CIIC - Artigos em Revistas com Peer Review
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- High dynamic range - a gateway for predictive ancient lightingPublication . Gonçalves, Alexandrino José Marques; Magalhães, Luís; Moura, João; Chalmers, AlanIn the last few years, the number of projects involving historical reconstruction has increased significantly. Recent technologies have proven a powerful tool for a better understanding of our cultural heritage through which to attain a glimpse of the environments in which our ancestors lived. However, to accomplish such a purpose, these reconstructions should be presented to us as they may really have been perceived by a local inhabitant, according to the illumination and materials used back then and, equally important, the characteristics of the human visual system. The human visual system has a remarkable ability to adjust itself to almost all everyday scenarios. This is particularly evident in extreme lighting conditions, such as bright light or dark environments. However, a major portion of the visible spectra captured by our visual system cannot be represented in most display devices. High dynamic range imagery is a field of research which is developing techniques to correct such inaccuracies. This new viewing paradigm is perfectly suited for archaeological interpretation, since its high contrast and chromaticity can present us with an enhanced viewing experience, closer to what an inhabitant of that era may have seen. In this article we present a case study of the reconstruction of a Roman site. We generate high dynamic range images of mosaics and frescoes from one of the most impressive monuments in the ruins of Conimbriga, Portugal, an ancient city of the Roman Empire. To achieve the requisite level of precision, in addition to having a precise geometric 3D model, it is crucial to integrate in the virtual simulation authentic physical data of the light used in the period under consideration. Therefore, in order to create a realistic physical-based environment, we use in our lighting simulations real data obtained from simulated Roman luminaries of that time.
- Reconstruction and generation of virtual heritage sitesPublication . Rodrigues, Nuno; Magalhães, L.; Moura, J.; Chalmers, A.Traditionally procedural modelling techniques are commonly used to generate new structures and are presently established in several areas such as video games and computer animated movies. However they may also be used in heritage applications to efficiently produce models of non-existing worlds for which there is some kind of knowledge (e.g. floor plans, photographs) to support the reconstruction of realistic environments. Similarly they may also be used to support the generation of distinct possibilities that allow experts to draw some conclusions or conceive different hypotheses about lost worlds. The present paper shows the benefits and constraints that may arise from the use of such techniques in virtual heritage applications. Furthermore, a whole method is proposed, for the reconstruction and generation of virtual heritage traversable house models, provided through the means of a grammar, demonstrated with the reconstruction and generation of several Roman houses from the heritage site of Conimbriga, Portugal.
- A spam filtering multi-objective optimization study covering parsimony maximization and three-way classificationPublication . Basto-Fernandes, Vitor; Yevseyeva, Iryna; Méndez, José R.; Zhao, Jiaqi; Fdez-Riverola, Florentino; Emmerich, Michael T.M.Classifier performance optimization in machine learning can be stated as a multi-objective optimization problem. In this context, recent works have shown the utility of simple evolutionary multi-objective algorithms (NSGA-II, SPEA2) to conveniently optimize the global performance of different anti-spam filters. The present work extends existing contributions in the spam filtering domain by using three novel indicator-based (SMS-EMOA, CH-EMOA) and decomposition-based (MOEA/D) evolutionary multiobjective algorithms. The proposed approaches are used to optimize the performance of a heterogeneous ensemble of classifiers into two different but complementary scenarios: parsimony maximization and e-mail classification under low confidence level. Experimental results using a publicly available standard corpus allowed us to identify interesting conclusions regarding both the utility of rule-based classification filters and the appropriateness of a three-way classification system in the spam filtering domain.
