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arXiv 2018年

作者： Chen, Yao Xia, Weiguo Cao, Ming Lü, Jinhu Department of Computer Science Southwestern University of Finance and Economics Chengdu611130 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China Faculty of Science and Engineering ENTEG University of Groningen Groningen9747 AG Netherlands School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

Distributed coordination algorithms (DCA) carry out information processing processes among a group of networked agents without centralized information fusion. Though it is well known that DCA characterized by an SIA (stochastic, indecomposable, aperiodic) matrix generate consensus asymptotically via synchronous iterations, the dynamics of DCA with asynchronous iterations have not been studied extensively, especially when viewed as stochastic processes. This paper aims to show that for any given irreducible stochastic matrix, even non-SIA, the corresponding DCA lead to consensus successfully via random asynchronous iterations under a wide range of conditions on the transition probability. Particularly, the transition probability is neither required to be independent and identically distributed, nor characterized by a Markov chain. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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Modified cuckoo search ased neural networks for forest types classification 2

Modified cuckoo search ased neural networks for forest types...

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2nd International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2017

作者： Chatterjee, Sankhadeep Dey, Nilanjan Sen, Soumya Ashour, Amira S. Fong, Simon James Shi, Fuqian Department of Computer Science and Engineering University of Calcutta Kolkata India Department of Information Technology Techno India College of Technology Kolkata India A. K. Choudhury School of Information Technology University of Calcutta Kolkata West Bengal India Department of Electronics and Electrical Communications Engineering Faculty of Engineering Tanta University Egypt Department of Computer and Information Science Data Analytics and Collaborative Computing Laboratory University of Macau Taipa China College of Information and Engineering Wenzhou Medical University Wenzhou China

ISBN: (纸本)9781614997849

Pixel classification in land scape images is a challenging process especially in forest images due to the similar spectral features of pixels situated close to each other. Previously, meta-heuristic coupled artificial neural network (ANN) models have been used to classify the two-different species, namely Japanese Cedar, Japanese Cypress and one mixed forest class. Previous attempts have shown reasonable improvement in the classification process using genetic algorithm (GA) supported neural network over other traditional approaches. Consequently, in the current work, a modified Cuckoo Search (CS) supported Neural Network (NN-MCS) classifier is proposed. The lévy flight associated with cuckoo search has been modified using McCulloch's method of generating stable random numbers. The proposed approach is compared with GA-NN using single objective function and CS-NN (ANN trained with CS) classifiers in terms of confusion matrix based performance metrics. The results depicted the dominance of the suggested NN-MCS model compared to the CS-NN model to a greater extent. © 2017 The authors and IOS Press. All rights reserved.

关键词： Neural networks

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The parkes pulsar timing array project: Second data release

arXiv

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arXiv 2020年

作者： Kerr, M. Reardon, D.J. Hobbs, G. Shannon, R.M. Manchester, R.N. Dai, S. Russell, C.J. Zhang, S.-B. van Straten, W. Oslowski, S. Parthasarathy, A. Spiewak, R. Bailes, M. Bhat, N.D.R. Cameron, A.D. Coles, W.A. Dempsey, J. Deng, X. Goncharov, B. Kaczmarek, J.F. Keith, M.J. Lasky, P.D. Lower, M.E. Preisig, B. Sarkissian, J.M. Toomey, L. Wang, H. Wang, J. Zhang, L. Zhu, X. Space Science Division Naval Research Laboratory WashingtonDC20375-5352 United States Centre for Astrophysics and Supercomputing Swinburne University of Technology P.O. Box 218 HawthornVIC3122 Australia CSIRO Astronomy and Space Science Australia Telescope National Facility PO Box 76 EppingNSW1710 Australia CSIRO Scientific Computing Australian Technology Park Locked Bag 9013 AlexandriaNSW1435 Australia University of Chinese Academy of Sciences Beijing100049 China Purple Mountain Observatory Chinese Academy of Sciences Nanjing210008 China International Centre for Radio Astronomy Research University of Western Australia CrawleyWA6009 Australia Institute for Radio Astronomy & Space Research Auckland University of Technology Private Bag 92006 Auckland1142 New Zealand International Centre for Radio Astronomy Research Curtin University BentleyWA6102 Australia Department of Electrical and Computer Engineering University of California San DiegoCA92093 United States CSIRO Information Management & Technology GPO Box 1700 CanberraACT2601 Australia School of Physics and Astronomy Monash University VIC3800 Australia CSIRO Astronomy and Space Science Parkes Observatory 473 Telescope road ParkesNSW2870 Australia Jodrell Bank Centre for Astrophysics Department of Physics and Astronomy University of Manchester Alan Turing Building Oxford Road ManchesterM13 9PL United Kingdom School of Physics and Electronic Engineering Guangzhou University Guangzhou510006 China Xinjiang Astronomical Observatory Chinese Academy of Sciences 150 Science 1-Street Urumqi Xinjiang830011 China National Astronomical Observatories Chinese Academy of Sciences A20 Datun Road Chaoyang District Beijing100101 China

