Artículos de conferencia

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Browsing Artículos de conferencia by browse.metadata.fuente "Scopus"

Now showing 1 - 16 of 16
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    CAI Asynchronous Methodology for Emergency Remote Teaching: An Experience in Introduction to Programming
    (IEEE Computer Society, 2021) Muñoz Gama, Jorge; Salas-Morales J.; Herskovic V.
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    CLNews: The First Dataset of the Chilean Social Outbreak for Disinformation Analysis
    (Association for Computing Machinery, 2022) Providel, Eliana; Toro, Daniel; Riquelme, Fabián; Mendoza Rocha, Marcelo Gabriel; Puraivan, E.
    Disinformation is one of the main threats that loom on social networks. Detecting disinformation is not trivial and requires training and maintaining fact-checking teams, which is labor-intensive. Recent studies show that the propagation structure of claims and user messages allows a better understanding of rumor dynamics. Despite these findings, the availability of verified claims and structural propagation data is low. This paper presents a new dataset with Twitter claims verified by fact-checkers along with the propagation structure of retweets and replies. The dataset contains verified claims checked during the Chilean social outbreak, which allows for studying the phenomenon of disinformation during this crisis. We study propagation patterns of verified content in CLNews, showing differences between false rumors and other types of content. Our results show that false rumors are more persistent than the rest of verified contents, reaching more people than truthful news and presenting low barriers of readability to users. The dataset is fully available and helps understand the phenomenon of disinformation during social crises being one of the first of its kind to be released.
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    Development and Operationalisation of Local Sustainability Indicators - A Global South Perspective on Data Challenges and Opportunities for GIScience
    (Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 2023) Steiniger, Stefan; Rojas Quezada, Carolina Alejandra; Truffello Robledo, Ricardo Enrique; Barton Jonathan, Richard
    Evaluating and monitoring the sustainable development of nations and cities requires sets of indicators. Such indicator sets should measure equity, health, environmental, or governmental progress or recess - among other sustainability aspects. In 2015 the United Nations ratified 17 Sustainable Development Goals (SDG) assessed through 231 indicators. However, other - local - sets of indicators have been developed too. In this paper we review geodata challenges that emerged when we developed four sustainability indicator sets in Chile. Faced challenges include (geo)data availability and data representativeness, among others. We analyse how GIScience knowledge has contributed to indicator development and outline three priority research topics: (i) updating indicators based on automated processes, while respecting representativeness, (ii) tools for planning scenario generation, and (iii) methods for short- and long-term forecasting.
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    Economic and Environmental Impact of Military Electrical Vehicle Conversion and Solar Electricity Production
    (2020) Pierre Simon, François; Roberts, C.; Girard, Aymeric; Ordoñez, Javier; Rossel, G.S.; CEDEUS (Chile)
    Military vehicles carry out defence and training functions; however, they also participate extensively in military operations apart from war, such as supporting citizens in emergency situations. Nonetheless, they continue to contribute to pollution, and carbon emissions in Chile have doubled in recent years. Thus, this study seeks a partial solution to this problem, extending the useful life of an archetypal military vehicle, i.e. AIL Storm internal combustion engine vehicle (ICEV), 4.0L gasoline, through its conversion into an electric vehicle (EV) using lithium-ion batteries. AIL Storm ICE emissions are compared with an equivalent EV conversion prototype, analysing the CO emissions of the EV charged from the Chilean electricity grid or from a solar photovoltaic charging station, taking advantage of the high levels of solar radiation in Chile. This studied model obtains a travel cost of 0.04USD/km in the electric grid charge mode and 0.02USD/km in the Solar power station charge mode, affecting the environment with 155kgCO2 emissions per year of use. In the future, technologies to manufacture or assemble lithium batteries must be developed in the Chilean market. Given the availability of this mineral in Chile, this step would reduce costs and make electric mobility more attractive and affordable.
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    Exploring the Effects of Applying Learning Analytics for Teaching Procedural Skills in Health Sciences Education
    (2021) Villagrán I.
    © 2021 ACM.In Health Science Education (HSE), students must demonstrate technical skills in many procedures. However, traditional teaching methodologies limit the possibilities for personalized feedback from an instructor and generally do not allow students to achieve the required proficiency levels. Concerning this, technology has been installed as a learning resource with numerous benefits that allow new multidisciplinary lines of research, such as learning analytics (LA) and educational data mining (EDM). Both LA and EDM seek to improve educational practice based on the intensive use of educational data, such as analyzing online learning patterns, creating performance predictions, and incorporating artificial intelligence techniques. There is a range of possibilities in applying LA and EDM in teaching procedural skills that have not yet been explored. For this reason, this study aims to answer (1) How the educational data explain the development of procedural skills in virtual environments to support the teaching-learning process in Health Science Education?; and (2) How automatic feedback and adaptive personalization affect the performance and instructional design of the procedural skills learning process of health science students? We expect that this study contributes to the field of technical skills learning mediated by technology in higher education by using the data provided by the interaction of students with virtual resources to support educational decision-making and optimize the teaching and learning processes in HSE.
