2021
Authors
Lourenço, J; Teixeira, J; Carvalho, P; Pádua, L; Adao, T; Peres, E; Sousa, JJ;
Publication
2021 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM IGARSS
Abstract
The development and implementation of a virtual environment that aims to support farmers in managing their land and crops in a more sustainable way is presented in this paper. It allows both textual and 3D visualization of crop-related biophysical parameters, such as height, volume and length. Moreover, the latter can be dynamically altered according to various criteria. A case study was conducted in a Portuguese vineyard. The application was developed using the Unity software, while a real agricultural data feed was provided by mySense interface. The virtual environment can be seen as a valuable decision support system to assist farmers.
2021
Authors
Moreira, AC;
Publication
CUADERNOS DE GESTION
Abstract
This special issue of the Management Letters/Cuadernos de Gestion is dedicated, on one hand, to presenting those articles that are included as part of the special issue on innovation and, on the other hand, to disclose the top priorities on innovation research taking into account challenging topics we are witnessing in the business world that fuel research creativity. The first part of this editorial presents the four articles that make up this special issue on innovation. The second part of this editorial addresses the main topics of the shifting landscape innovation faces: business model innovation, artificial intelligence, Industry 4.0, Internet of things, innovation ecosystems and gamification.
2021
Authors
Almeida, F;
Publication
Entrepreneurship
Abstract
2021
Authors
Jalali, SMJ; Khodayar, M; Khosravi, A; Osorio, GJ; Nahavandi, S; Catalao, JPS;
Publication
2021 21ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2021 5TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC/I&CPS EUROPE)
Abstract
This paper presents a deep generative model for capturing the conditional probability distribution of future wind power given its history by modeling and pattern recognition in a dynamic graph. The dynamic nodes show the wind sites while the dynamic edges reflect the correlation between the nodes. We propose a scalable optimization model, which is theoretically proved to catch distributions at nodes of the graph, contrary with all learning formulations in the sector of discriminatory pattern recognition. The density of probabilities for each node can be used as samples in our framework. This probabilistic deep convolutional Auto-encoder (PDCA), is based on the deep learning of localized first-order approximation of spectral graph convolutions, a novel evolutionary algorithm and the Bayesian variational inference concepts. The presented generative model is used for the spatiotemporal probabilistic wind power problem in a wide 25 wind sites located in California, the USA for up to 24 hr ahead prediction. The experimental findings reveal that our proposed model outperforms other competitive temporal and spatio-temporal algorithms in terms of reliability, sharpness, and continuous ranked probability score.
2021
Authors
Almeida, F;
Publication
Journal of Open Innovation: Technology, Market, and Complexity
Abstract
This study aimed to explore the diversity of open-innovation practices that are adopted in Portuguese SMEs considering the outside-in, inside-out, and coupled paradigms. A quantitative study was carried out considering a sample of 187 Portuguese SMEs. The findings revealed that these organizations favored the adoption of the outside-in paradigm. The inside-out model was the least relevant, especially for smaller companies (i.e., small and micro-companies). The most adopted outside-in practices were the integration of external knowledge from suppliers and clients; in the inside-out model, licensing processes were more important; while in the coupled model, joint ventures and network consortiums stood out. The increase in the innovation capacity of these organizations was highlighted as the most relevant benefit, while the lack of resources and difficulties in integrating knowledge emerged as challenges. This study is especially relevant for the establishment of public-support policies that promote the involvement of Portuguese SMEs in open-innovation processes. © 2021 by the author. Licensee MDPI, Basel, Switzerland.
2021
Authors
Diogo, CC; Fonseca, B; de Almeida, FSM; da Costa, LM; Pereira, JE; Filipe, V; Couto, PA; Geuna, S; Armada da Silva, PA; Mauricio, AC; Varejao, ASP;
Publication
CIENCIA RURAL
Abstract
Analysis of locomotion is often used as a measure for impairment and recovery following experimental peripheral nerve injury. Compared to rodents, sheep offer several advantages for studying peripheral nerve regeneration. In the present study, we compared for the first time, two-dimensional (2D) and three-dimensional (3D) hindlimb kinematics during obstacle avoidance in the ovine model. This study obtained kinematic data to serve as a template for an objective assessment of the ankle joint motion in future studies of common peroneal nerve (CP) injury and repair in the ovine model. The strategy used by the sheep to bring the hindlimb over a moderately high obstacle, set to 10% of its hindlimb length, was pronounced knee, ankle and metatarsophalangeal flexion when approaching and clearing the obstacle. Despite the overall time course kinematic patterns about the hip, knee, ankle, and metatarsophalangeal were identical, we found significant differences between values of the 2D and 3D joint angular motion. Our results showed that the most apparent changes that occurred during the gait cycle were for the ankle (2D-measured STANCEmax: 157 +/- 2.4 degrees vs. 3D-measured STANCEmax: 151 +/- 1.2 degrees; P<.05) and metatarsophalangeal joints (2D-measured STANCEmin: 151 +/- 2.2 degrees vs. 3D-measured STANCEmin: 162 +/- 2.2 degrees; P<.01 and 2D-measured TO: 163 +/- 4.9 degrees vs. 3D-measured TO: 177 +/- 1.4 degrees; P<.05), whereas the hip and knee joints were much less affected. Data and techniques described here are useful for an objective assessment of altered gait after CP injury and repairin an ovine model.
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