ESTG - Comunicações em conferências e congressos internacionais
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Browsing ESTG - Comunicações em conferências e congressos internacionais by Field of Science and Technology (FOS) "Ciências Naturais::Matemáticas"
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- An adaptive strategy for improving the performance of genetic programming-based approaches to evolutionary testingPublication . Ribeiro, José; Zenha-Rela, Mário Alberto; Vega, Francisco Fernández deThis paper proposes an adaptive strategy for enhancing Genetic Programming-based approaches to automatic test case generation. The main contribution of this study is that of proposing an adaptive Evolutionary Testing methodology for promoting the introduction of relevant instructions into the generated test cases by means of mutation; the instructions from which the algorithm can choose are ranked, with their rankings being updated every generation in accordance to the feedback obtained from the individuals evaluated in the preceding generation. The experimental studies developed show that the adaptive strategy proposed improves the algorithm's efficiency considerably, while introducing a negligible computational overhead.
- Assessing the influence of uncertainty in land cover mapping and digital elevation models on flood risk mappingPublication . Gonçalves, Luísa M.S.; Fonte, Cidália C.; Gomes, RicardoThis paper proposes an approach to assess the influence of the uncertainty present in the parameters dependent on the land cover and elevation data over the peak flow values and the subsequent delineation of flooded areas. The proposed approach was applied to produce vulnerability and risk maps that integrate uncertainty for the urban area of Leiria, Portugal. A SPOT-4 satellite image and DEMs of the region were used. The peak flow was computed using the Soil Conservation Service method and HECHMS, HEC-RAS, Matlab and ArcGIS software programs were used. The analysis of the results obtained for the presented case study enables the identification of the order of magnitude of uncertainty associated to the watershed peak flow value and the identification of the areas which are more susceptible to flood risk to be identified.
- Clock Repeater Characterization for Jitter-Aware Clock Tree SynthesisPublication . Figueiredo, Monica; Aguiar, Rui L.This paper presents a simple jitter model for clock repeaters. The model is scalable and technology independent, which makes it suitable for integration in current clock tree synthesis algorithms. It is based on the timing characterization of a reference inverter, which can be performed for different process corners to account for process variability. Simulation results show that the model is accurate to within 10% for the most common inverter and NAND based repeaters.
- Complexity Estimation for Load Balancing of 360-Degree Intra Versatile Video CodingPublication . Filipe, Jose N.; Monteiro Carreira, João Filipe; Tavora, Luis M. N.; Faria, Sergio; Navarro, Antonio; Assuncao, Pedro A. A.The ever increasing demand for image and video content poses new requirements to support higher resolutions and richer representation formats, creating new challenges in coding algorithms. The forthcoming Versatile Video Coding (VVC) standard aims to increase the coding efficiency of existing algorithms and it is particularly suitable for Ultra-High Definition (UHD) resolutions and 360° video. However, since coding efficiency gains are obtained at the cost of increased complexity, fast computational approaches are needed to cope with realtime requirements, such as parallel processing. Thus, this work presents a contribution towards efficient parallel encoding of 360° video, based on coding complexity estimation and nonuniform data-level splitting (slice-based) for load balancing across multiple processors. A machine learning approach is proposed to estimate the complexity of intra coding VVC, using uncorrelated features, obtained through Principal Component Analysis (PCA) and Extremely Randomised Trees (ERT). Then, a complexity-balanced slice partition is devised, taking advantage of the clustered complexity inherent to Equirectangular Projection (ERP). It is shown that coding complexity is estimated with an accuracy of 92.25%, and the encoding time is reduced by 8.50%, when compared to the case where the 360° frames are evenly split.
