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2017 World Congress on engineering, WCE 2017

作者： Jin, Ma Song, Yan McLoughlin, Ian National Engineering Laboratory of Speech and Language Information Processing Anhui China University of Kent School of Computing Medway United Kingdom

ISBN: (纸本)9789881404749

A defining problem in spoken language identification (LID) is how to design effective representations which allow features to be extracted that are specific to language information. Recent advances in deep neural networks for feature extraction have led to significant improvements in results, with deep end-to-end methods proving effective. In this paper, a novel network is proposed and explored that models an effective representation using first and second-order statistics of features extracted from a well-trained phoneme-related DNN bottleneck network followed by a stack of CNN convolutional layers. The high-order statistics extracted through second order pooling at the output of the CNN are robust to speaker and channel variability, and background noise. Evaluation with NIST LRE 2009 shows improved performance compared to current state-of-the-art systems, achieving over 33% and 20% relative equal error rate (EER) improvement for 3s and 10s utterances.

关键词： Extraction

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Role of diagrams in problem solving: An evaluation of eye-tracking parameters as a measure of visual attention

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Physical Review Physics Education Research 2019年第1期15卷 013101-013101页

作者： Ana Susac Andreja Bubic Maja Planinic Marko Movre Marijan Palmovic Department of Applied Physics Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 10000 Zagreb Croatia Department of Physics Faculty of Science University of Zagreb Bijenicka 32 10000 Zagreb Croatia Chair for Psychology Faculty of Humanities and Social Sciences University of Split Sinjska 2 21000 Split Croatia Laboratory for Psycholinguistic Research Department of Speech and Language Pathology University of Zagreb Borongajska cesta 83h 10000 Zagreb Croatia

Typical physics textbook problems often include supportive diagrams that visualize the physical situation although the potential benefits of providing such diagrams is not yet fully established. We used eye tracking to explore the role of supportive diagrams in problem solving. Including a supportive diagram with the text of the problem improved students’ percentage of correct answer in one of the six problems used in the study. Eye-tracking data showed that students typically spent less time on the text of the problem if they were presented with a diagram, but the total viewing time did not change. When a diagram was presented students split their attention between the diagram and the text without speeding up problem solving. Cognitive load theory and dual coding theory suggest that giving information in two formats (verbal and visual) might reduce extraneous cognitive load and leave more cognitive resources available for further steps in problem solving. However, this does not necessarily lead to a higher percentage of correct answers to the problem, because supportive diagrams influence only one step of the complex process of problem solving. In addition to the role of diagrams, we evaluated different eye-tracking measures as measures of visual attention during physics problem solving. It seems that the fixation duration is rather constant, and not always sensitive to the manipulation in the task. On the other hand, dwell time and the number of fixations show more variability across problems and participants, so they seem to be appropriate measures of the visual attention. Since dwell time and fixation number are dependent measures, and they show a similar pattern of responses, in most cases it seems sufficient to report only one of them.

关键词： Research methodology Scientific reasoning & problem solving

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Influential Factors and Strategic Analysis on the Development of Cross-border E-commerce between China and Russia under “the Belt and Road” Initiative

Influential Factors and Strategic Analysis on the Developmen...

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第30届中国控制与决策会议

作者： Zhao Jiuru Guangdong University of Foreign Studies Laboratory of Language Engineering and Computing Guangdong University of Foreign Studies Guangdong Institute for International Strategies Guangdong University of Foreign Studies Center for European Studies

With the implementation of China's "the belt and road" initiative, especially the formation of China-Russia comprehensive strategic partnership of coordination, bilateral trade cooperation between China and Russia needs to be strengthened urgently. In recent years, the rapid development of cross-border e-commerce between China and Russia as a new and efficient trade means has become a new engine for the economic and trade development of China and Russia. It is of great significance to promote the pragmatic cooperation in economy and trade between China and Russia. This paper takes "the belt and road" initiative as the breakthrough point to study the development of cross-border e-commerce between China and Russia. This paper analyzes the influential factors and puts forward the development strategies of cross-border e-commerce between China and Russia to provide strategies and suggestions for the Chinese government and enterprises about accelerating the development of cross-border e-commerce between China and Russia.

