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Power tech Conference

作者： Fabian Heymann Pablo Duenas Filipe Joel Soares Vladimiro Miranda Martin Rüdisüli Faculty of Engineering University of Porto Porto Portugal Massachussetts Institute of Technology MIT Energy Initiative Cambridge MA USA CPES INESC TEC Porto Portugal CPES/ Faculty of Engineering INESC TEC/ University of Porto Porto Portugal Urban Energy Systems Lab Swiss Federal Laboratories for Materials Science and Technology (Empa) Dübendorf Switzerland

Recent studies found that the adoption of distributed energy resources (DER) tends to cluster spatially and temporally which has significant implications for distribution network planning. Currently, residential DER adoption is mostly driven by public support schemes, also called incentive designs. Therefore, changes in those incentive designs will result in alternative spatiotemporal DER adoption patterns that affect distribution networks differently. Consequently, distribution network operators urgently need to understand the effects of energy policy changes on the spatial distribution of DER to guide network expansion based on realistic scenarios. The presented work and tool allow network operators to plan network expansion with robustness under future incentive design changes.

关键词： Graphical models Substations Tariffs Distribution networks Tools Robustness Spatiotemporal phenomena

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DC Microgrid Energy Management System Containing Photovoltaic Sources Considering Supercapacitor and Battery Storages

DC Microgrid Energy Management System Containing Photovoltai...

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International Conference on Smart Energy systems and technologies (SEST)

作者： Mohammad Amin Jarrahi Farzad Roozitalab Mohammad Mehdi Arefi Mohammad Sadegh Javadi João P.S. Catalão School of Electrical and Computer Engineering Shiraz University Shiraz Iran School of Industrial and Information Engineering Politecnico di Milano Univesity Milan Italy Insitute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal Faculty of Engineering of the University of Porto (FEUP) Porto Portugal

ISBN: (数字)9781728147017

ISBN: (纸本)9781728147024

The tendency to use renewable energies in DC microgrids (MGs) has been increased in the past decades. Due to the unpredictable behavior of renewable resources, it is vital to utilize energy storage resources in the MG structure. The generation sources and storages in DC MGs should be chosen in order to meet the maximum demand in both grid-connected and islanded mode. Also, penetration of power electronic based devices is essential to connect these resources to the network. The control of these devices are another challenge in this regard. So, a proper configuration along with an efficient control approach is needed for development of DC MGs. In this paper, a new structure for DC MG is presented which includes solar photovoltaic (PV) as generation sources and supercapacitor and battery as storages. Furthermore, an innovative control method based on voltage variations is introduced for the proposed structure. It is shown that simultaneous usage of battery and supercapacitor improves the performance of the MG in handling the abrupt load changes in the both grid-connected and islanded mode operations. To evaluate the performance of the proposed structure and control algorithm, different conditions are simulated in MATLAB/Simulink software and the results are presented. The results confirm a high degree of performance for proposed structure and control method.

关键词： Batteries Voltage control Supercapacitors Energy management Switches

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Making a Robot Dance to Diverse Musical Genre in Noisy Environments

Making a Robot Dance to Diverse Musical Genre in Noisy Envir...

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Joao Lobato Oliveira Keisuke Nakamura Thibault Langlois Fabien Gouyon Kazuhiro Nakadai Angelica Lim Luis Paulo Reis Hiroshi G. Okuno Artificial Intelligence and Computer Science Laboratory (LIACC) - FEUP Porto Portugal Honda Research Institute Japan Co. Ltd. Saitama Japan Science Faculty of the University of Lisbon (FCUL) Lisbon Portugal Institute for Systems and Computer Engineering of Science and Technology (INESC TEC) Porto Portugal Department of Intelligence Science and Technology Graduate School of Informatics Kyoto University Kyoto Japan

ISBN: (纸本)9781479969357

In this paper we address the problem of musical genre recognition for a dancing robot with embedded microphones capable of distinguishing the genre of a musical piece while moving in a real-world scenario. For this purpose, we assess and compare two state-of-the-art musical genre recognition systems, based on Support Vector Machines and Markov Models, in the context of different real-world acoustic environments. In addition, we compare different preprocessing robot audition variants (single channel and separated signal from multiple channels) and test different acoustic models, learned a priori, to tackle multiple noise conditions of increasing complexity in the presence of noises of different natures (e.g., robot motion, speech). The results with six different musical genres suggest improved results, in the order of 43.6pp for the most complex conditions, when recurring to Sound Source Separation and acoustic models trained in similar conditions to the testing scenarios. A robot dance demonstration session confirms the applicability of the proposed integration for genre-adaptive dancing robots in real-world noisy environments.

