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- 3D PARTICLE SYSTEMS FOR AUDIO APPLICATIONSPublication . Fonseca, NunoAlthough particle systems are well know for their use in computer graphics, their application in sound is very rare or almost non-existent. This paper presents a conceptual model for the use of particle systems in audio applications, using a full rendering system with virtual microphones: several virtual particles are spread over a virtual 3D space, where each particle reproduces one of the available audio streams (or a modified version), and the overall sound is captured by virtual microphones. Such system can be used on several audio-related areas like sound design, 3D mixing, reverb/impulse response design, granular synthesis, audio up-mixing, and impulse response up-mixing.
- 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.
- Adaptive Evolutionary Testing: An Adaptive Approach to Search-Based Test Case Generation for Object-Oriented SoftwarePublication . Ribeiro, José Carlos Bregieiro; Zenha-Rela, Mário Alberto; de Vega, Francisco FernándezAdaptive Evolutionary Algorithms are distinguished by their dynamic manipulation of selected parameters during the course of evolving a problem solution; they have an advantage over their static counterparts in that they are more reactive to the unanticipated particulars of the problem. This paper proposes an adaptive strategy for enhancing Genetic Programming-based approaches to automatic test case generation. The main contribution of this study is that of proposing an Adaptive Evolutionary Testing methodology for promoting the introduction of relevant instructions into the generated test cases by means of mutation; the instructions from which the algorithm can choose are ranked, with their rankings being updated every generation in accordance to the feedback obtained from the individuals evaluated in the preceding generation. The experimental studies developed show that the adaptive strategy proposed improves the test case generation algorithm's efficiency considerably, while introducing a negligible computational overhead.
- Additive manufacturing as an enabling technology for digital construction: A perspective on Construction 4.0Publication . Duarte, José Pinto; Bartolo, Paulo Jorge; Craveiro, Flávio; Bartolo, HelenaThe construction sector plays a key role in any country's economy.According to a report published by the World Economic Forum, the construction industry currently accounts for about 6% of the world GDP [1] and is expected to reach around 14.7% in 2030 [2]. Construction is a strategically important sector for the European economy involving a wide range of stakeholders and companies, providing 18 million jobs[209]. According to the World Economic Forum, a 1% rise in productivity worldwide could save $100 billion a year in construction costs [3], with the potential to contribute for a country's competitiveness and sustainable development [4–6]. The construction industry consumes a very significant proportion of the raw materials produced around the world, using for instance 50% ofthe global steel production, and is responsible for 30% of the world greenhouse gas emissions. Nonetheless, it provides the fabric of the built environment on which society depends [1,3]. The population living in urban areas is rapidly increasing, which impacts the need for affordable houses, public transportation and utility infrastructure. Yet the perceived image of the construction sector is predominantly low-tech, still relying on craft-based methods, characterized by a poorperformance and quality image [7–10]. The 2016 survey ‘Sustainability in the Supply Chain’ carried out bythe Scape Group [11] concluded that 58% of all construction supplier And contractor respondents identified skilled workforce shortages as anobstacle for a future modernized construction sector
- Agglomeration Externalities in National Systems of Innovation: The Role of Industrial Diversity and Competition on Countries’ Innovative LevelsPublication . Duarte, Marcelo Pereira; Carvalho, Fernando Manuel Pereira de Oliveira; Ferreira, Manuel; Ferreira, Manuel PortugalEconomic geographers, industrial economists and innovation scholars have long debated the impact of agglomeration externalities on innovation, often with conflicting results. We argue that rather than focusing on which agglomeration externality most influences innovation, we should gain a deeper understanding of how agglomeration externalities influence innovation. Drawing on the concept of national systems of innovation (NSI), we examine the role of industrial diversity and domestic competition as contingency factors that affect the relationship between national innovation inputs and outputs. Using secondary data from 86 countries, we developed interaction models, and our findings indicate that industrial diversity positively influences the relationship between innovation inputs and outputs. Additionally, we found that the relationship between innovation inputs and outputs is strengthened at higher levels of diversity and competition. Also, the positive effects of institutions on innovation outputs increase with high industrial diversity and medium to high domestic competition. Similarly, the positive marginal effect of human capital and research on innovation outputs is strengthened by increasing industrial diversity, although a medium-low level of competition can undermine this effect. This study contributes to the ongoing debate on agglomeration externalities and the NSI literature by highlighting the role of industrial diversity and competition in shaping national innovation outcomes.
- Alternative heavy tailed models in seismologyPublication . Felgueiras, Miguel; Martins, João; Santos, RuiGreat earthquakes are commonly considered as the ones with moment magnitude (Mw ) above or equal to 8.0. Since these earthquakes can destroy entire communities located near the epicentre, the search of physical laws that explain the energy released by them is an important issue. There is a connection between the radiated energy of an earthquake, its magnitude and its seismic moment (M 0). Thence, when fitting a heavy or an extremely heavy tailed distribution to a seismic moment dataset, we are in fact adjusting a mathematical model which explains the amount of energy released by these great seisms. Therefore, the main goal of this work is to study the more appropriated Pareto based models (the most used family in this field) when explaining the seismic moment of the great earthquakes. With this purpose in mind, we selected two different catalogs that accommodate recent events and are considered more accurate than other catalogs used in previous works. We conclude that the traditional Pareto distribution remains a good choice to deal with this kind of data, but Log-Pareto lead to higher p-values and Location-scale Pareto is better fitted to the biggest events.
- Application of Renewable Energy—The Case of San Tomé IslandPublication . Ceita, Ludcelma de; Manso, Ricardo; Eugénio, TeresaIn the current context, the energy sector is one of the most important strategic points for the economic transformation of any society. Access to energy is a universal human right and a concern of the state. Whatever national development strategy is defined or implemented, it will always require measures to promote access to energy for all. Although the strong growth of renewable energies worldwide is evident, there are still few studies on their applicability in developing countries. The aim of this study is to contribute to energy sustainability in an emerging country where renewable energies have been little analysed and developed. The country analysed is São Tomé and Príncipe (STP). This paper develops a study on the application of renewable energy, energy sustainability, and clean electricity generation as challenges of the present and ways forward. Aware of the potential of natural resources on the islands of São Tomé and Príncipe, the study follows the following methodology: first phase: a preliminary study to describe the current energy situation on the island; second phase: presentation of a simulation on the use of available resources that has a direct impact on minimising the consumption of fossil fuels on the islands and on the country’s dependence on foreign fuel imports. As a result, the following proposal is made: Utilisation of photovoltaic solar energy with the help of agro-voltaic systems and floating panels, a biomass plant and a transition to electromobility with the help of electric vehicles as energy storage and means of transport.
- 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.