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A multidisciplinary approach to prevent student anxiety: a Toolkit for educators

Procedia Computer Science 2025年 256卷 852-860页

作者： Alberto Freitas Bruno Costa Diogo Martinho Fatima Pais Ivone Duarte Constantino Martins Goreti Marreiros Rute Almeida MEDCIDS Faculty of Medicine University of Porto Porto 4200-450 Portugal CINTESIS@RISE University of Porto Porto 4200-450 Portugal Centro Hospitalar Universitário São João 4200-319 Porto GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering – Polytechnic of Porto Porto 4249-015 Portugal & LASI – Intelligent Systems Associate Laboratory Guimarães 4800-058 Portugal Sucessos Criativos Lda São João da Madeira 3700-121 Portugal

The project WAI aims to tackle the growth of mental health disorders among the younger population, namely the most prevalent anxiety disorders. It intends to enhance educational strategies to help schools, teachers, and other professionals dealing with student anxiety. With that purpose, a suite of resources with a focus on mental health promotion in the school environment was organized by collecting existing tools and creating new elements for completeness. Information on mental health, AI, and AI use on mental health, classroom strategies, and best practices, structured for interdisciplinary application and use by both teachers and students, were considered. These resources were integrated into a Toolkit with a recommendation feature, which allows easy location and access to the most adequate tool for the specific need or educational challeng.. To maximize accessibility, resources will be translated into several languages. The Toolkit will guide the implementation of a capacitation formative program for educators that will be implemented based on its resources. The development of the project involves participatory design with contributions from educators, mental health experts, and AI technologists to ensure a comprehensive approach. The Toolkit is intended to provide a systematic framework for educators to promote sustainable mental health promotion practices and, when appropriate, to use AI in ways that are ethically sound, while fostering digital responsibility.

关键词： Mental Health Promotion Anxiety Disorders Educational Strategies AI in Education Toolkit Teacher Capacitation

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Clustering Support for an Aggregator in a Smart Grid Context 18th

Clustering Support for an Aggregator in a Smart Grid Context

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18th International Conference on Hybrid intelligent Systems, HIS 2018

作者： Silva, Cátia Faria, Pedro Vale, Zita GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Rua Dr. António Bernardino de Almeida Porto4200-072 Portugal

ISBN: (纸本)9783030143466

The future of the industry foresees the automation and allocation of more intelligence to processes. A revolution in relation to the present. With this, new challeng.s and consequently more complexity is added to the management of the sectors. In the electric sector is introduced the theme of the Smart grids and so all the concepts aggregated with it. The possibility of the existence of demand response programs and the expansion of the distributed generation units for small players are key concepts and with enormous influence in the management of the markets belonging to this sector. Thus, a method is proposed that would help manage these resources through their aggregation, opening a new port for business models based on this idea. The benefit will be to take advantage of a more effective and efficient way the energy potential present in each group that is formed. Thus, in this paper will be explored the potential of clustering methods for the aggregation of resources. © 2020, Springer Nature Switzerland AG.

关键词： Smart power grids

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A systematic review of explainability in computational intelligence for optimization

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Computer Science Review 2025年 57卷

作者： José Almeida João Soares Fernando Lezama Steffen Limmer Tobias Rodemann Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI - Intelligent Systems Associate Laboratory ISEP Polytechnic of Porto Porto Portugal HRI-EU – Honda Research Institute Europe Offenbach Germany

This systematic review explores the need for explainability in computational intelligence methods for optimization, such as metaheuristic optimizers, including evolutionary algorithms and swarm intelligence. The work focuses on four aspects: (1) the contribution of Explainable AI (XAI) methods to interpreting metaheuristic performance; (2) the influence of problem features on search behavior and explainability; (3) the role of mathematical theory in providing transparent explanations; and (4) the potential of metaheuristics to enhance the explainability of AI models, such as machine learning (ML). XAI methods such as SHAP, LIME, and visualization techniques provide valuable insights into metaheuristic performance, while landscape analysis and quality diversity approaches reveal algorithm performance across different problem landscapes. The review also explores how metaheuristic algorithms can enhance the interpretability of ML models, turning black-box models into more transparent systems. The work moves on to proposing ”Explainergy,” a novel concept for integrating explainability into metaheuristic algorithms within the energy domain, enhancing the transparency and usability of optimization models. This review is a foundation for future research combining explainability with evolutionary computation and metaheuristic optimization to address real-world challeng.s in diverse fields, including energy systems.

关键词： Artificial intelligence Black box optimization Computational intelligence Explainability Explainergy Metaheuristics Systematic review

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Study of multi-tariff influence on the distributed generation remuneration 16th

Study of multi-tariff influence on the distributed generatio...

