Browsing by Issue Date, starting with "2025-03"
Now showing 1 - 10 of 24
Results Per Page
Sort Options
- The JPEG Pleno Learning-Based Point Cloud Coding Standard: Serving Man and MachinePublication . Guarda, André; M. M. Rodrigues, Nuno; Pereira, FernandoEfficient point cloud coding has become increasingly critical for multiple applications such as virtual reality, autonomous driving, and digital twin systems, where rich and interactive 3D data representations may functionally make the difference. Deep learning has emerged as a powerful tool in this domain, offering advanced techniques for compressing point clouds more efficiently than conventional coding methods while also allowing effective computer vision tasks performed in the compressed domain thus, for the first time, making available a common compressed visual representation effective for both man and machine. Taking advantage of this potential, JPEG has recently finalized the JPEG Pleno Learning-based Point Cloud Coding (PCC) standard offering efficient lossy coding of static point clouds, targeting both human visualization and machine processing by leveraging deep learning models for geometry and color coding. The geometry is processed directly in its original 3D form using sparse convolutional neural networks, while the color data is projected onto 2D images and encoded using the also learning-based JPEG AI standard. The goal of this paper is to provide a complete technical description of the JPEG PCC standard, along with a thorough benchmarking of its performance against the state-of-the-art, while highlighting its main strengths and weaknesses. In terms of compression performance, JPEG PCC outperforms the conventional MPEG PCC standards, especially in geometry coding, achieving significant rate reductions. Color compression performance is less competitive but this is overcome by the power of a full learning-based coding framework for both geometry and color and the associated effective compressed domain processing.
- A Double Deep Learning-Based Solution for Efficient Event Data Coding and ClassificationPublication . Seleem, Abdelrahman; Guarda, André; M. M. Rodrigues, Nuno; Pereira, FernandoEvent cameras have the ability to capture asynchronous per-pixel brightness changes, usually called "events", offering advantages over traditional frame-based cameras for computer vision tasks. Efficiently coding event data is critical for practical transmission and storage, given the very significant number of events captured. This paper proposes a novel double deep learning-based solution for efficient event data coding and classification, using a point cloud-based representation for events. Moreover, since the conversions from events to point clouds and back to events are key steps in the proposed solution, novel tools are proposed and their impact is evaluated in terms of compression and classification performance. Experimental results show that it is possible to achieve a classification performance for decompressed events which is similar to the one for original events, even after applying a lossy point cloud codec, notably the recent deep learning-based JPEG Pleno Point Cloud Coding standard, with a clear rate reduction. Experimental results also demonstrate that events coded using the JPEG standard achieve better classification performance than those coded using the conventional lossy MPEG Geometry-based Point Cloud Coding standard for the same rate. Furthermore, the adoption of deep learning-based coding offers future high potential for performing computer vision tasks in the compressed domain, which allows skipping the decoding stage, thus mitigating the impact of compression artifact
- Synthetic image generation for effective deep learning model training for ceramic industry applicationsPublication . Gaspar, Fábio; Daniel Carreira; Rodrigues, Nuno; Miragaia, Rolando; Ribeiro, José; Costa, Paulo; Pereira, AntónioIn the rapidly evolving field of machine learning engineering, access to large, high-quality, and well-balanced labeled datasets is indispensable for accurate product classification. This necessity holds particular significance in sectors such as the ceramics industry, in which effective production line activities are paramount and deep learning classification mechanisms are particularly relevant for streamlining processes; but real-world image samples are scarce and difficult to obtain, hindering dataset building and consequently model training and deployment. This paper presents a novel approach for dataset building in the context of the ceramic industry, which involves employing synthetic images for building or complementing datasets for image classification problems. The proposed methodology was implemented in CeramicFlow, an innovative computer graphics rendering pipeline designed to create synthetic images by employing computer-aided design models of ceramic objects and incorporating domain randomization techniques. As a result, a fully synthetic image dataset named Synthetic CeramicNet was created and validated in real-world ceramic classification problems. The results demonstrate that synthetic images provide an adequate basis for datasets and can significantly reduce reliance on real-world data when developing deep learning approaches for image classification problems in the ceramic industry. Furthermore, the proposed approach can potentially be applied to other industrial fields.
