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检索条件"机构=INESC TEC - Institute for Systems and Computer Engineering- Technology and Science"

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Evaluation of different bidding strategies for a battery energy storage system performing energy arbitrage – a neural network approach

Evaluation of different bidding strategies for a battery ene...

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International Conference on European Electricity Market, EEM

作者： Pedro Santos Igor Rezende Tiago Soares Vladimiro Miranda Institute for Systems and Computer Engineering Technology and Science (INESC TEC) University of Porto Faculty of Engineering (FEUP) Porto Portugal

The rising potential for battery energy storage systems (BESS) to generate revenue in a market environment is addressed in this work, where a tool based on neural network predictions is proposed. The tool's main objective is predicting, based on historical data, the most lucrative out of three established bidding approaches for the participation of a BESS in the day-ahead energy market and thus aid the strategic bidding process of the BESS operator. Each of these bidding strategies reflects BESS’s operator approach concerning bidding frequency and the tolerated risk of loss of profit from having its bids rejected, leading to the development of a conservative (strategy A), an aggressive (strategy B), and a moderate strategy (strategy C). A case study was then used to test the tool for a full year allowing to ascertain the assertiveness of this tool in predicting the best strategy, which for this case was above 88%.

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Flexibility Modeling and Trading in Renewable Energy Communities

Flexibility Modeling and Trading in Renewable Energy Communi...

引用

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...

引用

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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Energy Allocation and Settlement in Collective Self-Consumption

Energy Allocation and Settlement in Collective Self-Consumpt...

引用

International Conference on European Electricity Market, EEM

作者： João Mello Luís Rodrigues José Villar João Saraiva INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculdade de Engenharia Universidade do Porto Porto Portugal

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

Energy allocation rules are one of the core aspects of collective self-consumption (CSC) regulations. It allows final consumers to share their surplus generation with other CSC members, while keeping their full rights as consumers, i.e., maintaining a supply contract with the retailers of their choice. Some European Union member states regulations use allocation coefficients so that local allocations are integrated with wholesale settlement and directly affect the retailers' billing. Several AC methods have been proposed so far, each one adapted to distribution system operators' settlement procedures with specific rules that can impact the benefits that each CSC member obtain. This paper analyses, assesses and compares two relevant AC methods, namely pre-delivery fixed AC and post-delivery dynamic AC, by developing a settlement formulation for a community with members with flexible assets and different opportunity costs. AC policy recommendations based on findings are provided.

关键词： Costs Force Dynamics Europe Dynamic scheduling Regulation Demand response

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Cybersecurity Challenges in Healthcare Medical Devices 1st

Cybersecurity Challenges in Healthcare Medical Devices

引用

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

引用

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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Sigma-Delta Modulation for Enhanced Underwater Optical Wireless Communication systems

Sigma-Delta Modulation for Enhanced Underwater Optical Wirel...

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International Conference on Transparent Optical Networks

作者： João H. Araújo Henrique J. Rocha Joana S. Tavares Henrique M. Salgado INESC TEC—Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculty of Engineering University of Porto Porto Portugal

This paper presents an experimental investigation of sigma-delta modulation (SDM) as a means of improving the performance of underwater optical communication systems. The study considers the impact of the key parameters of SDM, including oversampling ratio, the system’s signal-to-noise ratio, bandwidth, and optical link distance. The results of this study provide insights into the design and optimization of SDM-based underwater optical communication systems, paving the way for future research in this field. A fully digital solution, albeit operating at a lower bit rate than previously published OFDM counterparts, provides immunity against nonlinearities of the system and robustness to noise, which is relevant in harsh environments. Moreover, the proposed solution based on a first-order bandpass SDM architecture avoids the employment of a DAC at the receiver, simplifying its operation and reducing costs. An experimental investigation is carried out for the transmission of 16-QAM over SDM, and a transmission distance of 4.8 m over the underwater channel is achieved with a maximum transmission rate of 400 Mbit/s with an MER of 28 dB.

