Unidade de Investigação - CIIC - Computer Science and Communication Research Centre
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Percorrer Unidade de Investigação - CIIC - Computer Science and Communication Research Centre por Objetivos de Desenvolvimento Sustentável (ODS) "08:Trabalho Digno e Crescimento Económico"
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- 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.
- AMIGA - An Interactive Musical Environment for GerontechnologyPublication . Reis, Lee Scott; Reis, Gustavo; Barroso, João; Pereira, AntónioBenefits provided by music in humans have been reinforced through several studies, mainly by active participation in musical therapy sessons, with surprising results in physical and psychological rehabilitation. However, all the previous implemented approaches require specialized hardware to function and complex configurations to set-up. We define a computational system focused on the elderly to allow musical expressiveness through motion, solely using the resources available in an ordinary home computer. To evaluate our approach, we developed a prototype and piloted acceptance tests on several senior citizens, with an average age of eighty-three. Our experiments showed high levels of interest from the senior citizens, denoting positive capabilities of well-being and life quality enrichment. The performed experiments have also shown that an ordinary computer is capable of performing the proposed methodology, without any restriction.
- Artificial intelligence applied to the stone manufacturing industry: A systematic literature reviewPublication . Santos Silva, Alexandre; Antunes, Carolina; Miragaia, Rolando; Costa, Rogério Luís C.; Silva, Fernando; Ribeiro, JoséNatural stone has long been used in construction, as its properties provide functional and visual value, and the natural stone market currently holds significant importance in the global economy. It is important to consider integrating new technologies in the production chain to aid the industry in moving forward, increasing profit margins and reducing wasted material. This article reviews recent trends in using Artificial Intelligence and Machine Learning techniques in the industry between 2017 and 2024, following a methodology for Systematic Literature Reviews in computer science. It was found that extensive research has been conducted on the subject of tile classification, with solid solutions proposed, achieving results that can be considered robust enough for industrial application. Other subjects comprise tasks regarding stone cutting and defect detection, as well as variable prediction, and quarry activity monitoring. Some authors propose solutions to integrate new technologies into the complete production chain. While more research needs to be done on specific subjects, this review provides a solid first step to future research.
- Artificial Intelligence-Driven User Interaction with Smart Homes: Architecture Proposal and Case StudyPublication . Lemos, João; Ramos, João; Gomes, Mário; Coelho, PauloThe evolution of Smart Grids enabled the deployment of intelligent and decentralized energy management solutions at the residential level. This work presents a comprehensive Smart Home architecture that integrates real-time energy monitoring, appliance-level consumption analysis, and environmental data acquisition using smart metering technologies and distributed IoT sensors. All collected data are structured into a scalable infrastructure that supports advanced Artificial Intelligence (AI) methods, including Large Language Models (LLMs) and machine learning, enabling predictive analysis, personalized energy recommendations, and natural language interaction. Proposed architecture is experimentally validated through a case study on a domestic refrigerator. Two series of tests were conducted. In the first phase, extreme usage scenarios were evaluated: one with intensive usage and another with highly restricted usage. In the second phase, normal usage scenarios were tested without AI feedback and with AI recommendations following them whenever possible. Under the extreme scenarios, AI-assisted interaction resulted in a reduction in daily energy consumption of about 81.4%. In the normal usage scenarios, AI assistance resulted in a reduction of around 13.6%. These results confirm that integrating AI-driven behavioral optimization within Smart Home environments significantly improves energy efficiency, reduces electrical stress, and promotes more sustainable energy usage.
- Automatic Transcription of Polyphonic Piano Music Using Genetic Algorithms, Adaptive Spectral Envelope Modeling, and Dynamic Noise Level EstimationPublication . Reis, Gustavo; Fernandez de Vega, Francisco; Ferreira, AníbalThis paper presents a new method for multiple fundamental frequency (F0) estimation on piano recordings. We propose a framework based on a genetic algorithm in order to analyze the overlapping overtones and search for the most likely F0 combination. The search process is aided by adaptive spectral envelope modeling and dynamic noise level estimation: while the noise is dynamically estimated, the spectral envelope of previously recorded piano samples (internal database) is adapted in order to best match the piano played on the input signals and aid the search process for the most likely combination of F0s. For comparison, several state-of-the-art algorithms were run across various musical pieces played by different pianos and then compared using three different metrics. The proposed algorithm ranked first place on Hybrid Decay/Sustain Score metric, which has better correlation with the human hearing perception and ranked second place on both onset-only and onset–offset metrics. A previous genetic algorithm approach is also included in the comparison to show how the proposed system brings significant improvements on both quality of the results and computing time.
- Building and Using an Ontology of Preference-Based Multiobjective Evolutionary AlgorithmsPublication . Li, Longmei; Yevseyeva, Iryna; Basto-Fernandes, Vitor; Trautmann, Heike; Jing, Ning; Emmerich, MichaelIntegrating user preferences in Evolutionary Multiobjective Optimization (EMO) is currently a prevalent research topic. There is a large variety of preference handling methods (originated from Multicriteria decision making, MCDM) and EMO methods, which have been combined in various ways. This paper proposes a Web Ontology Language (OWL) ontology to model and systematize the knowledge of preferencebased multiobjective evolutionary algorithms (PMOEAs). Detailed procedure is given on how to build and use the ontology with the help of Prot´eg´e. Different use-cases, including training new learners, querying and reasoning are exemplified and show remarkable benefit for both EMO and MCDM communities.