We describe 14 years of public data from the Parkes Pulsar Timing Array (PPTA), an ongoing project that is producing precise measurements of pulse times of arrival from 26 millisecond pulsars using the 64-m Parkes radio telescope with a cadence of approximately three weeks in three observing bands. A comprehensive description of the pulsar observing systems employed at the telescope since 2004 is provided, including the calibration methodology and an analysis of the stability of system components. We attempt to provide full accounting of the reduction from the raw measured Stokes parameters to pulse times of arrival to aid third parties in reproducing our results. This conversion is encapsulated in a processing pipeline designed to track provenance. Our data products include pulse times of arrival for each of the pulsars along with an initial set of pulsar parameters and noise models. The calibrated pulse profiles and timing template profiles are also available. These data represent almost 21,000 hrs of recorded data spanning over 14 years. After accounting for processes that induce time-correlated noise, 22 of the pulsars have weighted root-mean-square timing residuals of Copyright © 2020, The Authors. All rights reserved.

关键词： Pulsars

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Keep Your Friends Close and Your Colleagues Nearby: The Hidden Ties That Improve STEM Education

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Change 2019年第1期51卷 42页

作者： Mestre, Jose P. Herman, Geoffrey L. Tomkin, Jonathan H. West, Matthew Jose P. Mestre (mestre@illinois.edu). A theoretical nuclear physicist by training Mestre’s research focuses on the learning of physics contributing in areas such as the acquisition and use of knowledge by experts and novices transfer of learning problem solving and instructional design. He has offered Congressional testimony on The Science of Learning has published numerous articles and books and is a Fellow of the American Physical Society.http://***/0000-0003-2110-1954 Geoffrey L. Herman (glherman@illinois.edu). Herman has a Ph.D. in Electrical and Computer Engineering and is a Teaching Assistant Professor in Computer Science and a Research Assistant Professor in the Department of Curriculum & Instruction at the University of Illinois. His research focuses on how students learn engineering and computing concepts and studying processes for creating systemic instructional change in college settings. Previously he was a postdoctoral researcher in Engineering Education at Purdue University.http://***/0000-0002-9501-2295 Jonathan H. Tomkin (tomkin@illinois.edu). Tomkin is a mathematically based geoscientist with two research focus areas: first he uses models and large data sets to determine how climates glaciers tectonics and landscapes interact. Second he explores how new technological and organizational approaches can improve STEM education. He produced the first geoscience MOOC is the editor of an open-source textbook and has published widely in both geoscience and STEM education. Matthew West (mwest@illinois.edu). Matthew West is an Associate Professor of Mechanical Science and Engineering at the University of Illinois with research interests in scientific computing that include time integration of deterministic and stochastic systems distributed computation and particle methods for simulation and estimation. In education he researches computer-based assessment and the development of innovative teaching cultures. Professor West is a University of Illinois Distinguished Teacher-Scholar and Colleg

A science department on the campus of the University of Illinois has received numerous national awards for excellence in undergraduate teaching. The secret to their success? For nearly two decades, they have collaboratively used evidence-based instructional practices (EBIP) in their introductory level courses. Despite these successes and efforts to spread their EBIP, no other departments followed this department's lead. Then, suddenly six years ago, many instructors from other departments began adopting EBIP in their classrooms. This article asks what was the catalyst for this change? Why had previous attempts at institutional change failed? The authors answer these questions by analyzing their efforts to transform the teaching practices in large-enrollment science and engineering introductory courses on their campus.

