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arXiv 2021年

作者： Martínez-Gallego, Kevin Álvarez-Ortiz, Andrés M. Arias-Londoño, Julián D. Intelligent Information Systems Lab Universidad de Antioquia Calle 67 No. 53 - 108 Medellín050010 Colombia Intelligent Information Systems Lab Dpt. of Systems Engineering and Computer Science Universidad de Antioquia Calle 67 No. 53 - 108 Medellín050010 Colombia

This paper addresses the problem of fake news detection in Spanish using Machine Learning techniques. It is fundamentally the same problem tackled for the English language;however, there is not a significant amount of publicly available and adequately labeled fake news in Spanish to effectively train a Machine Learning model, similarly to those proposed for the English language. Therefore, this work explores different training strategies and architectures to establish a baseline for further research in this area. Four datasets were used, two in English and two in Spanish, and four experimental schemes were tested, including a baseline with classical Machine Learning models, trained and validated using a small dataset in Spanish. The remaining schemes include state-of-the-art Deep Learning models trained (or fine-tuned) and validated in English, trained and validated in Spanish, and fitted in English and validated with automatic translated Spanish sentences. The Deep Learning architectures were built on top of different pre-trained Word Embedding representations, including GloVe, ELMo, BERT, and BETO (a BERT version trained on a large corpus in Spanish). According to the results, the best strategy was a combination of a pre-trained BETO model and a Recurrent Neural Network based on LSTM layers, yielding an accuracy of up to 80%;nonetheless, a baseline model using a Random Forest estimator obtained similar outcomes. Additionally, the translation strategy did not yield acceptable results because of the propagation error;there was also observed a significant difference in models performance when trained in English or Spanish, mainly attributable to the number of samples available for each language. Copyright © 2021, The Authors. All rights reserved.

关键词： Embeddings

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Learning System Based on Contextual Awareness for Clinical Practice in Nursing Courses

Learning System Based on Contextual Awareness for Clinical P...

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International Conference on Advanced Learning Technologies (ICALT)

作者： Jorge Gómez Gómez J.F. Huete Velssy Hernandez Riaño Department of Systems Engineering - Research Group GNOCIX Universidad del Sinu-Monteria Colombia Dpt. Computer Science and Artificial Intelligence University of Granada-CITIC_UGR Spain Research Group SOCRATES Universidad de Cordoba-Monteria Colombia

The ubiquitous learning is used as a means of supporting teaching processes by means of the use of mobile and wireless communication technologies, sensors and tracking mechanisms / tracking, working together to integrate students with their environment. The process of clinical learning for nursing students may be the main cause of increased stress on teachers and students, given the problematic nature of the patients. This paper presents an ubiquitous learning system based on active learning methodology that provides context awareness support for nursing courses. An experiment with control and experimental groups with nursing students demonstrates that for theoretical concepts to be successfully transferred into practice, the context of practice needs to be considered.

关键词： Medical services Context Education Mobile communication Learning systems Mobile handsets Personal digital assistants

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Pattern-based Transformation of Diagrammatic Conceptual Models for Semantic Enrichment in the Web of Data

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Procedia computer science 2015年 60卷 150-159页

作者： Robert Andrei Buchmann Dimitris Karagiannis Business Information Systems Dpt. Faculty of Economic Sciences and Business Administration University Babeş Bolyai str. T. Mihali 58-60 400591 Cluj Napoca Romania Knowledge Engineering Research Group Faculty of Computer Science University of Vienna Waehringerstr. 29 1090 Vienna Austria

The goal of this paper is to bridge the paradigms of Linked Data and Conceptual Modeling, which have been developed from quite distinct concerns, although certain opportunities may stimulate the evolution of the Web towards a new type of knowledge space driven by diagrammatic models. To this end, the work at hand investigates structural patterns in a multitude of modeling languages accumulated over time within the Open Model Initiative Laboratory and defines for each pattern transformation rules that produce graph-based model serializations, thus enabling the processing of diagrammatic models using the Web of Data tech-nological space and practices.

