Uso de sistemas de control de versiones para aplicar estrategias de evaluación por pares en contextos tecnológicos [Using Version Control Systems to apply peer review techniques in engineering education]

Diferentes metodologías educativas han demostrado que un aspecto muy positivo para mejorar el aprendizaje del estudiante es que éste sea parte central del mismo, y especialmente que se involucre de manera activa en los procesos de aprendizaje. En este sentido la aplicación de técnicas de evaluación por pares ha sido una aproximación muy popular. Sin embargo, en enseñanzas de carácter ingenieril y especialmente enseñanzas técnicas, las actividades a evaluar implican en muchas ocasiones el uso de lenguajes o herramientas muy específicas. Esto hace que la evaluación por pares sea más compleja e implique que tanto alumnos como profesores tengan que utilizar diferentes contextos para la evaluación (como una herramienta de desarrollo software y una plataforma de aprendizaje). De cara a solventar este problema el presente trabajo propone el uso de sistemas de control de versiones que van a permitir almacenar los resultados obtenidos e interactuar al responsable del trabajo con sus revisores. En concreto, en este artículo se presenta la aplicación de técnicas de evaluación por pares en un grupo de 46 alumnos. Los resultados muestran que los discentes que usan activamente la herramienta con fines de evaluación tienen mejores resultados asociados. [Different studies have shown that a very positive factor to improve students learning is that they were the center of teaching and learning processes and also to be an active part in them. In this sense, the application of peer review techniques is a very popular approach. However, in engineering education and special in technical degrees the activities to assess consist of the use of very specific tools and languages. This makes peer evaluation more complex in this context than in others. It requires that both teachers and students use different tools and platforms to complete the evaluation. In order to solve this, the present work aims to apply a version control system to facilitate manage different results versions and also to interact with reviewers in the peer review process. In this specific work, the authors present a case study with 46 students that employ a version control system to apply peer review. Results show that students that use properly the tool have better performance.

Evaluación del resultado académico de los estudiantes a partir del análisis del uso de los Sistemas de Control de Versiones

Version Control Systems are commonly used by Information and Communication Technology professionals. These systems allow for monitoring programmers' activity working in a project. Thus, the usage of such systems should be encouraged by educational institutions. The aim of this work is to evaluate if students’ academic success can be predicted by monitoring their interaction with a Version Control System. In order to do so, we have built a model that predicts students’ results in a specific practical assignment of the Operating Systems Extension subject. A second-year subject in the degree in Computer Science at the University of León. In order to obtain a prediction, the model analyzes students’ interaction with a Git repository. To build the model, several classifiers and predictors have been evaluated by using the MoEv tool. The tool allows for evaluating several classification and prediction models in order to get the most suitable one for a specific problem. Prior to the model development, Moev performs a feature selection from input data to select the most significant ones. The resulting model has been trained using results from the 2016 – 2017 course year. Later, in order to ensure an optimal generalization, the model has been validated by using results from the 2017 – 2018 course. Results conclude that the model predicts students' outcomes? with a success high percentage.Una de las herramientas más utilizadas por los profesionales de las tecnologías de la información y la comunicación son los sistemas de control de versiones. Estas herramientas permiten, entre otras cosas, monitorizar la actividad de las personas que trabajan en un proyecto. Por tanto, es recomendable que se utilicen también en las instituciones educativas. El objetivo de este trabajo es evaluar si el resultado académico de los estudiantes se puede predecir monitorizando su actividad en uno de estos sistemas. Para tal efecto, hemos construido un modelo que predice el resultado de los estudiantes en una práctica de la asignatura Ampliación de Sistemas Operativos, perteneciente al segundo curso del grado en Ingeniería Informática de la Universidad de León. Para obtener la predicción, el modelo analiza la interacción del estudiante con un repositorio Git. Para diseñar el modelo, se evalúan varios modelos de clasificación y predicción utilizando la herramienta MoEv. Esta herramienta permite entrenar y validar diferentes modelos de clasificación y obtener el más adecuado para un problema concreto. Además, la herramienta permite identificar las características más discriminantes dentro de los datos de entrada. El modelo resultante ha sido entrenado utilizando los resultados del curso 2016 – 2017. Posteriormente, para asegurar que el modelo generaliza correctamente, se ha validado utilizando datos del curso 2017 – 2018. Los resultados concluyen que el modelo predice el éxito de los estudiantes con un alto porcentaje de acierto

Towards explainability in robotics: A performance analysis of a cloud accountability system

[EN] Understanding why a robot's behaviour was triggered is a growing concern to get human-acceptable social robots. Every action, expected and unexpected, should be able to be explained and audited. The formal model proposed here deals with different information levels, from low-level data, such as sensors' data logging; to high-level data that provide an explanation of the robot's behaviour. This study examines the impact on the robot system of a custom log engine based on a custom ROS logging node and investigates pros and cons when used together with a NoSQL database locally and in a cloud environment. Results allow to characterize these alternatives and explore the best strategy for offering a fully log-based accountability engine that maximizes the mapping between robot behaviour and robot logs.SIInstituto Nacional de CiberseguridadMinisterio de Ciencia e Innovació

Integration of Large Language Models within Cognitive Architectures for Autonomous Robots

