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Discovering collective narratives shifts in online discussions

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arXiv 2023年

作者： Zhao, Wanying Guo, Fiona Lerman, Kristina Ahn, Yong-Yeol Center for Complex Networks and Systems Research Luddy School of Informatics Computing and Engineering Indiana University United States Department of Computer Science University of Southern California United States Information Sciences Institute University of Southern California United States Network Science Institute Indiana University BloomingtonIN United States

Narrative is a foundation of human cognition and decision making. Because narratives play a crucial role in societal discourses and spread of misinformation and because of the pervasive use of social media, the narrative dynamics on social media can have profound societal impact. Yet, systematic and computational understanding of online narratives faces critical challenge of the scale and dynamics;how can we reliably and automatically extract narratives from massive amount of texts? How do narratives emerge, spread, and die? Here, we propose a systematic narrative discovery framework that fill this gap by combining change point detection, semantic role labeling (SRL), and automatic aggregation of narrative fragments into narrative networks. We evaluate our model with synthetic and empirical data-two Twitter corpora about COVID-19 and 2017 French Election. Results demonstrate that our approach can recover major narrative shifts that correspond to the major events. © 2023, CC BY-NC-ND.

关键词： Decision making

Local Periodicity-Based Beat Tracking for Expressive Classical Piano Music

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arXiv 2023年

作者： Chiu, Ching-Yu Müller, Meinard Davies, Matthew E.P. Su, Alvin Wen-Yu Yang, Yi-Hsuan The Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University Academia Sinica Taiwan The International Audio Laboratories Erlangen Germany The Department of Informatics Engineering Centre for Informatics and Systems of the University of Coimbra University of Coimbra Portugal The Department of Computer Science and Information Engineering National Cheng Kung University Taiwan Yating Music Team Taiwan AI Labs Taiwan Research Center for IT Innovation Academia Sinica Taiwan

To model the periodicity of beats, state-of-the-art beat tracking systems use "post-processing trackers" (PPTs) that rely on several empirically determined global assumptions for tempo transition, which work well for music with a steady tempo. For expressive classical music, however, these assumptions can be too rigid. With two large datasets of Western classical piano music, namely the Aligned Scores and Performances (ASAP) dataset and a dataset of Chopin's Mazurkas (Maz-5), we report on experiments showing the failure of existing PPTs to cope with local tempo changes, thus calling for new methods. In this paper, we propose a new local periodicity-based PPT, called predominant local pulse-based dynamic programming (PLPDP) tracking, that allows for more flexible tempo transitions. Specifically, the new PPT incorporates a method called "predominant local pulses" (PLP) in combination with a dynamic programming (DP) component to jointly consider the locally detected periodicity and beat activation strength at each time instant. Accordingly, PLPDP accounts for the local periodicity, rather than relying on a global tempo assumption. Compared to existing PPTs, PLPDP particularly enhances the recall values at the cost of a lower precision, resulting in an overall improvement of F1-score for beat tracking in ASAP (from 0.473 to 0.493) and Maz-5 (from 0.595 to 0.838). © 2023, CC BY.

关键词： Dynamic programming

LMI-Based Non-Iterative Design Strategies for Guaranteed Cost Static Output Feedback Control for Linear systems

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LMI-Based Non-Iterative Design Strategies for Guaranteed Cos...

International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)

作者： Hidetoshi Oya Takuya Nakagawa Shunya Nagai Kazushi Nakano Department of Computer Science Tokyo City University Tokyo Japan Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Department of Electronics and Control Engineering National Institute of Technology (KOSEN) Niihama College Ehime Japan Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan

This paper proposes a non-iterative LMI-based design strategy for guaranteed cost static output feedback controllers for linear systems. The proposed design approach is based on the well-known necessary and sufficient condition for the existence of the static output feedback stabilizing control for linear systems. In this paper, for linear systems we show the non-iterative LMI-based design procedure for static output feedback controllers which minimize the upper bound of a given quadratic cost function, and the effectiveness of the proposed static output feedback controller with guaranteed cost is presented through a simple numerical example.

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Hybrid Time-Frequency Domain Analysis for Cardiovascular Disease Forecasting Over ECG Data 1st

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Hybrid Time-Frequency Domain Analysis for Cardiovascular Dis...

