ICI - Instituto Coordenador da Investigação
URI permanente desta comunidade:
O ICI integra Unidades de Investigação que exerçam as suas atividades na UBI e que tenham sido classificados com notação igual ou superior a Bom pelos painéis internacionais de avaliação periódica designados pela Fundação para a Ciência e Tecnologia.
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Percorrer ICI - Instituto Coordenador da Investigação por Objetivos de Desenvolvimento Sustentável (ODS) "09:Indústria, Inovação e Infraestruturas"
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- Assessment of Airport Pavement Condition Index (PCI) Using Machine LearningPublication . Santos, Bertha; Studart, André; Almeida, Pedro G.Pavement condition assessment is a fundamental aspect of airport pavement management systems (APMS) for ensuring safe and efficient airport operations. However, conventional methods, which rely on extensive on-site inspections and complex calculations, are often time-consuming and resource-intensive. In response, Industry 4.0 has introduced machine learning (ML) as a powerful tool to streamline these processes. This study explores five ML algorithms (Linear Regression (LR), Decision Tree (DT), Random Forest (RF), Artificial Neural Network (ANN), and Support Vector Machine (SVM)) for predicting the Pavement Condition Index (PCI). Using basic alphanumeric distress data from three international airports, this study predicts both numerical PCI values (on a 0–100 scale) and categorical PCI values (3 and 7 condition classes). To address data imbalance, random oversampling (SMOTE—Synthetic Minority Oversampling Technique) and undersampling (RUS) were used. This study fills a critical knowledge gap by identifying the most effective algorithms for both numerical and categorical PCI determination, with a particular focus on validating class-based predictions using relatively small data samples. The results demonstrate that ML algorithms, particularly Random Forest, are highly effective at predicting both the numerical and the three-class PCI for the original database. However, accurate prediction of the seven-class PCI required the application of oversampling techniques, indicating that a larger, more balanced database is necessary for this detailed classification. Using 10-fold cross-validation, the successful models achieved excellent performance, yielding Kappa statistics between 0.88 and 0.93, an error rate of less than 7.17%, and an area under the ROC curve greater than 0.93. The approach not only significantly reduces the complexity and time required for PCI calculation, but it also makes the technology accessible, enabling resource-limited airports and smaller management entities to adopt advanced pavement management practices.
- Automated and Intelligent Inspection of Airport Pavements: A Systematic Review of Methods, Accuracy and Validation ChallengesPublication . Feitosa, Ianca; Santos, Bertha; Almeida, Pedro G.; mdpiAirport pavement condition assessment plays a critical role in ensuring operational safety, surface functionality, and long-term infrastructure sustainability. Traditional visual inspection methods, although widely used, are increasingly challenged by limitations in accuracy, subjectivity, and scalability. In response, the field has seen a growing adoption of automated and intelligent inspection technologies, incorporating tools such as unmanned aerial vehicles (UAVs), Laser Crack Measurement Systems (LCMS), and machine learning algorithms. This systematic review aims to identify, categorize, and analyze the main technological approaches applied to functional pavement inspections, with a particular focus on surface distress detection. The study examines data collection techniques, processing methods, and validation procedures used in assessing both flexible and rigid airport pavements. Special emphasis is placed on the precision, applicability, and robustness of automated systems in comparison to traditional approaches. The reviewed literature reveals a consistent trend toward greater accuracy and efficiency in systems that integrate deep learning, photogrammetry, and predictive modeling. However, the absence of standardized validation protocols and statistically robust datasets continues to hinder comparability and broader implementation. By mapping existing technologies, identifying methodological gaps, and proposing strategic research directions, this review provides a comprehensive foundation for the development of scalable, data-driven airport pavement management systems.
- Computational Resources and Infrastructures for a Novel Bioinformatics Laboratory: A Case StudyPublication . Maldonado, Emanuel Filipe Escaleira ; Lemos, Manuel; Manoj, Gupta; Dennis, DouroumisIntroduction: Bioinformatics is a relatively recent multidisciplinary research field continuously offering novel opportunities. Although many researchers are actively working in/with bioinformatics, some research centers still face difficulties in hiring bioinformaticians and establishing the appropriate (first) bioinformatics infrastructures and computational resources. In our research center, we started from scratch and established initial bioinformatics infrastructures for common use and also for the specific case of precision/personalized medicine. Case description: Here, we report a case study reflecting our specific needs and circumstances during the implementation of a novel bioinformatics laboratory. This involved the preparation of rooms, computer networks, computational resources novel designs, and upgrades to existing designs. Moreover, this work involved people from diverse areas and institutions, such as companies, institutional projects, informatics, and technical infrastructures services. Discussion and evaluation: The work resulted in the implementation of four novel designs dedicated to genomic medicine and in the adaptation of two existing designs dedicated to common use located in the dry-lab room. This is not an accurate and objective work, as it often depends on the available computer hardware and the target bioinformatics field(s). The four novel designs offered substantial improvements when compared to the upgraded designs, additionally corroborated by performance evaluations, which resulted in an overall highest performance of the novel designs. Conclusions: We present work that was developed over two years until completion with functioning infrastructure. This project enabled us to learn many novel aspects not only related to redundant disk technologies, but also related to computer networks, hardware, storage-management operating systems, file systems, performance evaluation, and also in the management of services. Moreover, additional equipment will be important to maintain and expand the potential and reliability of the bioinformatics laboratory. We hope that this work can be helpful for other researchers seeking to design their bioinformatics equipment or laboratories.
