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- Optimization of shoe sole design according to individual feet pressure mapsPublication . Spahiu, Tatjana; Almeida, Henrique; Ascenso, Rita M. T.; Vitorino, Liliana; Marto, AnabelaInnovative technologies are shaping the future of product development in many industries. From the wide range of applications apparel industry as garments, footwear and accessories has involved advanced technologies in different steps of product development. The focus of companies is quality and fit of products, especially for footwear products, where fit is one of the most important elements for the wearer. This is strongly related with comfort and poor fit leads to foot injuries. Considering this fact, a case study of different steps for shoe designing according to individual foot shape will be presented. Taking into consideration the aesthetics of the sole and in a more sustainable view, through topological optimization reducing of material wastage for sole production will be presented. By means of the topological optimization in the shoe design process, sole optimization is realized. As a part of personalization, feet's plantar pressure maps taken from 3 participants gave a better explanation of weight distribution of each foot. Following, sole personalization according the plantar pressure maps for each foot gives the possibility to obtain the best least material design according to the feet's pressure while maintaining biomechanical performance and aesthetics.
- Distributed Architecture for Unmanned Vehicle ServicesPublication . Ramos, João; Ribeiro, Roberto; Safadinho, David; Barroso, João; Rabadão, Carlos; Pereira, AntónioThe demand for online services is increasing. Services that would require a long time to understand, use and master are becoming as transparent as possible to the users, that tend to focus only on the final goals. Combined with the advantages of the unmanned vehicles (UV), from the unmanned factor to the reduced size and costs, we found an opportunity to bring to users a wide variety of services supported by UV, through the Internet of Unmanned Vehicles (IoUV). Current solutions were analyzed and we discussed scalability and genericity as the principal concerns. Then, we proposed a solution that combines several services and UVs, available from anywhere at any time, from a cloud platform. The solution considers a cloud distributed architecture, composed by users, services, vehicles and a platform, interconnected through the Internet. Each vehicle provides to the platform an abstract and generic interface for the essential commands. Therefore, this modular design makes easier the creation of new services and the reuse of the different vehicles. To confirm the feasibility of the solution we implemented a prototype considering a cloud-hosted platform and the integration of custom-built small-sized cars, a custom-built quadcopter, and a commercial Vertical Take-Off and Landing (VTOL) aircraft. To validate the prototype and the vehicles’ remote control, we created several services accessible via a web browser and controlled through a computer keyboard. We tested the solution in a local network, remote networks and mobile networks (i.e., 3G and Long-Term Evolution (LTE)) and proved the benefits of decentralizing the communications into multiple point-to-point links for the remote control. Consequently, the solution can provide scalable UV-based services, with low technical effort, for anyone at anytime and anywhere.
- Web AR Solution for UAV Pilot Training and Usability TestingPublication . Ribeiro, Roberto; Ramos, João; Safadinho, David; Reis, Arsénio; Rabadão, Carlos; Barroso, João; Pereira, AntónioData and services are available anywhere at any time thanks to the Internet and mobile devices. Nowadays, there are new ways of representing data through trendy technologies such as augmented reality (AR), which extends our perception of reality through the addition of a virtual layer on top of real-time images. The great potential of unmanned aerial vehicles (UAVs) for carrying out routine and professional tasks has encouraged their use in the creation of several services, such as package delivery or industrial maintenance. Unfortunately, drone piloting is difficult to learn and requires specific training. Since regular training is performed with virtual simulations, we decided to propose a multiplatform cloud-hosted solution based in Web AR for drone training and usability testing. This solution defines a configurable trajectory through virtual elements represented over barcode markers placed on a real environment. The main goal is to provide an inclusive and accessible training solution which could be used by anyone who wants to learn how to pilot or test research related to UAV control. For this paper, we reviewed drones, AR, and human–drone interaction (HDI) to propose an architecture and implement a prototype, which was built using a Raspberry Pi 3, a camera, and barcode markers. The validation was conducted using several test scenarios. The results show that a real-time AR experience for drone pilot training and usability testing is achievable through web technologies. Some of the advantages of this approach, compared to traditional methods, are its high availability by using the web and other ubiquitous devices; the minimization of technophobia related to crashes; and the development of cost-effective alternatives to train pilots and make the testing phase easier for drone researchers and developers through trendy technologies.
- Perceptual images of Conimbriga using High Dynamic RangePublication . Gonçalves, Alexandrino; Moura, João Paulo; Magalhães, Luís; Chalmers, AlanIt is widely recognized that new technologies can play an important role in the interpretation of our cultural heritage legacy. This has become a powerful tool providing a better understanding of our past, and thereby, allowing us to attain a glimpse of the environments in which our ancestors lived. In this domain, the way we see such reconstructed environments is particularly important in order to establish an accurate interpretation of that historical setting. However, the desired visual accuracy in the representation of any archaeological scenario is strictly related to the technology used to visualize it. High Dynamic Range (HDR) technology encompasses the capacity to produce visual results similar to the visual acuity of the human eye, particularly in extreme lighting conditions, such as bright light or dim environments. In this paper we present an ancient flame light simulation method and a perceptual visual user study with HDR images of Roman mosaics and frescoes, illuminated by luminaries of that period, located in one of the most impressive monuments in the ruins of Conimbriga, Portugal. With this work we intend to demonstrate how the use of this particular low intensity Roman light, when compared to other modern illumination, affects the subjects’ perception of ancient artefacts and influences the scenario viewing pattern.