1st International Conference on Advanced Network Technologies and Computational Intelligence, ICANTCI 2024

作者： Zaidi, Abdelhamid Byeon, Haewon Keshta, Ismail Soni, Mukesh Kumar, K. Keshav Garg, Ansh Department of Mathematics College of Science Qassim University P.O.Box 6644 Buraydah51452 Saudi Arabia Department of Digital Anti-Aging Healthcare Inje University Gimhae Korea Republic of Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Dr. D. Y. Patil School of Science and Technology Tathawade Pune India College Telangana Hyderabad500 104 India Institute of Engineering and Technology Chitkara University Chitkara University Punjab India

ISBN: (纸本)9783031860683

Due to the few data samples available for computer-aided systems, arrhythmia, a common cardiovascular ailment, creates hurdles for accurate identification. This paper presents a unique methodology for feature extraction in arrhythmia classification that uses a hybrid time-frequency domain analysis within a Convolutional Neural Network (CNN) architecture. The suggested method combines temporal information from RR intervals, frequency-domain information from the Hilbert-Huang transformation, and combined time-frequency information from the continuous wavelet transformation. Following that, a CNN is trained with Focal Loss as the designated loss function. The approach has been carefully tested and verified on an arrhythmia database, proving its ability to classify four unique types of electrocardiogram (ECG) data. Empirical results show that the proposed hybrid time-frequency domain feature extraction method outperforms current classification methodologies in terms of accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Hilbert-Huang transform

Strategic argumentation dialogues for persuasion: Framework and experiments based on modelling the beliefs and concerns of the persuadee

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arXiv 2021年

作者： Hadoux, Emmanuel Hunter, Anthony Polberg, Sylwia Department of Computer Science University College London United Kingdom School of Computer Science and Informatics Cardiff University United Kingdom Scribe Labs London United Kingdom

Persuasion is an important and yet complex aspect of human intelligence. When undertaken through dialogue, the deployment of good arguments, and therefore counterarguments, clearly has a significant effect on the ability to be successful in persuasion. Two key dimensions for determining whether an argument is "good" in a particular dialogue are the degree to which the intended audience believes the argument and counterarguments, and the impact that the argument has on the concerns of the intended audience. In this paper, we present a framework for modelling persuadees in terms of their beliefs and concerns, and for harnessing these models in optimizing the choice of move in persuasion dialogues. Our approach is based on the Monte Carlo Tree Search which allows optimization in real-time. We provide empirical results of a study with human participants showing that our automated persuasion system based on this technology is superior to a baseline system that does not take the beliefs and concerns into account in its strategy. Copyright © 2021, The Authors. All rights reserved.

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Semi-supervised hypothesis transfer for source-free domain adaptation

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arXiv 2021年

作者： Ma, Ning Bu, Jiajun Lu, Lixian Wen, Jun Zhang, Zhen Zhou, Sheng Yan, Xifeng College of Computer Science Zhejiang University China Department of Biomedical Informatics Harvard Medical School United States Computer Science Department University of California Santa Barbara United States

Domain Adaptation has been widely used to deal with the distribution shift in vision, language, multimedia etc. Most domain adaptation methods learn domain-invariant features with data from both domains available. However, such a strategy might be infeasible in practice when source data are unavailable due to data-privacy concerns. To address this issue, we propose a novel adaptation method via hypothesis transfer without accessing source data at adaptation stage. In order to fully use the limited target data, a semi-supervised mutual enhancement method is proposed, in which entropy minimization and augmented label propagation are used iteratively to perform inter-domain and intra-domain alignments. Compared with state-of-the-art methods, the experimental results on three public datasets demonstrate that our method gets up to 19.9% improvements on semi-supervised adaptation tasks. © 2021, CC BY.

关键词： Iterative methods

The effect of emojis on arabic text in sentiment analysis using deep learning

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AIP Conference Proceedings 2025年第1期3255卷

作者： Suhad Nasrallah Taraf Ahmed T. Sadiq Informatics Institute for Postgraduate Studies Iraqi Commission for Computers & Informatics Baghdad Iraq Department of computer science College of science University of Technology-Iraq Baghdad Iraq

The emergence of social media has enabled the swift proliferation of explanatory content across various domains, encompassing advertisements, movies, politics, and economics. The growth has been ascertained through the escalation in emotional analysis, encompassing diverse facets. The Arabic review and OMCD big data sets were amalgamated with Twitter data. The textual content was segregated from emojis, and various word embedding techniques were applied, including Spacy (W2V), Fast Text, and Arabic Bidirectional Encoding Representation (AraBERT), resulting in record-high percentages. Convolutional neural networks (CNN), long short-term memory (LSTM), and recurrent neural networks (RNN) were employed in the development of sentiment analysis models. The assessment of model performance was predicated on achieving optimal accuracy, utilizing the voting method to formulate decisions based on weighting. Deep learning (DL) methodologies with the AST (Arabic et al.) dataset resulted in accurate textual content and emoji models. The symbols occupied exact proportions and significantly impacted the final classification. In contrast, for OMCD (Moroccan Offensive Comments Dataset), the text had a more significant impact due to its small number of symbols.

