynamic interaction patterns in oscillatory neocortical sensorimotor networks. Methods: The Geweke’s spectral measure is combined with the TVARX (time-varying autoregressive with exogenous input) modelling approach, which uses multiwavelets and ultra-regularized orthogonal least squares (UROLS) algorithm aided by APRESS (adjustable prediction error sum of squares), to obtain high-resolution time-varying CGC representations. The UROLS-APRESS algorithm, which adopts both the regularization technique and the ultra-least squares criterion to measure not only the signal data themselves but also the weak derivatives of them, is a novel powerful method in constructing time-varying models with good generalization performance, and can accurately track smooth and fast changing causalities. The generalized measurement based on CGC decomposition is able to eliminate indirect influences in multivariate systems. Results: The proposed method is validated on two simulations and then applied to multichannel motor imagery (MI)-EEG signals at scalp- and source-level, where the predicted distributions are well recovered with high TF precision, and the detected connectivity patterns of MI-EEG data are physiologically and anatomically interpretable and yield new insights into the dynamical organization of oscillatory cortical networks. Conclusion: Experimental results confirm the effectiveness of the proposed TF-CGC method in tracking rapidly varying causalities of EEG-based oscillatory networks. Significance: The novel TF-CGC method is expected to provide important information of neural mechanisms of perception and cognition. Copyright © 2018, The Authors. All rights reserved.

关键词： Statistical tests

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A Demands-Matching Multi-Criteria Decision-Making Method for Reverse Logistics

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Procedia CIRP 2018年 72卷 1398-1403页

作者： Han Wang Zhigang Jiang Yan Wang Ying Liu Fei Li Wei Yan Hua Zhang Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science & Technology Wuhan 430081 China Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science & Technology Wuhan 430081 China Department of Computing Engineering and Mathematics University of Brighton Brighton BN2 4GJ United Kingdom Institute of mechanical and manufacturing engineering School of Engineering Cardiff University Cardiff CF24 3AA

A demand matching oriented Multi-Criteria Decision-Making method is presented to identify the best collection mode for used components. In this method, the damage condition and remaining service life are incorporated into the evaluation criteria of reuse mode, then a hybrid method (AHP-EW) integrating Analytic Hierarchy Process (AHP) and Entropy Weight (EW) is used to derive the criteria weights and the grey Multi-Attributive Border Approximation Area Comparison (MABAC) is adopted to rank the collection modes. Finally, a sensitivity analysis is used to test the stability of the method and a demands-matching method is proposed to validate the feasibility of the optimal alternative. The method is validated using the collection of used pressurizers as case study. The results of which show the effectiveness of the proposed method.

关键词： Reverse Logistics Multiple Criteria Decision Making Demands matching Damage condition Remaining Service life

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Human intention estimation based on hidden Markov model motion validation for safe flexible robotized warehouses

arXiv

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arXiv 2018年

作者： Petković, Tomislav Puljiz, David Marković, Ivan Hein, Björn University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems and Mobile Robotics Unska 3 ZagrebHR-10000 Croatia Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics Intelligent Process Automation and Robotics Lab Kaiserstraße 12 Deutschland KarlsruheDE-76131

With the substantial growth of logistics businesses the need for larger warehouses and their automation arises, thus using robots as assistants to human workers is becoming a priority. In order to operate efficiently and safely, robot assistants or the supervising system should recognize human intentions in real-time. Theory of mind (ToM) is an intuitive human conception of other humans' mental state, i.e., beliefs and desires, and how they cause behavior. In this paper we propose a ToM based human intention estimation algorithm for flexible robotized warehouses. We observe human's, i.e., worker's motion and validate it with respect to the goal locations using generalized Voronoi diagram based path planning. These observations are then processed by the proposed hidden Markov model framework which estimates worker intentions in an online manner, capable of handling changing environments. To test the proposed intention estimation we ran experiments in a real-world laboratory warehouse with a worker wearing Microsoft Hololens augmented reality glasses. Furthermore, in order to demonstrate the scalability of the approach to larger warehouses, we propose to use virtual reality digital warehouse twins in order to realistically simulate worker behavior. We conducted intention estimation experiments in the larger warehouse digital twin with up to 24 running robots. We demonstrate that the proposed framework estimates warehouse worker intentions precisely and in the end we discuss the experimental results. Copyright © 2018, The Authors. All rights reserved.

关键词： Virtual reality

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Visual Place Recognition in Long-term and Large-scale Environment based on CNN Feature

Visual Place Recognition in Long-term and Large-scale Enviro...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Zhu, Jianliang Ai, Yunfeng Tian, Bin Cao, Dongpu Scherer, Sebastian School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Robotics Institute Carnegie Mellon University PittsburghPA15213 United States

ISBN: (纸本)9781538644522

With the universal application of camera in intelligent vehicles, visual place recognition has become a major problem in intelligent vehicle localization. The traditional solution is to make visual description of place images using hand-crafted feature for matching places, but this description method is not very good for extreme variability, especially for seasonal transformation. In this paper, we propose a new method based on convolutional neural network (CNN), by putting images into the pre-trained network model to get automatically learned image descriptors, and through some operations of pooling, fusion and binarization to optimize them, then the similarity result of place recognition is presented with the Hamming distance of the place sequence. In the experimental part, we compare our method with some state-of-the-art algorithms, FABMAP, ABLE-M and SeqSLAM, to illustrate its advantages. The experimental results show that our method based on CNN achieves better performance than other methods on the representative public datasets. © 2018 IEEE.

关键词： Hamming distance

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Forecasting transportation network speed using deep capsule networks with nested LSTM models

arXiv

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arXiv 2018年

作者： Ma, Xiaolei Li, Yi Cui, Zhiyong Wang, Yinhai School of Transportation Science and Engineering Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Department of Civil and Environmental Engineering University of Washington Seattle98195 United States

Accurate and reliable traffic forecasting for complicated transportation networks is of vital importance to modern transportation management. The complicated spatial dependencies of roadway links and the dynamic temporal patterns of traffic states make it particularly challenging. To address these challenges, we propose a new capsule network (CapsNet) to extract the spatial features of traffic networks and utilize a nested LSTM (NLSTM) structure to capture the hierarchical temporal dependencies in traffic sequence data. A framework for network-level traffic forecasting is also proposed by sequentially connecting CapsNet and NLSTM. On the basis of literature review, our study is the first to adopt CapsNet and NLSTM in the field of traffic forecasting. An experiment on a Beijing transportation network with 278 links shows that the proposed framework with the capability of capturing complicated spatiotemporal traffic patterns outperforms multiple state-of-the-art traffic forecasting baseline models. The superiority and feasibility of CapsNet and NLSTM are also demonstrated, respectively, by visualizing and quantitatively evaluating the experimental results. Copyright © 2018, The Authors. All rights reserved.

关键词： Long short-term memory

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