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Parametrized black hole quasinormal ringdown formalism for higher overtones

Physical Review D 2024年第2期110卷 024015-024015页

作者： Shin’ichi Hirano Masashi Kimura Masahide Yamaguchi Jiale Zhang Oyama 323-0806 Japan Department of Physics Department of Information Artificial Intelligence and Data Science Cosmology Gravity and Astroparticle Physics Group Center for Theoretical Physics of the Universe Department of Physics Graduate School of Humanities and Sciences

We investigate the parametrized black hole quasinormal ringdown formalism, which is a robust framework used to analyze quasinormal modes in systems that closely resemble general relativity, paying particular attention to the higher overtones. We find that larger deviations from the general relativity case typically appear in the quasinormal frequencies for the higher overtones. This growing tendency for higher overtones can be understood using an analytical method, and its relations to previous works are briefly discussed. Our findings indicate that we can impose a strong constraint on gravity theories by considering the overtones of quasinormal modes.

关键词： Alternative gravity theories Classical black holes Fluids & classical fields in curved spacetime General relativity Gravitational waves

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Heterogeneous Information Network Embedding Based on Adaptive Meta-Schema Considering Relation Distinction and Semantic Preservation 19th

Heterogeneous Information Network Embedding Based on Adapti...

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19th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2024

作者： Wu, Ling Gao, Pingping Lu, Jinlu Guo, Kun Zhang, Qishan College of Computer and Data Science Fuzhou University Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350108 China Fuzhou350108 China Xianda College of Economics and Humanities Shanghai International Studies University Shanghai China

ISBN: (纸本)9789819623723

Many real-world networks can be treated as heterogeneous information networks (HINs) that consist of various types of nodes, like different proteins and molecules in biological networks and different authors and papers in citation networks. Multiple network data mining tasks can be conducted on HINs to capture the complex relationships between multi-type nodes. In recent years, random walk based HIN embedding has drawn increasing attention. Furthermore, the meta-path or meta-graph guided random walk is one of the most widely used techniques in HIN embedding methods. However, existing HIN embedding methods still face several difficulties. Firstly, the meta-paths or meta-graphs often need to be predefined, which relies heavily on domain knowledge and incomplete information coverage. Secondly, these methods treat all relations without distinction, which inevitably limits the capability of HIN embedding. Thirdly, they do not focus on preserving finer-grained meta-graph semantics. In this paper, a HIN embedding algorithm based on adaptive meta-schema considering relation distinction and semantic preservation (HINEAS) is proposed. In order to avoid the selection of meta-paths or meta-graphs, an adaptive meta-schema extraction is designed. In heterogeneous node sequence generation, a biased random walk strategy based on the adaptive meta-schema is presented to embed the different relationships’ influence. Finally, an enhanced embedding strategy based on semantic preservation of the adaptive meta-schema is proposed to effectively extract topology and preserve the meta-graph’s fine-grained semantics. Experiments on real-world datasets show that HINEAS significantly outperforms state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network embeddings

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Secure and Efficient Federated Multi-label Propagation via Secret Sharing 19th

Secure and Efficient Federated Multi-label Propagation via...

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19th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2024

作者： Guo, Chen Hu, Wenbin Xiang, Zhishang Dong, Shiyu Zhang, Qishan Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350108 China Fuzhou350108 China Xianda College of Economics & Humanities Shanghai International Studies University Shanghai China

ISBN: (纸本)9789819623723

The Multi-Label Propagation Algorithm (MLPA) identifies and reveals community structure by passing labels between network nodes, and is also suitable for dealing with complex networks with overlapping communities. Due to its flexibility and effectiveness, the algorithm has been successfully applied in a number of fields, including image segmentation, text classification, and bioinformatics. In today’s society where personal privacy protection is increasingly important, how to detect communities without revealing sensitive information has become a hot issue in the field of network analysis. Existing privacy-preserving multi-label propagation algorithms primarily rely on anonymization and homomorphic encryption techniques. While homomorphic encryption can protect privacy, the complex encryption and decryption processes incur significant computational costs, making it challenging to achieve efficient computation while ensuring accuracy and privacy. In this paper, we propose a Secure and Efficient Federated Multi-Label Propagation Algorithm (SEFMLPA) that combines an anonymization strategy with a secret sharing strategy, considering the attribute similarities between nodes to ensure privacy, accuracy, and efficiency. The experimental results indicate that SEFMLPA achieves an accuracy comparable to the latest algorithms and reduces runtime by 80%. These significant improvements validate the effectiveness and superiority of our approach. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Differential privacy

