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arXiv 2024年

作者： de Jesus, Gabriel Nunes, Sérgio INESC TEC Institute for Systems and Computer Engineering Technology and Science Portugal FEUP Faculty of Engineering University of Porto Portugal

The Cranfield paradigm has served as a foundational approach for developing test collections, with relevance judgments typically conducted by human assessors. However, the emergence of large language models (LLMs) has introduced new possibilities for automating these tasks. This paper explores the feasibility of using LLMs to automate relevance assessments, particularly within the context of low-resource languages. In our study, LLMs are employed to automate relevance judgment tasks, by providing a series of query-document pairs in Tetun as the input text. The models are tasked with assigning relevance scores to each pair, where these scores are then compared to those from human annotators to evaluate the inter-annotator agreement levels. Our investigation reveals results that align closely with those reported in studies of high-resource languages. © 2024, CC BY.

关键词： Computational linguistics

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Flexibility Modeling and Trading in Renewable Energy Communities

Flexibility Modeling and Trading in Renewable Energy Communi...

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International Conference on European Electricity Market, EEM

作者： João Agrela Igor Rezende Tiago Soares Clara Gouveia Ricardo Silva José Villar Institute for Systems and Computer Engineering Technology and Science (INESC TEC) University of Porto Faculty of Engineering (FEUP) Porto Portugal

This ork presents an approach to the flexibility of energy consumption in Renewable Energy Communities (RECs). A two-stage model for quantifying the flexibility provided by the domestic energy resources operation and its negotiation in a market platform is proposed. In stage 1, the optimal consumption of each prosumer is determined, as well as the respective technical flexibility of their resources, namely the maximum and minimum resource operation limits. In stage 2, this technical flexibility is offered in a local flexibility-only market structure, in which both the DSO and the prosumers can present their flexibility needs and requirements. The flexibility selling and buying bids of the prosumers participating in the market are priced based on their base tariff, which is the energy cost of the prosumers corresponding to their optimal schedule of the first stage when no flexibility is provided. Therefore, providing flexibility is an incentive to reduce their energy bill or increase their utility, encouraging their participation in the local flexibility market.

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Deep Learning for Segmentation of the Left Ventricle in Echocardiography

Deep Learning for Segmentation of the Left Ventricle in Echo...

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Bioengineering (ENBENG), Portuguese Meeting in

作者： Sofia Ferraz Miguel Coimbra João Pedrosa Faculty of Engineering of the University of Porto (FEUP) Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal

Two-dimensional echocardiography is the most widely used non-invasive imaging modality due to its fast acquisition time, low cost, and high temporal resolution. Accurate segmentation of the left ventricle in echocardiography is vital for ensuring the accuracy of subsequent diagnosis. Currently, numerous efforts have been made to automatize this task and various public datasets have been released in recent decades to further develop present research. However, medical datasets acquired at different institutions have inherent bias caused by various confounding factors, such as operation policies, machine protocols, treatment preference, etc. As a result, models trained on one dataset, regardless of volume, cannot be confidently utilized for the others. In this study, we investigated model robustness to dataset bias using two publicly available echocardiographic datasets. This work validates the efficacy of a supervised deep learning model for left ventricle segmentation and ejection fraction prediction, outside the dataset on which it was trained. The exposure of this model to unseen, but related samples without additional training maintained a good performance. However, a performance decrease from the original results can be observed, while the impact of quality is also noteworthy with lower quality data leading to decreased performance.

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Incremental Redundancy HARQ Communication Schemes applied to Energy Efficient IoT systems

Incremental Redundancy HARQ Communication Schemes applied to...

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Mediterranean Electrotechnical Conference (MELECON)

作者： Sérgio Miguel Silva Nuno T. Almeida Institute for Systems and Computer Engineering Technology and Science (INESC TEC) and Faculty of Engineering (FEUP) University of Porto Porto Portugal

ISBN: (数字)9798350387025

ISBN: (纸本)9798350387032

The rapid proliferation of Internet of Things (IoT) systems, encompassing a wide range of devices and sensors with limited battery life, has highlighted the critical need for energy-efficient solutions to extend the operational lifespan of these battery-powered *** effective strategy for reducing energy consumption is minimizing the number and size of retransmitted packets in case of communication errors. Among the potential solutions, Incremental Redundancy Hybrid Automatic Repeat reQuest (IR-HARQ) communication schemes have emerged as particularly compelling options by adopting the best aspects of error control, namely, automatic repetition and variable *** work addresses the challenge by developing a simulator capable of executing and analysing several (H)ARQ schemes using different channel models, such as the Additive White Gaussian Noise (AWGN) and Gilbert-Elliott (GE) models. The primary objective is to compare their performance across multiple metrics, enabling a thorough evaluation of their *** results indicate that IR-HARQ outperforms alternative methods, especially in the presence of burst errors. Furthermore, its potential for further adaptation and enhancement opens up new ways for optimizing energy consumption and extending the lifespan of battery-powered IoT devices.

