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arXiv 2017年

作者： Qi, Zhongang Wang, Tianchun Song, Guojie Hu, Weisong Li, Xi Zhang, Zhongfei School of Electrical Engineering and Computer Science Oregon State University 1148 Kelley Engineering Center CorvallisOR97331-5501 United States School of Information Systems Singapore Management University 178902 Singapore Peking University Beijing100871 China NEC Laboratories China 11F Bldg. A Innovation Plaza Tsinghua Science Park Haidian District Beijing100084 China College of Computer Science and Technology Zhejiang University No. 38 Zheda Road Hangzhou310027 China Computer Science Department Watson School State University of New York BinghamtonNY13902-6000 United States

—The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of urban air computing. The solutions to these topics can provide extremely useful information to support air pollution control, and consequently generate great societal and technical impacts. Most of the existing work solves the three problems separately by different models. In this paper, we propose a general and effective approach to solve the three problems in one model called the Deep Air Learning (DAL). The main idea of DAL lies in embedding feature selection and semi-supervised learning in different layers of the deep learning network. The proposed approach utilizes the information pertaining to the unlabeled spatio-temporal data to improve the performance of the interpolation and the prediction, and performs feature selection and association analysis to reveal the main relevant features to the variation of the air quality. We evaluate our approach with extensive experiments based on real data sources obtained in Beijing, China. Experiments show that DAL is superior to the peer models from the recent literature when solving the topics of interpolation, prediction, and feature analysis of fine-gained air quality. Copyright © 2017, The Authors. All rights reserved.

关键词： Feature extraction

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Terahertz multiheterodyne spectroscopy with quantum cascade lasers - a feasibility study

Terahertz multiheterodyne spectroscopy with quantum cascade ...

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International Conference on Infrared, Millimeter, and Terahertz Waves

作者： Lukasz A. Sterczewski Jonas Westberg Yang Yang David Burghoff John Reno Qing Hu Gerard Wysocki Department of Electrical Engineering Princeton University Princeton New Jersey USA Faculty of Electronics Wroclaw University of Science and Technology Wroclaw Poland Department of Electrical Engineering and Computer Science MIT Cambridge MA USA Center for Integrated Nanotechnology Sandia National Laboratories Albuquerque New Mexico USA

We study the feasibility of dispersion compensated terahertz quantum cascade lasers combs operating around 2.65 - 2.95 THz to perform multiheterodyne spectroscopy. The devices show short-term intermode beat note frequency drift after 30 μs, which indicates that reliable multiheterodyne spectroscopy over extended time-scale requires phase and timing correction to allow for coherent averaging.

关键词： Quantum cascade lasers Spectroscopy Radio frequency Adaptive optics Optical mixing Laser modes Time-frequency analysis

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System Vulnerability Analysis Using Graph Pathfinding Strategies in Partitioned Networks

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Journal of Power and Energy engineering（电力能源） 2017年第4期

作者： Milad Ghiasi Rad Pedram Gharghabi Mohiyeddin Rahmani Bamdad Falahati Computer Science and Engineering Department University of Nebraska-Lincoln Lincoln United States Department of Computer and Electrical Engineering Mississippi State University Department of Electrical Engineering Amirkabir University of Technology Engineering Services Schweitzer Engineering Laboratories Inc. Pullman WA United States

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ZnO Films Deposited on Glass by Means of DC Sputtering

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Journal of Materials science and Chemical engineering 2016年第10期4卷 1-7页

作者： Masato Ohmukai Takuya Nakagawa Ayumu Matsumoto Department of Electrical and Computer Engineering Akashi College of Technology Akashi Japan Technical Education Support Center Akashi College of Technology Akashi Japan Collaborative Laboratories for Advanced Decommissioning Science Japan Atomic Energy Agency Ibaraki Japan

ZnO films were deposited on glass substrates by means of a direct current (DC) sputtering technique. The physical properties of the films were investigated on the basis of X-ray diffraction measurements. It was found that as-deposited films show c-axis oriented crystal normal to the surface with the extension of c axis by 1.27% that is estimated from the shift of the peak in the X-ray diffraction pattern. Post-deposition annealing in air at higher than 400℃ eliminates the shift and sharpens the diffraction peak structure at the same time. The electrical resistivity continues to decrease from 500 Ω•cm down to 0.6 Ω•cm by annealing as high as 600℃.

关键词： ZnO Film DC Sputtering Annealing X-Ray Analysis

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Online Battery State-of-Charge Estimation Based on Sparse Gaussian Process Regression

Online Battery State-of-Charge Estimation Based on Sparse Ga...

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IEEE Power and Energy Society General Meeting

作者： Gozde Ozcan Milutin Pajovic Zafer Sahinoglu Yebin Wang Philip V. Orlik Toshihiro Wada Department of Electrical Engineering and Computer Science Syracuse University Mitsubishi Electric Research Laboratories Advanced Technology R&D Center Mitsubishi Electric Corporation

ISBN: (纸本)9781509041695

This paper presents a new online method for state-of charge (SoC) estimation of Lithium-ion (Li-ion) batteries based on sparse Gaussian process regression (GPR). Building upon sparse approximation of the regular GPR, the proposed method is computationally more efficient. The battery SoC is estimated based on measured voltage, current and temperature. The accuracy of the proposed method is verified using LiMn2O4/hard-carbon battery data collected from a constant-current discharge test. In addition, the estimation performance of the proposed method is compared with a SoC estimation method using regular GPR with different covariance functions.