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The relationship between visual confirmation bias, belief consistency, and belief polarization

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Comprehensive Results in Social Psychology 2022年第1-3期6卷 1-38页

作者： Qu-Lee, Jennie Seidel, Brina Harel, Daphna Granot, Yael Balcetis, Emily Department of Psychology New York University New York NY United States Center for Data Science New York University New York NY United States Department of Applied Statistics Social Science and Humanities New York University New York NY United States Department of Psychology Smith College Massachusetts MA United States

Video evidence depicting physical altercations has polarized public opinions and courtroom decisions about social issues including race relations and police use-of-force, we believe, in part because of the way people process dynamic visual stimuli across repeated viewing opportunities. We reanalyzed two studies that covertly collected eye-tracking data to quantify and model visual confirmation bias (VCB)–the degree to which eye movements replicate previous patterns of looking across multiple viewing opportunities. We tracked the location of eye gaze when participants (N₁ = 320;N₂ = 212) watched the same video twice depicting an altercation between an officer and a civilian (Study 1) or a Black and a White actor (Study 2). In pilot tests, we provided evidence regarding the construct validity of statistical measures of concordance tracking similarities in where perceivers directed eye gaze across viewings as an index of VCB. In our pre-registered analytic plan, we used these metrics to probe for relationships with punishment decisions made about targets after the first and second viewings. Contrary to predictions, our pre-registered analyses found no associations between VCB, consistency, and polarization in punishment. We present exploratory analyses probing potential moderators of the association between VCB and these outcome measures. We offer practical suggestions for researchers measuring and modeling eye gaze during the presentation of dynamic stimuli across multiple viewings, particularly in the context of intergroup decision research. © 2022 European Association of Social Psychology.

关键词： belief consistency belief polarization Confirmation bias eye-tracking gaze similarity legal decisions

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Pilot test of the mutual assistance system using a wearable device for the elderly in WEB3.0 technology 14

Pilot test of the mutual assistance system using a wearable ...

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14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023

作者： Nakamura, Kenji Yamazaki, Keiichi Arano, Yusuke Yamazaki, Akiko Koga, Hiroshi Ohta, Naoya Mitsuhashi, Takuya Obinata, Hideru Ohyama, Yoshiaki Gunma University Center for Mathematics and Data Science Gunma Japan Saitama University Graduate School of Humanities and Social Sciences Saitama Japan Tokyo University of Technology Faculty of Media Studies Tokyo Japan Shinshu University School of Medicine Department of Dermatology Nagano Japan Gunma University Faculty of Engineering Gunma Japan Japan Advanced Institute of Science and Technology Division of Advanced Science and Technology Tokyo Japan Gunma University Graduate School of Medicine Gunma Japan Gunma University Hospital Innovative Medical Research Center Gunma Japan

ISBN: (纸本)9798350324228

Using wearable devices and WEB3.0 to make doctor-patient interaction smarter. The aging of the population and COVID-19 have placed a tremendous workload on the medical field. Traditional monitoring has been centralized, with healthcare professionals providing face-to-face care to all patients. This is where blockchain is utilized, where users themselves have data and monitor each other. Mutual monitoring of medical information on the blockchain creates a mutually supportive relationship where users themselves monitor each other. In this demonstration experiment, the system was introduced to six elderly people. This decentralized system in which users themselves monitor each other is called the Web3 type. The Web type is a technology that is expected to break through the current concentration of data in overseas digital industries and leave digital data resources in Japan. This research is unique in that it combines blockchain technology, which is at the core of this technology, with medical information. A mutual assistance system was constructed to visualize and mutually monitor their exercise habits using wearable terminals. As a result, the exercise habits of all participants improved, and unique information was obtained from the questionnaire survey. © 2023 IEEE.

