2018
Authors
Mani, V; Delgado, C;
Publication
India Studies in Business and Economics - Supply Chain Social Sustainability for Manufacturing
Abstract
2018
Authors
Rodrigues*, S; Paiva, JS; Dias, D; Pereira, T; Cunha, JPS;
Publication
The European Proceedings of Social and Behavioural Sciences
Abstract
2018
Authors
Varela, LR; Putnik, GD; Manupti, V; Madureira, A; Santos, AS; Amaral, G; Ferreirinha, L;
Publication
HIS
Abstract
In this paper a scheduling meta-model is proposed for supporting hybrid collaboration, regarding machine-machine and human-machine scheduling interactions, based on a scheduling ontology. The utilization of the proposed scheduling ontology-based meta-model is illustrated through an example, which is further analysed, and some main features and advantages of each kind of collaborative interaction are discussed.
2018
Authors
Faia, R; Pinto, T; Vale, Z; Corchado, JM;
Publication
APPLIED ARTIFICIAL INTELLIGENCE
Abstract
The portfolio optimization is a well-known problem in the areas of economy and finance. This problem has also become increasingly important in electrical power systems, particularly in the area of electricity markets, mostly due to the growing number of alternative/complementary market types that are being introduced to deal with important issues, such as the massive integration of renewable energy sources in power systems. The optimization of electricity market players' participation portfolio comprises significant time constraints, which cannot be satisfied by the use of deterministic techniques. For this reason, meta-heuristic solutions are used, such as particle swarm optimization. The inertia is one of the most important parameter in this method, and it is the main focus of this paper. This paper studies 18 popular inertia calculation strategies, by comparing their performance in the portfolio optimization problem. A strategic methodology for the automatic selection of the best inertia calculation method for the needs of each optimization is also proposed. Results show that the proposed approach is able to automatically adapt the inertia parameter according to the needs in each execution.
2018
Authors
Bhanu, M; Chandra, J; Mendes Moreira, J;
Publication
2018 10TH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS & NETWORKS (COMSNETS)
Abstract
Handling major challenges like traffic volume estimation, mobility pattern detection and feature extraction in mobility network usually form a weak balance among them. Most of the works are focused towards one of these areas which fail in improving altogether. In this paper, we present a model with modified conventional methods meeting all three above challenges to an extent. Extracting new temporal & directional feature, we introduce Reciprocity metric. It proves to be more informative and efficient in capturing mobility pattern of the network than existing metrics. We introduce the idea of network skeleton which is a reduced form of mobility network but captures approx 90% of its inherent characteristics. Network Skeleton can extract higher level of information from the network while enhancing network's short-term predictability. Our work has the following steps: 1) extracting and building "link reciprocity", a more informative feature; 2) pattern detection in random mobility introduced by "convergence of mobility network"; and 3) estimation of network skeleton formed using a link based approach for short-term forecasting. Our network convergence method outperforms conventional approaches and detects active regions at a very fast rate compared to other approaches. Long ShortTerm Memory (LSTM), a kind of Recursive Neural Networks (RNN) capable of learning long-term dependencies is used to estimate network traffic. Indicating link based network-skeleton helps to reduce short-term forecasting error up to 6% and 3/4 times in different time-slots. Our network skeleton approach can be used to meet the general problems of the traffic-rules formulation by characterizing important routes (links), detecting regions of high importance in less time and predicting short-term traffic volume in a more accurate way. Moreover, network skeleton with reduced network-size can be easily operable with existing methodologies, which is another essential contribution of our work.
2018
Authors
Paulino, D; Reis, A; Barroso, J; Paredes, H;
Publication
UNIVERSAL ACCESS IN HUMAN-COMPUTER INTERACTION: VIRTUAL, AUGMENTED, AND INTELLIGENT ENVIRONMENTS
Abstract
In this review the objective is to search for technologies that supervise the exercise or physical activity of people suffering from Peripheral Arterial Disease (PAD) at home or in the community. Patients with PAD have walking limitations and their quality of life progressively deteriorates. The regular practice of exercise can help mitigate these effects and even improve their health status. The methodology used was to search for scientific articles published since 2008, with the final result of 18 articles. The results show the most frequent technologies used are based on the accelerometer device, with the tests being performed on a treadmill at a hospital. The hospital tests are expensive, so a useful and viable alternative is the usage of mobile devices to help the health professionals record the exercise performed by their patients suffering with PAD.
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