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International Symposium on Chinese Spoken Language Processing

作者： Yue Sun Manwa L. Ng Chongyuan Lian Lan Wang Feng Yang Nan Yan College of Big Data and Information Engineering Guizhou University Guiyang China Speech Science Laboratory University of Hong Kong Hong Kong China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Department of Speech Therapy Shenzhen Children’s Hospital Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Instimtes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781538656280;9781538656273

Hypokinetic dysarthria is one of the core symptoms of Parkinson's disease, characterized by reduced loudness, slurred speech and distorted consonant productions. Dopaminergic medication for Parkinson's disease (PD) has been proven to be effective in treating limb and gross motor movement problems. However, the literature sees contradictory findings regarding dopaminergic effects on speech problems associated with PD. Previous perceptual and acoustic studies of PD hypokinetic dysarthria mostly involved heterogeneous population and variations of speech tasks which complicated data interpretation. Also, the lack of kinematic data limited our understanding of the details of articulation errors associated with PD, as well as the medication effects. Electromagnetic articulography (EMA) enabled the examination of PD articulatory patterns with high degree of accuracy and safety. The aim of the present study was to address these inconsistencies by providing an integrative description of basic kinematic and acoustic parameters of speech production about the dopaminergic effect on early PD speech by using EMA. The results revealed a significant improvement of articulatory function on dopaminergic effects for PD speech, evidenced by increased vowel space, the velocity and accelerated velocity initiation and coordination of articulation during bilabial or alveolar productions.

关键词： Kinematics Acoustics Auditory system Sun Parameter extraction Schedules Lips

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Experimental quantification of coherence of a tunable quantum detector

arXiv

引用

arXiv 2019年

作者： Xu, Huichao Xu, Feixiang Theurer, Thomas Egloff, Dario Liu, Zi-Wen Yu, Nengkun Plenio, Martin B. Zhang, Lijian National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences School of Physics Nanjing University Nanjing210093 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China Institute of Theoretical Physics and IQST Universität Ulm Albert-Einstein-Allee 11 UlmD-89069 Germany Technical University Dresden Institute of Theoretical Physics DresdenD-01062 Germany Perimeter Institute for Theoretical Physics WaterlooONN2L 2Y5 Canada Center for Theoretical Physics Massachusetts Institute of Technology CambridgeMA02139 United States Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia

Quantum coherence is a fundamental resource that quantum technologies exploit to achieve performance beyond that of classical devices. A necessary prerequisite to achieve this advantage is the ability of measurement devices to detect coherence from the measurement statistics. Based on a recently developed resource theory of quantum operations, here we quantify experimentally the ability of a typical quantum-optical detector, the weak-field homodyne detector, to detect coherence. We derive an improved algorithm for quantum detector tomography and apply it to reconstruct the positive-operator-valued measures (POVMs) of the detector in different configurations. The reconstructed POVMs are then employed to evaluate how well the detector can detect coherence using two computable measures. These results shed new light on the experimental investigation of quantum detectors from a resource theoretic point of view. Copyright © 2019, The Authors. All rights reserved.

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Author Correction: π-HuB: the proteomic navigator of the human body