关键词： "the Belt and Road" Initiative Cross-Border E-commerce between China and Russia Influential Factors Strategic Analysis

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Verb Complementation in China English——The Case of “Give”

Verb Complementation in China English——The Case of “Give”

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2018 3rd International Conference on Education, Management and Systems engineering(EMSE 2018)

作者： Li-xin XIA Yun XIA Qian LI Laboratory of Language Engineering and Computing/Center for Lexicographical Studies of Guangdong University of Foreign Studies Nanfang College of Sun Yat-Sen University Center for Lexicographical Studies of Guangdong University of Foreign Studies

The present paper aims to reveal the differences across different English varieties in the use of the verb complementation patterns. To that end, a corpus-based methodology was adopted to compare the complementation profiles between China English, British English and Indian English. Through a comparative analysis of the data, it was found that there were marked differences between them in verb complementation. For the pair of China English and British English, the Type IP and Type IIIP patterns were significantly underused in China English. In addition, speakers of China English tended to use the Type III patterns less frequently than their British counterparts. For the pair of China English and Indian English, there was a significant difference in the use of Type III and Type IIIP patterns. China English speakers did not use them as frequently as their Indian counterparts. By contrast, Indian English speakers underused the Type I patterns. The paper argues that linguistic transfer and cultural influences might be the underlying reasons to lead to these differences.

关键词： Verb complementation Structrual nativization China English Corpus linguistics Information technology Management engineering Computational linguistics

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Deep learning based joint resource scheduling algorithms for hybrid MEC networks

arXiv

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arXiv 2019年

作者： Jiang, Feibo Wang, Kezhi Dong, Li Pan, Cunhua Xu, Wei Yang, Kun Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha China Department of Computer and Information Sciences Northumbria University United Kingdom Key Laboratory of Hunan Province for New Retail Virtual Reality Technology Hunan University of Technology and Business Changsha China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom NCRL Southeast University Nanjing China School of Computer Technology and Engineering Changchun Institute of Technology Changchun China School of Computer Sciences and Electrical Engineering University of Essex ColchesterCO4 3SQ United Kingdom

In this paper, we consider a hybrid mobile edge computing (H-MEC) platform, which includes ground stations (GSs), ground vehicles (GVs) and unmanned aerial vehicle (UAVs), all with mobile edge cloud installed to enable user equipments (UEs) or Internet of thing (IoT) devices with intensive computing tasks to offload. Our objective is to obtain an online offloading algorithm to minimize the energy consumption of all the UEs, by jointly optimizing the positions of GVs and UAVs, user association and resource allocation in real-time, while considering the dynamic environment. To this end, we propose a hybrid deep learning based online offloading (H2O) framework where a large-scale path-loss fuzzy c-means (LSFCM) algorithm is first proposed and used to predict the optimal positions of GVs and UAVs. Secondly, a fuzzy membership matrix U-based particle swarm optimization (U-PSO) algorithm is applied to solve the mixed integer nonlinear programming (MINLP) problems and generate the sample datasets for the deep neural network (DNN) where the fuzzy membership matrix can capture the small-scale fading effects and the information of mutual interference. Thirdly, a DNN with the scheduling layer is introduced to provide user association and computing resource allocation under the practical latency requirement of the tasks and limited available computing resource of H-MEC. In addition, different from traditional DNN predictor, we only input one UEs information to the DNN at one time, which will be suitable for the scenarios where the number of UE is varying and avoid the curse of dimensionality in DNN. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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Fair Efficiency Comparisons of Decoy-state Quantum Key Distribution Protocols

arXiv

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arXiv 2018年

作者： Hong-Xin, Li Ming, Gao Xue-Ping, Yan Bao, Yan Yu, Han Ling, Shan Zhi, Ma Department of Language Engineering LuoyangUniversity of Foreign Languages Luoyang Henan471003 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China College of Animal Science and Technology Henan University of Science and Technology Luoyang Henan471003 China

Secure key rate of decoy-state quantum key distribution protocols hasbeen improved with biased basis choice, however, the securitystandardsand parameters of current protocols are *** a result, we cannotgive an accurate key rate comparison between different kinds of protocols. Taking the schemes based on different formula of secure key rate as examples, we give a fair comparison between typical protocols under universalcomposable securitystandard. Through analyzing the relationship of security parameters in post-processing stage and final secure key, we achieve the unified quantification between protocols based on Gottesman-Lo-Lütkenhaus-Preskill formula and the ones under universal composable security. Based on the above research, the impact of different sending length and secure parameters on secure key rate is investigated, meanwhile, we give the dependent relationship between secure key rate and sending length under different secure parameters. Besides, we analyze the importance and conditions of fair comparison. For the first time we give a fair comparison betweenthe protocols based on GLLP formula and smooth entropy, and taking Raymond protocol and Toshiba protocol as examples, we analyze the way for improving secure key rate in the light intensity choice and the singlebit error rate estimation method. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum cryptography

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Author Correction: Spatial communication systems across languages reflect universal action constraints

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Nature human behaviour 2024年第1期8卷 181页