关键词： Battery management system Lithium-ion battery Sparse Gaussian process regression State of charge estimation Battery management systems lithium ion battery Battery charging status ground penetrating radar Batteries Gaussian processes Gauss

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Multi-channel feature adaptation for robust speech recognition

Multi-channel feature adaptation for robust speech recogniti...

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International Symposium on Chinese Spoken Language Processing

作者： Zhaofeng Zhang Xiong Xiao Longbiao Wang Jianwu Dang Masahiro Iwahashi Eng Siong Chng Haizhou Li Nagaoka University of Technology Japan Temasek Laboratories Nanyang Technological University (NTU) Singapore Tianjin University China School of Computer Science and Engineering NTU Singapore Department of Electrical and Computer Engineering National University of Singapore

ISBN: (纸本)9781509042951

In this paper, we propose a feature adaptation method that combines speech features from multiple microphone channels for robust automatic speech recognition (ASR). The proposed method first transforms the features in all channels using channel-dependent linear transforms, and then sum the channels into one channel for acoustic modeling. The transform parameters are estimated by maximizing the likelihood of the transformed features on a Gaussian mixture model (GMM) trained from clean features. To use diagonal covariance matrices for efficient estimation algorithm, the likelihood function is evaluated in the cepstral domain, while the transformation is in the log Mel filterbank domain. We evaluate the proposed feature adaptation on the 6-channel evaluation data in the CHiME-3 task. Results show that the proposed feature adaptation method with diagonal channel-dependent transforms reduces word error rate (WER) from 21.05% (best single channel) to 16.96% when a DNN-based acoustic model is used. This result is also slightly better than the 17.60% obtained by the minimum variance distortionless response beamforming.

关键词： Transforms Acoustics Microphones Adaptation models Covariance matrices Array signal processing Linear programming

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Suspended microring resonator sensor using internal sub-wavelength grating

Suspended microring resonator sensor using internal sub-wave...

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Optical Sensors, Sensors 2015

作者： Yousuf, Soha E. Shahin, Mahmoud M. Gevorgyan, Hayk Voort, Bob Taha, Ayat M. Dimas, Clara Dahlem, Marcus S. Khilo, Anatol Department of Electrical Engineering and Computer Science Institute Center for Microsystems Masdar Institute of Science and Technology Abu Dhabi United Arab Emirates

A fully suspended microring resonator sensor supported by a sub-wavelength grating is proposed. Sensitivity of 503nm/RIU and Q-factor of 75k are predicted for a resonator with 450nm-period grating. Q=29k is measured f... 详细信息

ISBN: (纸本)9781557520005

关键词： Q factor measurement

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TM polarizer using segmented silicon waveguide

TM polarizer using segmented silicon waveguide

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Integrated Photonics Research, Silicon and Nanophotonics, IPRSN 2015

作者： Shahin, Mahmoud M. Gevorgyan, Hayk Dahlem, Marcus S. Khilo, Anatol Institute Centre for Microsystems Department of Electrical Engineering and Computer Science Masdar Institute of Science and Technology Abu Dhabi United Arab Emirates

High-performance segmented-waveguide TM polarizer is proposed. Extinction ratio 0.1dB are predicted for a 27.4μm device. The fabricated 144μm device had 18-29dB extinction and 1.4-2.3dB insertion loss over 110nm ban... 详细信息

ISBN: (纸本)9781557520005

关键词： Insertion losses

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Self-Grouping Multi-network Clustering

Self-Grouping Multi-network Clustering

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IEEE International Conference on Data Mining (ICDM)

作者： Jingchao Ni Wei Cheng Wei Fan Xiang Zhang Department of Electrical Engineering and Computer Science Case Western Reserve University NEC Laboratories America Baidu Research Big Data Lab College of Information Sciences and Technology Pennsylvania State University

ISBN: (纸本)9781509054749

Joint clustering of multiple networks has been shown to be more accurate than performing clustering on individual networks separately. Many multi-view and multi-domain network clustering methods have been developed for joint multi-network clustering. These methods typically assume there is a common clustering structure shared by all networks, and different networks can provide complementary information on this underlying clustering structure. However, this assumption is too strict to hold in many emerging real-life applications, where multiple networks have diverse data distributions. More popularly, the networks in consideration belong to different underlying groups. Only networks in the same underlying group share similar clustering structures. Better clustering performance can be achieved by considering such groups differently. As a result, an ideal method should be able to automatically detect network groups so that networks in the same group share a common clustering structure. To address this problem, we propose a novel method, ComClus, to simultaneously group and cluster multiple networks. ComClus treats node clusters as features of networks and uses them to differentiate different network groups. Network grouping and clustering are coupled and mutually enhanced during the learning process. Extensive experimental evaluation on a variety of synthetic and real datasets demonstrates the effectiveness of our method.

关键词： Clustering methods Tensile stress Measurement Symmetric matrices Conferences Data mining electrical engineering

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Time-wavelength pulse interleaver on a silicon platform

Time-wavelength pulse interleaver on a silicon platform

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Integrated Photonics Research, Silicon and Nanophotonics, IPRSN 2015

作者： Gevorgyan, Hayk Al Qubaisi, Kenaish Dahlem, Marcus S. Khilo, Anatol Department of Electrical Engineering and Computer Science Institute Center for Microsystems Masdar Institute of Science and Technology Abu Dhabi United Arab Emirates

An integrated 4-channel time-wavelength pulse interleaver for 1GHz optical pulse trains is implemented on a silicon platform. The interleaver has 0.35% RMS pulse timing error, 1.6-5.8dB insertion loss, less than -24dB... 详细信息

ISBN: (纸本)9781557520005

关键词： Silicon

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