- Contact center: information systems designPublication . Rijo, Rui; Varajão, João; Gonçalves, RamiroThe economic sector of contact centers is growing by more than 8% a year. It is a multidisciplinary area in which information systems are decisive to organizations' success. Contact Centers' Information Systems deal with real time requisites and critical business information. A theorybuilding research shows a framework with 12 key design factors to consider, which managers might use to develop projects and researchers may adopt for further investigation in the area of Contact Center design. This work intends to provide a valuable link between the research community and practitioners in industry.
- A Dataset of Photos and Videos for Digital Forensics Analysis Using Machine Learning ProcessingPublication . Ferreira, Sara; Antunes, Mário; Correia, Manuel E.Deepfake and manipulated digital photos and videos are being increasingly used in a myriad of cybercrimes. Ransomware, the dissemination of fake news, and digital kidnapping-related crimes are the most recurrent, in which tampered multimedia content has been the primordial disseminating vehicle. Digital forensic analysis tools are being widely used by criminal investigations to automate the identification of digital evidence in seized electronic equipment. The number of files to be processed and the complexity of the crimes under analysis have highlighted the need to employ efficient digital forensics techniques grounded on state-of-the-art technologies. Machine Learning (ML) researchers have been challenged to apply techniques and methods to improve the automatic detection of manipulated multimedia content. However, the implementation of such methods have not yet been massively incorporated into digital forensic tools, mostly due to the lack of realistic and well-structured datasets of photos and videos. The diversity and richness of the datasets are crucial to benchmark the ML models and to evaluate their appropriateness to be applied in real-world digital forensics applications. An example is the development of third-party modules for the widely used Autopsy digital forensic application. This paper presents a dataset obtained by extracting a set of simple features from genuine and manipulated photos and videos, which are part of state-of-the-art existing datasets. The resulting dataset is balanced, and each entry comprises a label and a vector of numeric values corresponding to the features extracted through a Discrete Fourier Transform (DFT). The dataset is available in a GitHub repository, and the total amount of photos and video frames is 40, 588 and 12, 400, respectively. The dataset was validated and benchmarked with deep learning Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) methods; however, a plethora of other existing ones can be applied. Generically, the results show a better F1-score for CNN when comparing with SVM, both for photos and videos processing. CNN achieved an F1-score of 0.9968 and 0.8415 for photos and videos, respectively. Regarding SVM, the results obtained with 5-fold cross-validation are 0.9953 and 0.7955, respectively, for photos and videos processing. A set of methods written in Python is available for the researchers, namely to preprocess and extract the features from the original photos and videos files and to build the training and testing sets. Additional methods are also available to convert the original PKL files into CSV and TXT, which gives more flexibility for the ML researchers to use the dataset on existing ML frameworks and tools.
- Os Desafios Web no Processo Formativo - O Caso de Estudo da humansoftPublication . Sousa, Mayelson de; Gonçalves, AlexandrinoA constante evolução das tecnologias web tem originado o aparecimento de plataformas que facilitam a gestão das tarefas dos utilizadores nos dias de hoje. No sentido de maximizar a satisfação do cliente e disporem de soluções de acordo com os padrões de atuais do mercado, as empresas devem adaptar os seus produtos, com particular enfoque nas soluções web-based, com vista a potenciar a usabilidade e a fluidez do seu uso. Neste sentido, este artigo apresenta um caso de estudo real, de desenvolvimento web na empresa humansoft, onde foram desenvolvidos diversos módulos relativos aos dois principais produtos da empresa, o humantrain, que é um sistema de gestão do processo formativo, e o humanportal, que é uma aplicação web que permite a interoperabilidade entre o humantrain e a web. Ambas as aplicações permitem às entidades formadoras e/ou empresas rentabilizarem a gestão dos seus recursos tanto ao nível pedagógico como financeiros.
- Dispositivo de Navegación Portable para Personas No VidentesPublication . Yanez, Daniel Vera; Marcillo, Diego; Pereira, AntónioLa visión es uno de los más importantes sentidos que ayuda a las personas a navegar en nuestro mundo. Comúnmente las personas no videntes desarrollan sus otros sentidos para poder sentir sus alrededores, pero en ciertos casos esto no es suficiente. Los sentidos pueden ser perturbados por el ruido o enfermedades. Por esta razón se han desarrollado muchos artefactos para ayudar a este grupo de personas. Artefactos como bastones blancos o perros guía ayudan a las personas no videntes a moverse en su entorno. Este artículo propone el uso de un sistema que detecta y reconoce obstáculos cercanos, dando una retroalimentación audible al usuario, evitando una colisión. Es un sistema inalámbrico para que sea cómodo para el usuario. El sistema ayuda a las personas con discapacidad visual a moverse en escenarios interiores o exteriores. Los objetivos del sistema es detectar los obstáculos que los bastones blancos o los perros guía no pueden, ampliando su rango de detección.