关键词： Blockchain

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Society with Trust: A Scientometrics Review of Zero-Knowledge Proof Advanced Applications in Preserving Digital Privacy for Society 5.0 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Dominic, Nicholas Pratama, Naufal Rizqi Cornelius, Kenny Senewe, Shavellin Herliman Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Universitas Multimedia Nusantara Tangerang15111 Indonesia Psychology Department Faculty of Humanities Bina Nusantara University Jakarta11480 Indonesia BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Society 5.0 focuses on human productivity in the midst of advanced technological services. While the concept has human trust at its core, technology development is now leading to zero-trust architecture. In this scientometrics review, 107 selected papers were analyzed to obtain the nature of the Zero-knowledge Proof (ZKP) theory and its advanced applications to favor digital privacy in greater society. With the common literature review strategy, it was found that the most citations in this field appeared in 2018, with IEEE, Springer, and Elsevier as the top three publishers. By affiliations, China and United States are both leading countries where the researcher comes from. And as the positive trend emerged, the ZKP mechanism will keep being leveraged as one of the cryptographic toolsets in the cloud services, Internet of Things (IoT), smart contracts, healthcare, electronic systems, and many other industrial needs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Smart contract

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Recognizing modern Japanese magazines by combining Deep Learning with language models 13

Recognizing modern Japanese magazines by combining Deep Lear...

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13th International Conference Knowledge and Systems Engineering, KSE 2021

作者： Nguyen, Nhan Thien Nguyen, Dang Minh Le, Anh Duc Quan, Tho Thanh University of Technology Vietnam National University Hcmc Faculty of Computer Science and Engineering Ho Chi Minh Viet Nam Center for Open Data in the Humanities Tokyo Japan

ISBN: (纸本)9781665499750

As one of the most culturally rich countries globally, Japan also has a rich history of magazines. In modern Japanese magazines, which were published during the 19-20th centuries, Japanese usage is similar to the current style of the contemporary Japanese language. However, most of those documents are not digitized but stored as images. Due to their importance to Japanese culture, history, and other socio-scientific topics, the problem of using computers to help identify these image-based modern magazines has been investigated from research and widely disseminated through the use of different methods in Deep Learning. However, these methods are still limited to achieve strong performance in recognizing handwriting images, especially uncommon Kanji characters. In this research, we address this problem by developing a deep learning-based language model and integrating it into the current OCR system for modern Japanese magazine documents. We also propose a combination strategy between the current Japanese OCR tool and our language model. The strategy will learn where the system should rely on OCR (e.g., Hiragana and Common kanji characters recognized correctly by OCR) or language model (uncommon Kanji characters are frequently recognized incorrectly by OCR, the system should rely on the language model). Our method enjoys visible improvement once experimented with real data. © 2021 IEEE.

关键词： Optical character recognition

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Multiloop Incremental Bootstrapping for Low-Resource Machine Translation 19

Multiloop Incremental Bootstrapping for Low-Resource Machine...

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19th Machine Translation Summit, MT Summit 2023

作者： Liu, Wuying Li, Wei Wang, Lin Shandong Key Laboratory of Language Resources Development and Application Ludong University Yantai264025 China Center for Linguistics and Applied Linguistics Guangdong University of Foreign Studies Guangzhou510420 China School of Computer and Big Data Science Jiujiang University Jiujiang332005 China Xianda College of Economics and Humanities Shanghai International Studies University Shanghai200083 China

Due to the scarcity of high-quality bilingual sentence pairs, some deep-learning-based machine translation algorithms cannot achieve better performance in low-resource machine translation. On this basis, we are committed to integrating the ideas of machine learning algorithm improvement and data augmentation, propose a novel multiloop incremental bootstrapping framework, and design the corresponding semi-supervised learning algorithm. This framework is a meta-frame independent of specific machine translation algorithms. This algorithm makes full use of bilingual seed data of appropriate scale and super-large-scale monolingual data to expand bilingual sentence pair data incrementally, and trains machine translation models step by step to improve the translation quality. The experimental results of neural machine translation on multiple language pairs prove that our proposed framework can make use of continuous monolingual data to raise itself. Its effectiveness is not only reflected in the easy implementation of state-of-the-art low-resource machine translation, but also in the practical option to quickly establish precise domain machine translation systems. © 2023 The authors. This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0)

关键词： Learning algorithms

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Sentiment Analysis of Movie Review using Hybrid Optimization with Convolutional Neural Network in English Language 3

Sentiment Analysis of Movie Review using Hybrid Optimization...

