ESTG - Artigos em revistas internacionais
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- Abordagem baseada em Algoritmos Genéticos para deteção de vulnerabilidades de SQL Injection em Aplicações Web PHPPublication . Baptista, Kevin; Bernardino, Anabela Moreira; Bernardino, Eugénia MoreiraHoje em dia, existe uma maior preocupação com a segurança no desenvolvimento de aplicações web. No entanto, ainda existem muitos ataques a este tipo de aplicações, perpetuados por hackers que se aproveitam das vulnerabilidades destas aplicações. Estas vulnerabilidades podem estar associadas a inúmeros fatores, desde configurações incorretas, falhas nas políticas de segurança, sistemas ou componentes desatualizados ou problemas diretamente associados ao código desenvolvido. Os ataques a aplicações web tem como resultado perda de informação privilegiada. Para mitigar este problema, existem varias ferramentas automatizadas que permitem auxiliar profissionais da área a identificar estas vulnerabilidades. No entanto, manter estas ferramentas atualizadas com a evolução tecnológica tem-se demonstrado um desafio. Neste artigo, propomos uma abordagem para detetar vulnerabilidades de SQL Injection no código-fonte de varias aplicações web PHP, usando Algoritmos Genéticos (AG). Os resultados obtidos mostram a eficiência do AG em relação a outras ferramentas existentes.
- 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.
- An Annotated Corpus of Crime-Related Portuguese Documents for NLP and Machine Learning ProcessingPublication . Carnaz, Gonçalo; Antunes, Mário; Nogueira, Vitor BeiresCriminal investigations collect and analyze the facts related to a crime, from which the investigators can deduce evidence to be used in court. It is a multidisciplinary and applied science, which includes interviews, interrogations, evidence collection, preservation of the chain of custody, and other methods and techniques of investigation. These techniques produce both digital and paper documents that have to be carefully analyzed to identify correlations and interactions among suspects, places, license plates, and other entities that are mentioned in the investigation. The computerized processing of these documents is a helping hand to the criminal investigation, as it allows the automatic identification of entities and their relations, being some of which difficult to identify manually. There exists a wide set of dedicated tools, but they have a major limitation: they are unable to process criminal reports in the Portuguese language, as an annotated corpus for that purpose does not exist. This paper presents an annotated corpus, composed of a collection of anonymized crime-related documents, which were extracted from official and open sources. The dataset was produced as the result of an exploratory initiative to collect crime-related data from websites and conditioned-access police reports. The dataset was evaluated and a mean precision of 0.808, recall of 0.722, and F1-score of 0.733 were obtained with the classification of the annotated named-entities present in the crime-related documents. This corpus can be employed to benchmark Machine Learning (ML) and Natural Language Processing (NLP) methods and tools to detect and correlate entities in the documents. Some examples are sentence detection, named-entity recognition, and identification of terms related to the criminal domain.
- Application of "thematic analysis" to a set of businesses success stories in the internationalization processPublication . Brás, Gonçalo Nuno RodriguesThis current work is an example of applying the methodology of "thematic analysis" to a set of business success stories in the process of internationalization. It is assumed that these cases, as a hypothesis, constitute discourses obtained appropriately allowing synthesizing and relating some of the basic features inherent in the internationalization of companies. Results showed the prevalence of stimuli intrinsic to the company, to the detriment of extrinsic stimuli, and lower incidence that companies expose their barriers to internationalization. In the area of internationalization of firms, it confirms the association of entrepreneurial characteristics and the fundamental export nature of Portuguese business companies.
- Aprendizagem Interorganizacional e Capacidade Absortiva: Investigação em Pequenas e Médias EmpresasPublication . Cassol, Alessandra; Marietto, Márcio L.; Tonial, Graciele; Werlang, Nathalia B.Objetivo: Esta pesquisa analisa a influência da aprendizagem interorganizacional (AIO) sobre a capacidade absortiva (Acap), potencial (Pacap) e realizada (Racap), no ambiente de pequenas e médias empresas (PMEs). Originalidade/valor: O estudo contribuiu para o entendimento e a expansão das pesquisas da AIO operacionalizadas por meio dos elementos da Acap. A compreensão desses elementos é fundamental para o desenvolvimento de novas competências das PMEs brasileiras e/ou de países emergentes, imersas em setores dinâmicos e de alta mobilidade tecnológica, para se adaptarem e desenvolverem novas capacidades dinâmicas. Design/metodologia/abordagem: A pesquisa foi realizada por meio de uma survey em uma amostra de 215 PMEs do setor de tecnologia da informação e comunicação (TIC) no estado de Santa Catarina, Brasil. Os dados foram analisados a partir da técnica de modelagem de equações estruturais. Resultados: Os resultados demonstraram que as relações de AIO são capazes de influenciar o desenvolvimento de novas competências e possuem forte influência sobre o desenvolvimento da Acap. A habilidade das organizações em adquirir, assimilar, aplicar e internalizar os conhecimentos disponíveis no setor, por meio de relações interorganizacionais, foi fundamental para a adaptação e sobrevivência.
- 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.
- Beyond Leakage: Non-Revenue Water Loss and Economic SustainabilityPublication . Santos, EleonoraWater loss in urban supply systems poses significant challenges for water utility companies worldwide, affecting both sustainable access to clean water and the financial viability of utility operations. This study analyzes the evolution of water losses in high-level supply systems from 2017 to 2021 in Portugal, focusing on its implications for the profitability of water utility companies across NUTs II regions. Drawing on data from various sources, including the National Information System for Water Resources, PORDATA, ERSAR, and ORBIS, this analysis identifies trends, patterns, and potential factors influencing water loss dynamics. Key components of the analysis include calculating average annual losses, examining unbilled water percentages, and conducting regression analysis to quantify the impact of water loss on profit margins. The findings contribute to the literature on water loss management and financial performance in the water utility sector, offering insights for policymakers, water utility managers, and stakeholders to enhance financial sustainability and reduce water losses.