- 3D fast convex-hull-based evolutionary multiobjective optimization algorithmPublication . Zhao, Jiaqi; Jiao, Licheng; Liu, Fang; Basto-Fernandes, Vitor; Yevseyeva, Iryna; Xia, Shixiong; Emmerich, Michael T.M.The receiver operating characteristic (ROC) and detection error tradeoff (DET) curves have been widely used in the machine learning community to analyze the performance of classifiers. The area (or volume) under the convex hull has been used as a scalar indicator for the performance of a set of classifiers in ROC and DET space. Recently, 3D convex-hull-based evolutionary multiobjective optimization algorithm (3DCH-EMOA) has been proposed to maximize the volume of convex hull for binary classification combined with parsimony and three-way classification problems. However, 3DCH-EMOA revealed high consumption of computational resources due to redundant convex hull calculations and a frequent execution of nondominated sorting. In this paper, we introduce incremental convex hull calculation and a fast replacement for non-dominated sorting. While achieving the same high quality results, the computational effort of 3DCH-EMOA can be reduced by orders of magnitude. The average time complexity of 3DCH-EMOA in each generation is reduced from to per iteration, where n is the population size. Six test function problems are used to test the performance of the newly proposed method, and the algorithms are compared to several state-of-the-art algorithms, including NSGA-III, RVEA, etc., which were not compared to 3DCH-EMOA before. Experimental results show that the new version of the algorithm (3DFCH-EMOA) can speed up 3DCH-EMOA for about 30 times for a typical population size of 300 without reducing the performance of the method. Besides, the proposed algorithm is applied for neural networks pruning, and several UCI datasets are used to test the performance.
- Multiobjective sparse ensemble learning by means of evolutionary algorithmsPublication . Zhao, Jiaqi; Jiao, Licheng; Xia, Shixiong; Basto-Fernandes, Vitor; Yevseyeva, Iryna; Zhou, Yong; Emmerich, Michael T.M.Ensemble learning can improve the performance of individual classifiers by combining their decisions. The sparseness of ensemble learning has attracted much attention in recent years. In this paper, a novel multiobjective sparse ensemble learning (MOSEL) model is proposed. Firstly, to describe the ensemble classifiers more precisely the detection error trade-off (DET) curve is taken into consideration. The sparsity ratio (sr) is treated as the third objective to be minimized, in addition to false positive rate (fpr) and false negative rate (fnr) minimization. The MOSEL turns out to be augmented DET (ADET) convex hull maximization problem. Secondly, several evolutionary multiobjective algorithms are exploited to find sparse ensemble classifiers with strong performance. The relationship between the sparsity and the performance of ensemble classifiers on the ADET space is explained. Thirdly, an adaptive MOSEL classifiers selection method is designed to select the most suitable ensemble classifiers for a given dataset. The proposed MOSEL method is applied to well-known MNIST datasets and a real-world remote sensing image change detection problem, and several datasets are used to test the performance of the method on this problem. Experimental results based on both MNIST datasets and remote sensing image change detection show that MOSEL performs significantly better than conventional ensemble learning methods.
- A review on the use of additive manufacturing to produce lower limb orthosesPublication . Alqahtani, Mohammed S.; Al-Tamimi, Abdulsalam; Almeida, Henrique; Cooper, Glen; Bartolo, PauloOrthoses (exoskeletons and fracture fixation devices) enhance users’ ability to function and improve their quality of life by supporting alignment correction, restoring mobility, providing protection, immobilisation and stabilisation. Ideally, these devices should be personalised to each patient to improve comfort and performance. Production costs have been one of the main constraints for the production of personalised orthoses. However, customisation and personalisation of orthoses are now possible through the use of additive manufacturing. This paper presents the current state of the art of additive manufacturing for the fabrication of orthoses, providing several examples, and discusses key research challenges to be addressed to further develop this field.