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3rd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2023

作者： Tidake, Vishal M. Mazumdar, Nilanjan Suresh Kumar, A. Nageswara Rao, B. Fatma, Gulnaz Infant Raj, I. Kiran Bala, B. Savitribai Phule Pune University Sanjivani College of Engineering India University of Science and Technology Department of Business Administration Meghalaya India Computer Science and Engineering Coimbatore India Lendi Institute of Engineering and Technology Jonnada Department of Science and Humanities Vizinagaram535005 India Center Jazan University Dept of English Language Jazan Saudi Arabia K.Ramakrishnan College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy India K.Ramakrishnan College of Engineering Department of Artificial Intelligence and Data Science Tamil Nadu Trichy India

ISBN: (纸本)9781665462167

There seems to be a growing amount of user-generated material online as more people become familiar with the Internet. Understanding hidden thoughts, emotions, and attitudes in tweets, emails, comments, and reviews is difficult yet essential for market analysis, brand tracking, social media tracking, and customer support. Sentiment Analysis (SA) identifies the emotional undertone of a string of words and also might basically be employed to comprehend a user's attitude, thoughts, and emotions. The Harris Hawks Optimization - Sparrow S earch Algorithm with Convolutional Neural Network i.e., (HH-SSA-CNN) proposed in this study is an innovative SA algorithm. Pre-processing, sentiment categorization, and feature extraction make up the procedure. The preprocessing phase removes the unwanted info from input text evaluations using NLP algorithms. A hybrid technique that combines review-related features and aspect-related features has been presented for efficiently retrieving the features. This method creates unique composite features for every review. The created HH- SSA-CNN is used to accomplish sentiment categorization. This approach has been used in the IMDb dataset. To assess the model's efficacy, the outcomes of the HH-SSA-CNN model are contrasted with those of alternative methodologies. The result indicates that the developed model accurately classifies the sentiments while compared to other existing methods. © 2023 IEEE.

关键词： Sentiment analysis

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Introduction to Machine Learning with Robots and Playful Learning 35

Introduction to Machine Learning with Robots and Playful Lea...

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35th AAAI Conference on Artificial Intelligence, AAAI 2021

作者： Olari, Viktoriya Cvejoski, Kostadin Eide, Øyvind Department for Digital Humanities University of Cologne Cologne50923 Germany Fraunhofer IAIS Sankt Augustin53757 Germany Center for Data and Simulation Science University of Cologne Cologne50923 Germany

ISBN: (纸本)9781713835974

Inspired by explanations of machine learning concepts in children's books, we developed an approach to introduce supervised, unsupervised, and reinforcement learning using a block-based programming language in combination with the benefits of educational robotics. Instead of using blocks as high-end APIs to access AI cloud services or to reproduce the machine learning algorithms, we use them as a means to put the student "in the algorithm's shoes." We adapt the training of neural networks, Q-learning, and k-means algorithms to a design and format suitable for children and equip the students with hands-on tools for playful experimentation. The children learn about direct supervision by modifying the weights in the neural networks and immediately observing the effects on the simulated robot. Following the ideas of constructionism, they experience how the algorithms and underlying machine learning concepts work in practice. We conducted and evaluated this approach with students in primary, middle, and high school. All the age groups perceived the topics to be very easy to moderately hard to grasp. Younger students experienced direct supervision as challenging, whereas they found Q-learning and k-means algorithms much more accessible. Most high-school students could cope with all the topics without particular difficulties. Copyright © 2021, Association for the Advancement of Artificial Intelligence (***). All rights reserved

关键词： Students

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