- Sex-related differences in ST-segment elevation myocardial infarction: A Portuguese multicenter national registry analysisPublication . Gonçalves, Carolina Miguel; Carvalho, Mariana; Vazão, Adriana; Cabral, Margarida; Martins, André; Saraiva, Fátima; Morais, João; Oliveira, MárioIntroduction and objectives Sex differences among patients with acute myocardial infarctions remain a matter of debate. Inequalities in presentation, diagnosis, treatment, and prognosis are frequently observed, contributing to a worse prognosis in women. The aim of this study was to investigate sex-related differences in Portuguese ST-segment elevation myocardial infarction (STEMI) patients. Methods The authors conducted a retrospective analysis of STEMI patients included in the Portuguese Registry on Acute Coronary Syndromes, between October 2010 and 2022. The two co-primary endpoints were in-hospital and one-year mortality. Results A total of 14 470 STEMI patients were studied. Women were underrepresented with 3721 individuals (25.7%). They were significantly older (70 vs. 62 years, p<0.001), with higher prevalence of cardiovascular risk factors, and underwent less frequently coronary angiography (84.4% vs. 88.5%, p<0.001) and guideline-directed medical therapy (e.g., aspirin 92.5% vs. 95.4%, beta blockers 79.2% vs. 83%, p<0.001). Furthermore, they experienced more complications, such as congestive heart failure (23.4% vs. 14.6%), ischemic stroke (47% vs. 40%), and in-hospital mortality (8.5% vs. 4.1%) (p<0.001 for all comparisons). Similarly, they presented higher one-year mortality (11.5% vs. 6.3%, p<0.001). However, after a multivariate analysis testing significant clinical variables, female sex remained an independent predictor for in-hospital (odds ratio=1.633; 95% CI [1.065–2.504]; p=0.025), but not for one-year mortality. Conclusions This analysis reveals sex-related disparities in Portuguese STEMI patients. Despite limitations inherent to registry-based analysis, women were significantly older, with increased cardiovascular risk, less treated, and with higher in-hospital mortality. These disparities should be a concern for clinicians to further improve outcomes and move toward equitable medical care.
- 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.
- The impact of Covid-19 on Portuguese Accommodation Sector DefaultPublication . Costa, Magali; Lisboa, Inês; Fortes, FabritonPurpose: Worldwide travel restrictions and other measures to mitigate the pandemic situation caused a period of instability for accommodation companies. The consequences of this global phenomenon are still being explored. This study aims to understand the impact of Covid-19 on the probability of not fulfilling its obligations (default risk) and on its determinants in the Portuguese accommodation sector. Methodology: A Logistic regression on a panel data of 8,688 companies located in Portugal, from 2017 to 2022 was used. Results: The results show that Covid-19 contributed to an increase in the percentage of defaulters. Moreover, the pandemic situation had an impact on what determines financial difficulties. The determinants are different depending on the period analyzed, and the company’s size. Originality: This study adds empirical evidence on the impact of non-payment in the accommodation sector in Portugal and, to the best of our knowledge, there is a lack of literature on the impact of Covid-19.
- Model testing – decision-making on capacity expansion in family businesses. Evidence from PortugalPublication . Nemes, Kinga; Lisboa, Inês; Konczos-Szombathelyi, MártaThis paper aims to test and validate a model of internal factors influencing the capacity expansion decisions of family businesses, thereby helping these organizations better understand their decision-making processes. The identified internal factors include socio-emotional wealth, intergenerational cooperation, and a heterogeneous top management team. The study focuses on family businesses in the Portuguese food industry and employs both qualitative and quantitative methods. A structured online questionnaire, completed by 150 respondents, was analyzed using SPSS. Additionally, in-depth interviews were conducted to confirm the quantitative findings and provide a broader conceptual perspective. The results indicate that both qualitative and quantitative analyses support the proposed model.
- Prospetiva 2035 - Três Cenários para o Futuro de Leiria e OestePublication . Lopes, Carla, Alexandra Calado Lopes; Almeida, Isabel; Carriço, Silvia; Mouga, Teresa; Fernandes, Isabel; Siopa, Jorge; Gala, Pedro; Antunes, Mário; Silva, AgostinhoA EM@IPLeiria é um think tank criado em 2023 para impulsionar um desenvolvimento sustentável, inovador e competitivo na região de Leiria e Oeste. Mais do que um centro de estudos, é uma fábrica de ideias e soluções, dedicada à análise dos desafios estruturais do território, à identificação de novas oportunidades e ao teste de respostas concretas para problemas reais. Como espaço de cocriação e experimentação, a EM@IPLeiria envolve diversos atores regionais, incluindo autarquias, empresas, instituições de ensino e a sociedade civil, promovendo um modelo de trabalho colaborativo e participativo na construção de estratégias para o futuro. A sua abordagem alia design thinking e prospetiva estratégica, permitindo antecipar tendências, conceber cenários e testar soluções inovadoras antes da sua aplicação em larga escala.