关键词： Noisy environment Dancing Source separation Robot Acoustic models MULTICHANNEL Support Vector Network Environments

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Interactive segmentation via deep learning and B-spline explicit active surfaces

arXiv

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arXiv 2021年

作者： Williams, Helena Pedrosa, João Cattani, Laura Housmans, Susanne Vercauteren, Tom Deprest, Jan D'hooge, Jan Department of Obstetrics and Gynaecology University Hospitals Leuven Belgium INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Department of Cardiovascular Sciences KU Leuven Belgium

Automatic medical image segmentation via convolutional neural networks (CNNs) has shown promising results. However, they may not always be robust enough for clinical use. Sub-optimal segmentation would require clinician’s to manually delineate the target object, causing frustration. To address this problem, a novel interactive CNN-based segmentation framework is proposed in this work. The aim is to represent the CNN segmentation contour as B-splines by utilising B-spline explicit active surfaces (BEAS). The interactive element of the framework allows the user to precisely edit the contour in real-time, and by utilising BEAS it ensures the final contour is smooth and anatomically plausible. This framework was applied to the task of 2D segmentation of the levator hiatus from 2D ultrasound (US) images, and compared to the current clinical tools used in pelvic floor disorder clinic (4DView, GE Healthcare;Zipf, Austria). Experimental results show that: 1) the proposed framework is more robust than current state-of-the-art CNNs;2) the perceived workload calculated via the NASA-TLX index was reduced more than half for the proposed approach in comparison to current clinical tools;and 3) the proposed tool requires at least 13 seconds less user time than the clinical tools, which was significant (p=0.001). © 2021, CC BY-NC-ND.

关键词： Interpolation

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Investigating the Perception of the Elderly Population About Comfort, Safety and Security When Using Active Modes of Transport 11th

Investigating the Perception of the Elderly Population Ab...

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11th EAI International Conference on Wireless Mobile Communication and Healthcare, MobiHealth 2022

作者： Felício, Soraia Hora, Joana Ferreira, Marta Campos Abrantes, Diogo Luna, Fábio Silva, Jorge Coimbra, Miguel Galvão, Teresa Faculty of Engineering of the University of Porto Rua Dr. Roberto Frias s/n Porto4200-465 Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science R. Dr. Roberto Frias s/n Porto4200-465 Portugal Faculty of Sciences of the University of Porto Rua do Campo Alegre s/n Porto4169-007 Portugal Bosch Security Systems R. Pardala Zona Ind. de Ovar Estrada Nacional 109 Aptd. 653 Aveiro Portugal

ISBN: (纸本)9783031320286

Promoting active modes of transport, such as walking and cycling, has a positive impact on environmental sustainability and the health and well-being of citizens. This study explores the elderly population’s perception of comfort, safety and security when using active modes of transport. It begins with a systematic review of the literature considering research works that relate to active travel, the elderly population, and random forest. Then a questionnaire was applied to 653 participants and the results were analyzed. This analysis consisted of using statistics to evaluate the socio-demographic profile, the preferences regarding the use of active modes of this population, and the importance given to each dimension: comfort, safety, distance, and time, comparing these indicators through the Wilcoxon Rank Sum test and the Random Forest algorithm. The results showed that people over 56 years old walk as much as younger people. Furthermore, the importance given by this group of people to indicators referring to active modes is related to safety and security, distance, time, and comfort. The statistical results of the Wilcoxon Rank Sum test indicate the most important indicators: Adequate Travel Distance & Time and Existence of Commercial Areas by age group [0–55], and Absence of Allergenics and Existence of Green Areas by age group [56+]. Finally, the Random Forest algorithm provides the relative importance for both age groups, [0–55] and [56+], where the indicators that stand out in the [56+] age group, which is the focus of our study, are air quality, adequate travel distance & time, adequate crowd density, adequate thermal sensation, absence of allergenic, good street illumination level, adequate traffic volume, and adequate noise level. © 2023, ICST institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Air quality

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Pallet and Pocket Detection Based on Deep Learning techniques

Pallet and Pocket Detection Based on Deep Learning Technique...