关键词： Web of Data Conceptual Modeling Linked Data Graph databases

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Robust Voltage Control in DC Networks with Uncertain Nonlinear Load Dynamics

Robust Voltage Control in DC Networks with Uncertain Nonline...

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IEEE Conference on Decision and Control

作者： Amirreza Silani Giacomo Casadei Michele Cucuzzella Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen AG Groningen The Netherlands Control & Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Laboratoire Ampere Dpt. EEA of the Ecole Centrale de Lyon Université de Lyon Ecully France Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

In this letter, we propose a control scheme for regulating the voltage in Direct Current (DC) power networks. In contrast with other works in the literature where the loads are assumed to be constant, we consider uncertain time-varying loads described as the outputs of nonlinear dynamical exosystems with uncertain parameters. Based on the output regulation methodology, the proposed control scheme ensures the robust stability of the overall network and achieves voltage regulation in presence of impedance (Z), current (I), and power (P) loads. The simulation results illustrate excellent performance of the proposed control scheme.

关键词： Robust stability Simulation Regulation Impedance Voltage control

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The MPEG-7 query format: a new standard in progress for multimedia query by content

The MPEG-7 query format: a new standard in progress for mult...

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International Symposium on Communications and Information Technologies (ISCIT)

作者： Kevin Adistambha Mario Doeller Ruben Tous Matthias Gruhne Masanori Sano Chrisa Tsinaraki Stavros Christodoulakis Kyoungro Yoon Christian H. Ritz Ian S. Burnett School of Electrical Computer and Telecommunications Engineering University of Wollongong Australia Department Distributed Information Technology University of Passau Passau Germany Dpt. d'Arquitectura de Computadors Universitat Poliltècnica de Catalunya Barcelona Spain Department Metadata Fraunhofer IDMT Germany NHK Science and Technology Research Laboratories Japan Laboratory of Distributed Multimedia Information Systems & Applications Technical University of Crete Greece School of Computer Science and Engineering Konkuk University Seoul South Korea

In recent years, the amount of Internet accessible digital audiovisual media files has vastly increased. Therefore the need to describe the media (by way of metadata) has also increased significantly. MPEG-7 (finalized in 2001) provides a comprehensive and rich metadata standard for the description of multimedia content. Unfortunately, a standardized query format does not exist for MPEG-7, or other multimedia metadata. Such a standard would provide for communications between querying clients and databases, supporting cross-modal and cross-media retrieval. The lSO/lEC SC29WG11 committee decided therefore to contribute to this application space by adding such functionality as a new part of the MPEG-7 series of standards. In response to a Call for Proposals, six proposals were submitted. This paper describes the strengths of each proposal as well as the resulting draft standard for the MPEG-7 query format.

关键词： MPEG 7 Standard Multimedia databases Electronic mail Proposals Database languages Multimedia systems Telecommunication computing Identity-based encryption ISO IEC

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External localization system for mobile robotics

External localization system for mobile robotics

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International Conference on Advanced Robotics (ICAR)

作者： Tomáš Krajník Matías Nitsche Jan Faigl Tom Duckett Marta Mejail Libor Přeučil University of Lincoln Lincoln Lincolnshire GB Lab. of Robotics and Emb. Systems Univ. of Buenos Aires Argentina Dpt. of Computer Science and Engineering FEE Czech Technical Univ. in Prague Lincoln Centre for Autonomous Systems Univ. of Lincoln United Kingdom Intelligent and Mobile Robotics Group FEE Czech Technical Univ. in Prague

We present a fast and precise vision-based software intended for multiple robot localization. The core component of the proposed localization system is an efficient method for black and white circular pattern detection. The method is robust to variable lighting conditions, achieves sub-pixel precision, and its computational complexity is independent of the processed image size. With off-the-shelf computational equipment and low-cost camera, its core algorithm is able to process hundreds of images per second while tracking hundreds of objects with millimeter precision. We propose a mathematical model of the method that allows to calculate its precision, area of coverage, and processing speed from the camera's intrinsic parameters and hardware's processing capacity. The correctness of the presented model and performance of the algorithm in real-world conditions are verified in several experiments. Apart from the method description, we also publish its source code; so, it can be used as an enabling technology for various mobile robotics problems.