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16th International Conference on Distributed computing and Artificial Intelligence, DCAI 2019

作者： Silva, Cátia Faria, Pedro Vale, Zita GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development IPP - Polytechnic Institute of Porto Rua DR. Antonio Bernardino de Almeida Porto431 4200-072 Portugal

ISBN: (纸本)9783030239459

The energy market, with the introduction of the smart grids concept, opens the door to small distributed energy resources. However, these resources introduce an added level of difficulty to market management, requiring an entity to aggregate and manage them optimally. This paper proposes an approach that integrates these small resources. The methodology is composed of optimal scheduling, aggregation and remuneration based on aggregation. The method chosen for aggregation is k-means. In relation to previous works, the innovation goes through the multi-period and the comparison that this can have in the formation of groups. Thus, three scenarios were created: Whole Week, Work Days and Weekend. Profiles were added for 548 units of DG. The justification for the formation of groups will be a fairer remuneration and according to the contribution of each resource to the management of the network. © 2020, Springer Nature Switzerland AG.

关键词： Distributed power generation

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A Consumer Trustworthiness Rate for Participation in Demand Response Programs

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IFAC-PapersOnLine 2020年第2期53卷 12596-12601页

作者： Cátia Silva Pedro Faria Zita Vale GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal Polytechnic of Porto Porto Portugal

Local energy communities with information from the real-time market may improve the market operation but also increase the complexity of the management problem thanks to the uncertainty associated with the actual response of these resources. For instance, consumers with price knowledge may change their power consumption to lower-cost periods. The authors present a model to deal with uncertainty from the Aggregator perspective: apply reliability rates to each consumer according to their actual response in events of Demand Response (DR). The consumers with higher rates are chosen to participate in the local flexibility markets. To compute the final rate, three different independent rates are used: Historical rate with past information, Cut-rate from the response in the actual period and the Last Day Rate which is the final reliability rate from the previous day. In the present paper, the influence of each independent rate, through the weight used, is studied.

关键词： Demand Response Uncertainty Aggregator Smart Grids Optimization

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Key Performance Indicators to Support the Participation in Demand Response Programs:A Testing Framework for End Users

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IFAC-PapersOnLine 2020年第2期53卷 12602-12607页

作者： Débora de São José Pedro Faria Cátia Silva Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal Polytechnic of Porto Porto Portugal

With the new challeng.s and complexity in power electricity management, demand response programs can be a way to reduce stress and streng.hen power grids. However, as demand response implies end users to intentionally change their consuming patterns to adapt to grids needs, some decision-making support tools are necessary. The present paper proposes an energy management and controlling tool to assist electricity end users to make their decision to change consumption pattern in a DR scenario while using key performance indicators. The tool was tested using a group of 20 end users and showed a consistent result throughout all the elements in the sample.

关键词： System Management Monitoring Key Performance Indicators KPI Demand Response

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Innovative Electricity Market Designs to Support a Transition to (Near) 100% Renewable Power System: First Results from H2020 TradeRES Project 22

Innovative Electricity Market Designs to Support a Transitio...

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22nd Wind and Solar Integration Workshop, WIW 2023

作者： Estanqueiro, Ana Strbac, Goran Chrysanthopoulos, Nikolaos Santos, Gabriel Johanndeiter, Silke Algarvio, Hugo Syse, Helleik Sperber, Evelyn Wang, Ni Jimenez, Ingrid Qiu, Dawei Vale, Zita Nienhaus, Kristina Kochems, Johannes Schimeczek, Christoph Sijm, Jos de Vries, Laurens Lopes, Fernando Couto, António Renewable Energies and Energy Efficiency Unit Laboratório Nacional de Energia e Geologia I.P. Estrada do Paço do Lumiar Lisboa Portugal Department of Electrical and Electronic Engineering Imperial College London London United Kingdom GECAD - Research Group on Intelligent Eng. and Computing for Advanced Innovation and Development LASI - Intelligent Systems Associate Laboratory Polytechnic of Porto Rua Dr. António Bernardino de Almeida Porto Portugal EnBW Baden-Württemberg Department of Energy Economics Durlacher Allee 93 Karlsruhe76137 Germany Bityoga AS Prof. Olav Hansens vei 7A Stavanger4021 Norway Inst. of Networked Energy Systems Energy Systems Analysis Stuttgart Germany Energy Transition Studies TNO Radarweg 60 Amsterdam1043 NT Netherlands Faculty of Technology Policy and Management TU Delft Jaffalaan 5 2628 BX Netherlands