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Iberian Robotics Conference (ROBOT)

作者： Daniele Caldana Artur Cordeiro João Pedro Souza Ricardo B. Sousa Paulo M. Rebelo António Joaquim Silva Manuel F. Silva CRIIS - Centre for Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Portugal Faculty of Engineering University of Porto (FEUP) Portugal School of Science and Technology University of Trás-os-Montes e Alto Douro (UTAD) Portugal Seúibal Industrial Complex The Navigator Company Portugal ISEP Polytechnic of Porto Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

The high level of precision and consistency required for pallet detection in industrial environments and logistics tasks is a critical challenge that has been the subject of extensive research. This paper proposes a system for detecting pallets and its pockets using the You Only Look Once (YOLO) v8 Open Neural Network Exchange (ONNX) model, followed by the segmentation of the pallet surface. On the basis of the system a pipeline built on the ROS Action Server whose structure promotes modularity and ease of implementation of heuristics. Additionally, is presented a comparison between the YOLOv5 and YOLOv8 models in the detection task, trained with a customised dataset from a factory environment. The results demonstrate that the pipeline can consistently perform pallet and pocket detection, even when tested in the laboratory and with successive 3D pallet segmentation. When comparing the models, YOLOv8 achieved higher average metric values, with YOLOv8m providing better detection performance in the laboratory setting.

关键词： YOLO Measurement Three-dimensional displays Pipelines Neural networks Production facilities Servers Pallets Robots Logistics

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Optical signal recording of cellular activity in optogenetic stimulation of human pulp dental cells using a twin-core fiber-based Mach-Zehnder interferometer biosensor

arXiv

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arXiv 2024年

作者： Akbari, Faezeh Zibaii, Mohammad Ismail Nezhad, Sara Chavoshi Layeghi, Azam Dargahi, Leila Frazao, Orlando Department of Biomedical Engineering University of Kentucky LexingtonKY40504 United States Laser and Plasma Research Institute Shahid Beheshti University Tehran Iran Neuroscience research Center Shahid Beheshti University Tehran Iran INESC TEC Institute for Systems and Computer Engineering Technology and Science Porto Portugal

This paper introduces an innovative two-core fiber (TCF) optic sensor employing a Mach-Zehnder interferometer (MZI) to monitor the optogenetic response of light-sensitive human dental pulp stem cells (hDPSCs). The in-fiber MZI, formed using a segment of TCF optic, detects refractive index (RI) changes in the surrounding medium. The sensor utilizes the evanescent wave of one core as the sensing arm, necessitating a thin cladding achieved through one-sided chemical etching. This design allows the sensor to detect subtle alterations in the RI of the environment by observing displacements in the interference spectrum. The optogenetic stimulation of light-sensitive cells induces variations in ion concentrations, leading to a corresponding change in refractive index. The fabricated sensor, with a peak sensitivity of 675.74 nm/RIU within the RI range of 1.39-1.43, can detect these changes. A computer simulation validated the sensitivity and optimized fabrication parameters, exhibiting satisfactory agreement with experimental results. Spectrum displacements were recorded for both light-sensitive hDPSCs and regular hDPSCs (as a control test). Results from the experiment, analyzed and compared using data analysis software, revealed that 473 nm blue light effectively stimulated light-sensitive hDPSCs. Notably, the proposed sensor, a novel structure, demonstrated its capability to detect RI changes in the cell medium during optogenetic applications. © 2024, CC BY-NC-ND.

关键词： Refractive index

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Optimal Participation of Virtual Power Plants in the Electricity Market Considering Multi-Energy systems

Optimal Participation of Virtual Power Plants in the Electri...