- Effect of Preventive Exercise Programs for Swimmer’s Shoulder Injury on Rotator Cuff Torque and Balance in Competitive Swimmers: A Randomized Controlled TrialPublication . Tavares, Nuno; Vilas-Boas, João Paulo; Castro, Maria AntónioBackground: Over the season, competitive swimmers experience a progressive imbalance in rotator cuff strength, predisposing them to a significant risk factor for a swimmer’s shoulder injury. Objectives: Verify the effectiveness of two 12-week preventive programs on the shoulder rotators’ peak torque and conventional/functional ratios. Design: A care provider- and participant-blinded, parallel, randomized controlled trial with three groups. Participants: Competitive swimmers aged 16 to 35 years with no prior clinical issues related to their shoulders. Interventions: Twice a week, over 12 weeks, the two experimental groups performed five exercises where the only difference was executing the program with weights or elastic bands, and the control group performed a sham intervention. Main outcome measures: The concentric and eccentric peak torque of the internal and external rotators of the dominant shoulder were assessed before and after the intervention using an isokinetic dynamometer Biodex System 3, at 60°/s, 120°/s, and 180°/s. Results: Among the experimental groups, only one test indicated a reduction (p ≤ 0.05) in rotator peak torque, while the control group showed a decrease (p ≤ 0.05) in five tests. Swimmers who completed the prevention programs demonstrated less imbalance in conventional/functional ratios than controls. Conclusions: Implementing a 12-week preventive program minimizes the progressive shoulder rotational imbalance over the season in competitive swimmers. Clinical Trial Registration number: NCT06552585.
- STICKY COSTS IN THE CLASSROOM: RETHINKING MANAGEMENT ACCOUNTING EDUCATION FOR REAL-WORLD FINANCIAL CHALLENGESPublication . Lucas, Ana; Azevedo, Graça; Oliveira, J; Lima Santos, LuísIn recent years, research on cost behavior in accounting has advanced significantly, particularly with the introduction of the concept of “sticky costs.” These costs exhibit asymmetry, meaning they increase more rapidly with rising activity levels than they decrease with falling activity. This phenomenon challenges cost management as it complicates earnings predictability and financial stability for organizations. While the concept has gained traction in management accounting literature, its integration into higher education curricula, specifically in degree programs in accounting and management, remains limited. This study aims to analyze the incorporation of the sticky costs concept into the curricula of management accounting courses within degrees in management and accounting at Portuguese universities. The empirical research will involve analyzing the course syllabi to assess how topics related to the asymmetrical behavior of costs are addressed, either explicitly or implicitly, and to determine how these concepts can be better integrated into academic programs to enrich student learning. The study will evaluate the extent to which new theoretical approaches to cost behavior are integrated into the curriculum, comparing them with traditional models that classify costs as either fixed or variable. Furthermore, this research will explore the pedagogical implications of teaching sticky costs within management accounting curricular units, discussing how this knowledge can improve students’ understanding of the cost dynamics within real-world organizations. The study will also assess whether properly addressing sticky costs can better prepare students to tackle the complex financial challenges faced by organizations, particularly in today’s dynamic economic environments. This study also contributes to the broader conversation around the United Nations Sustainable Development Goals (SDGs), specifically SDG 4, which aims to ensure inclusive, equitable, and quality education for all. By integrating concepts such as sticky costs into management accounting curricula, the study seeks to promote a more relevant and practical education, equipping students with a deeper understanding of the financial challenges organizations face. Furthermore, by addressing the financial sustainability of organizations, this research indirectly supports SDG 8, which aims to promote sustained, inclusive, and sustainable economic growth, as well as increased productivity and decent work. The proposed curriculum updates not only enhance the quality of education in management accounting but also reinforce the role of higher education institutions as agents of change, fostering more responsible business practices aligned with global sustainability goals. This research will contribute to improving the academic formation of future professionals in accounting and management, providing both theoretical insights and practical recommendations for curriculum design. Ultimately, it seeks to align educational practices with the evolving needs of the business world, ensuring that students are equipped with the tools necessary for navigating complex financial landscapes and contributing to sustainable economic development.
- «
- 1 (current)
- 2
- 3
- »