关键词： Energy consumption Wireless sensor networks Redundancy Rician channels Rayleigh channels Energy efficiency Sensor systems

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Text Information Retrieval in Tetun: A Preliminary Study

arXiv

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arXiv 2024年

作者： de Jesus, Gabriel INESC TEC - Institute for Systems and Computer Engineering Technology and Science Portugal FEUP - Faculty of Engineering University of Porto Portugal

Tetun is one of Timor-Leste’s official languages alongside Portuguese. It is a low-resource language with over 932,400 speakers that started developing when Timor-Leste restored its independence in 2002. The media mainly uses Tetun, and more than ten national online newspapers actively broadcast news in Tetun every day. However, since information retrieval-based solutions for Tetun do not exist, finding Tetun information on the internet is challenging. This work aims to investigate and develop solutions that can enable the application of information retrieval techniques to develop search solutions for Tetun. We present a preliminary result of an experiment conducted on the task of ad-hoc retrieval in Tetun. © 2024, CC BY.

关键词： Information retrieval

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Next-generation smart homes: CO 2 monitoring with Matter protocol to support indoor air quality

Internet of Things

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Internet of Things 2025年

作者： Afonso Mota Carlos Serôdio Ana Briga-Sá Antonio Valente Department of Engineering School of Sciences and Technology Universidade de Trás-os-Montes e Alto Douro (UTAD) 5000-801 Vila Real Portugal Center ALGORITMI Universidade do Minho Campus de Azurém Guimarães 4800-058 Portugal CQ-VR (Center of Chemistry of Vila Real) Universidade de Trás-os-Montes e Alto Douro 5000-801 Vila Real Portugal CRIIS (Centre for Robotics in Industry and Intelligent Systems) INESC-TEC—Institute for Systems and Computer Engineering Technology and Science Campus da FEUP Porto 4200-465 Portugal

Humans spend most of their time indoors, where air quality and comfort are crucial to health and well-being. Elevated CO 2 levels in buildings can reduce cognitive function, discomfort, and health issues. Indoor CO 2 monitoring has emerged as a key focus in the literature, particularly in residential buildings, as it can play a vital role in helping to maintain adequate ventilation rates. The growing smart home market demands seamless integration and control, which are essential for implementing IAQ sensing devices. However, interoperability barriers between platforms and devices continue to hinder smart home adoption. To address these challenges, Matter protocol is starting to appear in the market. In this work, a wireless CO 2 sensor is developed based on ESP32-C6 and SCD40 and integrated into a created Matter-enabled ecosystem formed with the Home Assistant open-source platform. The utilized hardware and software enable the usage of two different wireless communication technologies, WiFi and Thread, enhancing compatibility. The study highlights the rapid and seamless onboarding of the developed CO 2 monitoring device into smart home ecosystems using the Matter protocol. As a result, once the device is successfully added to the ecosystem, the measurements can be accessed and analyzed through a mobile application, forming an IoT environment.

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Dynamic laplace: Efficient centrality measure for weighted or unweighted evolving networks

arXiv

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arXiv 2018年

作者： Cordeiro, Mário Sarmento, Rui Portocarrero Brazdil, Pavel Gama, João Doctoral Program in Informatics Engineering Faculty of Engineering University of Porto INESC TEC - Institute for Systems and Computer Engineering Technology and Science

With its origin in sociology, Social Network Analysis (SNA), quickly emerged and spread to other areas of research, including anthropology, biology, information science, organizational studies, political science, and computer science. Being it's objective the investigation of social structures through the use of networks and graph theory, Social Network Analysis is, nowadays, an important research area in several domains. Social Network Analysis cope with different problems namely network metrics, models, visualization and information spreading, each one with several approaches, methods and algorithms. One of the critical areas of Social Network Analysis involves the calculation of different centrality measures (i.e.: the most important vertices within a graph). Today, the challenge is how to do this fast and efficiently, as many increasingly larger datasets are available. Recently, the need to apply such centrality algorithms to non static networks (i.e.: networks that evolve over time) is also a new challenge. Incremental and dynamic versions of centrality measures are starting to emerge (betweenness, closeness, etc). Our contribution is the proposal of two incremental versions of the Laplacian Centrality measure, that can be applied not only to large graphs but also to, weighted or unweighted, dynamically changing networks. The experimental evaluation was performed with several tests in different types of evolving networks, incremental or fully dynamic. Results have shown that our incremental versions of the algorithm can calculate node centralities in large networks, faster and efficiently than the corresponding batch version in both incremental and full dynamic network setups. Copyright © 2018, The Authors. All rights reserved.