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    Inspecting the concept knowledge graph encoded by modern language models
    (Association for Computational Linguistics (ACL), 2021) Aspillaga, Carlos; Soto, Alvaro; Mendoza Rocha, Marcelo Gabriel
    The field of natural language understanding has experienced exponential progress in the last few years, with impressive results in several tasks. This success has motivated researchers to study the underlying knowledge encoded by these models. Despite this, attempts to understand their semantic capabilities have not been successful, often leading to non-conclusive, or contradictory conclusions among different works. Via a probing classifier, we extract the underlying knowledge graph of nine of the most influential language models of the last years, including word embeddings, text generators, and context encoders. This probe is based on concept relatedness, grounded on WordNet. Our results reveal that all the models encode this knowledge, but suffer from several inaccuracies. Furthermore, we show that the different architectures and training strategies lead to different model biases. We conduct a systematic evaluation to discover specific factors that explain why some concepts are challenging. We hope our insights will motivate the development of models that capture concepts more precisely.
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    Inspecting the concept knowledge graph encoded by modern language models
    (Association for Computational Linguistics (ACL), 2021) Aspillaga C.; Soto A.; Mendoza Rocha, Marcelo Gabriel
    © 2021 Association for Computational LinguisticsThe field of natural language understanding has experienced exponential progress in the last few years, with impressive results in several tasks. This success has motivated researchers to study the underlying knowledge encoded by these models. Despite this, attempts to understand their semantic capabilities have not been successful, often leading to non-conclusive, or contradictory conclusions among different works. Via a probing classifier, we extract the underlying knowledge graph of nine of the most influential language models of the last years, including word embeddings, text generators, and context encoders. This probe is based on concept relatedness, grounded on WordNet. Our results reveal that all the models encode this knowledge, but suffer from several inaccuracies. Furthermore, we show that the different architectures and training strategies lead to different model biases. We conduct a systematic evaluation to discover specific factors that explain why some concepts are challenging. We hope our insights will motivate the development of models that capture concepts more precisely.
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    Mathematics learning opportunities for students with learning disabilities at special schools
    (Psychology of Mathematics Education (PME), 2019) Martin, Constanza San; Rojas, Francico; Martinez, Maria; Ramirez, Chenda; Vega, Vanessa; Paniagua, Ximena
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    Recent Advances in Least-Squares and Discontinuous Petrov-Galerkin Finite Element Methods
    (De Gruyter, 2019) Bertrand F.; Demkowicz L.; Gopalakrishnan J.; Heuer N.
    © 2019 Walter de Gruyter GmbH, Berlin/Boston 2019.Least-squares (LS) and discontinuous Petrov-Galerkin (DPG) finite element methods are an emerging methodology in the computational partial differential equations with unconditional stability and built-in a posteriori error control. This special issue represents the state of the art in minimal residual methods in the L2-norm for the LS schemes and in dual norm with broken test-functions in the DPG schemes.
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    Retrofitting strategies for social housing buildings in different climate conditions.: The Corvi 1010-1020 block type in three Chilean cities
    (MDPI Open Access Journals, 2018) Bustamante Gómez, Waldo; Schmitt Rivera, Cristián; Bunster Milnes, Víctor Andrés; Martínez Torres, María Paula; Chateau Gannon, Francisco; CEDEUS (Chile)
    Currently, less than 2% of the residential building stock in Chile meets minimum of thermal performance conditions while the current approach to social housing development has proved incapable of ensuring appropriate living standards. Demolishing housing blocks to replace them with new buildings is economically inefficient, environmentally damaging and socially unacceptable, as these structures represent an opportunity to renovate and upgrade existing buildings without disrupting consolidated communities. This ongoing research focuses on renovating the CORVI 1010-1020 housing blocks, a building type that was massively built across the country between 1968 and 1978. Today it is possible to find more than 2,000 units of this type of building—with no significant design variations—throughout Chile, hence between latitudes 18°S and 53°S of extremely diverse climates. This paper analyses the impact of different energy retrofitting strategies in the thermal performance of these emblematic housing estates. Accordingly, building energy simulation is used to evaluate three scenarios, i.e., the original design without changes, a retrofitting proposal focused on meeting current thermal code requirements, and an expansion proposal aimed at increasing both thermal performance and life quality conditions. In order to assess the performance of these scenarios, the simulations focused on three cities with contrasting climatic conditions, i.e., hot-arid (Arica, 18°27'S), Mediterranean (Santiago, 33°27′S) and tundra (Punta Arenas, 53°08′S). Operational energy demand, accumulated hours of thermal discomfort, and payback time periods are considered for comparative analysis. Whereas the results evidence that the cost-effectiveness of the proposed alternatives increases in colder climatic conditions dependant on space heating; overall, this study demonstrates that the retrofitting of these social housing buildings can help achieving significant heating and cooling energy savings as well as improving indoor thermal comfort conditions.
