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Emotion recognition in conversations with transfer learning from generative conversation modeling

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arXiv 2019年

作者： Hazarika, Devamanyu Poria, Soujanya Zimmermann, Roger Mihalcea, Rada School of Computing National University of Singapore Computer Science & Engineering University of Michigan United States Information Systems Technology and Design Singapore University of Technology and Design

Recognizing emotions in conversations is a challenging task due to the presence of contextual dependencies governed by self- and inter-personal influences. Recent approaches have focused on modeling these dependencies primarily via supervised learning. However, purely supervised strategies demand large amounts of annotated data, which is lacking in most of the available corpora in this task. To tackle this challenge, we look at transfer learning approaches as a viable alternative. Given the large amount of available conversational data, we investigate whether generative conversational models can be leveraged to transfer affective knowledge for the target task of detecting emotions in context. We propose an approach, TL-ERC, where we first train a neural dialogue generation model and then perform parameter transfer to initiate our target emotion classifier. Apart from the traditional pre-trained sentence encoders, we also incorporate parameter transfer from the recurrent components that model inter-sentence context across the whole conversation. Based on this idea, we perform several experiments across multiple datasets and find improvement in performance and robustness against limited training data. TL-ERC also achieves better validation performances in significantly fewer epochs. Overall, we infer that knowledge acquired from dialogue generators can indeed help recognize emotions in conversations. Copyright © 2019, The Authors. All rights reserved.

关键词： Speech recognition

Spectrum learning-aided reconfigurable intelligent surfaces for 'green' 6G networks

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arXiv 2021年

作者： Yang, Bo Cao, Xuelin Huang, Chongwen Guan, Yong Liang Yuen, Chau Di Renzo, Marco Niyato, Dusit Debbah, Mérouane Hanzo, Lajos Engineering Product Development Pillar Singapore University of Technology and Design Singapore487372 Singapore College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China International Joint Innovation Center Zhejiang University Haining314400 China Hangzhou310027 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes 3 Rue Joliot-Curie Gif-sur-Yvette91192 France School of Computer Science and Engineering Nanyang Technological University Singapore Lagrange Mathematical and Computing Research Center Paris75007 France Université Paris-Saclay Centrale-Supélec Gif-sur-Yvette91190 France School of Electronics and Computer Science University of Southampton United Kingdom

In the sixth-generation (6G) era, emerging largescale computing based applications (for example processing enormous amounts of images in real-time in autonomous driving) tend to lead to excessive energy consumption for the end users, whose devices are usually energy-constrained. In this context, energy-efficiency becomes a critical challenge to be solved for harnessing these promising applications to realize 'green' 6G networks. As a remedy, reconfigurable intelligent surfaces (RIS) have been proposed for improving the energy efficiency by beneficially reconfiguring the wireless propagation environment. In conventional RIS solutions, however, the received signal-tointerference- plus-noise ratio (SINR) sometimes may even become degraded. This is because the signals impinging upon an RIS are typically contaminated by interfering signals which are usually dynamic and unknown. To address this issue, 'learning' the properties of the surrounding spectral environment is a promising solution, motivating the convergence of artificial intelligence and spectrum sensing, termed here as spectrum learning (SL). Inspired by this, we develop an SL-aided RIS framework for intelligently exploiting the inherent characteristics of the radio frequency (RF) spectrum for green 6G networks. Given the proposed framework, the RIS controller becomes capable of intelligently 'think-and-decide' whether to reflect or not the incident signals. Therefore, the received SINR can be improved by dynamically configuring the binary ON-OFF status of the RIS elements. The energy-efficiency benefits attained are validated with the aid of a specific case study. Finally, we conclude with a list of promising future research directions. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy efficiency

A Novel Solution of Underdetermined Equations for DGTD based on Prior knowledge

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A Novel Solution of Underdetermined Equations for DGTD based...

International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Qi Qi Xinyuan Cao Mingsheng Chen Zhixiang Huang Yi Liu Xianliang Wu Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei Anhui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University Hefei China School of Electronic Engineering Huainan Normal University Huainan China

ISBN: (数字)9781728157337

ISBN: (纸本)9781728157344

To accelerate solving transient electromagnetic problems by discontinuous Galerkin time domain (DGTD) method, a solution of underdetermined equations is established based on prior knowledge. In the proposed method, nodal basis function and a leapfrog scheme are used to Maxwell curl equations for spatial and time discretization. Electromagnetic fields in each element of computation domain are updated individually by applying conventional DGTD in initial time. When the electromagnetic wave covers the domain, the fields of all elements are updated as a whole. The underdetermined equations are established by randomly extracting rows from global mass matrix. Taking the results of a few previous time steps as the prior knowledge, a sparse transform is constructed. Then the underdetermined system of equations can be solved by recovery algorithms. Meanwhile,in order to maintain the advantage of low computational complexity, a restart mechanism is presented. The validity of the proposed method is verified by numerical experiments.

关键词： Microwave technology Millimeter wave technology Transforms Sparse matrices Electromagnetic fields Transient analysis Time-domain analysis

Adaptive Handover Decision Inspired By Biological Mechanism in Vehicle Ad-hoc Networks

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Computers, Materials & Continua 2019年第9期61卷 1117-1128页

作者： Xuting Duan Jingyi Wei Daxin Tian Jianshan Zhou Haiying Xia Xin Li Kunxian Zheng Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing100191China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&SafetyControl Beijing100191China School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Engineering and Design University of SussexBrightonBN19RHUK Research Institute of Highway Ministry Transport Beijing100088China Department of Computer Science and Technology Tsinghua UniversityHaidian DistrictBeijing100088China

In vehicle ad-hoc networks(VANETs),the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes *** by the self-adaptive paradigm of cellular attractors,this paper regards an individual communication as a cell,so that we can apply the revised attractor selection model to induce each connected *** at improving the Quality of Service(QoS),we presented the bio-inspired handover decision-making *** addition,we employ the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)for any vehicle to choose an access *** paper proposes a novel framework where the bio-inspired mechanism is combined with *** a dynamic and random mobility environment,our method achieves the coordination of performance of heterogeneous networks by guaranteeing the efficient utilization and fair distribution of network resources in a global *** experimental results confirm that the proposed method performs better when compared with conventional schemes.

关键词： Revised attraction selection model TOPSIS VANETs QoS

Where does stress happen? Ecological momentary assessment of daily stressors using a mobile phone app

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Mental Health Science

Mental Health Science 2024年第2期2卷

作者： Xing Yao Erik J. Nelson PhD Kostas Stavrianakis PhD Ting-Yen (Tim) Huang MBA Casey Moran MS Patrick C. Shih PhD Evan J. Jordan PhD Department of Health and Wellness Design School of Public Health Indiana University Bloomington Bloomington Indiana USA Department of Public Health College of Life Sciences Brigham Young University Provo Utah USA Department of People Organisations and Practice Aberdeen Business School Robert Gordon University Scotland UK Travel and Tourism Program International College Ming Chuan University Taoyuan City Taiwan Department of Recreation Sport and Tourism University of Illinois Champaign Illinois USA Department of Informatics Luddy School of Informatics Computing and Engineering Indiana University Bloomington Indiana USA

Despite the importance of daily stress to individuals' health and wellbeing, few studies have explored where stress happens in real time, that is, dynamic stress processes in different spaces. As such, stress interventions rarely account for the environment in which stress occurs. We used mobile phone based ecological momentary assessment (EMA) to collect daily stress data. Thirty-three participants utilized a mobile-phone-based EMA app to self-report stressors as they went about their daily lives. Geographic coordinates were automatically collected with each stress report. Data from thematic analysis of stressors by location (home, work, work from home, other) were used to determine whether certain stressors were more prevalent in certain environments. Nine daily stressors significantly differed by location. Work-related stress was reported more often at work. Pets, household chores, sleep, and media-related stressors were reported most at home. Physical illnesses, vehicle issues, and safety/security stressors occurred most often while participants were “working from home.” Traffic-related stress was experienced more commonly in “other” environments. Other 18 stressors were generated regardless of location, suggesting that these stressors were persistent and without respect to location. Study findings expand the understanding of environments in which specific stressors occur, providing baseline data for potential targeted “just-in-time” stress interventions tailored to unique stressors in specific environments. We also provide findings related to the “work from home” phenomenon. Further work is needed to better understand the unique stressors among the large number of individuals who transitioned to working from home during and after the COVID-19 pandemic.

关键词： daily stress ecological momentary assessment geospatial analysis workplace

The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels (vol 400, pg 1619, 2022)

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LANCET 2022年第10365期400卷 1766-1766页

作者： Romanello, M. Di Napoli, C. Drummond, P. Institute for Global Health University College London London UK School of Agriculture Policy and Development University of Reading Reading UK Institute for Sustainable Resources University College London London UK Department of Global Health Centre for Health and the Global Environment University of Washington Seattle WA USA UCL Energy Institute University College London London UK Department of Health Sciences University of York York UK Department of Meteorology University of Reading Reading UK Institute for Risk and Disaster Reduction University College London London UK School of Earth and Environment University of Leeds Leeds UK Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK School of Population Health University of Melbourne Melbourne VIC Australia Department of Earth System Science Tsinghua University Beijing China Mercator Research Institute on Global Commons and Climate Change Berlin Germany Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute of Environmental Sciences University of Geneva Geneva Switzerland Cardiovascular Epidemiology Unit Department of Public Health & Primary Care University of Cambridge Cambridge UK School of Government University of Birmingham Birmingham UK Economic Analysis of Climate Impacts and Policy Division Centro Euro-Mediterraneo sui Cambiamenti Climatici Venice Italy Institute for Environmental Design and Engineering University College London London UK Natural Resources Institute University of Greenwich London UK Department of Environmental Health Sciences and Yale Center on Climate Change and Health Yale University New Haven CT USA Department of Civil and Environmental Engineering Northeastern University Boston MA USA Department of Fish and Wildlife Conservation Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Geography University College London London UK NU

With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified. Because of the rapidly increasing temperatures, vulnerable populations (adults older than 65 years, and children younger than one year of age) were exposed to 3·7 billion more heatwave days in 2021 than annually in 1986–2005 (indicator 1.1.2), and heat-related deaths increased by 68% between 2000–04 and 2017–21 (indicator 1.1.5), a death toll that was significantly exacerbated by the confluence of the COVID-19 pandemic. Despite the local cooling and overall health benefits of urban greenspaces, only 277 (27%) of 1038 global urban centres were at least moderately green in 2021 (indicator 2.2.3), and the number of households with air conditioning increased by 66% from 2000 to 2020, a maladaptive response that worsens the energy crisis and further increases urban heat, air pollution, and greenhouse gas emissions. [...]millions of people do not have access to the energy needed to keep their homes at healthy temperatures, preserve food and medication, and meet the seventh Sustainable Development Goal (to ensure access to affordable, reliable, sustainable, and modern energy for all). Aggravating this situation even further, governments continue to incentivise fossil fuel production and consumption: 69 (80%) of 86 countries reviewed had net-negative carbon prices (ie, provided a net subsidy to fossil fuels) for a net total of US$400 billion

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Venn GAN: Discovering commonalities and particularities of multiple distributions

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arXiv 2019年

作者： Yazıcı, Yasin Lecouat, Bruno Foo, Chuan-Sheng Winkler, Stefan Yap, Kim-Hui Piliouras, Georgios Chandrasekhar, Vijay School of Electrical and Electronics Engineering Nanyang Technological University Singapore Institute for Infocomm Research A*STAR Singapore School of Computing National University of Singapore Singapore Engineering Systems and Design Singapore University of Technology and Design Singapore Singapore

