Procesamiento de flujo de datos : Un caso de estudio: análisis en tiempo real usando datos geolocalizados

La sociedad hoy plantea crecientes demandas de soluciones informáticas, cuando estas soluciones requieren el procesamiento de grandes volúmenes de datos, las herramientas tradicionales de procesamiento muestran limitaciones e inconvenientes derivados de la cantidad de datos a procesar o del tiempo necesario para realizarlo. Surge así, la necesidad de herramientas específicas, llamadas herramientas de Big Data. Dentro de estas existe un grupo concreto para el procesamiento de flujos de datos (stream processing), entendiendo por flujo de datos la recepción y procesamiento continuo de datos ilimitados desde diferentes fuentes. Debido a su naturaleza sin límite, estos flujos no pueden descargarse de manera completa, y deben ser procesados en línea a cuando se reciben. Dos de las principales herramientas para el procesamiento de flujos de datos son Apache Spark y Apache Flink, estas herramientas serán el objeto de estudio del presente trabajo. El caso de estudio a desarrollar tiene por finalidad comparar distintos aspectos de ambas herramientas. Como caso de estudio se propone obtener publicaciones que incluyan las expresiones coronavirus y/o covid (SARSCoV- 2), y agrupar las mismas de acuerdo a su geolocalización, ya que esto permitirá monitorear la evolución de la enfermedad de acuerdo a la localización de los usuarios y su participación en distintos lugares de la web (redes sociales, comentarios en publicaciones, etc.).XIII Workshop procesamiento de señales y sistemas de tiempo real (WPSSTR)Red de Universidades con Carreras en Informátic

GenoMus: Representing Procedural Musical Structures with an Encoded Functional Grammar Optimized for Metaprogramming and Machine Learning

We present GenoMus, a new model for artificial musical creativity based on a procedural approach, able to represent compositional techniques behind a musical score. This model aims to build a framework for automatic creativity, that is easily adaptable to other domains beyond music. The core of GenoMus is a functional grammar designed to cover a wide range of styles, integrating traditional and contemporary composing techniques. In its encoded form, both composing methods and music scores are represented as one-dimensional arrays of normalized values. On the other hand, the decoded form of GenoMus grammar is human-readable, allowing for manual editing and the implementation of user-defined processes. Musical procedures (genotypes) are functional trees, able to generate musical scores (phenotypes). Each subprocess uses the same generic functional structure, regardless of the time scale, polyphonic structure, or traditional or algorithmic process being employed. Some works produced with the algorithm have been already published. This highly homogeneous and modular approach simplifies metaprogramming and maximizes search space. Its abstract and compact representation of musical knowledge as pure numeric arrays is optimized for the application of different machine learning paradigms.FEDER/Junta de Andalucia A.TIC.244.UGR20 Spanish GovernmentEuropean Commission PID2021-125537NA-I0

Time Series Analysis for Predicting Hydroelectric Power Production: The Ecuador Case

Electrical generation in Ecuador mainly comes from hydroelectric and thermo-fossil sources, with the former amounting to almost half of the national production. Even though hydroelectric power sources are highly stable, there is a threat of droughts and floods affecting Ecuadorian water reservoirs and producing electrical faults, as highlighted by the 2009 Ecuador electricity crisis. Therefore, predicting the behavior of the hydroelectric system is crucial to develop appropriate planning strategies and a good starting point for energy policy decisions. In this paper, we developed a time series predictive model of hydroelectric power production in Ecuador. To this aim, we used production and precipitation data from 2000 to 2015 and compared the Box-Jenkins (ARIMA) and the Box-Tiao (ARIMAX) regression methods. The results showed that the best model is the ARIMAX (1,1,1) (1,0,0)12, which considers an exogenous variable precipitation in the Napo River basin and can accurately predict monthly production values up to a year in advance. This model can provide valuable insights to Ecuadorian energy managers and policymakers.This work has been funded by the Universidad de Guayaquil through the grant number FCI-015-2019. This work has been also supported by ESPOL, grant number FIMCP-CERA-05-2017

Analyzing gender disparities in STEAM: A Case Study from Bioinformatics Workshops in the University of Granada