- Fashion Products Through Digital Manufacturing - A Case Study With FDM TechnologyPublication . Spahiu, Tatjana; Almeida, Henrique; Manavis, Athanasios; Kyratsis, PanagiotisWe live in a digital world comprising the use of computer systems applicable to every process of manufacturing. Digital manufacturing is present in almost all areas of production by linking systems and process required from conceptualization to the final product. Through the use of digital manufacturing fashion products are designed and manufactured. Case studies of using the tools of 3D CAD software modeling to create novel products as textile structures, accessories and shoes parts as heels are presented. Taking inspiration from several sources, customized models are designed and with the great power of additive manufacturing as FDM technology, a non-expensive compared to the other types of additive manufacturing technologies, is implemented in the manufacturing of 3D CAD models. Without restriction on design, 3D models generated form CAD software are print directly by avoiding other process related to traditional manufacturing. The rise of new technologies in digital manufacturing releases new opportunities for companies to foster productivity, customization and sustainability.
- Prototype to Increase Crosswalk Safety by Integrating Computer Vision with ITS-G5 TechnologiesPublication . Gaspar, Francisco; Guerreiro, Vitor; Loureiro, Paulo; Costa, Paulo; Mendes, Sílvio; Rabadão, CarlosHuman errors are probably the main cause of car accidents, and this type of vehicle is one of the most dangerous forms of transport for people. The danger comes from the fact that on public roads there are simultaneously different types of actors (drivers, pedestrians or cyclists) and many objects that change their position over time, making difficult to predict their immediate movements. The intelligent transport system (ITS-G5) standard specifies the European communication technologies and protocols to assist public road users, providing them with relevant information. The scientific community is developing ITS-G5 applications for various purposes, among which is the increasing of pedestrian safety. This paper describes the developed work to implement an ITS-G5 prototype that aims at the increasing of pedestrian and driver safety in the vicinity of a pedestrian crosswalk by sending ITS-G5 decentralized environmental notification messages (DENM) to the vehicles. These messages are analyzed, and if they are relevant, they are presented to the driver through a car’s onboard infotainment system. This alert allows the driver to take safety precautions to prevent accidents. The implemented prototype was tested in a controlled environment pedestrian crosswalk. The results showed the capacity of the prototype for detecting pedestrians, suitable message sending, the reception and processing on a vehicle onboard unit (OBU) module and its presentation on the car onboard infotainment system.
- Structural optimisation for medical implants through additive manufacturingPublication . Al-Tamimi, Abdulsalam Abdulaziz; Almeida, Henrique; Bártolo, PauloAdvanced manufacturing techniques are being explored to fabricate degradable and non-degradable, porous or non-porous implants for medical applications. These implants have been designed using standard computer-aided design (CAD) and computer-aided engineering (CAE) tools and produced in a multitude of materials. The recent use of optimisation tech niques, mainly topology optimisation, allows the development of additive manufactured medical devices with improved performance. This review discusses the combined use of optimisation techniques and additive manufacturing to produce biocompatible and biodegradable scafolds for tissue engineering with improved mechanical and permeability properties; metallic lattice structures with reduced weight and minimal stress shielding efect; and lightweight personalised orthopae dic implants. Three optimisation routes are considered: topology optimisation; triply periodic minimal surfaces that can be manipulated by means of the equations parameters to optimise the overall performance; and the use of repetitive structures that are optimised as unit cells under certain conditions to compose a bulk object. Major limitations and research challenges are highlighted and discussed.
- A Systematic Review of IoT Solutions for Smart FarmingPublication . Navarro, Emerson; Costa, Nuno; Pereira, AntónioThe world population growth is increasing the demand for food production. Furthermore, the reduction of the workforce in rural areas and the increase in production costs are challenges for food production nowadays. Smart farming is a farm management concept that may use Internet of Things (IoT) to overcome the current challenges of food production. This work uses the preferred reporting items for systematic reviews (PRISMA) methodology to systematically review the existing literature on smart farming with IoT. The review aims to identify the main devices, platforms, network protocols, processing data technologies and the applicability of smart farming with IoT to agriculture. The review shows an evolution in the way data is processed in recent years. Traditional approaches mostly used data in a reactive manner. In more recent approaches, however, new technological developments allowed the use of data to prevent crop problems and to improve the accuracy of crop diagnosis.