Calvo, R., Alamos, N., Huneeus, N., & O'Ryan, R. (2022). Energy poverty effects on policy-based PM2.5 emissions mitigation in southern and central Chile. Energy Policy, 161, 112762.
Abstract: Residential firewood burning is the main source of PM2.5 emissions in southern and central Chile. In Chile, approximately 4000 premature deaths are observed each year due to air pollution. Mitigation policies aim to reduce dwellings' energy demand and foster cleaner but more expensive energy sources. Pre-existing energy poverty conditions are often overlooked in these policies, even though they can negatively affect the adoption of these measures. This article uses southern and central Chile as a case study to assess quantitatively different policy scenarios of PM2.5 emissions between 2017 and 2050, considering energy poverty-related effects. Results show that PM2.5 emissions will grow 16% over time under a business as usual scenario. If thermal improvement and stove/heater replacements are implemented, PM2.5 reductions depend on the scale of the policy: a 5%-6% reduction of total southern and central Chile PM2.5 emissions if only cities with Atmospheric Decontamination Plans are included; a 54%-56% reduction of PM2.5 emissions if these policies include other growing cities. Our study shows that the energy poverty effect potentially reduces the effectiveness of these measures in 25%. Consequently, if no anticipatory measures are taken, Chile's energy transition goals could be hindered and the effectiveness of mitigation policies to improve air quality significantly reduced.
|
Villalon, J., & Calvo, R. A. (2011). Concept Maps as Cognitive Visualizations of Writing Assignments. Educ. Technol. Soc., 14(3), 16–27.
Abstract: Writing assignments are ubiquitous in higher education. Writing develops not only communication skills, but also higher-level cognitive processes that facilitate deep learning. Cognitive visualizations, such as concept maps, can also be used as part of learning activities including as a form of scaffolding, or to trigger reflection by making conceptual understanding visible at different stages of the learning process. We present Concept Map Miner (CMM), a tool that automatically generates Concept Maps from students' compositions, and discuss its design and implementation, its integration to a writing support environment and its evaluation on a manually annotated corpora of university essays (N=43). Results show that complete CM, with concepts and labeled relationships, are possible and its precision depends the level of summarization (number of concepts) chosen.
|
Villalon, J., & Calvo, R. A. (2013). A Decoupled Architecture for Scalability in Text Mining Applications. J. Univers. Comput. Sci., 19(3), 406–427.
Abstract: Sophisticated Text Mining features such as visualization, summarization, and clustering are becoming increasingly common in software applications. In Text Mining, documents are processed using techniques from different areas which can be very expensive in computation cost. This poses a scalability challenge for real-life applications in which users behavior can not be entirely predicted. This paper proposes a decoupled architecture for document processing in Text Mining applications, that allows applications to be scalable for large corpora and real-time processing. It contributes a software architecture designed around these requirements and presents TML, a Text Mining Library that implements the architecture. An experimental evaluation on its scalability using a standard corpus is also presented, and empirical evidence on its performance as part of an automated feedback system for writing tasks used by real students.
|
