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Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2024年第10期21卷 1959页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

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Optimal Estimation of Sensor Biases for Asynchronous Multi-Sensor Data Fusion

arXiv

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arXiv 2017年

作者： Pu, Wenqiang Liu, Ya-Feng Yan, Junkun Liu, Hongwei Luo, Zhi-Quan National Laboratory of Radar Signal Processing Collaborative Innovation Center of Information Sensing and Understanding Xidian University Xi'an710071 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Shenzhen Research Institute of Big Data Chinese University of Hong Kong Shenzhen518100 China

An important step in a multi-sensor surveillance system is to estimate sensor biases from their noisy asynchronous measurements. This estimation problem is computationally challenging due to the highly nonlinear transformation between the global and local coordinate systems as well as the measurement asynchrony from different sensors. In this paper, we propose a novel nonlinear least squares (LS) formulation for the problem by assuming the existence of a reference target moving with an (unknown) constant velocity. We also propose an efficient block coordinate decent (BCD) optimization algorithm, with a judicious initialization, to solve the problem. The proposed BCD algorithm alternately updates the range and azimuth bias estimates by solving linear least squares problems and semidefinite programs (SDPs). In the absence of measurement noise, the proposed algorithm is guaranteed to find the global solution of the problem and the true biases. Simulation results show that the proposed algorithm significantly outperforms the existing approaches in terms of the root mean square error (RMSE). Copyright © 2017, The Authors. All rights reserved.

关键词： Mean square error

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Trace codes over Z4 and Boolean function

arXiv

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arXiv 2017年

作者： Shi, Minjia Liu, Yan Hugues, Randriam Sok, Lin Solé, Patrick Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University No. 3 Feixi Road Hefei Anhui Province230039 China National Mobile Communications Research Laboratory Southeast University School of Mathematical Sciences of Anhui University Anhui230601 China CNRS/LAGA Université Paris 8 2 rue de la Liberté Saint-Denis93 526 France

We construct trace codes over Z4 by using Boolean functions and skew sets, respectively. Their Lee weight distribution is studied by using a Galois ring version of the Walsh-Hadamard transform and exponential sums. We... 详细信息

关键词： Boolean functions

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Ultrasonic reflectivity function estimation using Cepstrum Sparse Deconvolution

Ultrasonic reflectivity function estimation using Cepstrum S...

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IEEE International Ultrasonics Symposium

作者： Juan Lu Ramazan Demirli Jafar Saniie Embedded Computing and Signal Processing Laboratory Department of Electrical and Computer Engineering Illinois Institute of Technology Chicago United States Center for Advanced Communications Villanova University Pennsylvania United States

ISBN: (纸本)9781467398985

The ultrasonic signals backscattered from multilayered materials using a pulse-echo method are inherently low-resolution due to the band-limited nature of the interrogating transducer. To improve resolution, the Wiener Filter (WF) based solutions have been used traditionally, although they provide limited improvement and are highly sensitive to noise. More recently, sparse deconvolution techniques (e.g., l1-regularized Least Squares Deconvolution (l1-LSD)) have proved to be effective in improving the resolution;however, they are highly dependent on pulse invariance. It is common for an ultrasonic wavelet to change its shape as it propagates through the materials due to frequency dependent attenuation, scattering and dispersion. Consequently, these changes in pulse shape limit the application of these algorithms which need a prior knowledge of pulse-wave of the system. In this paper we present an adaptive and highly efficient deconvolution technique, Cepstrum Sparse Deconvolution (CSD), which does not require any prior information of the system or the detected object but compensates for the pulse-wave variation by estimating the fundamental pulse-wave shape directly from the backscattered signal. This pulse-wave estimation is based on cepstrum processing of the signal prior to the deconvolution process. Applications and comparisons are made to evaluate the performance of CSD, WF and l1-LSD through experimental and simulated ultrasound data which contain varying-shape wavelets with respect to amplitude, center frequency, arrival time, bandwidth, and phase parameters. The Normalized Mean Absolute Score (NMAS) index, a measure of distance between the actual reflectivity function and the estimated function is used to evaluate these algorithms' performance. The results show that CSD is the fastest algorithm and offers highest resolution among these three algorithms even though the pulse-wave may have gone through a significant change.

关键词： l1-LSD Sparse Deconvolution Cepstrum processing Wiener Filter

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Perovskite Solar Cells: Unique Seamlessly Bonded CNT@Graphene Hybrid Nanostructure Introduced in an Interlayer for Efficient and Stable Perovskite Solar Cells (Adv. Funct. Mater. 32/2018)

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Advanced Functional Materials 2018年第32期28卷

作者： Xuanhua Li Tengteng Tong Qinjiang Wu Shaohui Guo Qiang Song Jian Han Zhixiang Huang State Key Laboratory of Solidification Processing Research and Development Institute of Northwestern Polytechnical University In Shenzhen Center for Nano Energy Materials School of Materials Science and Engineering Northwestern Polytechnical University and Shaanxi Joint Lab of Graphene (NPU) Xi'an 710072 China Northwestern Polytechnical University‐Queen Mary University of London (NPU‐QMUL) Joint Research Institute of Advanced Materials and Structures (JRI‐AMAS) Xi'an 710072 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University No. 3 Feixi Road Hefei Anhui Province 230039 P. R. China

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A New Method to Parallel Implementation for Batching Vast Small-scale computing Tasks Based on GPU

A New Method to Parallel Implementation for Batching Vast Sm...