The usage of Large Language Models (LLMs) has increased recently, not only due to the significant improvements in their accuracy but also because of the use of the quantization that allows running these models without intense hardware requirements. As a result, the LLMs have proliferated. It implies the creation of a great variety of LLMs with different capabilities. This way, this paper proposes the integration of LLMs in cognitive architectures for autonomous robots. Specifically, we present the design, development and deployment of the llama\_ros tool that allows the easy use and integration of LLMs in ROS 2-based environments, afterward integrated with the state-of-the-art cognitive architecture MERLIN2 for updating a PDDL-based planner system. This proposal is evaluated quantitatively and qualitatively, measuring the impact of incorporating the LLMs in the cognitive architecture.Comment: 8 pages, 6 figures, 2 tables, Submitted to ICRA 202

Procesamiento paralelo de los pronósticos meteorológicos del modelo WRF mediante NCL

La predicción meteorológica es un problema clásico de la programación paralela. Muchos de los modelos matemáticos que se utilizan en meteorología para pronosticar el comportamiento de la atmósfera tienen implementaciones preparadas para ejecutarse en entornos de cálculo paralelo. La información obtenida después de ejecutar un modelo matemático de predicción meteorológica es necesario procesarla para poder visualizar los resultados. Sin embargo, no es fácil encontrar herramientas que permitan el procesado en paralelo de estas salidas. El presente trabajo plantea la posibilidad de dar un paso más y mejorar el rendimiento, utilizando el paradigma paralelo para procesar las salidas de un modelo de predicción numérica, en concreto, el modelo WRF (Weather Research and Forecasting

Analyzing the influence of the sampling rate in the detection of malicious traffic on flow data

[EN] Cyberattacks are a growing concern for companies and public administrations. The literature shows that analyzing network-layer traffic can detect intrusion attempts. However, such detection usually implies studying every datagram in a computer network. Therefore, routers routing a significant volume of network traffic do not perform an in-depth analysis of every packet. Instead, they analyze traffic patterns based on network flows. However, even gathering and analyzing flow data has a high-computational cost, and therefore routers usually apply a sampling rate to generate flow data. Adjusting the sampling rate is a tricky problem. If the sampling rate is low, much information is lost and some cyberattacks may be neglected, but if the sampling rate is high, routers cannot deal with it. This paper tries to characterize the influence of this parameter in different detection methods based on machine learning. To do so, we trained and tested malicious-traffic detection models using synthetic flow data gathered with several sampling rates. Then, we double-check the above models with flow data from the public BoT-IoT dataset and with actual flow data collected on RedCAYLE, the Castilla y León regional academic network.S

Using Large Language Models for Interpreting Autonomous Robots Behaviors

The deployment of autonomous robots in various domains has raised significant concerns about their trustworthiness and accountability. This study explores the potential of Large Language Models (LLMs) in analyzing ROS 2 logs generated by autonomous robots and proposes a framework for log analysis that categorizes log files into different aspects. The study evaluates the performance of three different language models in answering questions related to StartUp, Warning, and PDDL logs. The results suggest that GPT 4, a transformer-based model, outperforms other models, however, their verbosity is not enough to answer why or how questions for all kinds of actors involved in the interaction

SQL injection attack detection in network flow data

[EN] SQL injections rank in the OWASP Top 3. The literature shows that analyzing network datagrams allows for detecting or preventing such attacks. Unfortunately, such detection usually implies studying all packets flowing in a computer network. Therefore, routers in charge of routing significant traffic loads usually cannot apply the solutions proposed in the literature. This work demonstrates that detecting SQL injection attacks on flow data from lightweight protocols is possible. For this purpose, we gathered two datasets collecting flow data from several SQL injection attacks on the most popular database engines. After evaluating several machine learning-based algorithms, we get a detection rate of over 97% with a false alarm rate of less than 0.07% with a Logistic Regression-based model.SIInstituto Nacional de Ciberseguridad de España (INCIBE)Universidad de Leó

Evaluación cuantitativa de la adquisición de la competencia de trabajo en equipo mediante la metodología CTMTC

Mención honorífica 2017[ES] La adquisición por los estudiantes de la competencia de trabajo en equipo (TE de aquí en adelante) se considera un aspecto fundamental en la formación de los individuos que ha llevado a su inclusión en los programas de la mayor parte de los grados de las universidades españolas. Esto se debe principalmente a dos razones: 1) El aprendizaje del estudiante se ve mejorado cuando este se lleva a cabo en grupo; de hecho compartir y debatir información en grupo facilita que los estudiantes construyan modelos mentales y por tanto conocimiento conjunto (Leidner & Jarvenpaa, 1995; Vogel, Davison, & Shroff, 2001); y 2) La competencia TE es algo muy apreciado en el ámbito laboral, ya que las instituciones buscan cooperación entre sus miembros para conseguir objetivos comunes (Iglesias-Pradas, Ruiz-de-Azcárate, & Agudo-Peregrina, 2015). Estas razones han hecho que la adquisición de la competencia TE sea algo especialmente tenido en cuenta en contextos educativos, como demuestra que sea una evidencia considerada por programas de evaluación de la calidad como ABET (Accreditation Board for Engineering and Technology) (ABET, 2013) o por la ANECA en sus programas de acreditación del profesorado (ANECA, 2015)

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio