Unidade de Investigação - CIIC - Computer Science and Communication Research Centre
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- 2ARTs: A Platform for Exercise Prescriptions in Cardiac Recovery PatientsPublication . Pereira, Andreia; Martinho, Ricardo; Pinto, Rui; Rijo, Rui; Grilo, CarlosDue to limited access, increasing costs and an ageing population, the global healthcare system faces significant coverage problems that call for innovative approaches. Health professionals are actively seeking alternative methods to provide care to an increasingly needy population, without increasing human effort and associated costs. eHealth platforms, which use technology to provide patient care, are emerging as transformative solutions for addressing these problems. This study is centered on the demand for a Decision Support System (DSS) in cardiology to enable doctors to prescribe individualized care inside Cardiac Rehabilitation Programmes (CRPs). The 2ARTs project’s main objective is to include a cardiac rehabilitation platform with a DSS within the hospital infrastructure. This DSS uses models to classify patients into different groups, delivering crucial information to assist with decisions regarding treatment. Regarding the DSS, Principal Component Analysis (PCA) emerged as a standout technique for dimensionality reduction, due to its interoperability with clustering algorithms and superior evaluation metrics. The most appropriate clustering technique was determined to be the K-means algorithm, which was supported by the experts analysis. In accordance with the goals of the 2ARTs project, this integration of PCA and K-means provides meaningful insights that improve reasoned decision-making.
- 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.
- 802.21-MPA-IMS ArchitecturePublication . Rodrigues, Carlos Miguel de Jesus; Rabadão, Carlos; Pereira, AntónioMobility has become a keyword nowadays with the evolution of mobile devices market and proliferation of realtime services. IP Multimedia Subsystem (IMS) is a single, standardized service framework that supports voice, video, data and messaging services, but does not provide seamless mobility for packet based sessions. This paper purposes an IMS architecture with IEEE 802.21 and media-independent pre-authentication (MPA) integrated. IEEE 802.21 can enable this seamless mobility in IMS and, additionally, MPA provides a secure handover optimization scheme, reducing, as a consequence, handover latency. The main goal of this architecture is to provide seamless and secure handovers between different access technologies in an IMS-based environment.
- ACCEPT: Web Applications for visualization and analytics of shop floor dataPublication . Godinho, Eduardo Miguel Ascenso; Piedade, Maria BeatrizNo contexto atual da Indústria 4.0 e do controlo metrológico de produtos pré-embalados, procura-se que os dados provenientes de chão de fábrica sejam recolhidos de forma automática e que diferentes tipos de dispositivos digitais tenham acesso aos mesmos dados de forma ubíqua. Pretendeu-se desenvolver e integrar aplicações Web no sistema ACCEPT, sistema que permite a recolha, armazenamento, visualização e análise de dados de chão de fábrica. Neste artigo é descrito o processo de desenvolvimento das aplicações ACCEPT Quality Hub e ACCEPT Analytics e a sua integração neste sistema.
- Advanced technologies for shoe sole productionPublication . Spahiu, Tatjana; Almeida, Henrique; Ascenso, Rita M. T.; Vitorino, Liliana; Marto, AnabelaAdvanced technologies for modelling and production are an important part in the whole process of product manufacturing. These advancements have changed the way of product development and play an important role in customization. In the footwear industry, as in any other industry, the use of these technologies is widely spread. Footwear comfort is one of the main selection criteria for purchase. 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 1 participant 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.
- Analyzing TikTok from a Digital Forensics PerspectivePublication . Domingues, Patricio; Nogueira, Ruben; Francisco, José Carlos; Frade, MiguelTikTok is a major hit in the digital mobile world, quickly reaching the top 10 installed applications for the two main mobile OS, iOS and Android. This paper studies Android's TikTok application from a digital forensic perspective, analyzing the digital forensic artifacts that can be retrieved on a post mortem analysis and their associations with operations performed by the user. The paper also presents FAMA (Forensic Analysis for Mobile Apps), an extensible framework for the forensic software Autopsy, and FAMA's TikTok module that collects, analyzes, and reports on the main digital forensic artifacts of TikTok's Android application. The most relevant digital artifacts of TikTok include messages exchanged between TikTok so-called ``friends'', parts of the email/phone number of registered users, data about devices, and transactions with TikTok's virtual currency. One of the results of this research is the set of forensic traces left by users' transactions with TikTok's in-app virtual currency. Another result is the detection of patterns that exist in TikTok's integer IDs, allowing to quickly link any 64-bit TikTok's integer ID to the type of resources -- user, device, video, etc. -- that it represents.