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Nature 2025年第8046期637卷 E22页

作者： Fuchu He Ruedi Aebersold Mark S Baker Xiuwu Bian Xiaochen Bo Daniel W Chan Cheng Chang Luonan Chen Xiangmei Chen Yu-Ju Chen Heping Cheng Ben C Collins Fernando Corrales Jürgen Cox Weinan E Jennifer E Van Eyk Jia Fan Pouya Faridi Daniel Figeys George Fu Gao Wen Gao Zu-Hua Gao Keisuke Goda Wilson Wen Bin Goh Dongfeng Gu Changjiang Guo Tiannan Guo Yuezhong He Albert J R Heck Henning Hermjakob Tony Hunter Narayanan Gopalakrishna Iyer Ying Jiang Connie R Jimenez Lokesh Joshi Neil L Kelleher Ming Li Yang Li Qingsong Lin Cui Hua Liu Fan Liu Guang-Hui Liu Yansheng Liu Zhihua Liu Teck Yew Low Ben Lu Matthias Mann Anming Meng Robert L Moritz Edouard Nice Guang Ning Gilbert S Omenn Christopher M Overall Giuseppe Palmisano Yaojin Peng Charles Pineau Terence Chuen Wai Poon Anthony W Purcell Jie Qiao Roger R Reddel Phillip J Robinson Paola Roncada Chris Sander Jiahao Sha Erwei Song Sanjeeva Srivastava Aihua Sun Siu Kwan Sze Chao Tang Liujun Tang Ruijun Tian Juan Antonio Vizcaíno Chanjuan Wang Chen Wang Xiaowen Wang Xinxing Wang Yan Wang Tobias Weiss Mathias Wilhelm Robert Winkler Bernd Wollscheid Limsoon Wong Linhai Xie Wei Xie Tao Xu Tianhao Xu Liying Yan Jing Yang Xiao Yang John Yates Tao Yun Qiwei Zhai Bing Zhang Hui Zhang Lihua Zhang Lingqiang Zhang Pingwen Zhang Yukui Zhang Yu Zi Zheng Qing Zhong Yunping Zhu State Key Laboratory of Medical Proteomics Beijing Proteome Research Center National Center for Protein Sciences (Beijing) Beijing Institute of Lifeomics Beijing China. hefc@***. International Academy of Phronesis Medicine (Guangdong) Guangdong China. hefc@***. Department of Biology Institute of Molecular Systems Biology ETH Zurich Zurich Switzerland. aebersold@imsb.biol.ethz.ch. Macquarie Medical School Macquarie University Sydney New South Wales Australia. Institute of Pathology and Southwest Cancer Center Southwest Hospital Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology Ministry of Education of China Chongqing China. Institute of Health Service and Transfusion Medicine Beijing China. Department of Pathology and The Sidney Kimmel Comprehensive Cancer Center Johns Hopkins University Baltimore MD USA. State Key Laboratory of Medical Proteomics Beijing Proteome Research Center National Center for Protein Sciences (Beijing) Beijing Institute of Lifeomics Beijing China. Key Laboratory of Systems Biology Center for Excellence in Molecular Cell Science Shanghai Institute of Biochemistry and Cell Biology Chinese Academy of Sciences Shanghai China. Department of Nephrology First Medical Center of Chinese PLA General Hospital Nephrology Institute of the Chinese People's Liberation Army State Key Laboratory of Kidney Diseases National Clinical Research Center for Kidney Diseases Beijing Key Laboratory of Kidney Disease Research Beijing China. Institute of Chemistry Academia Sinica Taipei China. National Biomedical Imaging Center State Key Laboratory of Membrane Biology Institute of Molecular Medicine Peking-Tsinghua Center for Life Sciences College of Future Technology Peking University Beijing China. School of Biological Sciences Queen's University of Belfast Belfast UK. Functional Proteomics Laboratory Centro Nacional de Biotecnología-CSIC Madrid Spain. Computational Systems Biochemistry Research Group Ma

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Strummer: An interactive guitar chord practice system

Strummer: An interactive guitar chord practice system

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Shunya Ariga Masataka Goto Koji Yatani Interactive Intelligent Systems Laboratory The University of Tokyo National Institute of Advanced Industrial Science and Technology (AIST)

ISBN: (纸本)9781509060689

Musical instrument playing is a skill many people desire to acquire, and learners now have a wide variety of learning materials. However, their volume is enormous, and novice learners may easily get lost in which songs they should practice first. We develop Strummer: an interactive multimedial system for guitar practice. Strummer provide data-driven and personalized practice for learners in order to identify important and easy-to-learn chords and songs. This practice design is intended to encourage smooth skill transfers to songs that learners even have not seen. Our user study confirms the benefits and possible improvements of the Strummer system. In particular, participants expressed their positive impressions on lessons provided by the system.