作者： Kenny R Coventry Harmen B Gudde Holger Diessel Jacqueline Collier Pedro Guijarro-Fuentes Mila Vulchanova Valentin Vulchanov Emanuela Todisco Maria Reile Merlijn Breunesse Helen Plado Juergen Bohnemeyer Raed Bsili Michela Caldano Rositsa Dekova Katharine Donelson Diana Forker Yesol Park Lekhnath Sharma Pathak David Peeters Gabriella Pizzuto Baris Serhan Linda Apse Florian Hesse Linh Hoang Phuong Hoang Yoko Igari Keerthana Kapiley Tamar Haupt-Khutsishvili Sara Kolding Katri Priiki Ieva Mačiukaitytė Vaisnavi Mohite Tiina Nahkola Sum Yi Tsoi Stefan Williams Shunei Yasuda Angelo Cangelosi Jon Andoni Duñabeitia Ramesh Kumar Mishra Roberta Rocca Jurģis Šķilters Mikkel Wallentin Eglė Žilinskaitė-Šinkūnienė Ozlem Durmaz Incel School of Psychology University of East Anglia Norwich UK. k.coventry@uea.ac.uk. School of Psychology University of East Anglia Norwich UK. Helmholtz Institute Department of Experimental Psychology Utrecht University Utrecht the Netherlands. Hanse-Wissenschaftskolleg Delmenhorst Germany. Department of English Friedrich-Schiller-Universität Jena Jena Germany. Department of Spanish Modern and Classic Philology University of the Balearic Islands Palma Spain. Language Acquisition and Language Processing Lab Department of Language and Literature Norwegian University of Science and Technology Trondheim Norway. Department of Spanish Language Linguistics and Literature Theory University of Seville Seville Spain. Institute of Estonian and General Linguistics University of Tartu Tartu Estonia. Centre for the Arts in Society Leiden University Leiden the Netherlands. Võro Institute Võru Estonia. Department of Linguistics University at Buffalo Buffalo NY USA. Danieli Telerobot Srl Genoa Italy. Istituto Italiano di Tecnologia (IIT) Genoa Italy. Paisii Hilendarski University of Plovdiv Plovdiv Bulgaria. Department of English University of Nevada Reno NV USA. Department of Slavonic Languages and Caucasus Studies Friedrich-Schiller-Universität Jena Jena Germany. Cognitive Science Department of Humanities Social and Political Sciences ETH Zürich Zürich Switzerland. Cognitive Science and Psycholinguistics Lab Central Department of Linguistics Tribhuvan University Kathmandu Nepal. Centre for Neural and Cognitive Sciences School of Medical Sciences University of Hyderabad Hyderabad India. Department of Communication and Cognition TiCC Tilburg University Tilburg the Netherlands. Max Planck Institute for Psycholinguistics Nijmegen the Netherlands. Department of Chemistry University of Liverpool Liverpool UK. Department of Computer Science University of Manchester Manchester UK. Laboratory for Perceptual and Cognitive Systems Faculty of Computing University o

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Automatic essay scoring based on Coh-Metrix feature selection for Chinese English Learners 1st

Automatic essay scoring based on Coh-Metrix feature selectio...

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1st International Symposium on Emerging Technologies for Education, SETE 2016 Held in Conjunction with ICWL 2016

作者： Li, Xia Liu, Jianda Key Laboratory of Language Engineering and Computing Guangdong University of Foreign Studies Guangzhou China National Key Research Center for Linguistics and Applied Linguistics Guangdong University of Foreign Studies Guangzhou China

ISBN: (纸本)9783319528359

Automatic essay scoring can be based on essay’s content or form. We believe that both classes of features can reflect some aspects of an essay’s quality and they should be combined. In this paper, we use Coh-Metrix and importance measure to extract features that cover a wide range of features relating to the essay’s grammatical structure, content, form, cohesion, and so on, and more related to the Chinese English Learners. This is a more complete set of features than those used in the literature and it is expected to better cover an essay’s characteristics. SVM and C5.0 classification methods based on these features are used to predict the essay’s score. Our experiments show that this set of features can produce good results on Chinese English essays even when we use top 5 and top 15 features with higher importance score. © Springer International Publishing AG 2017.

