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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Kun Li Shigang Li Bei Wang Yifeng Chen Yunquan Zhang State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing Department of Computer Science ETH Zurich HCST Key Lab at School of EECS Peking University Beijing

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Molecular dynamics is an extensively utilized computational tool for solids, liquids and molecules simulation. Currently, much research on molecular dynamics simulation focuses on simplifying forces or parallelizing tasks to reduce the overheads of forces computation. However, the molecular dynamics simulation still remains challenging since the communication and neighbor list construction are time-consuming in the existing algorithm. In this paper, we propose a swMD optimization strategy including a new communication mode called ghost communication to reduce superfluous communication overheads and an innovative neighbor list algorithm to improve the construction efficiency of it. Moreover, we accelerate computation by utilizing many-core resources on Sunway Taihulight and present an auto-tuning Producer-Consumer pairing algorithm to make neighbor list construction happen in fast register communication. Compared to traditional methods, swMD optimization strategy obtains a maximal 82.2% and an average of 79.4% performance improvement. We also evaluate the scalability up to 266,240 cores and the results demonstrate the high efficiency of swMD optimization strategy on communication, computation and neighbor list construction respectively.

关键词： Heuristic algorithms computer architecture Computational modeling Microprocessors Program processors Registers Surface treatment

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Poster: Tancreator: A tangible tool for children to create augmented reality games

Poster: Tancreator: A tangible tool for children to create a...

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2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable computers, ISWC 2018

作者： Jin, Qiao Wang, Danli Sun, Fang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China School of Computer and Information Technology Liaoning Normal University Dalian China

ISBN: (纸本)9781450359665

In this paper, we present TanCreator, a tangible authoring tool which facilitates children to create games based on Augmented Reality (AR) and sensor technologies. Combining AR elements and sensors in games bridges virtual world with realistic surroundings closely together, providing more joyful and intuitive creating experiment for children. Children could boost their creativity via creating their own maze games in daily life with paper tokens and sensors. It is also great training for children's motor skills such as hand-eye coordination. © 2018 Copyright is held by the owner/author(s).

关键词： Augmented reality

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Fuzzy control for maximum power-point tracking of a photovoltaic system 7

Fuzzy control for maximum power-point tracking of a photovol...

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7th International Conference on Systems and control, ICSC 2018

作者： Safia, Z. Ben Allouch, M. Harrabi, N. Bahloul, M. Chaabane, M. Aitouche, A. National Engineering School of SFAX Tunisia CRIStAL Research Center in Computer Science Signal and Automatic Control of Lille University of Lille France

ISBN: (纸本)9781538685372

This paper proposes a new T-S fuzzy method to deal with the power tracking problem of the power generating systems. First, a dynamic model of the PV system is developed which is subsequently converted into a Takagi-Sugeno (TS) model. Then, after leading to this exact model, a fuzzy controller is designed to obtain the MPP even during the variation of the climatic conditions. Based on the T-S fuzzy model, the fuzzy maximum power point tracking controller is designed by constructing fuzzy gain state feedback controller and an optimal reference model for the optimal PV output voltage, which corresponds actually to maximum power point (MPP).The controller gains are obtained by solving a set of linear matrix inequalities (LMIs). Finally, simulation results are given to illustrate the optimal tracking performance of the proposed fuzzy controller even in the case of abrupt changing climatic conditions. © 2018 IEEE.

关键词： Fuzzy control

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Path planning for autonomous bus driving in urban environments

arXiv

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arXiv 2019年

作者： Oliveira, Rui Lima, Pedro F. Pereira, Goncalo Collares Martensson, Jonas Wahlberg, Bo Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Scania Autonomous Transport Solutions Sodertalje Sweden