关键词： STEM Education Evidence Based Practice Teaching Methods Undergraduate Study College Faculty Educational Change Communities of Practice Mentors School CultureIllinois

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VFlash: Virtualized Flash for Optimizing the I/O Performance in Mobile Devices

VFlash: Virtualized Flash for Optimizing the I/O Performance...

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作者： Chen, Renhai Wang, Yi Hu, Jingtong Liu, Duo Shao, Zili Guan, Yong Beijing Advanced Innovation Center for Imaging Technology Beijing100048 China College of Information Engineering Capital Normal University Beijing China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74074 United States College of Computer Science Chongqing University Chongqing400044 China Embedded Systems and CPS Laboratory Department of Computing Hong Kong Polytechnic University Hong Kong

I/O is becoming one of major performance bottlenecks in NAND-flash-based mobile devices. Novel nonvolatile memories (NVMs), such as phase change memory and spin-transfer torque random access memory, can provide fast read/write operations. In this paper, we propose a unified NVM/flash architecture to improve the I/O performance. A transparent scheme, virtualized flash (vFlash), is also proposed to manage the unified architecture. Within vFlash, interapp and intra-app techniques are proposed to optimize the application performance by exploiting the historical locality and I/O access patterns of applications. Since vFlash is on the bottom of the I/O stack, the application features will be lost. Therefore, we also propose a cross-layer technique to transfer the application information from the application layer to the vFlash layer. The proposed scheme is evaluated based on an Android platform, and the experimental results show that the proposed scheme can effectively improve the I/O performance of mobile devices. © 1982-2012 IEEE.

关键词： Phase change memory

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Robust Online Spectrum Prediction with Incomplete and Corrupted Historical Observations

Robust Online Spectrum Prediction with Incomplete and Corrup...

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作者： Ding, Guoru Wu, Fan Wu, Qihui Tang, Shaojie Song, Fei Vasilakos, Athanasios V. Tsiftsis, Theodoros A. National Mobile Communications Research Laboratory Southeast University Nanjing210018 China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Electronics and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing210007 China Department of Information Systems University of Texas at Dallas RichardsonTX75080 United States College of Communications Engineering PLA University of Science and Technology Nanjing210007 China Department of Computer Science Electrical and Space Engineering Lulea University of Technology Lulea97187 Sweden School of Engineering Nazarbayev University Astana010000 Kazakhstan

A range of emerging applications, from adaptive spectrum sensing to proactive spectrum mobility, depend on the ability to foresee spectrum state evolution. Despite a number of studies appearing about spectrum prediction, fundamental issues still remain unresolved: 1) The existing studies do not explicitly account for anomalies, which may incur serious performance degradation;2) they focus on the design of batch spectrum prediction algorithms, which limit the scalability to analyze massive spectrum data in real time;3) they assume the historical data are complete, which may not hold in reality. To address these issues, we develop a Robust Online Spectrum Prediction (ROSP) framework, with incomplete and corrupted observations, in this paper. We first present data analytics of real-world spectrum measurements to reveal the correlation structures of spectrum evolution and to analyze the impact of anomalies on the rank distribution of spectrum matrices. Then, from a spectral-temporal 2-D perspective, we formulate the ROSP as a joint optimization problem of matrix completion and recovery by effectively integrating the time series forecasting techniques and develop an alternating direction optimization method to efficiently solve it. We apply ROSP to a wide range of real-world spectrum matrices of popular wireless services. Experiment results show that ROSP outperforms state-of-the-art spectrum prediction schemes. © 1967-2012 IEEE.

关键词： Forecasting

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Multi-antenna channel interpolation via Tucker decomposed extreme learning machine

arXiv

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arXiv 2018年

作者： Zhang, Han Ai, Bo Xu, Wenjun Xu, Li Cui, Shuguang Department of Electrical and Computer Engineering University of California DavisCA95616 United States State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Key Lab of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Institute of Computing Technology Chinese Academy of Science Beijing100190 China