- Cooperative and decomposable approaches on royal road functionsPublication . Reis, Gustavo; Fernandéz, Francisco; Olague, Gustavo
- Enabling Object Reuse on Genetic Programming-Based Approaches to Object-Oriented Evolutionary TestingPublication . Ribeiro, José Carlos Bregieiro; Zenha-Rela, Mário Alberto; Vega, Francisco Fernández deRecent research on search-based test data generation for Object-Oriented software has relied heavily on typed Genetic Programming for representing and evolving test data. However, standard typed Genetic Programming approaches do not allow Object Reuse; this paper proposes a novel methodology to overcome this limitation. Object Reuse means that one instance can be passed to multiple methods as an argument, or multiple times to the same method as arguments. In the context of Object-Oriented Evolutionary Testing, it enables the generation of test programs that exercise structures of the software under test that would not be reachable otherwise. Additionally, the experimental studies performed show that the proposed methodology is able to effectively increase the performance of the test data generation process.
- Extension of the dRET Model to Include Scattering from Tree Trunks in Microcell Urban Mobile ScenariosPublication . Caldeirinha, R. F. S.; Fernandes, T. R.; Leonor, N.; Ferreira, D.This paper proposes a framework for extending the applicability of the discrete RET (dRET) model to accommodate radiowave scattering from tree trunks, particularly in microcell urban mobile scenarios, at micro- and millimetre wave frequencies. This framework aims to provide accurate modelling of the signal emanated inside and around isolated blocks of tree trunks, for instances, in raised canopy forests or in urban street canyons like scenarios. Model validation against measurement results inside an anechoic chamber for a double line of regularly spaced metallic and dielectric trunks at 18.8 GHz, as well as recommendations for a more encompassing model, are presented.
- A hybrid multi-objective GRASP+SA algorithm with incorporation of preferencesPublication . Oliveira, Eunice; Antunes, Carlos Henggeler; Gomes, ÁlvaroA hybrid multi-objective approach based on GRASP (Greedy Randomized Adaptive Search Procedure) and SA (Simulated Annealing) meta-heuristics is proposed to provide decision support in a direct load control problem in electricity distribution networks. The main contributions of this paper are new techniques for the incorporation of preferences in these meta-heuristics and their hybridization. Preferences are included in the construction phase of multi-objective GRASP, in SA, as well as in the selection of solutions that go to the next generation, with the aim to obtain solutions more in accordance with the preferences elicited from a decision maker. The incorporation of preferences is made operational using the principles of the ELECTRE TRI method, which is based on the exploitation of an outranking relation in the framework of the sorting problem.
- Hybrid population-based incremental learning to assign terminals to concentratorsPublication . Bernardino, Eugénia Moreira; Bernardino, Anabela Moreira; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel AngelIn the last decade, we have seen a significant growth in communication networks. In centralised communication networks, a central computer serves several terminals or workstations. In large networks, some concentrators are used to increase the network efficiency. A collection of terminals is connected to a concentrator and each concentrator is connected to the central computer. In this paper we propose a Hybrid Population-based Incremental Learning (HPBIL) to assign terminals to concentrators. We use this algorithm to determine the minimum cost to form a network by connecting a given collection of terminals to a given collection of concentrators. We show that HPBIL is able to achieve good solutions, improving the results obtained by previous approaches.
- Low-Resolution Retinal Image Vessel SegmentationPublication . Zengin, Hasan; Camara, José; Coelho, Paulo; Rodrigues, João M. F.; Cunha, AntónioSegmentation process serves to aid the pathology diagnosing process since segmentation filters the interference from other anatomical structures and helps focus on the posterior segment structures of the eye, highlighting a set of signals that will serve for diagnosis of various retinal pathologies. Automatic retinal vessel segmentation can lead to a more accurate diagnosis. This paper presents a framework for automatic vessel segmentation of lower-resolution retinal images taken with a smartphone equipped with D-EYE lens. The framework is evaluated and the attained results were presented. A dataset was assembled and annotated of train models for automatic localisation retinal areas and for vessel segmentation. For the framework, two CNN based models were successfully trained, a Faster R-CNN that achieved a 96% correct detected of all regions with an MAE of 39 pixels, and a U-Net that achieved a DICE of 0.7547.