Driving in urban environments often presents difficult situations that require expert maneuvering of a vehicle. These situations become even more challenging when considering large vehicles, such as buses. We present a path planning framework that addresses the demanding driving task of buses in urban areas. The approach is formulated as an optimization problem using the road-aligned vehicle model. The road-aligned frame introduces a distortion on the vehicle body and obstacles, motivating the development of novel approximations that capture this distortion. These approximations allow for the formulation of safe and nonconservative collision avoidance constraints. Unlike other path planning approaches, our method exploits curbs and other sweepable regions, which a bus must often sweep over in order to manage certain maneuvers. Furthermore, it takes full advantage of the particular characteristics of buses, namely the overhangs, an elevated part of the vehicle chassis, that can sweep over curbs. Simulations are presented, showing the applicability and benefits of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Motion planning

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Convex Relaxation with Log-Determinant Divergence-L1 Regularization for 3D Shape Reconstruction

Convex Relaxation with Log-Determinant Divergence-L1 Regular...

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第三十八届中国控制会议

作者： Wei Cao Luefeng Chen Min Wu Witold Pedrycz School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta

Investigated is the problem of estimating the 3 D shape of an object defined by a set of 3 D landmarks with their 2 D correspondences in a single image. To solve this problem, we use a dictionary of the basic shape with LDD-L1 regularization,which is the construction of the shape space model. Based on the proposed convex optimization method, 3 D human pose reconstruction by shape space model and 3 D variable shape model was carried out on the mocap database. To improve accuracy and reduce the number of iterations, we use PSO algorithm to optimize initial value of the key parameter. The experimental results show that the improved algorithm exhibits less iterations but higher accuracy, which can be much helpful in practical applications.

关键词： LDD-L1 regularization 3D reconstruction PSO

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Secure Distributed Filtering for Unstable Dynamics Under Compromised Observations

Secure Distributed Filtering for Unstable Dynamics Under Com...

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IEEE Annual Conference on Decision and control

作者： Xingkang He Xiaoqiang Ren Henrik Sandberg Karl H. Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Department of Automation Shanghai University Shanghai China

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

In this paper, we consider a secure distributed filtering problem for linear time-invariant systems with bounded noises and unstable dynamics under compromised observations. A malicious attacker is able to compromise a subset of the agents and manipulate the observations arbitrarily. We first propose a recursive distributed filter consisting of two parts at each time. The first part employs a saturation-like scheme, which gives a small gain if the innovation is too large. The second part is a consensus operation of state estimates among neighboring agents. A sufficient condition is then established for the boundedness of estimation error, which is with respect to network topology, system structure, and the maximal compromised agent subset. We further provide an equivalent statement, which connects to 2s-sparse observability in the centralized framework in certain scenarios, such that the sufficient condition is feasible. Numerical simulations are finally provided to illustrate the developed results.

关键词： Observability Estimation error Technological innovation control systems State estimation Robustness

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Performance Comparison of Distributed State Estimation Algorithms for Power Systems

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Journal of Systems Science & Complexity 2017年第3期30卷 595-615页

作者： SUN Yibing FU Minyue ZHANG Huanshui School of Control Science and Engineering Shandong University School of Electrical Engineering and Computer Science University of Newcastle School of Automation Guangdong University of Technology

A newly proposed distributed dynamic state estimation algorithm based on the maximum a posteriori(MAP) technique is generalised and studied for power systems. The system model involves linear time-varying load dynamics and nonlinear measurements. The main contribution of this paper is to compare the performance and feasibility of this distributed algorithm with several existing distributed state estimation algorithms in the literature. Simulations are tested on the IEEE 39-bus and 118-bus systems under various operating conditions. The results show that this distributed algorithm performs better than distributed quasi-steady state estimation algorithms which do not use the load dynamic model. The results also show that the performance of this distributed method is very close to that by the centralized state estimation method. The merits of this algorithm over the centralized method lie in its low computational complexity and low communication load. Hence, the analysis supports the efficiency and benefits of the distributed algorithm in applications to large-scale power systems.

关键词： Distributed MAP estimation distributed state estimation extended Kalman filter power systems.