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    REVIEW AND COMPARISON OF DIFFERENT TIMBER BUILDING PRODUCTS' EMBODIED EMISSIONS USING FREE DATABASES
    (World Conference on Timber Engineering, 2023) Victorero Castaño, Felipe Andrés; Mendez, Daniela; Bascuñan, Felipe; Bustamante Gómez, Waldo; CEDEUS (Chile)
    This paper aims to present a brief review of sources of information for studying the variability of embodied carbon emissions in structural wood products commonly used in construction. The review considered 13 primary sources, focused on EPDs and generic databases, and allowed the collection of data for the study of 140 products divided into Sawn lumber, Glulam, OSB, and Plywood. The information collected made it possible to identify factors such as the variability of density properties, wood species, the origin of the products, among others. In addition to analyzing the variations in the biogenic carbon of the different products studied. The results allow us to conclude that although the variability of wood products can be significant, like any product of natural origin, when they are studied within the framework of the analysis of the materials of a building, they can present a smaller fluctuation than other materials such as concrete. Moreover, this effect can be accentuated in wood products with greater density or have undergone processes that increase the mass of biogenic carbon per cubic meter in the final product.
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    Speakers counting by proposed nested microphone array in combination with limited space SRP
    (European Signal Processing Conference, EUSIPCO, 2021) Firoozabadi A.D.; Durney H.; Sanhueza M.; Irarrazaval P.; Adasme P.; Zabala-Blanco D.; Palacios-Jativa P.; Azurdia-Meza C.
    © 2021 European Signal Processing Conference. All rights reserved.In this paper, a novel method is presented for estimating the number of speakers based on the microphone arrays. Firstly, a 3D snowflake nested microphone array (SNMA) is proposed for recording the speech signals. In the following, the steered response power (SRP) algorithm is implemented on subbands in limited spaces conditions for all microphone pairs related to the subarrays. Therefore, a weighted averaging method is implemented on subband limited spaces SRPs (LSRP), and the final energy map is compared with the histogram of the maximums of the SRP function on different subbands for various time frames. The passed candidate points are categorized by unsupervised K-means clustering and the number of speakers is estimated by the silhouette criteria. The accuracy of the proposed method is compared with PENS, i-vector PLDA, and wavelet-GEVD algorithms. The results show the superiority of the proposed method in comparison with other previous research.
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    Three-dimensional sound source localization by distributed microphone arrays
    (European Signal Processing Conference, EUSIPCO, 2021) Firoozabadi A.D.; Durney H.; Sanhueza M.; Irarrazaval P.; Adasme P.; Zabala-Blanco D.; Palacios-Jativa P.; Azurdia-Meza C.
    © 2021 European Signal Processing Conference. All rights reserved.Multiple sound source localization (SSL) is one of the applicable and important areas in the speech signal processing. In this paper, a two-step method is proposed for multiple 3D SSL based on the time delay estimation (TDE) in combination with distributed microphone arrays (DMA). In the first step, the direction of speakers are estimated by the use of a circular microphone array (CMA) in the center of the room and implementing the generalized cross-correlation (GCC) function. In the second step, the distributed T-shaped microphone arrays on the walls are considered for 3D SSL. The two most closed T-shaped array to each speaker are selected, where one of them is used for horizontal and the other one for vertical direction of arrival (DOA) estimation by the use of generalized eigenvalue decomposition (GEVD) algorithm. The experiments on the simulated data for 2 and 3 simultaneous speakers show the superiority of the proposed distributed microphone array-direction of arrival estimators (DMA-DOAE) method in comparison with other previous works in noisy and reverberant environments.
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    VR-Based User Interactions to Exploit Infinite Space in Programming Activities
    (IEEE Computer Society, 2021) Segura Castillo, Víctor Stefano; Merino Del Campo, Leonel Alejandro; Hecht, Geoffrey; Bergel, Alexandre
    © 2021 IEEE.Virtual reality (VR) devices have now become a commodity, and as such, VR is percolating the traditional working environment of software programmers. Current approaches to use VR as the medium to immerse software programmers essentially project classical IDE windows in the virtual environment: the very same VSCode or IntelliJ window is seen through the VR device. As a consequence, the same constraints imposed by a physical screen are found in the VR environment, thus representing a missed opportunity. VRIDE is a new VR-based environment for object-oriented programming to let software developers carry out their activities in a full VR-based immersed environment. VRIDE innovates by offering interactions based on Code Cubes that are designed to exploit the infinite space in the VR environment. Through code cube interactions our approach disrupts the traditional mapping of windows from desktop to VR by supporting dedicated actions for navigation, inspection, and space management. Our prototype illustrates the feasibility of having a full-immersive virtual environment for software programmers.