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CIRED Porto Workshop 2022: E-Mobility and Power Distribution systems

作者： Sampaio, Gil Gouveia, Clara Bessa, Ricardo Villar, Jose Retorta, Fábio Carvalho, Leonel Merckx, Christian Benothman, Féres Promel, François Panteli, Mathaios Mourão, Rita Lopes Louro, Miguel Águas, André Marques, Pedro INESC TEC - Institute for Systems and Computer Engineering Technology and Science Portugal ENGIE Impact Belgium Cyprus E-REDES Portugal

ISBN: (数字)9781839537059

ISBN: (纸本)9781839537196

EUniversal project aims to facilitate the use of flexibility services and interlink distribution system's active management with electricity markets. Implementing market-based flexibility services implies a change in distribution network monitoring and control towards a more predictive approach. However, integrating cost-effective monitoring and control tools for the LV network is still quite challenging. Within the project, a set of operation and planning tools have been developed for a coordinated quantification and activation of flexibility in HV, MV and LV distribution networks. The paper presents the tools developed for the Portuguese pilot and shows preliminary results obtained when considering network operation scenarios characterized by large scale integration of DER and EV. © 2022 CIRED workshop on E-mobility and power distribution systems. All rights reserved.

关键词： Electric power transmission networks

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Roadmap for Implementing Business Intelligence systems in Higher Education Institutions: Validation of a Case Study at the University of Trás-os-Montes and Alto Douro 21

Roadmap for Implementing Business Intelligence Systems in Hi...

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21st International Conference on Smart Business technologies, ICSBT 2024

作者： Sequeira, Romeu Reis, Arsénio Branco, Frederico Alves, Paulo School of Science and Technology University of Trás-os-Montes and Alto Douro Quinta dos Prados Vila Real Portugal Instituto Politécnico de Bragança Bragança Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal

ISBN: (纸本)9789897587108

The adoption of effective policies and access to relevant information are critical to improving strategic management and performance monitoring in Higher Education Institutions (HEIs), which is essential to promote data-driven decision-making. This article describes how an HEI can carry out the validation process when implementing a Business Intelligence (BI) system, and provides a detailed guide to doing so. Through a case study at the University of Trás-os-Montes and Alto Douro, a structured roadmap is validated, which acts as a visual and sequential guide to facilitate the effective implementation of BI solutions. The validation carried out through semi-structured interviews with experts and evaluation of dashboards by user groups, not only confirms the applicability and efficiency of the proposed model but also emphasises its practical relevance, providing valuable insights for the adaptation and use of BI in different educational contexts. Copyright © 2024 by SCITEPRESS - science and technology Publications, Lda.

关键词： Competitive intelligence

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Harnessing Parasitic Cavity as Reference for Low Coherence systems

Harnessing Parasitic Cavity as Reference for Low Coherence S...

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2024 IEEE Photonics Conference, IPC 2024

作者： Robalinho, Paulo Rodrigues, A. Novais, S. Lobo Ribeiro, A.B. Silva, S. Frazão, O. Institute for Systems and Computer Engineering Technology and Science Inesc Tec Porto Portugal Faculty of Engineering University of Porto Department of Engineering Physics Portugal University Fernando Pessoa Faculty of Health Sciences R. Carlos da Maia 296 Porto4200-150 Portugal

This work presents an implementation of a reference optical cavity based on parasitic cavities on a low coherence interferometric system. This method allows a maximization of the number of sensors to be implemented wi... 详细信息

ISBN: (纸本)9798350361957

关键词： Optical fibers

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Automatic Detection of Polyps Using Deep Learning 12th

Automatic Detection of Polyps Using Deep Learning

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

作者： Oliveira, Francisco Barbosa, Dalila Paçal, Ishak Leite, Danilo Cunha, António UTAD—University of Trás-os-Montes and Alto Douro Vila Real5001-801 Portugal INESC TEC—Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal Igdir University Iğdir Turkey

ISBN: (纸本)9783031606649

Colorectal cancer is a leading health concern worldwide, with late detection being a primary challenge due to its often-asymptomatic nature. Routine examinations like colonoscopies play a pivotal role in early detection. This study harnesses the potential of Deep Learning, specifically convolutional neural networks, in enhancing the accuracy of polyp detection from medical images. Three distinct models, YOLOv5, YOLOv7, and YOLOv8, were trained on the PICCOLO dataset, a comprehensive collection of polyp images. The comparative analysis revealed YOLOv5’s submodel S as the most efficient, achieving an accuracy of 92.2%, a sensitivity of 69%, an F1 score of 74% and a mAP of 76.8%, emphasizing the effectiveness of these networks in polyp detection. © ICST institute for computer sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Convolutional neural networks

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Exploring Large Language Models for Relevance Judgments in Tetun

arXiv

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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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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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Direct Search Algorithm for Load Frequency Control of a Time-Delayed Electric Vehicle Aggregator

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IEEE Transactions on Industry Applications 2022年第2期59卷 1-11页

作者： Abolpour R. Torabi K. Dehghani M. Vafamand N. Javadi M.S. Wang F. Catalao J.P.S. School of Electrical and Computer Engineering Shiraz University Shiraz Iran Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal Department of Electrical Engineering North China Electric Power University (NCEPU) Baoding China Faculty of Engineering University of Porto (FEUP) and INESC TEC Porto Portugal

This paper addresses the topic of frequency regulation of a single-area power system connected to an electric vehicle (EV) aggregator over a non-ideal communication network. It is considered that the command control action is received by the EV aggregator with constant delay and the power system includes uncertain parameters. Due to the presence of uncertainties and the delay term, the frequency regulation problem is non-convex and hard to solve. The present approaches in the literature convert the non-convex control design problem into a convex problem with a set of Linear Matrix Inequalities (LMIs), which is conservative and in many cases results infeasibility. In this paper, an innovative iterative algorithm, called direct search, is employed for the time-delayed system to design the unknown parameters of a pre-assumed controller. The controller choice is not limited and various controllers' structures can be assumed. Without loss of generality, a proportional-integral (PI) controller is designed. The novel direct search algorithm can determine a feasible solution whenever at least one solution lays in the design space. Hence, by selecting a wide design space, we can anticipate that the PI controller guarantees closed-loop stability. Numerical simulations are carried out to demonstrate the performance of the developed controller compared to the state-of-the-art approach. IEEE

关键词： Asymptotic stability Delay effects Delays direct search algorithm electric vehicle aggregator Frequency control Load frequency control Lyapunov Krasovskii Functional (LKF) Power system stability Renewable energy sources robust control Stability criteria time delay

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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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Autonomous UAV Landing Approach for Marine Operations

Autonomous UAV Landing Approach for Marine Operations

引用

OCEANS

作者： André Moura José Antunes João J. Martins André Dias Alfredo Martins José M. Almeida Eduardo Silva Robotics and Autonomous Systems Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal

The use of autonomous vehicles in maritime operations is a technological challenge. In the particular case of autonomous aerial vehicles (UAVs), their application ranges from inspection and surveillance of offshore power plants, and marine life observation, to search and rescue missions. Manually landing UAVs onboard water vessels can be very challenging due to limited space onboard and wave agitation. This paper proposes an autonomous solution for the task of landing commercial multicopter UAVs with onboard cameras on water vessels, based on the detection of a custom landing platform with computer vision techniques. The autonomous landing behavior was tested in real conditions, using a research vessel at sea, where the UAV was able to detect, locate, and safely land on top of the developed landing platform.

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