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Snow Cover Mapping for Mountainous Areas by Fusion of MODIS L1B and Geographic Data Based on Stacked Denoising Auto-Encoders

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computers, Materials & Continua 2018年第10期57卷 49-68页

作者： Xi Kan Yonghong Zhang Linglong Zhu Liming Xiao Jiangeng Wang Wei Tian Haowen Tan School of Atmospheric Science Nanjing University of Information Science and TechnologyNanjing210044China School of Information and Control Nanjing University of Information Science and TechnologyNanjing210044China School of Atmospheric Physics Nanjing University of Information Science and TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Department of Computer Engineering Chosun UniversityGwangju501-759South Korea

Snow cover plays an important role in meteorological and hydrological ***,the accuracies of currently available snow cover products are significantly lower in mountainous areas than in plains,due to the serious snow/cloud confusion problem caused by high altitude and complex *** at this problem,an improved snow cover mapping approach for mountainous areas was proposed and applied in Qinghai-Tibetan *** this work,a deep learning framework named Stacked Denoising Auto-Encoders(SDAE)was employed to fuse the MODIS multispectral images and various geographic datasets,which are then classified into three categories:Snow,cloud and snow-free ***,two independent SDAE models were trained for snow mapping in snow and snow-free seasons respectively in response to the seasonal variations of meteorological *** proposed approach was verified using in-situ snow depth records,and compared to the most widely used snow products MOD10A1 and *** comparison results show that our method got the best performance:Overall accuracy of 98.95%and F-measure of 73.84%.The results indicated that our method can effectively improve the snow recognition accuracy,and it can be further extended to other multi-source remote sensing image classification issues.

关键词： Snow cover remote sensing deep learning Qinghai-Tibetan Plateau MODIS L1B

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Learning structured twin-incoherent twin-projective latent dictionary pairsfor classification

arXiv

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arXiv 2019年

作者： Zhang, Zhao Sun, Yulin Zhang, Zheng Wang, Yang Liu, Guangcan Wang, Meng School of Computer Science and Technology Soochow University Suzhou215006 China Hefei University of Technology School of Computer Science and Information Engineering Hefei University of Technology Hefei China Shenzhen China School of Information and Control Nanjing University of Information Science and Technology Nanjing China

In this paper, we extendthe popular dictionary pair learning (DPL) into the scenario of twin-projective latent flexible DPL under a structured ***, a novel framework called Twin-Projective Latent Flexible DPL(TP-DPL) is proposed, which minimizes the twin-incoherence constrained flexibly-relaxed reconstruction errorto avoid the possible over-fitting issue and produce accurate reconstruction. In this setting, our TP-DPL integrates the twin-incoherence based latent flexible DPLand the joint embedding of codesas well assalient features by twin-projection into a unified model in an adaptive neighborhood-preserving manner. As a result, TP-DPL unifies the salient feature extraction, representation and classification. The twin-incoherence constrainton codesand features can explicitly ensure high intra-class compactness and inter-class separation overthem. TP-DPL also integrates the adaptive weighting to preserve the local neighborhood of the coefficientsand salient features with in each class explicitly. For efficiency, TP-DPL uses Frobenius-normand abandonsthe costly l0/l1-norm for group sparse representation. Another byproductis that TP-DPL can directly apply the class-specific twin-projective reconstruction residualto computethe label of data. Extensive results on publicdatabases show that TP-DPL can deliver the state-of-the-art performance. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Finite impulse response models: A non-asymptotic analysis of the least squares estimator

arXiv

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arXiv 2019年

作者： Djehiche, Boualem Mazhar, Othmane Rojas, Cristian R. Department of Mathematics School of Engineering Sciences Kth Royal Institute of Technology Stockholm100 44 Division of Decision and Control Systems School of Electrical Engineering and Computer Science Kth Royal Institute of Technology StockholmSE-100 44

We consider a finite impulse response system with centered independent sub-Gaussian design covariates and noise components that are not necessarily iden-tically distributed. We derive non-asymptotic near-optimal estimation and prediction bounds for the least squares estimator of the parameters. Our results are based on two concentration inequalities on the norm of sums of dependent covariate vectors and on the singular values of their covariance operator that are of independent value on their own and where the dependence arises from the time shift structure of the time series. These results generalize the known bounds for the independent case. Copyright © 2019, The Authors. All rights reserved.

关键词： Covariance matrix

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