Informes (Estadística e Investigación Operativa)
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Informe Exploratory analysis of the impact of humidity and temperature on human mortality(2025) Gómez Losada, Álvaro; Szewczyk, W.; Ciscar Martínez, J.C; Estadística e Investigación Operativa; FQM153: Estadística e Investigación OperativaThis study explores the relationship between temperature, humidity, and daily mortality in Brazil and Mexico, leveraging open mortality data and reanalyzed climatic records. Using descriptive analyses, empirical risk mapping, and statistical modeling, the research aimed to assess whether humidity modulates temperature-related mortality and to identify high-risk climatic conditions. Descriptive analyses suggested that mortality tends to increase with higher levels of temperature and humidity, particularly at sub-maximum values, with patterns that appeared consistent across regions and periods, underscoring the need to consider humidity when assessing temperature effects. Empirical risk maps identified specific high-risk combinations, such as high temperatures (31–36°C) and humidity (27–30 g/kg) in Brazil, and moderate conditions (15–20°C, 15–18 g/kg) in Mexico. Statistical modeling, including random forest and generalized linear models (GLMs), provided limited conclusive evidence, with median temperature occasionally highlighted as a significant predictor. Optimal lag analysis identified a consistent 3-day delay for Brazil and 10-day delay for Mexico, referring to the occurrence of mortality under specific climatic conditions. Additionally, the study evaluates the use of ChatGPT 4o as an aid in tasks related to research. While effective in programming, data processing, and communication, its scientific validation required critical supervision due to occasional errors and misinterpretationsInforme Artificial Intelligence at the JRC: 1st workshop on Artificial Intelligence at the JRC(2019-07-30) Nativi, Stefano; Gómez Losada, Álvaro; Estadística e Investigación Operativa; FQM153: Estadística e Investigación OperativaThis document presents the contributions presented at the first internal workshop on Artificial Intelligence (AI), organized by the Joint Research Centre (JRC) of the European Commission. This workshop was held on 23rd May at the premises of the JRC in Ispra (Italy), with video-conference to all JRC's sites. The workshop aimed to gather JRC specialists on AI to share their experience, to identify opportunities for meeting the EC demands on AI, and explore synergies among different JRC's working groups on AI. The full-day session workshop was organized around three main topical strands entitled Policy support, New Initiatives and Technology Development. Contributions covered a wide range of areas, including applications of AI to Cybersecurity, Transport, Environment, Health and other specific issues. This report is structured according to those main topics of study. According to the JRC Director General Vladimír Šucha: "The workshop was very stimulating and interesting presenting a broad spectrum of activities and competencies across JRC. It gave a great opportunity to build a strong and hopefully useful position in the field of AI/ML". While the first part of the workshop was mainly informative, in the second part we collectively discussed about JRC priorities and the set-up of a Community of Practice (now available at https://webgate.ec.europa.eu/connected/groups/community-of-practice-ai-and-big-data) dealing with AI and Big Data. Finally, the preliminary results of the online survey were presented. All colleagues were excellent in communicating their scientific activity in a flash and efficient way.Informe AI Watch - Evolution of the EU market share of Robotics(2023-04-14) Duch Brown, Néstor; Gómez Losada, Álvaro; Míguez, Sebastián; Rossetti, Fiammetta; Roy, Vincent van; Estadística e Investigación Operativa; FQM153: Estadística e Investigación OperativaThis report provides an overview of the robotics industry in Europe, as well as a description of the definitions, typologies and main differences between industrial and service robots. The aim is to build up a stronger and updated knowledge of research questions, approaches and data that scholars and policy makers could use to study robotics around the world, and more specifically in Europe. It also identifies the necessary actions to merge heterogeneous data into a meaningful and consistent dataset to estimate the EU shares of robotics from the demand and supply perspectives, and for both industrial and service robots. Complementing these data with other sources to enhance the value and significance of the overall estimation exercise of the EU robotics market shares, provides a comprehensive overview of the production and adoption sides for both industrial and service robots. The three main objectives of the report are: to build a dataset including the market shares of robots in the EU; to describe the main trends