Channel interpolation is an essential technique for providing high-accuracy estimation of the channel state information (CSI) for wireless systems design where the frequency-space structural correlations of multi-antenna channel are typically hidden in matrix or tensor forms. In this letter, a modified extreme learning machine (ELM) that can process tensorial data, or ELM model with tensorial inputs (TELM), is proposed to handle the channel interpolation task. The TELM inherits many good properties from ELMs. Based on the TELM, the Tucker decomposed extreme learning machine (TDELM) is proposed for further improving the performance. Furthermore, we establish a theoretical argument to measure the interpolation capability of the proposed learning machines. Experimental results verify that our proposed learning machines can achieve comparable mean squared error (MSE) performance against the traditional ELMs but with 15% shorter running time, and outperform the other methods for a 20% margin measured in MSE for channel interpolation. Copyright © 2018, The Authors. All rights reserved.

关键词： Interpolation

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Precision Analysis of the Imaging Pipeline in the Square Kilometre Array

Precision Analysis of the Imaging Pipeline in the Square Kil...

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European Signal Processing Conference

作者： Anthony Griffin Nicolas Pradel Brody Radford David I. Wilson Andrew Ensor Electrical and Electronic Engineering Department Mathematical Sciences Department High Performance Computing Research Laboratory Computer Science Department Auckland University of Technology New Zealand

In this paper we present our end-to-end model of the imaging pipeline in the Square Kilometre Array. Our Sky Generator models the signals that are received by the Central Signal Processor (CSP), our CSP Correlator model then processes those signals to generate visibilities to pass to the science Data Processor (SDP). Our SDP Imaging model then grids the visibilities and inverse Fourier transforms them to produce a dirty image of the sky. Our modelling allows us to investigate the error that is introduced due to reduced numerical precision, and we then propose techniques to mitigate this error, and thus reduce the required amount of computational hardware.

关键词： Mathematical model Delays Antenna arrays Correlators Imaging Computational modeling

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Fault diagnosis for multi-energy flows of energy internet: Framework and prospects

Fault diagnosis for multi-energy flows of energy internet: F...

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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Wang, Tao Wang, Jun Fan, Zhennan Wei, Xiaoguang Zang, Tianlei Pérez-Jiménez, Mario J. Huang, Tao School of Electrical Engineering and Electronic Information Sichuan Province Key Laboratory of Power Electronics Energy-saving Technologies and Equipment Key Laboratory of Fluid and Power Machinery Ministry of Education Xihua University Chengdu China School of Electrical Engineering Southwest Jiaotong University Chengdu China State Key Laboratory of Security Control and Simulation of Power Systems and Large Scale Generation Department of Electrical Engineering Tsinghua University Beijing China Research Groupon Natural Computing Department of Computer Science and Artificial Intelligence University of Sevilla Sevilla Spain Department of Energy Politecnico di Torino Torino Italy

ISBN: (纸本)9781538614273

Energy Internet (EI) is an inevitable development trend of energy systems under the background of technology development, environmental pressure and energy transition. Multi-energy flow coupling is one of the key characteristics of the EI, which enhances the interoperability of different types of energy flows while consequently increases the probability of cascading failures. Therefore it is of great significance to study the multi-energy flow fault diagnosis of the EI to ensure its safe and stable operation as well as the continuous energy supply. This paper introduces the concept of multi-energy flow cascading fault of the EI for the first time. The energy internet framework for multi-energy flow cascading fault diagnosis is firstly proposed, and then characteristics of various energy networks in the EI are analyzed from the perspective of fault diagnosis. Finally, future research prospects are discussed. © 2017 IEEE.

关键词： Failure analysis

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Spectrally multiplexed upconversion single-photon detection with C-band pump and signal wavelengths

Spectrally multiplexed upconversion single-photon detection ...

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Frontiers in Optics, FiO 2017

作者： Silver, Michael Velev, Vesselin G. Langrock, Carsten Fejer, Martin M. Kumar, Prem Kanter, Gregory S. Center for Photonic Communication and Computing Department of Electrical Engineering and Computer Science Northwestern University EvanstonIL60208 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States E. L. Ginzton Laboratory Stanford University StanfordCA94305 United States

We demonstrate low noise, spectrally multiplexed, upconversion single-photon detection using a waveguide with multiple phase-matching peaks. Two signal wavelengths are upconverted using two distinct pump wavelengths, ... 详细信息

ISBN: (纸本)9781943580330

关键词： Phase matching

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