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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Pei-Wei Tsai Jing Zhang Yao He Jui-Fang Chang Li-Hui Yang Wein-Duo Yang College of Information Science and Engineering Fujian Provincial Key Lab. of Big Data Mining & Apps. Fujian University of Technology Fuzhou China Department of International Business National Kaohsiung University of Applied Science Kaohsiung Taiwan

ISBN: (纸本)9781509042418

Taiwanese economy is extremely export-oriented. However, Taiwan also starts to actively look for opportunities for participation, because of the slowdown of multinational liberalizations, and as a result of the advance of the regional economic integration trend. As an example, Taiwan vigorously participates in FTAs with countries in Asia and Central America. International economic conditions are significantly important to the international trade and the volume of export/import volume, which is affected by the foreign exchange rate. If contemporary researchers could take full advantage of the exchange rate forecasting, Taiwan could maximize its trade surplus, thus boosting the economic growth. Conventional foreign exchange rate forecasting is usually provided by analyzing many financial indices or with the time-series method. Our goal is to produce the foreign exchange rate forecasting result by the robotic way with an evolutionary computing method called Interactive Artificial Bee Colony algorithm. Based on the event study methodology, the selected agreements include four FTA that are ECFA, BIA, ASTEP and ANZTEC, and the observation period setting is 70 days of pre-event period and 70 days of post-event period. This paper uses time series model (GARCH, EGARCH) and Interactive artificial bee colony (IABC) to establish the exchange rate predicting models. In addition, we adopt Mean Absolutely Percentage Error (MAPE) to compare the accuracy of exchange rate prediction. There are many exchange rate predicting models and the most frequently one to conduct maybe the time series model. This research reveals that even the IABC is relatively new it is the model has the best predictive ability among all the models.

关键词： Exchange rates Predictive models Forecasting Mathematical model Time series analysis

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Thermodynamic and Kinetic Fragility of Freon 113: The Most Fragile Plastic Crystal

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Physical Review Letters 2017年第10期118卷 105701-105701页

作者： A. Vispa M. Romanini M. A. Ramos L. C. Pardo F. J. Bermejo M. Hassaine A. I. Krivchikov J. W. Taylor J. Ll. Tamarit Grup de Caracterització de Materials Departament de Física EEBE and Barcelona Research Center in Multiscale Science and Engineering Eduard Maristany 10-14 08019 Barcelona Catalonia Spain Laboratorio de Bajas Temperaturas Departamento de Física de la Materia Condensada Condensed Matter Physics Center (IFIMAC) and Instituto Nicolás Cabrera Universidad Autónoma de Madrid Francisco Tomás y Valiente 7 28049 Madrid Spain Instituto de Estructura de la Materia CSIC Serrano 123 28006 Madrid Spain B. Verkin Institute for Low Temperature Physics and Engineering of NAS Ukraine 47 Science Avenue 61103 Kharkov Ukraine Rutherford Appleton Lab ISIS Facility Didcot OX11 0QX Oxon England and European Spallation Source Data management and software centre COBIS Copenhagen 2200 Denmark

We present a dynamic and thermodynamic study of the orientational glass former Freon 113 (1,1,2-trichloro-1,2,2-trifluoroethane, CCl2F−CClF2) in order to analyze its kinetic and thermodynamic fragilities. Freon 113 displays internal molecular degrees of freedom that promote a complex energy landscape. Experimental specific heat and its microscopic origin, the vibrational density of states from inelastic neutron scattering, together with the orientational dynamics obtained by means of dielectric spectroscopy have revealed the highest fragility value, both thermodynamic and kinetic, found for this orientational glass former. The excess in both Debye-reduced specific heat and density of states (boson peak) evidences the existence of glassy low-energy excitations. We demonstrate that early proposed correlations between the boson peak and the Debye specific heat value are elusive as revealed by the clear counterexample of the studied case.

