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Does my rebuttal matter? Insights from a major NLP conference

Does my rebuttal matter? Insights from a major NLP conferenc...

2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019

作者： Gao, Yang Eger, Steffen Kuznetsov, Ilia Gurevych, Iryna Miyao, Yusuke Ubiquitous Knowledge Processing Lab Department of Computer Science Technische Universität Darmstadt Germany Department of Computer Science Graduate School of Information Science and Technology University of Tokyo Japan

ISBN: (纸本)9781950737130

Peer review is a core element of the scientific process, particularly in conference-centered fields such as ML and NLP. However, only few studies have evaluated its properties empirically. Aiming to fill this gap, we present a corpus that contains over 4k reviews and 1.2k author responses from ACL-2018. We quantitatively and qualitatively assess the corpus. This includes a pilot study on paper weaknesses given by reviewers and on quality of author responses. We then focus on the role of the rebuttal phase, and propose a novel task to predict after-rebuttal (i.e., final) scores from initial reviews and author responses. Although author responses do have a marginal (and statistically significant) influence on the final scores, especially for borderline papers, our results suggest that a reviewer's final score is largely determined by her initial score and the distance to the other reviewers' initial scores. In this context, we discuss the conformity bias inherent to peer reviewing, a bias that has largely been overlooked in previous research. We hope our analyses will help better assess the usefulness of the rebuttal phase in NLP conferences. © 2019 Association for Computational Linguistics

关键词： Natural language processing systems

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Player’s Stress Reduction in Competitive Online Game by Presenting Calm Scent

Player’s Stress Reduction in Competitive Online Game by Pre...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Toshiki Goto Yu Shibuya Master’s Program of Information Science Graduate School of Science and Technology Kyoto Institute of Technology Kyoto Japan Faculty of Information and Human Sciences Kyoto Institute of Technology Kyoto Japan

ISBN: (数字)9781728198026

ISBN: (纸本)9781728198033

Playing competitive online games is usually fun but sometimes player feels unpleasant and is stressed regardless of games content. When a player is stressed, her/his motivation for games decrease. The purpose of this study is to make competitive online games more enjoyable by reducing player's stress. We propose a system that detects player's stress in a competitive online game by her/his RRI and automatically presents calm scent of lavender oil with an aroma diffuser and a fan when she/he is stressed. In the proposed system, each player wears an armband-type pulse sensor and plays a game with a controller while looking at the display. The system get the player's heart rate from armband-type pulse sensor in real time. Next, the system calculates the RRI from heart rate and determines that the player is stressed when her/his RRI is greater than the threshold. To evaluate the proposed system, we are going to experiment to check the functionality of the proposed system, investigate how long to play the game and under what conditions to detect participants' stress in the game and evaluate whether the proposed system can reduce participants stress in a real environment.

关键词： Heart rate Fans Rail to rail inputs Oils Games Real-time systems Stress

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Big Data Governance for Building A Smart Cities 10

Big Data Governance for Building A Smart Cities

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10th International Conference on ICT for Smart Society, ICISS 2019

作者： Zulkarnain, Novan Kosala, Raymond Ranti, Benny Supangkat, Suhono Harso Bina Nusantara University Computer Science Department BINUS Graduate Program Doctor of Computer Science Information Systems Department Jakarta11480 Indonesia Universitas Indonesia Computer Science Department Depok16424 Indonesia Institute of Technology Bandung School of Electrical and Informatics Engineering Bandung40132 Indonesia

ISBN: (纸本)9781728148809

There have been many studies conducted related to Smart City, IT Governance and Big Data. In this study aims to find out how the relationship between the three and how to form a framework to explain it. The methodology used is qualitative by looking for some literature on smart city framework, IT Governance framework, and a Big Data framework. From these results, an overall picture of the relationship between the three is concluded, where Big Data has a role in IT Governance. and also the relationship of IT Governance to the realization of Smart City. And the final results of this study produce a framework to explain the relationship between Smart City, IT Governance and Big Data. © 2019 IEEE.

