2018
Autores
Fernandes, V; Moreira, AC; Daniel, D;
Publicação
Socio-Economic Development
Abstract
Social entrepreneurship is emerging as an innovative approach for dealing with complex social and environmental needs, and is an important lever for the development of a sustainable society. Social entrepreneurship and related concepts have had a growing attention in the academy, giving rise to dissimilar approaches in the United States of America and in Western Europe. Despite the importance of the Third Sector in Portugal, it has been difficult to set ideal definitions for social entrepreneurship, social entrepreneur and social enterprises. By means of a qualitative study involving four Portuguese social ventures, this chapter identifies contemporary socio-cultural and economic factors that foster social innovation and intervention in Portugal, and contributes to understand the role of social entrepreneur in this context. © 2025 Elsevier B.V., All rights reserved.
2018
Autores
Gazafroudi A.S.; Prieto-Castrillo F.; Pinto T.; Corchado J.M.;
Publicação
2018 International Conference on Smart Energy Systems and Technologies, SEST 2018 - Proceedings
Abstract
Increasing penetration of distributed energy resources in power distribution systems and appearing the flexible behavior of end-users based on demand response programs make the distribution layer of the power systems more active. In this way, energy transaction management through a decentralized manner could be an appropriate solution to improve the efficiency of energy trading in the distribution power networks. This paper proposes a decentralized method to manage energy flexibility by consumers based on a bottom-up approach in distributed power systems. Also, a 33-bus distribution network is considered to assess the performance of our proposed decentralized energy flexibility management model based on impacts of flexible behaviors of end-user and uncertainty of distribution lines to flow energy in the power network.
2018
Autores
Paiva, LT; Fontes, FACC;
Publicação
ENERGIES
Abstract
This article addresses the problem of optimizing electrical power generation using kite power systems (KPSs). KPSs are airborne wind energy systems that aim to harvest the power of strong and steady high-altitude winds. With the aim of maximizing the total energy produced in a given time interval, we numerically solve an optimal control problem and thereby obtain trajectories and controls for kites. Efficiently solving these optimal control problems is crucial when the results are used in real-time control schemes, such as model predictive control. For this highly nonlinear problem, we derive continuous-time models-in 2D and 3D-and implement an adaptive time-mesh refinement algorithm. By solving the optimal control problem with such an adaptive refinement strategy, we generate a block-structured adapted mesh which gives results as accurate as those computed using fine mesh, yet with much less computing effort and high savings in memory and computing time.
2018
Autores
Almeida, JB; Cunha, A; Macedo, N; Pacheco, H; Proença, J;
Publicação
PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES
Abstract
Our department has long been an advocate of the functional-first school of programming and has been teaching Haskell as a first language in introductory programming course units for 20 years. Although the functional style is largely beneficial, it needs to be taught in an enthusiastic and captivating way to fight the unusually high computer science drop-out rates and appeal to a heterogeneous population of students. This paper reports our experience of restructuring, over the last 5 years, an introductory laboratory course unit that trains hands-on functional programming concepts and good software development practices. We have been using game programming to keep students motivated, and following a methodology that hinges on test-driven development and continuous bidirectional feedback. We summarise successes and missteps, and how we have learned from our experience to arrive at a model for comprehensive and interactive functional game programming assignments and a general functionally-powered automated assessment platform, that together provide a more engaging learning experience for students. In our experience, we have been able to teach increasingly more advanced functional programming concepts while improving student engagement.
2018
Autores
Neves, PP; Morgado, L; Zagalo, N;
Publicação
JOURNAL OF SCIENCE AND TECHNOLOGY OF THE ARTS
Abstract
This paper presents a novel descriptive model for agency in videogames as communication. Literature pertaining to interactive works including videogames has identified the need to overcome dyadic perspectives of communication in such works. Research specifically to do with agency has called for agency to no longer be confused with freedom of action, for an integrated perspective of the player and the system, and for that relationship to be viewed as a conversation. The transactional model in this paper achieves this by proposing a nested hierarchy of levels of communication that operate as an implicit contract, negotiated between the system and the player, where the object of the transaction is bio-costs, effected through the signalling of the attainability of understandings. The paper describes research antecedents, a research agenda, the basis for the model, the model itself, examples of how the model can be used to describe videogame designs, and future research.
2018
Autores
Rebelo, A; Oliveira, T; Correia, ME; Cardoso, JS;
Publicação
CIARP
Abstract
Currently the breakthroughs in most computer vision problems have been achieved by applying deep learning methods. The traditional methodologies that used to successfully discriminate the data features appear to be overwhelmed by the capabilities of learning of the deep network architectures. Nevertheless, many recent works choose to integrate the old handcrafted features into the deep convolutional networks to increase even more their impressive performance. In fingerprint recognition, the minutiae are specific points used to identify individuals and their extraction is a crucial module in a fingerprint recognition system. This can only be emphasized by the fact that the US Federal Bureau of Investigation (FBI) sets as a threshold for a positive identification a number of 8 common minutiae. Deep neural networks have been used to learn possible representations of fingerprint minutiae but, however surprisingly, in this paper it is shown that for now the best choice for an automatic minutiae extraction system is still the traditional road map. A comparison study was conducted with state-of-the-art methods and the best results were achieved by handcraft features.
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