that can be extracted from data; and, to sketch a conceptual framework to contextualise the results from the first two objectives.Informe Data science applications to connected vehicles: Key barriers to overcome(2017) Gómez Losada, Álvaro; Estadística e Investigación Operativa; FQM153: Estadística e Investigación OperativaAs our environments become more connected in general, Intelligent Transportation Systems will play a central role in our cities and across borders, forming part of a new vision of “mobility as a service.” Connected vehicle technology, with a prominent role in Intelligent Transportation Systems, will be capable of generating huge amounts of pervasive and real time data, at very high frequencies. These streaming data are the common type of data produced by Connected vehicles, and their analysis is of paramount importance for applications improving road safety, effective service delivery, eco-driving, traffic regulation and pollution reduction. This study aims to characterize this type of data from an analytical perspective, as well as to pose the challenges Data science faces in extracting knowledge from them in real time. Data generated by sensors and actuators in Connected vehicles include noisy, anomalous, redundant, rapidly changing, correlated and heterogeneous data. In such a context, numerous techniques have been proposed to adapt the data analytics in batch learning to these new dynamic and evolving streaming data, which are produced in huge volumes and transmitted at high velocity. The Internet of Vehicles has the potential to provide a pervasive network of Connected vehicles, smart sensors and road infrastructures, and big data has the potential to process and store that amount of data and information. Modelling, predicting, and extracting meaningful information in reasonable and efficient ways from big data represent a challenge for Data science in Connected vehicles.Informe Estimation of supply and demand of tertiary education places in advanced digital profiles in the EU(Publications Office, 2020) Gómez Losada, Álvaro; López Cobo, Montserrat; Samoili, Sofia; Alaveras, Georgios; Vázquez-Prada Baillet, Miguel; Cardona, Melisande; Righi, Riccardo; Ziemba, Lukasz; De Prato, Giuditta; Estadística e Investigación OperativaIn order to investigate the extent to which the education offer of advanced digital skills in Europe matches labour market needs, this study estimates the supply and demand of university places for studies covering the technological domains of Artificial Intelligence (AI), High Performance Computing (HPC), Cybersecurity (CS) and Data Science (DS), in the EU27, United Kingdom and Norway. The difference between demand and supply of tertiary education places (Bachelor and Master or equivalent level) in the mentioned technological domains is referred in this report as unmet students’ demand of places, or unmet demand. Demanded places, available places and unmet demand are estimated for the following dimensions: (a) the tertiary education level in which this demand is observed: Bachelor and Master or equivalent programmes; (b) the programme’s scope, or depth with which education programmes address the technological domain: broad and specialised; and (c) the main fields of education where this tuition is offered: Business Administration and Law; Natural sciences and Mathematics; Information and Communication Technology (ICT); and Engineering, Manufacturing and Construction, with the remaining fields grouped together in a fifth category. From these estimations, it is concluded that the number of available places in the EU27, at Bachelor level, reaches 587,000 for studies with AI content, 106,000 places offered in HPC, 307,000 places in CS and 444,000 places offered in the domain of DS. At Master level this demand is comparatively lower, except for the DS domain, were it equals the offer at bachelor level. DS outnumbers AI in demand of places at Master level, with 602,000 and 535,000 demanded places, respectively. The unmet demand for AI, HPC, CS and DS in EU27 at MSc level is approximately 150,000, 33,000, 59,000 and 167,000 places, respectively. At BSc level, the unmet demand reaches 273,000, 53,000, 159,000 and 213,000 places, respectively. Another finding is that the unmet demand for broad academic programmes is higher than for specialised programmes of all technological domains and education levels (Bachelor and Master). Higher availability of places for AI, HPC, CS and DS domains is found for academic programmes taught in the ICT field of education, both at Bachelor and Master levels. For Bachelor studies, Germany and Finland are estimated as the countries with the highest unmet demand in AI, HPC, CS and DS, either with a broad or specialised scope. United Kingdom is the only studied country offering places for all fields of education and technological domains at Bachelor level and Master level. For Master studies, this is also found in Germany, Ireland, France and Portugal.