关键词： Thermodynamics Dynamical systems Glassy systems Dielectric spectroscopy

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Self-Grouping Multi-network Clustering

Self-Grouping Multi-network Clustering

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IEEE International Conference on data Mining (ICDM)

作者： Jingchao Ni Wei Cheng Wei Fan Xiang Zhang Department of Electrical Engineering and Computer Science Case Western Reserve University NEC Laboratories America Baidu Research Big Data Lab College of Information Sciences and Technology Pennsylvania State University

ISBN: (纸本)9781509054749

Joint clustering of multiple networks has been shown to be more accurate than performing clustering on individual networks separately. Many multi-view and multi-domain network clustering methods have been developed for joint multi-network clustering. These methods typically assume there is a common clustering structure shared by all networks, and different networks can provide complementary information on this underlying clustering structure. However, this assumption is too strict to hold in many emerging real-life applications, where multiple networks have diverse data distributions. More popularly, the networks in consideration belong to different underlying groups. Only networks in the same underlying group share similar clustering structures. Better clustering performance can be achieved by considering such groups differently. As a result, an ideal method should be able to automatically detect network groups so that networks in the same group share a common clustering structure. To address this problem, we propose a novel method, ComClus, to simultaneously group and cluster multiple networks. ComClus treats node clusters as features of networks and uses them to differentiate different network groups. Network grouping and clustering are coupled and mutually enhanced during the learning process. Extensive experimental evaluation on a variety of synthetic and real datasets demonstrates the effectiveness of our method.

关键词： Clustering methods Tensile stress Measurement Symmetric matrices Conferences data mining Electrical engineering

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Constraint Free Preference Preserving Hashing for Fast Recommendation

Constraint Free Preference Preserving Hashing for Fast Recom...

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IEEE Global Communications Conference

作者： Yan Zhang Guowu Yang Defu Lian Hong Wen Jinsong Wu Center for Cyber Security University of Electronic Science and Technology of China Big Data Research Center University of Electronic Science and Technology of China National Key Lab of Commun. University of Electronic Science and Technology of China Department of Electrical Engineering Universidad de Chile

ISBN: (纸本)9781509013296

Recommender systems have been widely used to deal with information overload, by suggesting relevant items that match users' personal interest. One of the most popular recommendation techniques is matrix factorization (MF). The inner products of learned latent factors between users and items can estimate users' preferences for items with high accuracy, but the preferences ranking is time consuming. Thus, hashing-based fast search technologies were exploited in recommender systems. However, most previous approaches consist of two stages: continuous latent factor learning and binary quantization, but they didn't well deal with the change of inner product arising from quantization. To this end, in this paper, we propose a constraint free preference preserving hashing method, which quantizes both norm and similarity in dot product. We also design an algorithm to optimize the bit length for norm quantization. The performance of our method is evaluated on three real world datasets. The results confirm that the proposed model can improve recommendation performance by 11%-15%, as compared with the state-of-the-art hashing approaches.

关键词： Recommender system Preference ranking Nor-m quantization Optimal bit Recommender systems Dot product Quantization hashing Preferences User preferences preference Consumers

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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Computational analysis of the structural properties of economic and financial networks

arXiv

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arXiv 2017年

作者： Emmert-Streib, Frank Musa, Aliyu Baltakys, Kestutis Kanniainen, Juho Tripathi, Shailesh Yli-Harja, Olli Jodlbauer, Herbert Dehmer, Matthias Predictive Medicine and Data Analytics Lab Department of Signal Processing Tampere University of Technology Finland Institute of Biosciences and Medical Technology Tampere Finland Industrial and Information Management Tampere University of Technology Tampere Finland Institute for Systems Biology Seattle United States Institute for Intelligent Production Faculty for Management University of Applied Sciences Upper Austria Steyr Campus Austria Department for Biomedical Computer Science and Mechatronics UMIT - The Health and Lifesciences University Hall in Tyrol Austria College of Computer and Control Engineering Nankai University Tianjin300350 China

In recent years, methods from network science are gaining rapidly interest in economics and finance. A reason for this is that in a globalized world the interconnectedness among economic and financial entities are crucial to understand and networks provide a natural framework for representing and studying such systems. In this paper, we are surveying the use of networks and network-based methods for studying economy related questions. We start with a brief overview of graph theory and basic definitions. Then we discuss descriptive network measures and network complexity measures for quantifying structural properties of economic networks. Finally, we discuss different network and tree structures as relevant for applications. Copyright © 2017, The Authors. All rights reserved.