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IEEE Conference on Industrial Electronics and Applications

作者： Jun Zhu Haifeng Yao Tao Yang Qiaomei Zhou Kai Li Key laboratory of Intelligent Computing & Signal Processing (Anhui University) Ministry of Education Technology and Innovation Department Shanghai Research Center for Wireless Communications

ISBN: (纸本)9781467386456

The calculation of small-scale data is commonly used in scientific computing and application domain, and the high-efficiency method of small calculation can give play to the potency of many calculation and application. In this paper, a novel self-adaptive parallel computing method based on the graphics processing unit (GPU) architecture for batches of small scale computing tasks is proposed herein. It also provides two other implementation methods, which are the CPU algorithm and the traditional GPU algorithm, and then compares the efficiency of the three schemes. The experimental results show that the implementation efficiency of this new method on the GPU is better than that of method executed by the CPU and that of the traditional GPU algorithm for batching small-scale computing tasks. And this new approach is furthest utilizing the GPU resources, while a large amount of data is processed.

关键词： Small-scale GPU Batch processing Adaptation Parallel

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Pisano period codes

arXiv

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arXiv 2017年

作者： Shi, Minjia Zhang, Zhongyi Solé, Patrick Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University No. 3 Feixi Road Hefei Anhui Province230039 China School of Mathematical Sciences Anhui University Hefei230601 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China School of Wendian Anhui University Hefei Anhui230601 China CNRS/LAGA University of Paris 8 2 rue de la Liberté Saint-Denis93 526 France

The cyclic codes with parity check polynomial the reciprocal of the characteristic polynomial of the Fibonacci recurrence over a prime finite field are shown to have either one weight or two weights. When these codes are irreducible cyclic we obtain many counterexamples to the conjectural classification of two-weight irreducible cyclic codes of Schmidt and White (2002). When they are reducible and projective their duals are uniformly packed. Copyright © 2017, The Authors. All rights reserved.

关键词： Number theory

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Constructions of optimal LCD codes over large finite fields

arXiv

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arXiv 2017年

作者： Sok, Lin Shi, Minjia Solé, Patrick School of Mathematical Sciences Anhui University Hefei Anhui230601 Department of Mathematics Royal University of Phnom Penh Cambodia Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University No.3 Feixi Road Hefei Anhui230039 China School of Mathematical Sciences Anhui University HefeiAnhui230601 China National Mobile Communications Research Laboratory Southeast University China CNRS/LAGA University of Paris 8 Saint-Denis93 526 France

In this paper, we prove existence of optimal complementary dual codes (LCD codes) over large finite fields. We also give methods to generate orthogonal matrices over finite fields and then apply them to construct LCD codes. Construction methods include random sampling in the orthogonal group, code extension, matrix product codes and projection over a self-dual basis. Copyright © 2017, The Authors. All rights reserved.

关键词： Matrix algebra

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A comparative study of singular spectrum analysis and empirical mode decomposition for ultrasonic NDE

A comparative study of singular spectrum analysis and empiri...

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IEEE International Ultrasonics Symposium

作者： Yufeng Lu Jafar Saniie Electrical and Computer Engineering Department Bradley University Peoria Illinois 61625 United States Embedded Computing and Signal Processing Laboratory Electrical and Computer Engineering Department Illinois Institute of Technology Chicago 60616 United States

ISBN: (纸本)9781467398985

In this investigation, a comparative study of two time-series analysis techniques, singular spectrum analysis (SSA) and empirical mode decomposition (EMD), is carried out for ultrasonic NDE applications. Unlike transform-based approaches, the SSA and EMD are fully driven in the time domain by the data itself. The SSA method captures the trend of signals via eigenvalues from a trajectory matrix. Whereas EMD searches intrinsic mode functions (IMF) via local maxima and minima, then the instantaneous frequency of IMFs is used to disclose the signal trends. Simulation shows that the trend tracking becomes problematic for defect assessment when signal trends become too complicated. As a remedy, a technique combing these two methods is proposed. Experimental and simulation results reveal the effectiveness of the collective effort from EMD and SSA. The study demonstrates that the data-driven nature is unique and attractive to characterize non-stationary ultrasonic signals where scattering, absorption and dispersion effects become dominant.

关键词： Acoustics Market research Ultrasonic imaging Eigenvalues and eigenfunctions Transforms Noise measurement Trajectory Ultrasonography Noise measurement Spectrum Analysis market research Eigenfunctions trajectory Transform Acoustics SSA CALR gene NDE1 gene Nondestructive Testing Defect assessment TIME-DOMAIN

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Water Splitting: Optical and Electrical Enhancement of Hydrogen Evolution by MoS2@MoO3Core–Shell Nanowires with Designed Tunable Plasmon Resonance (Adv. Funct. Mater. 32/2018)

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Advanced Functional Materials 2018年第32期28卷

作者： Shaohui Guo Xuanhua Li Xingang Ren Lin Yang Jinmeng Zhu Bingqing Wei State Key Laboratory of Solidification Processing Center for Nano Energy Materials School of Materials Science and Engineering Northwestern Polytechnical University and Shaanxi Joint Lab of Graphene (NPU) Xi'an 710072 China Northwestern Polytechnical University‐Queen Mary University of London (NPU‐QMUL) Joint Research Institute of Advanced Materials and Structures (JRI‐AMAS) Xi'an 710072 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University No. 3 Feixi Road Hefei Anhui Province 230039 P. R. China Department of Mechanical Engineering University of Delaware Newark DE 19716 USA

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