关键词： Tutorials Training Instruments Music Bars Manuals Multimedia communication

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Parameter-transferred wasserstein generative adversarial network (PT-WGAN) for low-dose PET image denoising

arXiv

引用

arXiv 2019年

作者： Gong, Yu Shan, Hongming Teng, Yueyang Tu, Ning Li, Ming Liang, Guodong Wang, Ge Wang, Shanshan College of Medicine and Biological Information Engineering Northeastern University Shenyang110169 China Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Key Laboratory of Intelligent Computing in Medical Images Ministry of Education Shenyang110169 China Department of Biomedical Engineering Rensselaer Polytechnic Institute TroyNY12180 United States PET-CT/MRI Center Molecular Imaging Center Wuhan University Renmin Hospital Wuhan430060 China Neusoft Medical Systems Co. Ltd Shenyang110167 China

Due to the widespread use of positron emission tomography (PET) in clinical practice, the potential risk of PET-associated radiation dose to patients needs to be minimized. However, with the reduction in the radiation dose, the resultant images may suffer from noise and artifacts that compromise diagnostic performance. In this paper, we propose a parameter-transferred Wasserstein generative adversarial network (PT-WGAN) for lowdose PET image denoising. The contributions of this paper are twofold: i) a PT-WGAN framework is designed to denoise lowdose PET images without compromising structural details, and ii) a task-specific initialization based on transfer learning is developed to train PT-WGAN using trainable parameters transferred from a pretrained model, which significantly improves the training efficiency of PT-WGAN. The experimental results on clinical data show that the proposed network can suppress image noise more effectively while preserving better image fidelity than recently published state-of-the-art methods. We make our code available at https://***/90n9-yu/PT-WGAN. Copyright © 2019, The Authors. All rights reserved.

关键词： Positron emission tomography

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An automated pulmonary parenchyma segmentation method based on an improved region growing algorithm in PET-CT imaging

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Frontiers of Computer Science 2016年第1期10卷 189-200页

作者： Juanjuan ZHAO Guohua JI Xiaohong HAN Yan QIANG Xiaolei LIAO College of Computer Science and Technology Taiyuan University of Technology Taiyuan 030024 China Key Laboratory of Advanced Transducers and Intelligent Control Systems Taiyuan University of Technology Taiyuan 030024 China

To address the incomplete problem in pulmonary parenchyma segmentation based on the traditional methods, a novel automated segmentation method based on an eight- neighbor region growing algorithm with left-right scanning and four-corner rotating and scanning is proposed in this pa- per. The proposed method consists of four main stages： image binarization, rough segmentation of lung, image denoising and lung contour refining. First, the binarization of images is done and the regions of interest are extracted. After that, the rough segmentation of lung is performed through a general region growing method. Then the improved eight-neighbor region growing is used to remove noise for the upper, mid- dle, and bottom region of lung. Finally, corrosion and ex- pansion operations are utilized to smooth the lung boundary. The proposed method was validated on chest positron emis- sion tomography-computed tomography （PET-CT） data of 30 cases from a hospital in Shanxi, China. Experimental results show that our method can achieve an average volume overlap ratio of 96.21 ± 0.39% with the manual segmentation results. Compared with the existing methods, the proposed algorithm segments the lung in PET-CT images more efficiently and ac- curately.

关键词： pulmonary parenchyma segmentation bot-tom region of lung image binarization iterative threshold seeded region growing four-corner rotating and scanning,denoising contour refining PET-CT

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A four-stage localization method for epileptic seizure onset zones

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IFAC-PapersOnLine 2017年第1期50卷 4412-4417页

作者： Wan T. Wu M. Lai X. Wan X. She J. Du Y. School of Automation China University of Geosciences Wuhan Hubei 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei 430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan School of Automation Guangdong University of Technology Guangzhou Guangdong 510006 China

This paper presents a four-stage localization method for epileptic seizure onset zones (SOZs). This method combines the advantages of both the Shannon-entropy-based complex Morlet wavelet transform (SE-CMWT) and adaptive-genetic-algorithm-based matching pursuit (AGA-MP) methods to achieve satisfactory localization performance. The Hilbert transform method is used to identify events of interest. The SE-CMWT-based power spectral density method is applied to acquire channels of interest (CoIs). By using the Morlet wavelets as the dictionary elements, the AGA-MP method combined with Morlet wavelets is developed to detect high-frequency oscillations (HFOs) on CoIs with faster speed and higher accuracy than the AGA-MP method. And the characteristics of HFOs are used to localize SOZs based on the half-maximum method. A comparison shows that our method has higher sensitivity and specificity than four existing methods. © 2017

关键词： Epilepsy Four-stage localization method High-frequency oscillation (HFO) Seizure onset zone (SOZ)

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FCM-based multiple random forest for speech emotion recognition 5

FCM-based multiple random forest for speech emotion recognit...

