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Publications

2019

An ontology-based recommendation system for context-aware network monitoring

Authors
Silva, RF; Carvalho, P; Rito Lima, S; Álvarez Sabucedo, L; Santos Gago, JM; Silva, JMC;

Publication
Advances in Intelligent Systems and Computing

Abstract
Current network management systems urge for a context-aware perspective of the provided network services and the underlying infrastructure usage. This need results from the heterogeneity of services and technologies in place, and from the massive traffic volumes traversing today’s networks. To reduce complexity and improve interoperability, monitoring systems need to be flexible, context-aware, and able to self-configure measurement points (MPs) according to network monitoring tasks requirements. In addition, the use of sampling techniques in MPs to reduce the amount of traffic collected, analysed and stored has become mandatory and, currently, distinct sampling schemes are available for use in operational environments. In this context, the main objective of this paper is the ontological definition of measurement requirements and components in sampling-based monitoring environments, with the aim of supporting an expert recommendation system able to understand context and identify the appropriate configuration rules to apply to a selection of MPs. In this way, the ontology, defining management needs, network measurement topology and sampling techniques, is described and explored considering several network management activities. A use case focusing on traffic accounting as monitoring task is also provided, demonstrating the expressiveness of the ontology and the role of the recommendation system in assisting context-aware network monitoring based on traffic sampling. © Springer Nature Switzerland AG 2019.

2019

Speculative Design for Development of Serious Games: A Case Study in the Context of Anorexia Nervosa

Authors
Peçaibes, V; Cardoso, P; Giesteira, B;

Publication
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

Abstract
This article presents preliminary findings on the application of both Speculative Design and Game Design towards the conception of two prototypes of serious games with focus on anorexia. The first prototype focuses on psychoeducation of school-age youth, and the second aims to support research and sharing of knowledge about the disease, able to be used in focus groups and interviews. Anorexia is a complex and often fatal disease that has no cure, and by conceiving and playing these first prototypes we were able get a glimpse of the its context, making us more ready for this research’s next stages. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

2019

Anomaly Detection in Sequential Data: Principles and Case Studies

Authors
Andrade, T; Gama, J; Ribeiro, RP; Sousa, W; Carvalho, A;

Publication
Wiley Encyclopedia of Electrical and Electronics Engineering

Abstract

2019

A brief overview of the use of collaborative robots in industry 4.0: Human role and safety

Authors
Bragança, S; Costa, E; Castellucci, I; Arezes, PM;

Publication
Studies in Systems, Decision and Control

Abstract
Industry 4.0 is a new industrial paradigm that brings new challenges for workers as they have to actively collaborate with robots in an interconnected environment. The main purpose of this paper is to give a brief overview of how collaborative robots can be used to support human workers in Industry 4.0 manufacturing environments. The use of collaborative robots certainly brings many advantages as these machines enable more efficient product systems by supporting workers with both physical and cognitive tasks, as is the case of exoskeletons. On the other hand, human–robot interaction might also have some risks if human factors considerations are not well thought through throughout the process. Moreover, it becomes clear that the role that humans have been playing so far in a manufacturing environment is rapidly changing. Human workers will have to adapt to these new systems by acquiring and improving a set of skills that have sometime been neglected until nowadays. © Springer Nature Switzerland AG 2019.

2019

Application of genetic algorithms and the cross-entropy method in practical home energy management systems

Authors
Abreu, C; Soares, I; Oliveira, L; Rua, D; Machado, P; Carvalho, L; Pecas Lopes, JAP;

Publication
IET RENEWABLE POWER GENERATION

Abstract
Home energy management systems (HEMSs) are important platforms to allow consumers the use of flexibility in their consumption to optimise the total energy cost. The optimisation procedure embedded in these systems takes advantage of the nature of the existing loads and the generation equipment while complying with user preferences such as air temperature comfort configurations. The complexity in finding the best schedule for the appliances within an acceptable execution time for practical applications is leading not only to the development of different formulations for this optimisation problem, but also to the exploitation of non-deterministic optimisation methods as an alternative to traditional deterministic solvers. This study proposes the use of genetic algorithms (GAs) and the cross-entropy method (CEM) in low-power HEMS to solve a conventional mixed-integer linear programming formulation to optimise the total energy cost. Different scenarios for different countries are considered as well as different types of devices to assess the HEMS operation performance, namely, in terms of outputting fast and feasible schedules for the existing devices and systems. Simulation results in low-power HEMS show that GAs and the CEM can produce comparable solutions with the traditional deterministic solver requiring considerably less execution time.

2019

UAV-Based Automatic Detection and Monitoring of Chestnut Trees

Authors
Marques, P; Padua, L; Adao, T; Hruska, J; Peres, E; Sousa, A; Sousa, JJ;

Publication
Remote Sensing

Abstract
Unmanned aerial vehicles have become a popular remote sensing platform for agricultural applications, with an emphasis on crop monitoring. Although there are several methods to detect vegetation through aerial imagery, these remain dependent of manual extraction of vegetation parameters. This article presents an automatic method that allows for individual tree detection and multi-temporal analysis, which is crucial in the detection of missing and new trees and monitoring their health conditions over time. The proposed method is based on the computation of vegetation indices (VIs), while using visible (RGB) and near-infrared (NIR) domain combination bands combined with the canopy height model. An overall segmentation accuracy above 95% was reached, even when RGB-based VIs were used. The proposed method is divided in three major steps: (1) segmentation and first clustering; (2) cluster isolation; and (3) feature extraction. This approach was applied to several chestnut plantations and some parameters—such as the number of trees present in a plantation (accuracy above 97%), the canopy coverage (93% to 99% accuracy), the tree height (RMSE of 0.33 m and R2 = 0.86), and the crown diameter (RMSE of 0.44 m and R2 = 0.96)—were automatically extracted. Therefore, by enabling the substitution of time-consuming and costly field campaigns, the proposed method represents a good contribution in managing chestnut plantations in a quicker and more sustainable way.

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