关键词： Finance

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LRI: A LOW RANK APPROACH TO NON-LOCAL SPARSE REPRESENTATION FOR IMAGE INTERPOLATION

LRI: A LOW RANK APPROACH TO NON-LOCAL SPARSE REPRESENTATION ...

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International Joint Conference on Neural Networks

作者： Mingli Zhang Qiang Qu Sadegh Nobari Christian Desrosiers Software and IT Engineering école de Technologie Supérieure Montreal Canada H3C 1K3 Data Science and Information Systems (Dainfos) Lab Innopolis University Russia

ISBN: (纸本)9781509006212

The sparse representation models for image super-resolution have shown great potential in various imaging and vision tasks. However, most of them are challenged by the accuracy issue especially when images are significantly down-sampled. In this paper, we aim to improve the performance of sparse representation. We propose to incorporate a low rank approach into image non-local sparse representation model. To the best of our knowledge, this is the first work to integrate low rank approaches into non-local spare representation for image interpolation. The proposed method can obtain good estimation of sparse coefficients of original images. Experimental results show the effectiveness of our proposed method compared with the state-of-the-art.

关键词： Mathematical model Image reconstruction Image resolution Interpolation Dictionaries Artificial neural networks Estimation

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Knowledge graph embedding translation based on constraints

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Journal of Information Hiding and Multimedia Signal Processing 2017年第5期8卷 1119-1131页

作者： Wu, Yunbing Pan, Jengshyang Lu, Ping Lin, Kaibiao Yu, Xiaoyan College of Mathematics and Computer Science Fuzhou University No.2. Xueyuan Road University Town Minhou Fuzhou CityFujian Province350116 China Fujian Provincial Key Lab of Big Data Mining and Applications Fujian University of Technology No.3. Xueyuan Road University Town Minhou Fuzhou CityFujian Province350118 China Department of Business Xiamen University of Technology No.600 Ligong Road Jimei District XiamenFujian Province361024 China School of Computer and Information Engineering Xiamen University of Technology No.600 Ligong Road Jimei District XiamenFujian Province361024 China

Knowledge graph reasoning is discovering new entity relations by computing and inference from existing relations. However, most reasoning models of translation embedding-based knowledge graphs have not considered the semantic-type constraints of relations in the construction of corrupted triplets. Hence, the constructed corrupted triplets may not conform to the actual semantic information and may, thus, significantly affect the prediction accuracy of the model. Therefore, we propose a constraint-based embedding model in this paper. First, the model establishes the head and tail entity set for each relationship. Then, it ensures that both the replacing head and tail entities in the corrupted triplet belong to the respective entity set so that the corrupted triplets that do not conform to the responding semantic relations are excluded. To evaluate the proposed model, we conduct link prediction and triple classification on WordNet and Freebase databases. The experimental results show that our method remarkably improves the performance compared to several state-of-the-art baselines. © 2017, Ubiquitous International. All rights reserved.

关键词： Classification (of information)

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ACID encountering the CAP theorem: Two bank case studies 12

ACID encountering the CAP theorem: Two bank case studies

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12th Web Information System and Application Conference, WISA 2015

作者： Kong, Chao Gao, Ming Qian, Weining Zhou, Minqi Gong, Xueqing Zhang, Rong Zhou, Aoying Institute for Data Science and Engineering and Shanghai Key Lab for Trustworthy Computing East China Normal University Shanghai China

ISBN: (纸本)9781467393720

In the era of big data, we may adopt the distributed architecture for a transaction processing system due to some reasons, including distributed branches, heavy demand and operational expenditure, etc. In terms of the CAP Theorem, a transaction processing system associated with ACID properties is infeasible to work well in the distributed architecture. It is indispensable to address how to make a trade-off between availability and partition tolerance for a bank as it favors the consistency in the distributed system. In this research, we conduct two case studies to address the question using two transaction logs collected from a bank in China. We mainly analyze the table dependency and the table concurrency, and find that (1) it is arduous to partition the data in the database system associated with ACID properties, (2) in-memory architecture for updating transactions may be an alternative for building a transaction processing system. © 2015 IEEE.