La bioinformática es un área interdisciplinaria que ha despertado un gran interés tanto para el mundo académico como para las corporaciones en los últimos años. Esta área creciente combina conocimientos y habilidades de las áreas de biología y ciencia, tecnología, ingeniería, artes y matemáticas (STEM). Una de las ventajas de la sinergia entre estas dos áreas de trabajo es que ofrece una oportunidad para cerrar la brecha de género de STEM tradicional. A pesar de esta oportunidad y la importancia y amplia aplicación del campo de la bioinformática, este tema aún no ha ganado suficiente visibilidad en los programas de posgrado para los títulos de bachillerato en la Universidad de Granada. Esto ha motivado la organización de un "Taller educativo sobre bioinformática" anual en la Universidad de Granada por el Departamento de Ciencias de la Computación e Inteligencia Artificial. Los resultados del análisis de las dos primeras ediciones de este taller muestran un gran interés en el tema por la comunidad universitaria en todos los niveles (por ejemplo, estudiantes de pregrado y posgrado, docentes e investigadores) sin distinción significativa entre los géneros a nivel global. Al analizar el grupo de estudiantes, las mujeres mostraron un mayor interés en el tema. Sin embargo, este interés no se reflejó en los estratos universitarios superiores (docentes e investigadores), que representan un vistazo de la situación actual general española en el área.Bioinformatics is an interdisciplinary area that has raised a high interest for both academia and corporations in recent years. This rising area combines knowledge and skills from Bio and Science, Technology, Engineering, Arts and Mathematics (STEM) areas. One of the advantages of the synergy between these two work areas is that it offers an opportunity for closing the traditional STEM's gender gap. Despite this opportunity and the signi cance and wide application of bioinformatics eld, this topic has still not gained enough visibility in the graduate programs for the Bio Bachelor Degrees at the University of Granada. This has motivated the organization of an annual \Educational Workshop on Bioinformatics" at the University of Granada by the Department of Computer Science and Arti cial Intelligence. Results of the analysis of the rst two editions of this workshop show a great interest on the topic by the university community at all levels (e.g. undergraduate and graduate students, teachers and researchers) without signi cant distinction among genders at global level. When analyzing student group, women did show a higher interest on the subject. However, this interest was not reflected in the higher university strata (teachers and researchers), which represents a glimpse of the spanish general current situation on the area.Universidad de Granada: Departamento de Arquitectura y Tecnología de Computadore

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Hydropower production prediction using artificial neural networks: an Ecuadorian application case

The authors kindly acknowledge the support from University of Guayaquil. Computational and physical resources were provided by ESPOL. Juan Gomez-Romero is partially supported by the University of Granada and the Spanish Ministries of Science, Innovation and Universities (TIN2017-91223- EXP) and Economy and Competitiveness (TIN2015-64776-C3-1-R).Hydropower is among the most efficient technologies to produce renewable electrical energy. Hydropower systems present multiple advantages since they provide sustainable and controllable energy. However, hydropower plants’ effectiveness is affected by multiple factors such as river/reservoir inflows, temperature, electricity price, among others. The mentioned factors make the prediction and recommendation of a station’s operational output a difficult challenge. Therefore, reliable and accurate energy production forecasts are vital and of great importance for capacity planning, scheduling, and power systems operation. This research aims to develop and apply artificial neural network (ANN) models to predict hydroelectric production in Ecuador’s short and medium term, considering historical data such as hydropower production and precipitations. For this purpose, two scenarios based on the prediction horizon have been considered, i.e., one-step and multi-step forecasted problems. Sixteen ANN structures based on multilayer perceptron (MLP), long short-term memory (LSTM), and sequence-to-sequence (seq2seq) LSTM were designed. More than 3000 models were configured, trained, and validated using a grid search algorithm based on hyperparameters. The results show that the MLP univariate and differentiated model of one-step scenario outperforms the other architectures analyzed in both scenarios. The obtained model can be an important tool for energy planning and decision-making for sustainable hydropower production.University of GuayaquilUniversity of GranadaSpanish Government TIN2017-91223- EXP TIN2015-64776-C3-1-

Quillen-Suslin rings

In this paper we introduce the Quillen-Suslin rings and investigate its relation with some other classes of rings as Hermite rings (each stably free module is free), PSF rings (each ¯nitely generated projective module is stably free), PF rings (each ¯nitely generated projective module is free), etc. Quillen-Suslin rings are induced by the famous Serre's prob- lem formulated by J.P. Serre in 1955 ([30]) and solved independently by Quillen ([28]) and Suslin ([31]) in 1976. The solution is known as the Quillen-Suslin theorem and states that every ¯nitely generated projective module over the polynomial ring K[x1; : : : ; xn] is free, where K is a ¯eld. There are algorithmic proofs and some generalizations of this important theorem that we will also study in this paper. In particular, we will consider extended modules and rings, and the Bass-Quillen conjecture