ISBN: (纸本)9781839539824

Developing innovative electricity market designs to facilitate a sustainable transition to (near) 100% renewable power systems while meeting societal needs is a crucial and actual topic of research. This article presents preliminary key findings from the H2020 European project TradeRES, addressing this critical topic. The project uses agent-based and optimization models to effectively capture the behaviour of different market players, and to analyse the current and future power system energy mixes of selected European case studies with different physical and spatial scales from: i) local energy communities and local energy markets (LEMs);ii) national/regional - the Netherlands, Germany, and Iberia (Portugal and Spain);and iii) pan-European energy markets. The first results on LEMs indicate a substantial economic benefit for participants and enhanced revenue streams for distributed energy resources, able to i) incentivise further decentralised investments;ii) promote the growth of variable renewable energy systems (vRES) and iii) increase flexibility at the local level. The outcomes are sensitive to the tariffs’ structure, while the retail sector competitiveness was identified as a critical parameter affecting its efficiency. For the pan-European and national/regional case studies, the first set of simulations had consistent outcomes, namely, by pointing out current design of energy-only markets to be insufficient to incentivize the high levels of vRES foreseen in Europe. Different support schemes (e.g., fixed market premia, contract for differences) were tested and results suggest they may play a relevant role in effectively covering the cost of vRES in a market environment. © Energynautics GmbH.

关键词： Power markets

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Using Machine Learning to Predict the Users Ratings on TripAdvisor Based on Their Reviews

Using Machine Learning to Predict the Users Ratings on TripA...

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International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2021

作者： Carneiro, João Meira, Jorge Novais, Paulo Marreiros, Goreti GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering Polytechnic of Porto Porto4200-072 Portugal CITIC – Centro de Investigación en Tecnologías de la Información y las Comunicaciones University of A Coruña A Coruña15071 Spain ALGORITMI Centre University of Minho Guimarães4800-058 Portugal

ISBN: (纸本)9783030857097

Argumentation-based dialogue models have shown to be appropriate for decision contexts in which it is intended to overcome the lack of interaction between decision-makers, either because they are dispersed, they are too many, or they are simply not even known. However, to support decision processes with argumentation-based dialogue models, it is necessary to have knowledge of certain aspects that are specific to each decision-maker, such as preferences, interests, limitations, among others. Failure to obtain this knowledge could ruin the model’s success. In this work, we intend to facilitate the acquiring information process by studying strategies to automatically predict the tourists’ preferences (ratings) in relation to points of interest based on their reviews. We explored different Machine Learning algorithms (Logistic Regression, Random Forest, Decision Tree, K-Nearest Neighbors and Recurrent Neural Networks) and Natural Language Processing strategies to predict whether a review is positive or negative and the rating assigned by users on a scale of 1 to 5. The experiments carried out showed that the developed models can predict with high accuracy whether a review is positive or negative but have some difficulty in accurately predicting the rating assigned by users. © 2021, Springer Nature Switzerland AG.

关键词： Sentiment analysis

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A low-cost multi-agent system for physical security in smart buildings

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AIP Conference Proceedings 2024年第1期2919卷

作者： Tiago Fonseca Tiago Dias João Vitorino Luís Lino Ferreira Isabel Praça School of Engineering Polytechnic of Porto (ISEP/IPP) 4249-015 Porto Portugal Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) 4249-015 Porto Portugal

Modern organizations face numerous physical security threats, from fire hazards to more intricate concerns regarding surveillance and unauthorized personnel. Conventional standalone fire and intrusion detection solutions must be installed and maintained independently, which leads to high capital and operational costs. Nonetheless, due to recent developments in smart sensors, computer vision techniques, and wireless communication technologies, these solutions can be integrated in a modular and low-cost manner. This work introduces Integrated Physical Security System (IP2S), a multi-agent system capable of coordinating diverse Internet of Things (IoT) sensors and actuators for an efficient mitigation of multiple physical security events. The proposed system was tested in a live case study that combined fire and intrusion detection in an industrial shop floor environment with four different sectors, two surveillance cameras, and a firefighting robot. The experimental results demonstrate that the integration of several events in a single automated system can be advantageous for the security of smart buildings, reducing false alarms and delays.

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Defining the Optimal Number of Demand Response Programs and Tariffs Using Clustering Methods 20

Defining the Optimal Number of Demand Response Programs and ...

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20th International Conference on intelligent System Application to Power Systems, ISAP 2019

作者： Silva, Catia Faria, Pedro Vale, Zita GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto Porto Portugal

ISBN: (纸本)9781728131924

Nowadays, the data can be considered an asset when properly managed. An entity with the right tool to analyse the amount of data existent and withdraw crucial information will have the power to obliterate the competition. In the Energy sector, with Smart Grid introduction, small resources have more influence in the market through Demand Response and bidirectional communication. However, none of the actual business models is prepared to deal with the uncertainty related to these resources. The authors, in order to find a solution for this complex problem, proposed a methodology which the goal is to minimize operation costs and give fair compensation for resources who participate in the management of local markets. With this fair payment, it is expected continuous participation. Through clustering methods, remuneration groups are created. In the present paper, a study about the optimal number of clusters is performed. The information gives the Aggregator control in results of the following phases, understanding the impact in the remuneration of the resources. © 2019 IEEE.

关键词： Smart power grids

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