关键词： Memory architecture

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Searches After Gravitational-waves Using ARizona Observatories (SAGUARO): System Overview and First Results from Advanced LIGO/Virgo’s Third Observing Run

arXiv

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arXiv 2019年

作者： Lundquist, M.J. Paterson, K. Fong, W. Sand, D.J. Andrews, J.E. Shivaei, I. Daly, P.N. Valenti, S. Yang, S. Christensen, E. Gibbs, A.R. Shelly, F. Wyatt, S. Kuhn, O. Amaro, R.C. Arcavi, I. Behroozi, P. Butler, N. Chomiuk, L. Corsi, A. Drout, M.R. Egami, E. Fan, X. Foley, R.J. Frye, B. Gabor, P. Green, E.M. Grier, C.J. Guzman, F. Hamden, E. Howell, D.A. Jannuzi, B.T. Kelly, P. Milne, P. Moe, M. Nugent, A. Olszewski, E. Palazzi, E. Paschalidis, V. Psaltis, D. Reichart, D. Rest, A. Rossi, A. Schroeder, G. Smith, P.S. Smith, N. Spekkens, K. Strader, J. Stark, D.P. Trilling, D. Veillet, C. Wagner, M. Weiner, B. Wheeler, J.C. Williams, G.G. Zabludoff, A. Steward Observatory University of Arizona 933 North Cherry Avenue TucsonAZ85721-0065 United States Center for Interdisciplinary Exploration and Research in Astrophysics Department of Physics and Astronomy Northwestern University 2145 Sheridan Road EvanstonIL60208-3112 United States Hubble Fellow Department of Physics University of California 1 Shields Avenue DavisCA95616-5270 United States Department of Physics and Astronomy Galileo Galilei University of Padova Vicolo dell’Osservatorio 3 PadovaI-35122 Italy INAF Osservatorio Astronomico di Padova Vicolo dell’Osservatorio 5 PadovaI-35122 Italy Lunar and Planetary Lab Department of Planetary Sciences University of Arizona TucsonAZ85721 United States Large Binocular Telescope Observatory 933 North Cherry Avenue TucsonAZ United States School of Physics and Astronomy Tel Aviv University Tel Aviv69978 Israel School of Earth and Space Exploration Arizona State University TempeAZ85287 United States Center for Data Intensive and Time Domain Astronomy Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Department of Physics and Astronomy Texas Tech University Box 1051 LubbockTX79409-1051 United States Department of Astronomy and Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada Observatories of the Carnegie Institution for Science 813 Santa Barbara St. PasadenaCA91101 United States Department of Astronomy and Astrophysics University of California Santa CruzCA95064 United States Vatican Observatory Vatican City00120 Vat College of Optical Sciences University of Arizona 1630 E University Blvd TucsonAZ85719 United States Las Cumbres Observatory 6740 Cortona Drive Suite 102 GoletaCA93117-5575 United States College of Science & Engineering Minnesota Institute for Astrophysics University of Minnesota 115 Union St. SE MinneapolisMN55455 United States INAF - Osservatorio di Astrofisica e Scienza dello Spazio -

We present Searches After Gravitational-waves Using ARizona Observatories (SAGUARO), a comprehensive effort dedicated to the discovery and characterization of optical counterparts to gravitational wave (GW) events. SAGUARO utilizes ground-based facilities ranging from 1.5m to 10m in diameter, located primarily in the Northern Hemisphere. We provide an overview of SAGUARO’s telescopic resources, pipeline for transient detection, and database for candidate visualization. We describe SAGUARO’s discovery component, which utilizes the 5 deg2 field-of-view optical imager on the Mt. Lemmon 1.5m telescope, reaching limits of ≈ 21.3 AB mag while rapidly tiling large areas. We also describe the follow-up component of SAGUARO, used for rapid vetting and monitoring of Copyright © 2019, The Authors. All rights reserved.

关键词： Gravity waves

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