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Hundredfold increase of stimulated Brillouin-scattering bandwidth in whispering-gallery mode resonators

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Photonics Research 2023年第6期11卷 917-924页

作者： GUOPING LIN JINGYI TIAN TANG SUN QINGHAI SONG YANNE K.CHEMBO Ministry of Industry and Information Technology Key Laboratory of Micro-Nano Optoelectronic Information System School of ScienceHarbin Institute of TechnologyShenzhen 518055China Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Shenzhen 518055China Department of Electrical and Computer Engineering&Institute for Research in Electronics and Applied Physics(IREAP) University of MarylandCollege ParkMaryland 20742USA

Backward stimulated Brillouin scattering(SBS)is widely exploited for various applications in optics and *** typically features a narrow gain bandwidth of a few tens of megahertz in fluoride *** we report a hundredfold increase of SBS bandwidth in whispering-gallery mode *** crystalline orientation results in a large variation of the acoustic phase velocity upon propagation along the periphery,from which a broad Brillouin gain is *** 2.5 GHz wide Brillouin gain profile is theoretically found and experimentally *** phenomena with Brillouin shift frequencies ranging from 11.73 to 14.47 GHz in ultrahigh Q Z-cut magnesium fluoride cavities pumped at the telecommunication wavelength are ***,the Brillouin-Kerr comb in this device is *** 400 comb lines spanning across a spectral window of 120 nm are *** finding paves a new way for tailoring and harnessing the Brillouin gain in crystals.

关键词： scattering pumped Brillouin

The impact of Lacticaseibacillus paracasei GMNL-143 toothpaste on gingivitis and oral microbiota in adults: a randomized, double-blind, crossover, placebo-controlled trial

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BMC Oral Health 2024年第1期24卷 1页

作者： Lee, Min-Kang Chen, I-Hui Hsu, I-Ling Tsai, Wan-Hua Lee, Tzong-Yi Jhong, Jhih-Hua Liu, Bai-Chia Huang, Tsui-Yin Lin, Fang-Kuei Chang, Wen-Wei Wu, Ju-Hui Department of Dentistry Kaohsiung Medical University Hospital No.100 Shih-Chuan 1st Road Sanmin Dist Kaohsiung 807378 Taiwan Research and Development Department GenMont Biotech Incorporation Tainan 741014 Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu 300193 Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan 320315 Taiwan Departement of Biomedical Sciences Chung Shan Medical University No. 110 Section 1 Chien-Kuo N. Rd Taichung 402306 Taiwan Department of Medical Research Chung Shan Medical University Hospital Taichung 402306 Taiwan Department of Oral Hygiene College of Dental Medicine Kaohsiung Medical University Kaohsiung 807378 Taiwan

Background: This study examines the oral health benefits of heat-killed Lacticaseibacillus paracasei GMNL-143, particularly its potential in oral microbiota alterations and gingivitis improvement. Methods: We assessed GMNL-143’s in vitro interactions with oral pathogens and its ability to prevent pathogen adherence to gingival cells. A randomized, double-blind, crossover clinical trial was performed on gingivitis patients using GMNL-143 toothpaste or placebo for four weeks, followed by a crossover after a washout. Results: GMNL-143 showed coaggregation with oral pathogens in vitro, linked to its surface layer protein. In patients, GMNL-143 toothpaste lowered the gingival index and reduced Streptococcus mutans in crevicular fluid. A positive relationship was found between Aggregatibacter actinomycetemcomitans and gingival index changes, and a negative one between Campylobacter and gingival index changes in plaque. Conclusion: GMNL-143 toothpaste may shift oral bacterial composition towards a healthier state, suggesting its potential in managing mild to moderate gingivitis. Trial registration: ID NCT04190485 (https://***/);09/12/2019, retrospective registration. © The Author(s) 2024.

关键词： Gingivitis Lacticaseibacillus paracasei Oral microbiota Probiotic toothpaste