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Publications

2023

Capacity Management in Smart Grids Using Greedy Randomized Adaptive Search Procedure and Tabu Search

Authors
Serrano, HDM; Reiz, C; Leite, JB;

Publication
PROCESSES

Abstract
Over time, distribution systems have progressed from small-scale systems to complex networks, requiring modernization to adapt to these increasing levels of active loads and devices. It is essential to manage the capacity of distribution networks to support all these new technologies. This work, therefore, presents a method for evaluating the impact of optimal allocation and sizing of DGs and load shedding for response demand programs on distribution networks to improve the reliability and financial performance of electric power systems. The proposed optimization tool uses the Greedy Randomized Adaptive Search Procedure and Tabu Search algorithms. The combined optimization of DG allocation simultaneously with load shedding, reliability indices, load transference, and the possibility of islanded operation significantly improves the quality of the planning proposals obtained by the developed method. The results demonstrate the efficiency and robustness of the proposed method, improving the voltage profile by up to 2.02%, relieving the network capacity, and increasing the load restoration capability and reliability. Statistical analysis is also carried out to highlight the performance of the proposed methodology.

2023

A Quantitative PED Definition with Contextual Targets

Authors
Schneider, S; Zelger, T; Sengl, D; Baptista, J;

Publication

Abstract
This paper presents the goals and components of a quantitative energy balance assessment framework to define PEDs flexibly in three important contexts: the context of the district's density and RES potential, the context of a district's location, induced mobility and the context of the dis-trict's future environment and its decarbonized energy demand or supply. It starts by introducing the practical goals of this definition approach: achievable, yet sufficiently ambitious to be inline with Paris 2050 for most urban and rural Austrian district typologies. It goes on to identify the main design parts of the definition: system boundaries, balancing weights and balance targets and argue how they can be linked to the definition goals in detail. In particular we specify three levels of system boundaries and argue their individual necessity: operation, including everyday mobili-ty, including embodied energy and emissions. It argues that all three pillars of PEDs, energy effi-ciency, onsite renewables and energy flexibility can be assessed with the single metric of a prima-ry energy balance when using carefully designed, time-dependent conversion factors. Finally, it is discussed how balance targets can be interpreted as information and requirements from the sur-rounding energy system, which we identify as a "context factor". Three examples of such context factors, each corresponding to the balance target of one of the previously defined system bounda-ries operation, mobility and embodied emissions are presented: Density (as a context of opera-tion), sectoral energy balances and location (as a context for mobility) and an outlook of a person-al emission budgets (as a context for embodied emissions). Finally, the proposed definition framework is applied to seven distinct district typologies in Austria and discussed in terms of its design goals.

2023

Differences in Trapezius Muscle H-Reflex between Asymptomatic Subjects and Symptomatic Shoulder Pain Subjects

Authors
Melo, ASC; Taylor, JL; Ferreira, R; Cunha, B; Ascencao, M; Fernandes, M; Sousa, V; Cruz, EB; Vilas-Boas, JP; Sousa, ASP;

Publication
SENSORS

Abstract
In chronic shoulder pain, adaptations in the nervous system such as in motoneuron excitability, could contribute to impairments in scapular muscles, perpetuation and recurrence of pain and reduced improvements during rehabilitation. The present cross-sectional study aims to compare trapezius neural excitability between symptomatic and asymptomatic subjects. In 12 participants with chronic shoulder pain (symptomatic group) and 12 without shoulder pain (asymptomatic group), the H reflex was evoked in all trapezius muscle parts, through C3/4 nerve stimulation, and the M-wave through accessory nerve stimulation. The current intensity to evoke the maximum H reflex, the latency and the maximum peak-to-peak amplitude of both the H reflex and M-wave, as well as the ratio between these two variables, were calculated. The percentage of responses was considered. Overall, M-waves were elicited in most participants, while the H reflex was elicited only in 58-75% or in 42-58% of the asymptomatic and symptomatic participants, respectively. A comparison between groups revealed that the symptomatic group presented a smaller maximum H reflex as a percentage of M-wave from upper trapezius and longer maximal H reflex latency from the lower trapezius (p < 0.05). Subjects with chronic shoulder pain present changes in trapezius H reflex parameters, highlighting the need to consider trapezius neuromuscular control in these individuals' rehabilitation.

