CIIC - Artigos em Revistas com Peer Review
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Browsing CIIC - Artigos em Revistas com Peer Review by Sustainable Development Goals (SDG) "08:Trabalho Digno e Crescimento Económico"
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- 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.
- 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.
- Elder care architecture - A physical and social approachPublication . Marcelino, Isabel; Barroso, João; Cruz, José Bulas; Pereira, AntónioAs we observe society in our days, we can see that people live longer; this means that we have an older population, more likely to have health issues. The special needs presented by the elderly are becoming a major concern for all of us, along with the lack of time demonstrated by society as a whole and, as a consequence, the lack of time is seen when families are not able to take care of their own elders. Many solutions are being presented in order to solve this problem. Some of them are taking advantage of the new technological developments in the body sensor networks area. In this paper we propose the architecture of a system called Elder Care. The Elder Care solution has two primary goals: monitoring vital signs, sending alerts to family and to specialized help and providing a social network in order to help end the elderly's social isolation.
- Evolutionary Swarm based algorithms to minimise the link cost in Communication NetworksPublication . Moreira Bernardino, Anabela; Sánchez-Pérez, Juan Manuel; Gómez-Pulido, Juan Antonio; Vega-Rodríguez, Miguel Ángel; Bernardino, Eugénia MoreiraIn the last decades, nature-inspired algorithms have been widely used to solve complex combinatorial optimisation problems. Among them, Evolutionary Algorithms (EAs) and Swarm Intelligence (SI) algorithms have been extensively employed as search and optimisation tools in various problem domains. Evolutionary and Swarm Intelligent algorithms are Artificial Intelligence (AI) techniques, inspired by natural evolution and adaptation. This paper presents two new nature-inspired algorithms, which use concepts of EAs and SI. The combination of EAs and SI algorithms can unify the fast speed of EAs to find global solutions and the good precision of SI algorithms to find good solutions using the feedback information. The proposed algorithms are applied to a complex NP-hard optimisation problem - the Terminal Assignment Problem (TAP). The objective is to minimise the link cost to form a network. The proposed algorithms are compared with several EAs and SI algorithms from literature. We show that the proposed algorithms are suitable for solving very large scaled problems in short computational times.
- Explaining the seismic moment of large earthquakes by heavy and extremely heavy tailed modelsPublication . Felgueiras, Miguel MartinsThe search of physical laws that explain the energy released by the great magnitude earthquakes is a relevant question, since as a rule they cause heavy losses. Several statistical distributions have been considered in this process, namely heavy tailed laws, like the Pareto distribution with shape parameter α ≈ 0. 6667. Yet, for the usually considered Californian region (where earthquakes with moment magnitude, MW, greater than 7. 9 were never registered) the Pareto distribution with index near the above mentioned seems to have a "too heavy" tail for explaining the bigger earthquakes seismic moments. Usually an exponential tapper is applied to the distribution right tail (above the so called corner seismic moment), or another distribution is considered to explain these high seismic moment data (like another Pareto with different shape parameter). The situation is different for other regions where seisms of larger magnitudes do occur, leading to data sets for which heavy or even extremely heavy tailed models are appropriated. The purpose of this paper is to reduce the seismic moment, M0, of the very large earthquakes to particular heavy and extremely heavy tailed distributions. Using world seismic moment information, we apply Pareto, Log-Pareto and extended slash Pareto distributions to the data, truncated for M0 ≥ 1021 Nm and for M0 ≥ 1021. 25 Nm. For these great seisms we conclude that extended slash Pareto is a promising alternative to the more traditional Pareto and Log-Pareto distributions as a candidate to the real model underlying the data.
- 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.
- Illuminating the past: state of the artPublication . Happa, Jassim; Mudge, Mark; Debattista, Kurt; Artusi, Alessandro; Gonçalves, Alexandrino; Chalmers, AlanVirtual reconstruction and representation of historical environments and objects have been of research interest for nearly two decades. Physically based and historically accurate illumination allows archaeologists and historians to authentically visualise a past environment to deduce new knowledge. This report reviews the current state of illuminating cultural heritage sites and objects using computer graphics for scientific, preservation and research purposes. We present the most noteworthy and up-to-date examples of reconstructions employing appropriate illumination models in object and image space, and in the visual perception domain. Finally, we also discuss the difficulties in rendering, documentation, validation and identify probable research challenges for the future. The report is aimed for researchers new to cultural heritage reconstruction who wish to learn about methods to illuminate the past.
- Indicator-based multi objective evolutionary algorithms and an application in filament winding processPublication . Yevseyeva, Iryna; de Melo, Francisco Queirós; Grácio, José; Basto-Fernandes, VitorThis work presents recent developments on multi objective evolutionary algorithms, so-called set-based evolutionary algorithms. These techniques are shown to approximate a Pareto front of efficient solutions taking into account both quality of the approximation and its diversity, both important in the design of these methods. Set-based evolutionary algorithms outperform their predecessors on a variety of benchmark problems and are suggested as tools to be used for solving complex mechanical engineering problems, such as filament winding process discussed in this work.
- An Integrated Cybernetic Awareness Strategy to Assess Cybersecurity Attitudes and Behaviours in School ContextPublication . Antunes, Mário; Silva, Carina; Marques, FredericoDigital exposure to the Internet among the younger generations, notwithstanding their digital abilities, has increased and raised the alarm regarding the need to intensify the education on cybersecurity in schools. Understanding of the human factor and its influence on children, namely their attitudes and behaviors online, is pivotal to reinforce their awareness towards cyberattacks, and to promote their digital citizenship. This paper aims to present an integrated cybersecurity and cyberawareness strategy composed of three major steps: (1) Cybersecurity attitude and behavior assessment, (2) self-diagnosis, and (3) teaching/learning activities. The following contributions are made: Two questionnaires to assess risky attitudes and behaviors regarding cybersecurity; a self-diagnosis to measure students’ skills on cybersecurity; a lesson plan addressing cyberawareness to be applied on Information and Communications Technology (ICT) and citizenship education curricular units. Cybersecurity risky attitudes and behaviors were evaluated in a junior high school population of 164 students attending the sixth and ninth grades. The assessment focused on two main subjects: To identify the attitudes and behaviors that raise the risk on cybersecurity among the participating students; to characterize the acquired students’ cybersecurity and cyberawareness skills. Global and individual scores and the histograms for attitudes and behaviors are presented. The items in which we have observed significant differences between sixth and ninth grades are depicted and quantified by their corresponding p-values obtained through the Mann–Whitney non-parametric test. Regarding the results obtained on the assessment of attitudes and behaviors, although positive, we observed that the attitudes and behaviors in ninth grade students are globally inferior compared to those attained by sixth grade students. The deployed strategy for cyberawareness was applied in a school context; however, the same approach is suitable to be applied in other types of organizations, namely enterprises, healthcare institutions and public sector.