关键词： Feature Selection

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Music, computing, and Health: A Roadmap for the Current and Future Roles of Music Technology for Health Care and Well-Being

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Music and Science 2021年 4卷

作者： Agres, Kat R. Schaefer, Rebecca S. Volk, Anja van Hooren, Susan Holzapfel, Andre Dalla Bella, Simone Müller, Meinard de Witte, Martina Herremans, Dorien Ramirez Melendez, Rafael Neerincx, Mark Ruiz, Sebastian Meredith, David Dimitriadis, Theo Magee, Wendy L. Yong Siew Toh Conservatory of Music National University of Singapore Singapore Social and Cognitive Computing Department Institute of High Performance Computing A*STAR Singapore Institute for Psychology Health Medical Neuropsychology Unit Leiden University Leiden Netherlands Leiden Institute for Brain and Cognition Leiden University Leiden Netherlands Academy of Creative and Performing Arts Leiden University Leiden Netherlands Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Faculty of Health care Department of Arts Therapies Zuyd University of Applied Sciences Heerlen Netherlands KenVaK Research Centre for the Arts Therapies and Psychomotricity Heerlen Netherlands Faculty of Psychology Open University of The Netherlands Heerlen Netherlands Division of Media Technology and Interaction Design KTH Royal Institute of Technology Stockholm Sweden International Laboratory for Brain Music and Sound Research (BRAMS) Outremont QC Canada Department of Psychology University of Montreal Montreal QC Canada Centre for Research on Brain Language and Music (CRBLM) Montreal QC Canada University of Economics and Human Sciences in Warsaw Warsaw Poland International Audio Laboratories Erlangen Friedrich-Alexander Universität Erlangen-Nürnberg Erlangen Germany HAN University of Applied Sciences Department of Arts Therapies and Psychological Studies Nijmegen Netherlands University of Amsterdam Research Institute of Child Development and Education Amsterdam Netherlands Treatment Centre for People with Mild Intellectual Disabilities and Psychiatric and Behavioral Disorders Gennep Netherlands Information Systems Technology and Design Singapore University of Technology and Design Singapore Music and Machine Learning Lab Music Technology Group Universitat Pompeu Fabra Barcelona Spain Faculty of EEMCS Interactive Intelligence Group Delft University of Technology Delft Netherlands Centre for Digital Music School of Electronic Engineerin

The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the involved disciplines, the workshop “Music, computing, and Health” was held to discuss best practices and state-of-the-art at the intersection of these areas with researchers from music psychology and neuroscience, music therapy, music information retrieval, music technology, medical technology (medtech), and robotics. Following the discussions at the workshop, this article provides an overview of the different methods of the involved disciplines and their potential contributions to developing music technology for health and well-being. Furthermore, the article summarizes the state of the art in music technology that can be applied in various health scenarios and provides a perspective on challenges and opportunities for developing music technology that (1) supports person-centered care and evidence-based treatments, and (2) contributes to developing standardized, large-scale research on music-based interventions in an interdisciplinary manner. The article provides a resource for those seeking to engage in interdisciplinary research using music-based computational methods to develop technology for health care, and aims to inspire future research directions by evaluating the state of the art with respect to the challenges facing each field. © The Author(s) 2021.

关键词： health care interdisciplinarity MedTech music information retrieval (MIR) music neuroscience Music psychology music technology music therapy well-being

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Collaborative data collection scheme based on optimal clustering for wireless sensor networks

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Sensors (Switzerland) 2018年第8期18卷

作者： Li, Guorui Chen, Haobo Peng, Sancheng Li, Xinguang Wang, Cong Yu, Shui Yin, Pengfei School of Computer Science and Engineering Northeastern University Shenyang110819 China Laboratory of Language Engineering and Computing Guangdong University of Foreign Studies Guangzhou510006 China School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou510006 China School of Software University of Technology Sydney Sydney2007 Australia School of Information Science and Engineering Central South University Changsha410083 China College of Information Science and Engineering Jishou University Jishou416000 China

In recent years, energy-efficient data collection has evolved into the core problem in the resource-constrained Wireless Sensor Networks (WSNs). Different from existing data collection models in WSNs, we propose a collaborative data collection scheme based on optimal clustering to collect the sensed data in an energy-efficient and load-balanced manner. After dividing the data collection process into the intra-cluster data collection step and the inter-cluster data collection step, we model the optimal clustering problem as a separable convex optimization problem and solve it to obtain the analytical solutions of the optimal clustering size and the optimal data transmission radius. Then, we design a Cluster Heads (CHs)-linking algorithm based on the pseudo Hilbert curve to build a CH chain with the goal of collecting the compressed sensed data among CHs in an accumulative way. Furthermore, we also design a distributed cluster-constructing algorithm to construct the clusters around the virtual CHs in a distributed manner. The experimental results show that the proposed method not only reduces the total energy consumption and prolongs the network lifetime, but also effectively balances the distribution of energy consumption among CHs. By comparing it o the existing compression-based and non-compression-based data collection schemes, the average reductions of energy consumption are 17.9% and 67.9%, respectively. Furthermore, the average network lifetime extends no less than 20-times under the same comparison. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.

关键词： Wireless sensor networks

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