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International Conference on Smart Energy systems and technologies (SEST)

作者： Mohammad Sadegh Javadi Gerardo J. Osório André S. Parente João P.S. Catalão Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal Portucalense University Infante D. Henrique (UPT) / REMIT Porto Portugal Faculty of Engineering University of Porto Porto Portugal Research Center for Systems and Technologies (SYSTEC) Advanced Production and Intelligent Systems Associate Laboratory (ARISE) Faculty of Engineering University of Porto Porto Portugal

The growth and modernization of the power system are the keys to enabling economic progress. The deregulation, added to the new emerging production technologies, conversion, and storage, triggered a change in the way of managing the power system worldwide. This work analyses the optimal dispatch of a virtual power plant (VPP) with active participation in the electricity market, considering multi-energy systems. The objective is to minimize the total operating cost of the power plant. The power plant is fed by two external networks: electrical and natural gas. The VPP is composed of energy production, conversion, and storage technologies, also considering the integration of a wind turbine and a set of electric vehicles (EVs). In addition to the Grid-to-Vehicle (G2V) charging, the advantage of Vehicle-to-Grid (V2G) technology is also verified, which allows the injection of power into the grid through the vehicles and Vehicle-to-Load (V2L) technology, enabling EVs to contribute to the satisfaction of the electrical load, reducing the costs, showing the advantages as well of EVs' integration in the VPP under analysis.

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A Non-Parametric LPV Approach to the Indentification of Linear Periodic systems ⁎

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IFAC-PapersOnLine 2021年第8期54卷 13-19页

作者： Paulo Lopes dos Santos T-P Azevedo Perdicoúlis INESC TEC - Institute for Systems and Computer Engineering Technology and Science and FEUP - Faculty of Engineering University of Porto Rua Dr Roberto Frias s/n 4200-464 Porto Portugal Universidade de Trás-os-Montes e Alto Douro Vila Real and Instituto de Sistemas e Robótica (ISR) Coimbra both in Portugal

A non-parametric identification algorithm is proposed to identify Linear Time Periodic (LTP) systems. The period is unknown and can be any real positive number. The system is modelled as an ARX Linear Parameter Varying (LPV) system with a virtual scheduling signal consisting of two orthogonal sinusoids (a sine and a cosine) with a period equal to the system period. Hence, the system parameters are polynomial functions of the scheduling vector. As these polynomials may have infinite degree, a non-parametric model is adopted to describe the LPV system. This model is identified by a Gaussian Process Regression (GPR) algorithm where the system period is a hyperparameter. The performance of the proposed identification algorithm is illustrated through the identification of a simulated LTP continuous system described by a state-space model. The ARX-LTP discrete-time model estimated in the noiseless case was taken as the true model.

关键词： System Identification LTP systems LPV systems Arx Gaussian Process Regression Kernel

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A Kernel Principal Component Regressor for LPV System Identification ⁎

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IFAC-PapersOnLine 2019年第28期52卷 7-12页

This article describes a Kernel Principal Component Regressor (KPCR) to identify Auto Regressive eXogenous (ARX) Linear Parmeter Varying (LPV) models. The new method differs from the Least Squares Support Vector Machines (LS-SVM) algorithm in the regularisa-tion of the Least Squares (LS) problem, since the KPCR only keeps the principal components of the Gram matrix while LS-SVM performs the inversion of the same matrix after adding a regularisation factor. Also, in this new approach, the LS problem is formulated in the primal space but it ends up being solved in the dual space overcoming the fact that the regressors are unknown. The method is assessed and compared to the LS-SVM approach through 2 Monte Carlo (MC) experiments. Every experiment consists of 100 runs of a simulated example, and a different noise level is used in each experiment, with Signal to Noise Ratios of 20db and 10db, respectively. The obtained results are twofold, first the performance of the new method is comparable to the LS-SVM, for both noise levels, although the required calculations are much faster for the KPCR. Second, this new method reduces the dimension of the primal space and may convey a way of knowing the number of basis functions required in the Kernel. Furthermore, having a structure very similar to LS-SVM makes it possible to use this method in other types of models, e.g. the LPV state-space model identification.

关键词： System Identification LPV systems Arx Kernel Kernel Regression Least squares Principal Components Least Squares Support Vector Machines

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