The educational sector can be enriched by the incorporation of artificial intelligence (AI) in various aspects. field and its applications education give rise to a multidisciplinary that brings together computer science, statistics, psychology and, course, education. Within this context, review aimed synthesise existing research focused on provide improvements primary/secondary student assessment using some AI tool. Thus, nine original studies (641 participants), published between 2010 2023,...

El sector educativo puede enriquecerse con la incorporación de inteligencia artificial (IA) en diversos aspectos. campo y sus aplicaciones el dan lugar a un multidisciplinar que confluyen informática, estadística, psicología y, por supuesto, educación. Dentro este contexto, esta revisión pretende sintetizar las investigaciones existentes centradas proporcionar mejoras evaluación del alumnado primaria/secundaria utilizando alguna herramienta IA. Así, nueve estudios investigación originales...

Indoor environmental quality (IEQ) monitoring of in-use buildings has become essential in recent years due to the COVID-19 pandemic, as it significantly affects well-being, health and productivity building users. Nevertheless, knowing real time conditions large multi-zone areas is a difficult issue. Thus, use machine learning techniques estimate indoor increased considerably. The aim this paper present an interpolation model, based on optimised extreme gradient boosting algorithm, every...

Laminated parts made of FDM (Fused Deposition Modeling) are becoming increasingly popular in last years. This increment can be explained due to their potential field manufacturing order allow us make any kind geometry, but another way, these have not enough values stiffness and strength get an approach a final constructive part. However, advantages nowadays FEM programs analyze behavior main properties; previously mentioned structural parts. Then it we must need accurately predict the...

Today, different implant designs exist in the market; however, there is not a clear understanding of which are best design parameters to achieve mechanical optimal conditions. Therefore, aim this project was investigate if geometry commercial short stem hip prosthesis can be further optimized reduce stress shielding effects and better short-stemmed performance. To reach aim, potential machine learning techniques combined with parametric Finite Element analysis used. The selected geometrical...

Ground level concentrations of nitrogen oxide (NOx) can act as an indicator air quality in the urban environment. In cities with relatively good quality, and where NOx rarely exceed legal limits, adverse health effects on population may still occur. Therefore, detecting small deviations deriving methods controlling pollution are challenging. This study presents different data analytical which be used to monitor effectively evaluate policies or measures reduce emissions through detection...

Today, urban development faces complex global challenges that require new approaches to influence its practices and policies. By prioritizing sustainability, mobility, community resilience, we are moving towards a holistic approach protects the well-being of residents environment. In this dynamic design environment, finding ways identify pedestrian-friendly spaces create safe, efficient, sustainable environments is major challenge, it requires research seeks optimize choice, especially in...

In the field of data security intrusion detection, challenge lies in effectively identifying and categorizing activities amidst influx data. Current research predominantly focuses on traditional methods that may overlook subtle yet significant patterns, thereby hindering accurate detection. This paper addresses this gap by proposing a novel approach - A Density-Based Spatial Clustering Applications with Noise (DBSCAN) for Data Security Intrusion Detection. By harnessing power density-based...

Accurate prediction of building indoor temperatures and thermal demand is great help to control optimize the energy performance a building. However, inertia lag lead complex nonlinear systems difficult model. In this context, application artificial neural networks (ANNs) in buildings has grown considerably recent years. The aim work study by developing an innovative methodology using multi-layered perceptron (MLP) long short-term memory (LSTM) networks. This approach was applied public...

Solar PV generation is renewable energy source that in the last years has contributed to reduce use of fossil fuels. Controlling efficiency photovoltaic (PV) installations essential order for its spread. Deep learning (DL) models have demonstrated their this context. The purpose work show a methodology optimised deep and specific application model characterise installations. estimations yielded by are obtained without need real data training process; synthetic used. built multivariate neural...

Microfin design for industrial applications has been extensively studied in the past, but use of innovative techniques that can reveal hitherto unfamiliar morphologies realizable with novel additive manufacturing not yet fully exploited. Here, an attempt is made to develop a structured methodology assessment various randomly generated geometries, purpose identifying most significant geometrical parameters their thermohydraulic performance. To do so, computational fluid dynamics (CFD)...