关键词： Big data

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Fluctuating risk of acute kidney injury-related mortality for four weeks after exposure to air pollution: A multi-country time-series study in 6 countries

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Environment International 2024年 183卷 108367页

作者： Min, Jieun Kang, Duk-Hee Kang, Cinoo Bell, Michelle L. Kim, Ho Yang, Juyeon Gasparrini, Antonio Lavigne, Eric Hashizume, Masahiro Kim, Yoonhee Fook Sheng Ng, Chris Honda, Yasushi das Neves Pereira da Silva, Susana Madureira, Joana Leon Guo, Yue Pan, Shih-Chun Armstrong, Ben Sera, Francesco Masselot, Pierre Schwartz, Joel Maria Vicedo-Cabrera, Ana Pyo Lee, Jung Al-Aly, Ziyad Won Lee, Jung Kwag, Youngrin Ha, Eunhee Lee, Whanhee Department of Environmental Medicine College of Medicine Ewha Womans University Seoul Korea Republic of Graduate Program in System Health Science and Engineering College of Medicine Ewha Womans University Seoul Korea Republic of Division of Nephrology Department of Internal Medicine Ewha Womans University School of Medicine Ewha Medical Research Center Seoul Korea Republic of Department of Public Health Sciences Graduate School of Public Health Seoul National University Seoul Korea Republic of Yale School of the Environment Yale University New HavenCT United States Biostatistics Collaboration Unit Yonsei University College of Medicine Seoul Korea Republic of Lab Department of Public Health Environments and Society London School of Hygiene & Tropical Medicine London United Kingdom School of Epidemiology & Public Health Faculty of Medicine University of Ottawa Ottawa Canada Department of Global Health Policy Graduate School of Medicine The University of Tokyo Tokyo Japan Department of Global Environmental Health Graduate School of Medicine University of Tokyo Tokyo Japan School of Tropical Medicine and Global Health Nagasaki University Nagasaki Japan Center for Climate Change Adaptation National Institute for Environmental Studies Tsukuba Japan Department of Epidemiology Instituto Nacional de Saúde Dr. Ricardo Jorge Lisbon Portugal EPIUnit-Institute of Public Health University of Porto Porto Portugal Porto Portugal College of Medicine and NTU Hospital Taipei Taiwan National Institute of Environmental Health Science National Health Research Institutes Zhunan Taiwan Department of Public Health Environments and Society London School of Hygiene & Tropical Medicine London United Kingdom Department of Statistics Computer Science and Applications "G. Parenti" University of Florence Florence Italy Department of Environmental Health Harvard T.H. Chan School of Public Health BostonMA United States Institute of Social and Preventive Medicine Universi

Background: Recent studies have reported that air pollution is related to kidney diseases. However, the global evidence on the risk of death from acute kidney injury (AKI) owing to air pollution is limited. Therefore, we investigated the association between short-term exposure to air pollution—particulate matter ≤ 2.5 μm (PM2.5), ozone (O3), and nitrogen dioxide (NO2)—and AKI-related mortality using a multi-country dataset. Methods: This study included 41,379 AKI-related deaths in 136 locations in six countries during 1987–2018. A novel case time-series design was applied to each air pollutant during 0–28 lag days to estimate the association between air pollution and AKI-related deaths. Moreover, we calculated AKI deaths attributable to non-compliance with the World Health Organization (WHO) air quality guidelines. Results: The relative risks (95% confidence interval) of AKI-related deaths are 1.052 (1.003, 1.103), 1.022 (0.994, 1.050), and 1.022 (0.982, 1.063) for 5, 10, and 10 µg/m3 increase in lag 0–28 days of PM2.5, warm-season O3, and NO2, respectively. The lag-distributed association showed that the risk appeared immediately on the day of exposure to air pollution, gradually decreased, and then increased again reaching the peak approximately 20 days after exposure to PM2.5 and O3. We also found that 1.9%, 6.3%, and 5.2% of AKI deaths were attributed to PM2.5, warm-season O3, and NO2 concentrations above the WHO guidelines. Conclusions: This study provides evidence that public health policies to reduce air pollution may alleviate the burden of death from AKI and suggests the need to investigate the several pathways between air pollution and AKI death. © 2023 The Author(s)

关键词： Air quality

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Transverse acoustic spin and torque from pure spinning of objects

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Physical Review B 2021年第6期104卷 L060104-L060104页

作者： M. Farhat P.-Y. Chen M. Amin A. Alù Y. Wu Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Department of Electrical and Computer Engineering University of Illinois at Chicago Chicago Illinois 60607 USA College of Engineering Taibah University Madinah 42353 Saudi Arabia Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10016 USA

Acoustic spin has been recently explored for many applications. In particular, transverse acoustic spin was demonstrated for inhomogeneous acoustic fields. In this Letter, we show the emergence of acoustic spin and torque in rotating acoustic objects of the same physical properties as the surrounding, to single out the effects purely due to rotation. The spinning of a cylindrical column of air or water in the same medium possesses intrinsic spin angular momentum, and we study the torque and force it experiences in evanescent acoustic fields. The resulting discontinuity can thus scatter sound in unusual ways, including a negative radiation force, although it has no imaginary part in its parameters.

