2023
Autores
Mourão, RL; Gouveia, C; Sampaio, G; Retorta, F; Merckx, C; Benothman, F; Águas, A; Boto, P; Silva, CD; Milzer, G; Marzano, G; Dumont, C; Crucifix, P; Kaffash, M; Heylen, E;
Publicação
IET Conference Proceedings
Abstract
The EUniversal project, funded by the European Union, aims to establish a universal approach to the utilization of flexibility by Distribution System Operators (DSOs) and their engagement with new flexibility markets. To achieve this objective, the project team has focused on developing the Universal Market Enabling Interface (UMEI) concept. This paper presents an overview of the process of adapting grid core systems to interact with different market platforms and agents, which is a key aspect of the real-world demonstration set to take place in Portugal. © The Institution of Engineering and Technology 2023.
2023
Autores
Homayouni, SM; Fontes, DBMM; Fontes, FACC;
Publicação
PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANION
Abstract
This paper addresses the joint scheduling of production operations, transport tasks, and storage/retrieval activities in flexible job shop systems where the production operations and transport tasks can be done by one of the several resources available. Jobs need to be retrieved from storage and delivered to a load/unload area, from there, they are transported to and between the machines where their operations are processed on. Once all operations of a job are processed, the job is taken back to the load/unload area and then returned to the storage cell. Therefore, the problem under study requires, concurrently, solving job routing, machine scheduling, transport allocation, vehicle scheduling, and shuttle schedule. To this end, we propose a hybrid biased random-key genetic algorithm (BRKGA) in which the mutation operator resorts to six local search heuristics. The computational experiments conducted on a set of benchmark instances show the effectiveness of the proposed mutation operator.
2023
Autores
Teixeira, B; Carvalhais, L; Pinto, T; Vale, Z;
Publicação
2023 IEEE CONFERENCE ON ARTIFICIAL INTELLIGENCE, CAI
Abstract
The structural changes in the energy sector caused by renewable sources and digitization have resulted in an increased use of Artificial Intelligence (AI), including Machine Learning (ML) models. However, these models' black-box nature and complexity can create issues with transparency and trust, thereby hindering their interpretability. The use of Explainable AI (XAI) can offer a solution to these challenges. This paper explores the application of an XAI-based framework to analyze and evaluate a photovoltaic energy generation forecasting problem and contribute to the trustworthiness of ML solutions.
2023
Autores
Soares, RM; Nabais, M; Pereiro, TD; Dias, R; Hipólito, J; Fonte, J; Seco, LG; Menéndez Marsh, F; Neves, A;
Publicação
Estudos do Quaternario
Abstract
This study presents a new tridimensional perspective on Castelo Velho de Safara (Moura), one of the great walled settlements of the Iron Age/Roman Republic by the Guadiana River, obtained through a high-resolution survey using a drone integrated with a LiDAR sensor. The outline of the walls was defined in more detail, which meant revising the occupation area, now estimated at circa 1.36 hectares. Several unknown elements were detected, such as the entrance area and other possible defensive structures. The data obtained for the Castelo Velho de Safara demonstrate the potential of LiDAR for understanding the topographical characteristics of this type of fortified enclosure, whose structural remains are not always clear to the naked eye. © 2023, APEQ - Associacao Portuguesa para o Estudo do Quaternario. All rights reserved.
2023
Autores
Saura, JR; Palacios Marques, D; Barbosa, B;
Publicação
INTERNATIONAL JOURNAL OF ENTREPRENEURIAL BEHAVIOR & RESEARCH
Abstract
Purpose Technological advances in the last decade have caused both business and economic sectors to seek for new ways to adapt their business models to a connected data-centric era. Family businesses have also been forced to leave behind traditional strategies rooted in family stimuli and ties and to adapt their actions in digital environments. In this context, this study aims to identify major online marketing strategies, business models and technology applications developed to date by family firms. Methodology: Upon a systematic literature review, we develop a multiple correspondence analysis (MCA) under the homogeneity analysis of variance by means of alternating least squares (HOMALS) framework programmed in the R language. Based on the results, the analyzed contributions are visually analyzed in clusters. Design/methodology/approach Upon a systematic literature review, we develop an MCA under the HOMALS framework programmed in the R language. Based on the results, the analyzed contributions are visually analyzed in clusters. Findings Relevant indicators are identified for the successful development of digital family businesses classified in the following three categories: (1) digital business models, (2) digital marketing techniques and (3) technology applications. The first category consists of four digital business models: mobile marketing, e-commerce, cost per click, cost per mile and cost per acquisition. The second category includes six digital marketing techniques: search marketing (search engine optimization and search engine marketing (SEM) strategies), social media marketing, social ads, social selling, websites and online reputation optimization. Finally, the third category consists of the following aspects: digital innovation, digital tools, innovative marketing, knowledge discovery and online decision making. In addition, five research propositions are developed for further discussion and future research. Originality/value To the best of our knowledge, this study is the first to cover this research topic applying the emerging programming language R for the development of an MCA under the HOMALS framework.
2023
Autores
Machado, I; Ferreira, J; Magalhaes, C; Sousa, P; Dias, L; Santarém, D; Sousa, N; Paredes, H; Abrantes, C;
Publicação
INTERNATIONAL ANGIOLOGY
Abstract
Background: In peripheral arterial disease (PAD) patients with intermittent claudication (IC), the combination of aerobic and resistance exercises could counteract muscle loss and attenuate disease progression. This study analyzed the effects of six months of a combined exercise program on walking ability, lower limb body composition, cardiovascular risk factors, and Ankle-Brachial Index (ABI). Methods: Twenty-three patients (age 63.2 +/- 1.5 years and ABI 0.58 +/- 0.07) with PAD and IC were allocated to a control group (CG) or a supervised exercise group (SUP). Ten patients underwent six months of treadmill walking combined with resistance exercises, three times a week. The CG (N.=13) received a recommendation for walking. All patients were measured at baseline (M0), after three months (M3), and six months (M6). Results: During constant treadmill protocol, the claudication onset time/distance (COT/COD), absolute claudication time/distance (ACT/ACD), and number of pauses of overall patients significantly improved at M3 and M6. Between groups were found significant differences in COT and COD at M6 (P=0.005 and P=0.007, respectively); and in ACT and ACD at M3 (P=0.003 for both) and at M6 (P=0.005 and P=0.005, respectively), with major improvements in the SUP. Over the six months, a significant group effect was found in fat-free mass (P=0.041) and predicted muscle mass (P=0.039) of the lower ABI leg, with greater improvements in the SUP. Conclusions: A supervised exercise program that combines aerobic and resistance training improves PAD symptoms and has additional benefits for patients. Patients in the program showed improvements in walking ability, lower-limb body composition, perceived exertion, and heart rate during treadmill walking.
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