关键词： Cameras Three-dimensional displays Robots Mathematical model Estimation Equations Detectors

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BACH: grand challenge on breast cancer histology images

arXiv

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arXiv 2018年

作者： Aresta, Guilherme Araújo, Teresa Kwok, Scotty Chennamsetty, Sai Saketh Safwan, Mohammed Alex, Varghese Marami, Bahram Prastawa, Marcel Chan, Monica Donovan, Michael Fernandez, Gerardo Zeineh, Jack Kohl, Matthias Walz, Christoph Ludwig, Florian Braunewell, Stefan Baust, Maximilian Vu, Quoc Dang Nhat To, Minh Nguyen Kim, Eal Kwak, Jin Tae Galal, Sameh Sanchez-Freire, Veronica Brancati, Nadia Frucci, Maria Riccio, Daniel Wang, Yaqi Sun, Lingling Ma, Kaiqiang Fang, Jiannan Kone, Ismael Boulmane, Lahsen Campilho, Aurélio Eloy, Catarina Polónia, António Aguiar, Paulo INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal Faculty of Engineering of University of Porto Porto4200-465 Portugal Seek AI Limited Hong Kong Bangalore India Gurgaon India Chennai India Center for Computational and Systems Pathology Dpt. of Pathology Icahn School of Medicine at Mount Sinai Mount Sinai Hospital New York United States Konica Minolta Laboratory Europe Munich Germany Institute of Pathology Faculty of Medicine LMU Munich Munich Germany Department of Computer Science and Engineering Sejong University Seoul05006 Korea Republic of Chicago IL United States Naples Italy University of Naples "Federico II" Naples Italy Key Laboratory of RF Circuits and Systems Ministry of Education Hangzhou Dianzi University Hangzhou310018 China Zhejiang Provincial Laboratory of Integrated Circuits Design Hangzhou Dianzi University Hangzhou310018 China p2MIA Research Group LEM2A Lab Faculté des Sciences Université Moulay Ismail Meknes Morocco qLaboratório de Anatomia Patológica Ipatimup Diagnósticos Rua Júilio Amaral de Carvalho 45 Porto4200-135 Portugal Faculdade de Medicina Universidade do Porto Alameda Prof Hernâni Monteiro Porto4200-319 Portugal Universidade do Porto Rua Alfredo Allen 208 Porto4200-135 Portugal Universidade do Porto Rua Alfredo Allen 208 Porto4200-135 Portugal

Breast cancer is the most common invasive cancer in women, affecting more than 10% of women worldwide. Microscopic analysis of a biopsy remains one of the most important methods to diagnose the type of breast cancer. This requires specialized analysis by pathologists, in a task that i) is highly time- and cost-consuming and ii) often leads to nonconsensual results. The relevance and potential of automatic classification algorithms using hematoxylin-eosin stained histopathological images has already been demonstrated, but the reported results are still sub-optimal for clinical use. With the goal of advancing the state-of-the-art in automatic classification, the Grand Challenge on BreAst Cancer Histology images (BACH) was organized in conjunction with the 15th International Conference on Image Analysis and Recognition (ICIAR 2018). BACH aimed at the classification and localization of clinically relevant histopathological classes in microscopy and whole-slide images from a large annotated dataset, specifically compiled and made publicly available for the challenge. Following a positive response from the scientific community, a total of 64 submissions, out of 677 registrations, effectively entered the competition. The submitted algorithms improved the state-of-the-art in automatic classification of breast cancer with microscopy images to an accuracy of 87%. Convolutional neuronal networks were the most successful methodology in the BACH challenge. Detailed analysis of the collective results allowed the identification of remaining challenges in the field and recommendations for future developments. The BACH dataset remains publicly available as to promote further improvements to the field of automatic classification in digital pathology. Copyright © 2018, The Authors. All rights reserved.

关键词： Neurons

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