- Swarm optimisation algorithms applied to large balanced communication networksPublication . Bernardino, Eugénia Moreira; Bernardino, Anabela Moreira; Sánchez-Pérez, Juan Manuel; Pulido, Juan Antonio Gómez; Rodríguez, Miguel A. VegaIn the last years, several combinatorial optimisation problems have arisen in the computer communications networking field. In many cases, for solving these problems it is necessary the use of metaheuristics. An important problem in communication networks is the Terminal Assignment Problem (TAP). Our goal is to minimise the link cost of large balanced communication networks. TAP is a NP-Hard problem. The intractability of this problem is the motivation for the pursuits of Swarm Intelligence (SI) algorithms that produce approximate, rather than exact, solutions. This paper makes a comparison among the effectiveness of three SI algorithms: Ant Colony Optimisation, Discrete Particle Swarm Optimisation and Artificial Bee Colony. We also compare the SI algorithms with several algorithms from literature. Simulation results verify the effectiveness of the proposed algorithms. The results show that SI algorithms provide good solutions in a better running time.
- Corrigendum to “A spam filtering multi-objective optimization study covering parsimony maximization and three-way classification” [Applied Soft Computing Volume 48 (2016) 111–123]Publication . Basto-Fernandes, Vitor; Yevseyeva, Iryna; Méndez, José R.; Zhao, Jiaqi; Fdez-Riverola, Florentino; Emmerich, Michael T. M.
- Corrigendum to ‘Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms’ [Information Sciences volumes 367–368 (2016) 80–104]Publication . Zhao, Jiaqi; Basto-Fernandes, Vitor; Jiao, Licheng; Yevseyeva, Iryna; Maulana, Asep; Li, Rui; Bäck, Thomas; Tang, Ke; Emmerich, Michael T. M.
- Model optimisation for server loading forecasting with genetic algorithmsPublication . Silva, Cláudio; Grilo, Carlos; Silva, Catarina; Silva, CatarinaServer load prediction has different approaches and applications, with the general goal of predicting future load for a period of time ahead on a given system. Depending on the specific goal, different methodologies can be defined. In this paper, we study the use of temporal factors, along with its manual or optimised application using genetic algorithms. The main steps involved are data transformations, a novel pre-processing method based on enrichment of data through the inducing of temporal factors and a genetic algorithms wrapper that optimises all the variables in our approach. The created model was tested on a short-term load forecasting problem, with the use of data from single and combined months, regarding real data from Wikipedia servers. The learning methods used for creating the different models were linear regression, neural networks, and support vector machines. A basic dataset, as well as an enriched dataset, were the core elements for the two scenarios studied. Results show that it is possible to tune the dataset features, e.g., granularity and time window to improve prediction results.
- Evolving a multi-classifier system with cartesian genetic programming for multi-pitch estimation of polyphonic piano musicPublication . Miragaia, Rolando; Vega, Francisco Fernandez de; Reis, GustavoThis paper presents a new method for multi-pitch estimation on piano recordings. We propose a framework based on a set of classifiers to analyze the audio input and identify the piano notes present on the given audio signal. Our system's classifiers were evolved using Cartesian Genetic Programming: we take advantage of Cartesian Genetic Programming to evolve a set of mathematical functions that act as independent classifiers for piano notes. Our latest improvements are also presented, including test results using F-measure metrics. Our system architecture is also described to show the feasibility of its parallelization and implementation as a real time system. The proposed approach achieved competitive results, when compared to the state of the art.
- Evolving a Multi-Classifier System for Multi-Pitch Estimation of Piano Music and Beyond: An Application of Cartesian Genetic ProgrammingPublication . Miragaia, Rolando; Fernández, Francisco; Reis, Gustavo; Inácio, TiagoThis paper presents a new method with a set of desirable properties for multi-pitch estimation of piano recordings. We propose a framework based on a set of classifiers to analyze audio input and to identify piano notes present in a given audio signal. Our system’s classifiers are evolved using Cartesian genetic programming: we take advantage of Cartesian genetic programming to evolve a set of mathematical functions that act as independent classifiers for piano notes. Two significant improvements are described: the use of a harmonic mask for better fitness values and a data augmentation process for improving the training stage. The proposed approach achieves com-petitive results using F-measure metrics when compared to state-of-the-art algorithms. Then, we go beyond piano and show how it can be directly applied to other musical instruments, achieving even better results. Our system’s architecture is also described to show the feasibility of its parallelization and its implementation as a real-time system. Our methodology is also a white-box optimization approach that allows for clear analysis of the solutions found and for researchers to learn and test improvements based on the new findings.