关键词： Laplace transforms

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Cybersecurity Challenges in Healthcare Medical Devices 1st

Cybersecurity Challenges in Healthcare Medical Devices

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1st EAI International Conference on Internet of Everything, IoECon 2022

作者： Longras, Ana Pereira, Teresa Amaral, António Instituto Politécnico de Viana do Castelo Viana do Castelo Portugal Centro ALGORITMI Universidade do Minho Guimarães Portugal INESC TEC–Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal

ISBN: (纸本)9783031252211

Medical devices are rapidly evolving and becoming more interconnected with healthcare networks, overcoming resource constraints, and increasingly focused on patient well-being and needs. This work intends to identify future research themes in the area of cybersecurity in health by surveying the articles being developed and identifying their current limitations and future work. The developed analysis was based on the publications with the highest number of citations, enabling us to find several challenges and restrictions such as integrating devices in systems. Innovations and the emergence of new technologies with inherent security vulnerabilities, will continue to evolve, escalating the attackers interest in exploiting unknown cybersecurity risks within healthcare. It is mandatory to consider cybersecurity risks since the conception of the devices to reduce security flaws, ensure the patients with a better quality of life, and guarantee information security properties. © 2023, ICST institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Cybersecurity

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Performing Aerobatic Maneuver with Imitation Learning 23rd

Performing Aerobatic Maneuver with Imitation Learning

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23rd International Conference on Computational science, ICCS 2023

作者： Freitas, Henrique Camacho, Rui Silva, Daniel Castro Department of Informatics Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias s/n. Porto4200-465 Portugal LIAAD/INESC TEC - Artificial Intelligence and Decision Support Laboratory/Institute for Systems and Computer Engineering Technology and Science Porto Portugal LIACC - Artificial Intelligence and Computer Science Laboratory Porto Portugal

ISBN: (纸本)9783031359941

The work reported in this article addresses the challenge of building models for non-trivial aerobatic aircraft maneuvers in an automated fashion. It is built using a Behavioural Cloning approach where human pilots provide a set of example maneuvers used by a Machine Learning algorithm to induce a control model for each maneuver. The best examples for each maneuver were selected using a set of objective evaluation metrics. Using those example sets, robust models were induced that could replicate (and in some cases outperform) the human pilots that provided the examples (the clean-up effect). Complete complex maneuvers were performed using a meta-controller capable of sequencing the basic ones learned by imitation. This endeavor was rewarded by the results that show several Machine Learning models capable of performing highly complex aircraft maneuvers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cloning

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A Vision Transformer Approach to Fundus Image Classification 12th

A Vision Transformer Approach to Fundus Image Classification

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12th International Conference on Mobile Communication and Healthcare, MobiHealth 2023

作者： Leite, Danilo Camara, José Rodrigues, João Cunha, António University of Trás-os-Montes and Alto Douro Vila Real Portugal INESC TEC—Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal LARSyS & ISE Universidade do Algarve Faro8005-226 Portugal

ISBN: (纸本)9783031606649

Glaucoma is a condition that affects the optic nerve, with loss of retinal nerve fibers, increased excavation of the optic nerve, and a progressive decrease in the visual field. It is the leading cause of irreversible blindness in the world. Manual classification of glaucoma is a complex and time-consuming process that requires assessing a variety of ocular features by experienced clinicians. Automated detection can assist the specialist in early diagnosis and effective treatment of glaucoma and prevent vision loss. This study developed a deep learning model based on vision transformers, called ViT-BRSET, to detect patients with increased excavation of the optic nerve automatically. ViT-BRSET is a neural network architecture that is particularly effective for computer vision tasks. The results of this study were promising, with an accuracy of 0.94, an F1-score of 0.91, and a recall of 0.94. The model was trained on a new dataset called BRSET, which consists of 16,112 fundus images of patients with increased excavation of the optic nerve. The results of this study suggest that ViT-BRSET has the potential to improve early diagnosis through early detection of optic nerve excavation, one of the main signs of glaucomatous disease. ViT-BRSET can be used to mass-screen patients, identifying those who need further examination by a doctor. © ICST institute for computer sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Excavation

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