- Applying deep learning to real-time UAV-based forest monitoring: Leveraging multi-sensor imagery for improved resultsPublication . Marques, Tomás; Carreira, Samuel; Miragaia, Rolando; Ramos, João; Pereira, AntónioRising global fire incidents necessitate effective solutions, with forest surveillance emerging as a crucial strategy. This paper proposes a complete solution using technology that integrates visible and infrared spectrum images through Unmanned Aerial Vehicles (UAVs) for enhanced detection of people and vehicles in forest environments. Unlike existing computer vision models relying on single-sensor imagery, this approach overcomes limitations posed by limited spectrum coverage, particularly addressing challenges in low-light conditions, fog, or smoke. The developed 4-channel model uses both types of images to take advantage of the strengths of each one simultaneously. This article presents the development and implementation of a solution for forest monitoring ranging from the transmission of images captured by a UAV to their analysis with an object detection model without human intervention. This model consists of a new version of the YOLOv5 (You Only Look Once) architecture. After the model analyzes the images, the results can be observed on a web platform on any device, anywhere in the world. For the model training, a dataset with thermal and visible images from the aerial perspective was captured with a UAV. From the development of this proposal, a new 4- channel model was created, presenting a substantial increase in precision and mAP (Mean Average Precision) metrics compared to traditional SOTA (state-of-the-art) models that only make use of red, green, and blue (RGB) images. Allied with the increase in precision, we confirmed the hypothesis that our model would perform better in conditions unfavorable to RGB images, identifying objects in situations with low light and reduced visibility with partial occlusions. With the model’s training using our dataset, we observed a significant increase in the model’s performance for images in the aerial perspective. This study introduces a modular system architecture featuring key modules: multisensor image capture, transmission, processing, analysis, and results presentation. Powered by an innovative object detection deep-learning model, these components collaborate to enable real-time, efficient, and distributed forest monitoring across diverse environments.
- AR Mobile Application to Enhance the Birdwatching ExperiencePublication . Venâncio, José; Marto, Anabela; Ascenso, Rita Margarida Teixeira; Rodrigues, Nuno; Gonçalves, Alexandrino José MarquesGuard@Lis application was developed to ease the birdwatching activity. The main purpose was to support the discovery and identification of bird species along a trail, encouraging the preservation and protection of nature. To create a new bird observation perspective since augmented reality features were developed to enhance the experience of birdwatching, ensuring the chance to watch even the most elusive birds. Adding animated 3D models of some birds allows the observation of these species that, for several reasons, may not be easy to encounter in their natural habitat when the user is making the trail. The solution is composed of a multiplatform app and a back-office. It is prepared to create routes with hotspots and improve the bird species list. This first version was designed with a route in the city of Leiria, having specific points along the way, defined for the observation of certain species. Guard@Lis application intends to encourage the didactic and educational facets, so the whole development process of this application was to create a guide that allows users to be able to identify and list the number of bird species found. At this stage, the app allows its users to trail the main historical and tourist points of Leiria and collect the bird species observed.
- Benchmarking bioinspired machine learning algorithms with CSE-CIC-IDS2018 network intrusions datasetPublication . Ferreira, Paulo; Antunes, MárioThis paper aims to evaluate CSE-CIC-IDS2018 network intrusions dataset and benchmark a set of supervised bioinspired machine learning algo rithms, namely CLONALG Artificial Immune System, Learning Vector Quantization (LVQ) and Back-Propagation Multi-Layer Perceptron (MLP). The results obtained were also compared with an ensemble strategy based on a majority voting algorithm. The results obtained show the appropri ateness of using the dataset to test behaviour based network intrusion de tection algorithms and the efficiency of MLP algorithm to detect zero-day attacks, when comparing with CLONALG and LVQ.
- Billing in the Mobile Era : Octa Code’s Study CasePublication . Andrade, Eduardo; Bernardino, Anabela; Bernardino, EugeniaNa era digital, cada vez mais os serviços existentes se adaptam às novas tecnologias e aos seus benefícios. Com o surgimento de nova legislação, irá passar a ser obrigatório a utilização de plataformas digitas para todos os documentos de faturação. Com esta alteração, surge a necessidade de aplicações móveis que possam ser utilizadas em qualquer lado para substituir a tradicional fatura manual ainda utilizada em muitos negócios de cariz ambulante, onde o manuseamento de computadores ou portáteis não é fácil. Mas este novo mercado cria também novos desafios e problemas que serão explorados no caso de estudo em questão. Octa Gest Faturas, da Octa Code, é uma nova aplicação que pretende destacar-se ao oferecer uma experiência de fácil utilização, enquanto ao mesmo tempo aplica as práticas recomendadas no desenvolvimento de aplicações móveis.