2023

Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Authors
Koprinska, I; Mignone, P; Guidotti, R; Jaroszewicz, S; Fröning, H; Gullo, F; Ferreira, PM; Roqueiro, D; Ceddia, G; Nowaczyk, S; Gama, J; Ribeiro, R; Gavaldà, R; Masciari, E; Ras, Z; Ritacco, E; Naretto, F; Theissler, A; Biecek, P; Verbeke, W; Schiele, G; Pernkopf, F; Blott, M; Bordino, I; Danesi, IL; Ponti, G; Severini, L; Appice, A; Andresini, G; Medeiros, I; Graça, G; Cooper, L; Ghazaleh, N; Richiardi, J; Saldana, D; Sechidis, K; Canakoglu, A; Pido, S; Pinoli, P; Bifet, A; Pashami, S;

Publication
Communications in Computer and Information Science

Abstract

2023

Interpreting Deep Machine Learning Models: An Easy Guide for Oncologists

Authors
Amorim, JP; Abreu, PH; Fernandez, A; Reyes, M; Santos, J; Abreu, MH;

Publication
IEEE REVIEWS IN BIOMEDICAL ENGINEERING

Abstract
Healthcare agents, in particular in the oncology field, are currently collecting vast amounts of diverse patient data. In this context, some decision-support systems, mostly based on deep learning techniques, have already been approved for clinical purposes. Despite all the efforts in introducing artificial intelligence methods in the workflow of clinicians, its lack of interpretability - understand how the methods make decisions - still inhibits their dissemination in clinical practice. The aim of this article is to present an easy guide for oncologists explaining how these methods make decisions and illustrating the strategies to explain them. Theoretical concepts were illustrated based on oncological examples and a literature review of research works was performed from PubMed between January 2014 to September 2020, using deep learning techniques, interpretability and oncology as keywords. Overall, more than 60% are related to breast, skin or brain cancers and the majority focused on explaining the importance of tumor characteristics (e.g. dimension, shape) in the predictions. The most used computational methods are multilayer perceptrons and convolutional neural networks. Nevertheless, despite being successfully applied in different cancers scenarios, endowing deep learning techniques with interpretability, while maintaining their performance, continues to be one of the greatest challenges of artificial intelligence.

2023

Global Analysis of COP Excursion for Stabilometry Assessment of Impulse Phase on Standard Maximum Vertical Jump

Authors
Rodrigues, C; Correia, M; Abrantes, J; Rodrigues, M; Nadal, J;

Publication
Lecture Notes in Bioengineering

Abstract
This study presents and applies global metrics for the analysis of the center of pressure (COP) excursion during impulse phases at different standard maximum vertical jump (MVJ) with long, short and no countermovement (CM) at countermovement jump (CMJ), drop jump (DJ) and squat jump (SJ) expanding COP analysis from static to dynamic condition of CM in association with lower limb muscle stretch–shortening cycle (SSC) and complementing previous studies on time structural analysis of COP excursion during impulse phase at standard MVJ. Whereas literature is abundant on COP excursion at gait, run and orthostatic standing position, there is a lack of studies on COP analysis at standard MVJ with an open issue on its contribution to long, short and no CM performance. Fifty-four trial tests were assessed with the selection of the best CMJ, DJ and SJ for each subject based on vertical flight height hflight. During trial tests ground reaction forces (GRF) and force moments were acquired and the COP coordinates were computed during the impulse phases. COP stabilograms and statokinesigrams were plotted and global metrics were computed namely the COPxA antero-posterior and COPyA mediolateral amplitudes of COP excursion, mean radial distance R, the length L of the path and the average velocity v during COP excursion. Statistical significative differences were detected at 5% significance, with higher mean COPxA than COPyA and higher mean COP global metrics at CMJ than SJ both higher than DJ, with DJ higher velocity of COP excursion than CMJ both higher than SJ. Global correlational analysis presented a positive linear association of COP metrics with hflight whereas at segmented MVJ this association wasn’t detected, thus rejecting the negative impact of larger COP excursion on MVJ performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

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