关键词： Acoustic interactions Acoustic metamaterials Acoustic wave phenomena Linear acoustics

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Aircraft Detection Based on Saliency Map and Convolution Neural Network 23

Aircraft Detection Based on Saliency Map and Convolution Neu...

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23rd International computer science and Engineering Conference, ICSEC 2019

作者： Sun, Yuwei Cooharojananone, Nagul Ochiai, Hideya University of Tokyo Graduate School of Information Science and Technology Tokyo Japan Chulalongkorn University Department of Mathematics and Computer Science Faculty of Science Bangkok Thailand

ISBN: (纸本)9781728125442

Detection of the aircraft from the remote sensing images attracts many attentions. Not only the aircraft taking off and landing but also the aircraft landing in the airport need to be monitored. This paper proposes a saliency-based CNN (convolutional neural network) method for aircraft detection in the remote sensing images. Many researches of aircraft detection access to a method of R-CNN (region convolutional neural network), which generates two thousand or more of proposal regions as candidates of the aircraft. The researches of using a saliency map to extract the objects from the images are still not so many. We adapt a series of preprocessing as transforming to a gray scale image, deleting the noise, binarizing by threshold, the closing operation, and floodfill to generate a saliency map where the contours of all objects are reinforced. Compared to R-CNN, the using of a saliency map greatly reduces the number of proposal regions, thus improving the efficiency. After this, we find the contours of objects and the minimum rectangles enclosing objects to extract proposed regions. Then, we prepare a negative dataset consisting of different types of backgrounds including the land, grass land and concrete. And for a positive dataset, we prepare images of aircraft in different angles and different sizes. To add more variation data into the dataset, we also use methods of augmentation like elastic distortion and perspective transforms. Then, we train a CNN model using the prepared dataset, which can tell whether a proposed region contains aircraft, after training. At last, we use a method named recall to evaluate the performance of the scheme, attaining an average recall of 0.7217, which shows the rate of aircraft successfully detected in all aircraft. © 2019 IEEE.

关键词： Aircraft detection

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Beyond Lambertian light trapping for large-area silicon solar cells:fabrication methods

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Opto-Electronic Advances 2022年第9期5卷 14-25页

作者： Jovan Maksimovic Jingwen Hu Soon Hock Ng Tomas Katkus Gediminas Seniutinas Tatiana Pinedo Rivera Michael Stuiber Yoshiaki Nishijima Sajeev John Saulius Juodkazis Optical Sciences Centre and ARC Training Centre in Surface Engineering for Advanced Materials(SEAM) School of ScienceSwinburne University of TechnologyHawthorn Vic 3122Australia Melbourne Centre for Nanofabrication ANFF Victoria151 Wellington Rd.Clayton Vic 3168 Australia Department of Electrical and Computer Engineering Graduate School of EngineeringYokohama National University79-5 TokiwadaiHodogaya-kuYokohama 240-8501Japan Institute of Advanced Sciences Yokohama National University79-5 TokiwadaiHodogaya-kuYokohama 240-8501Japan Department of Physics University of Toronto60 St.George StreetTorontoONM5S 1A7Canada World Research Hub Initiative(WRHI) School of Materials and Chemical TechnologyTokyo Institute of Technology2-12-1OokayamaMeguro-kuTokyo 152-8550Japan

Light trapping photonic crystal(PhC)patterns on the surface of Si solar cells provides a novel opportunity to approach the theoretical efficiency limit of 32.3%,for light-to-electrical power conversion with a single junction *** is beyond the efficiency limit implied by the Lambertian limit of ray trapping~29%.The interference and slow light effects are harnessed for collecting light even at the long wavelengths near the Si *** compare two different methods for surface patterning,that can be extended to large area surface patterning:1)laser direct write and 2)step-&-repeat 5×reduction projection *** area throughput limitations of these methods are compared with the established elec-tron beam lithography(EBL)route,which is conventionally utilised but much slower than the presented ***-tral characterisation of the PhC light trapping is compared for samples fabricated by different *** of Si etched via laser patterned mask was~7%at visible wavelengths and was comparable with Si patterned via EBL made *** later pattern showed a stronger absorbance than the Lambertian limit6.

关键词： silicon solar cells laser ablation light trapping Lambertian limit

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Towards unbiased COVID-19 lesion localisation and segmentation via weakly supervised learning

arXiv

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arXiv 2021年

作者： Yang, Yang Chen, Jiancong Wang, Ruixuan Ma, Ting Chen, Jie Zheng, Wei-Shi Zhang, Tong Wang, Lingwei Artificial Intelligence Research Center Peng Cheng Laboratory Shenzhen China School of Computer Science and Engineering Sun Yat-sen University China School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China Shenzhen People’s Hospital Shenzhen Institute of Respiratory Diseases Shenzhen China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School China

Despite tremendous efforts, it is very challenging to generate a robust model to assist in the accurate quantification assessment of COVID-19 on chest CT images. Due to the nature of blurred boundaries, the supervised segmentation methods usually suffer from annotation biases. To support unbiased lesion localisation and to minimise the labelling costs, we propose a data-driven framework supervised by only image level labels. The framework can explicitly separate potential lesions from original images, with the help of an generative adversarial network and a lesion-specific decoder. Experiments on two COVID-19 datasets demonstrates the effectiveness of the proposed framework and its superior performance to several existing methods. © 2021, CC BY.

关键词： Generative adversarial networks

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Deep learning assisted calibrated beam training for millimeter-wave communication systems

arXiv

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arXiv 2021年

作者： Ma, Ke He, Dongxuan Sun, Hancun Wang, Zhaocheng Chen, Sheng Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Tsinghua University Beijing100084 China Tsinghua Shenzhen International Graduate School Shenzhen518055 China The School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

Huge overhead of beam training imposes a significant challenge in millimeter-wave (mmWave) wireless communications. To address this issue, in this paper, we propose a wide beam based training approach to calibrate the narrow beam direction according to the channel power leakage. To handle the complex nonlinear properties of the channel power leakage, deep learning is utilized to predict the optimal narrow beam directly. Specifically, three deep learning assisted calibrated beam training schemes are proposed. The first scheme adopts convolution neural network to implement the prediction based on the instantaneous received signals of wide beam training. We also perform the additional narrow beam training based on the predicted probabilities for further beam direction calibrations. However, the first scheme only depends on one wide beam training, which lacks the robustness to noise. To tackle this problem, the second scheme adopts long-short term memory (LSTM) network for tracking the movement of users and calibrating the beam direction according to the received signals of prior beam training, in order to enhance the robustness to noise. To further reduce the overhead of wide beam training, our third scheme, an adaptive beam training strategy, selects partial wide beams to be trained based on the prior received signals. Two criteria, namely, optimal neighboring criterion and maximum probability criterion, are designed for the selection. Furthermore, to handle mobile scenarios, auxiliary LSTM is introduced to calibrate the directions of the selected wide beams more precisely. Simulation results demonstrate that our proposed schemes achieve significantly higher beamforming gain with smaller beam training overhead compared with the conventional and existing deep-learning based counterparts. Copyright © 2021, The Authors. All rights reserved.

关键词： Forecasting

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Smart photonic wristband for pulse wave monitoring

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Opto-Electronic science 2024年第12期3卷 12-27页

作者： Renfei Kuang Zhuo Wang Lin Ma Heng Wang Qingming Chen Arnaldo Leal Junior Santosh Kumar Xiaoli Li Carlos Marques Rui Min Center for Cognition and Neuroergonomics State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityZhuhai 519087China College of Science Shenyang Aerospace UniversityShenyang 110136China School of Microelectronics Science and Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and SystemsSun Yat-Sen UniversityZhuhai 519082China Graduate Program in Electrical Engineering Federal University of Espírito SantoFernando Ferrari AvenueVitoria 29075-910Brazil Department of Electronics and Communication Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAndhra Pradesh 522302India CICECO-Aveiro Institute of Materials Physics DepartmentUniversity of AveiroAveiro 3810-193Portugal

Real-time acquisition of human pulse signals in daily life is clinically important for cardiovascular disease monitoring and ***,we propose a smart photonic wristband for pulse signal monitoring based on speckle pattern analysis with a polymer optical fiber(POF)integrated into a sports *** different speckle pattern processing algorithms and POFs with different core diameters were *** results indicated that the smart photonic wristband had a high signal-to-noise ratio and low latency,with the measurement error controlled at approximately 3.7%.This optimized pulse signal could be used for further medical diagnosis and was capable of objectively monitoring subtle pulse signal changes,such as the pulse waveform at different positions of Cunkou and pulse waveforms before and after *** the assistance of artificial intelligence(AI),functions such as gesture recognition have been realized through the established prediction model by processing pulse signals,in which the recognition accuracy reaches 95%.Our AI-assisted smart photonic wristband has potential applications for clinical treatment of cardiovascular diseases and home monitoring,paving the way for medical Internet of Things-enabled smart systems.

关键词： smart healthcare specklegram pulse monitoring gesture recognition artificial intelligence wearable sensor

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