We propose a GAN design which models multiple distributions effectively and discovers their commonalities and particularities. Each data distribution is modeled with a mixture of K generator distributions. As the generators are partially shared between the modeling of different true data distributions, shared ones captures the commonality of the distributions, while non-shared ones capture unique aspects of them. We show the effectiveness of our method on various datasets (MNIST, Fashion MNIST, CIFAR-10, Omniglot, CelebA) with compelling results1. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

Smith-Purcell radiation from time grating

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Newton 2025年第2期1卷

作者： Juan-Feng Zhu Ayan Nussupbekov Yudi Fan Wenjie Zhou Zicheng Song Xuchen Wang Zi-Wen Zhang Chao-Hai Du Xianlong Wei Ping Bai Ching Eng Png Cheng-Wei Qiu Lin Wu Science Mathematics and Technology Singapore University of Technology and Design 8 Somapah Road Singapore 487372 Singapore Institute of High Performance Computing Agency for Science Technology and Research (A∗STAR) 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Singapore Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 Singapore Center for Composite Materials and Structures School of Astronautics Harbin Institute of Technology Harbin China Institute of Nanotechnology Karlsruhe Institute of Technology Karlsruhe Germany Optical Communication Systems and Networks School of Electronics Peking University Beijing China Key Laboratory for the Physics and Chemistry of Nanodevices School of Electronics Peking University Beijing China

Smith-Purcell radiation (SPR) arises when an electron moves above a spatial grating, where fixed momentum compensation constrains the emission wavelength. In contrast, temporal SPR ( t -SPR) utilizes a time grating to leverage temporal periodicity for energy compensation, enabling more flexible radiation control. We introduce a generalized dispersion equation for t -SPR that predicts the interplay between radiation frequency, direction, electron velocity, modulation period, and harmonic orders. t -SPR offers several advantages over conventional SPR: robustness ( t -SPR maintains stable emission intensity without rapid decay as the electron moves away from the time grating), versatility ( t -SPR enables precise control via temporal modulation of period, amplitude, and waveform), and amplified emission (temporal modulation introduces additional energy channels, boosting emission). These features make t -SPR highly promising for advanced applications in on-chip light sources and electron accelerators.

关键词： Smith-Purcell radiation time grating photonic time crystal free-electron radiation

A Novel Application of Quantum Speed Limit to String Theory

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arXiv 2023年

作者： Shabir, Arshid Wani, Salman Sajad Ali, Raja Nisar Kannan, S. Sheikh, Aasiya Faizal, Mir Sheikh, Javid A. Rubab, Seemin Al-Kuwari, Saif Department of Physics National Institute of Technology Srinagar190006 India Department of Physics University of Kashmir Srinagar190006 India Department of Physics Central University of Kashmir Tulmulla Ganderbal191131 India Qatar Center for Quantum Computing College of Science and Engineering Hamad Bin Khalifa University Qatar ISRO Inertial Systems Unit Thiruvananthapuram695013 India Design and Manufacturing Technology Division Raja Ramanna Centre for Advanced Technology Indore452013 India Canadian Quantum Research Center 204-3002 32 Ave VernonBCV1T 2L7 Canada Irving K. Barber School of Arts and Sciences University of British Columbia Okanagan KelownaBCV1V 1V7 Canada

In this work, we investigate the implications of the concept of quantum speed limit in string field theory. We adopt a novel approach to the problem of time on world-sheet based on Fisher information, and arrive at a minimum time for a particle state to evolve into another particle state. This is done using both the Mandelstam-Tamm bound and the Margolus-Levitin bound. This implies that any interaction has to be smeared over such an interval, and any interaction in the effective quantum field theory has to be non-local. As non-local quantum field theories are known to be finite, it is expected that divergences should be removed from effective quantum field theories due to the quantum speed limit of string theory. © 2023, CC BY.

关键词： String theory