引用

5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Zhou, Mengtian Chen, Luefeng Xu, Jianping Cheng, Xianghui Wu, Min Cao, Weihua She, Jinhua Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan Tokyo Institute of Technology Yokohama226-8502 Japan

Speech emotion recognition (SER) is of great importance in the human-robot interaction, and SER have been developed rapidly in recent years. How to identify high correlation features is a main question. In this paper, multiple random forest (MRF) is proposed, which can effectively predict up to several thousand explanatory variables, and improve the recognition result. At the mean time, personalized features and non-personalized features are fused for SER that can be divided into different subclasses by adopting the fuzzy C-means (FCM) clustering algorithm, then FCM-based MRF is proposed. Finally, our model is established, and the confusion matrix is output. Moreover, we conduct a separate classification of some certain emotion, which are difficult to recognition to some extent. And results show that the proposed method of FCM-based MRF achieves good performance for SER, which the recognition accuracy is 84.17%.

关键词： Clustering algorithms

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A prediction model of edge gas flow development state based on BP neural network 5

A prediction model of edge gas flow development state based ...

引用

5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Zhang, Jialiang An, Jianqi Wu, Min Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

The development and distribution states of the blast furnace (BF) gas flow determine whether the reaction in the furnace can proceed normally and decide the utilization efficiency of the carbon in the furnace and the stable smooth operation of the furnace. The internal environment of BF is closed with high temperature and high pressure, which causes that the relationship between the development situation of edge gas flow of the BF and the BF operation is uncertain. In this paper, a prediction model of edge gas flow development state based on BP neural network (BPNN) is proposed, clarifying the relationship between the development state of edge gas flow and the edge burden parameters. Firstly, this paper gets the relative operation factors of effecting the development situation of edge gas flow through analyzing the process mechanism of the BF ironmaking, and proposes the development index of edge gas flow and the heat load of cooling stave to measure the development state of the edge gas flow. Secondly, the intrinsic correlation between the data is verified, and the data are analyzed by Spearman's rank correlation coefficient (SRCC) analysis. Finally, according to the analysis results, combined with the burden mechanism, the edge gas flow prediction model is established to realize the prediction of the development state of the edge gas flow. The calculation of the data collected in the metallurgy scene of the BF suggested that this prediction model of the edge gas flow development state of the BF could describe the relationship between BF operation parameters and the developing state of the edge gas flow.

关键词： Flow of gases

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Barrier-certified adaptive reinforcement learning with applications to brushbot navigation

arXiv

引用

arXiv 2018年

作者： Ohnishi, Motoya Wang, Li Notomista, Gennaro Egerstedt, Magnus School of Electrical Engineering Royal Institute of Technology Stockholm11428 Sweden Georgia Robotics and Intelligent Systems Laboratory Georgia Institute of Technology AtlantaGA30332 United States RIKEN Center for Advanced Intelligence Project Tokyo103-0027 Japan School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30313 United States

This paper presents a safe learning framework that employs an adaptive model learning algorithm together with barrier certificates for systems with possibly nonstationary agent dynamics. To extract the dynamic structure of the model, we use a sparse optimization technique. We use the learned model in combination with control barrier certificates which constrain policies (feedback controllers) in order to maintain safety, which refers to avoiding particular undesirable regions of the state space. Under certain conditions, recovery of safety in the sense of Lyapunov stability after violations of safety due to the nonstationarity is guaranteed. In addition, we reformulate an action-value function approximation to make any kernel-based nonlinear function estimation method applicable to our adaptive learning framework. Lastly, solutions to the barrier-certified policy optimization are guaranteed to be globally optimal, ensuring the greedy policy improvement under mild conditions. The resulting framework is validated via simulations of a quadrotor, which has previously been used under stationarity assumptions in the safe learnings literature, and is then tested on a real robot, the brushbot, whose dynamics is unknown, highly complex and nonstationary. Copyright © 2018, The Authors. All rights reserved.

关键词： Reinforcement learning

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