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Integrating Multimodal Perception into Ground Mobile Robots

Integrating Multimodal Perception into Ground Mobile Robots

引用

IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Ricardo B. Sousa Héber Miguel Sobreira João G. Martins Paulo G. Costa Manuel F. Silva António Paulo Moreira Faculty of Engineering University of Porto (FEUP) Porto Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal ISEP Polytechnic of Porto Porto Portugal

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Multimodal perception systems enhance the robustness and adaptability of autonomous mobile robots by integrating heterogeneous sensor modalities, improving long-term localisation and mapping in dynamic environments and human-robot interaction. Current mobile platforms often focus on specific sensor configurations and prioritise cost-effectiveness, possibly limiting the flexibility of the user to extend the original robots further. This paper presents a methodology to integrate multimodal perception into a ground mobile platform, incorporating wheel odometry, 2D laser scanners, 3D Light Detection and Ranging (LiDAR), and RGBD cameras. The methodology describes the electronics design to power devices, firmware, computation and networking architecture aspects, and mechanical mounting for the sensory system based on 3D printing, laser cutting, and bending metal sheet processes. Experiments demonstrate the usage of the revised platform in 2D and 3D localisation and mapping and pallet pocket estimation applications. All the documentation and designs are accessible in a public repository.

关键词： Laser radar Robot vision systems Wheels Three-dimensional printing Cameras Distance measurement Robustness Mobile robots Laser beam cutting Autonomous robots

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GDBN, A Customer-centric Digital Platform to Support the Value Chain of Flexibility Provision

GDBN, A Customer-centric Digital Platform to Support the Val...

引用

International Conference on European Electricity Market, EEM

作者： Fábio Coelho Luís Rodrigues João Mello José Villar Ricardo Bessa INESC TEC - Institute for Systems and Computer Engineering Technology and Science Universidade do Minho Faculdade de Engenharia da Universidade do Porto Portugal

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

This paper proposes an original framework for a flexibility-centric value chain and describes the pre-specification of the Grid Data and Business Network (GDBN), a digital platform to provide support to the flexibility value chain activities. First, it outlines the structure of the value chain with the most important tasks and actors in each activity. Next, it describes the GDBN concept, including stakeholders’ engagement and conceptual architecture. It presents the main GDBN services to support the flexibility value chain, including, matching consumers and assets and service providers, assets installation and operationalization to provide flexibility, services for energy communities and services, for consumers, aggregators, and distribution systems operators, to participate in flexibility markets. At last, it details the workflow and life cycle management of this platform and discusses candidate business models that could support its implementation in real-life scenarios.

关键词： Procurement Renewable energy sources Europe Focusing Regulation Stakeholders Task analysis

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Classification of endoscopic capsule pathologies using Multiple Instance Learning methods 16

Classification of endoscopic capsule pathologies using Multi...

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16th International Conference on ENTERprise Information systems, CENTERIS 2024 - 12th International Conference on Project MANagement, ProjMAN 2024 - 14th International Conference on Health and Social Care Information systems and technologies, HCist 2024

作者： Moreira, Vitor Machado, Eduardo Barbosa, Dalila Salgado, Marta Braz, Geraldo Cunha, António University of Trás-os-Montes e Alto Douro Vila Real5001-801 Portugal INESC TEC Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal Centro Hospitalar Universitário de Santo António Porto Portugal MA São Luís Brazil

This article presents an investigation into the classification of endoscopic capsule pathologies using Multiple Instance Learning (MIL) methods in conjunction with deep neural network architectures. The primary problem addressed in this study is the accurate and efficient detection of gastrointestinal pathologies, a significant challenge in medical diagnostics that can have a profound impact on patient outcomes. The use of endoscopic capsules is particularly important as they provide a minimally invasive method to capture comprehensive images of the gastrointestinal tract, facilitating early detection of conditions such as ulcers, polyps, bleeding, and Crohn's disease. Specifically, we explore three variants of MIL-Max, Mean, and Attention-for analysing sets of images captured by the endoscopic capsule. MIL was employed because it effectively handles scenarios where individual image instances are not explicitly labelled but are grouped in bags with known labels, making it suitable for the complex nature of endoscopic data. Furthermore, MIL has not yet been extensively applied in this modality, highlighting the innovative aspect of our approach. In addition, we evaluated the performance of three convolutional neural network architectures-VGG16, ResNet50, and DenseNet121-in the classification task. The results indicate that the combination of MIL methods and deep neural network architectures offers a promising approach to the detection and classification of gastrointestinal pathologies, with significant improvements in diagnostic accuracy and efficiency. © 2025 The Author(s).

关键词： Endoscopy

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