- Driving Healthcare Monitoring with IoT and Wearable Devices: A Systematic ReviewPublication . João Pedro da Silva Baiense; Zdravevski, Eftim; Coelho, Paulo Jorge Simões; Serrano Pires, Ivan Miguel; Velez, Fernando J.Wearable technologies have become a significant part of the healthcare industry, collecting personal health data and extracting valuable information for real-time assistance. This review article analyzes 35 scientific publications on driving healthcare monitoring with IoT and wearable device applications. These articles were considered in a quantitative and qualitative analysis using the Natural Language Processing framework and the PRISMA methodology to filter the search results. The selected articles were published between January 2010 and May 2024 in one of the following scientific databases: IEEE Xplore, Springer, ScienceDirect (i.e., El- sevier), Association for Computing Machinery (ACM), Multidisciplinary Digital Publishing Institute (MDPI), or PubMed Central. The analysis considers population, methods, hardware, features, and communications. The research highlights that data collected from one or numerous sensors is processed and accessible in a database server for various uses, such as informing professional careers or assisting users. The review sug- gests that robust and efficient driving healthcare monitoring with IoT and wearable devices applications can be designed considering the valuable principles presented in this review.
- Dual-Purpose Star Tracker and Space Debris Detector: Miniature Instrument for Small SatellitesPublication . Beltran Nadal Arribas; Maia, João G.; Castanheira, João Pedro Conceição ; Filho, Joel Alves Costa ; Melício, Rui; Gordo, Paulo Romeu Seabra; Onderwater, Hugo; Duarte, Rui; Silva, André Resende Rodrigues daThis paper presents the conception, design and real miniature instrument implementation of a dual-purpose sensor for small satellites that can act as a star tracker and space debris detector. In the previous research work, the authors conceived, designed and implemented a breadboard consisting of a computer laptop, a camera interface and camera controller, an image sensor, an optics system, a temperature sensor and a temperature controller. It showed that the instrument was feasible. In this paper, a new real star tracker miniature instrument is designed, physically realized and tested. The implementation follows a New Space approach; it is made with Commercial Off-the-Shelf (COTS) components with space heritage. The instrument’s development, implementation and testing are presented.
- Fractal Patch Antenna based on Photonic Crystal for Enhanced Millimeter-Wave Communication in Intelligent Transportation SystemsPublication . Bagheri, Nila; Peha, Jon; Velez, Fernando J.; VelezThis paper introduces a Fractal Patch Antenna (FPA) integrated with Photonic Crystals (PhC) designed for Intelligent Transportation Systems (ITS) in the Millimeter-wave bands (mmWaves) given the importance of the application of mmWaves in Vehicle-to-Everything (V2X) networks, we assumed, as examples, that the antenna is designed to resonate at three frequency bands: 31.42 GHz, 37.76 GHz, and 38.92 GHz. With a gain of 10.88 dBi, at 38.92GHz, the antenna demonstrates promising signal reception and transmission capabilities, which are anticipated to be important for ITS operations. The antenna bandwidth covers multiple frequency bands, enabling versatile communication in mmWaves V2X applications. To evaluate the performance of the antenna, we conducted a detailed analysis of its configuration. This included a comparison of the antenna with and without the PhC integration, as well as an exploration of rectangular lattice structure. In addition, variations in hole sizes and spacing were examined to assess their impact on key parameters such as the gain and reflection coefficient. The integration of fractal geometry and PhC structures results in a compact, high-performance antenna suitable for mmWave communication. The integration of fractal geometry and PhC structure results in compactness and high performance in mmWaves communication applications. Through simulation and analysis, including radiation pattern, gain, and reflection coefficient plot assessment, the antenna performance is thoroughly evaluated. The study highlights the potential of the proposed FPA-PhC antenna configuration to enhance communication networks within the ITS, significantly advancing the ITS system with support from the mmWave bands.
- Heuristic Global Optimization for Thermal Model Reduction and Correlation in Aerospace ApplicationsPublication . Castanheira, João Pedro Conceição ; Arribas, Beltran; Melício, Rui; Gordo, Paulo Romeu Seabra; Silva, André Resende Rodrigues daThis study addresses the challenge of accurately correlating detailed and reduced thermal models in aerospace applications by using heuristic global optimization methods. In the context of increasingly complex thermal systems, traditional manual correlation methods are usually a time-consuming task. This research employs a series of numerical simulations using methods such as Genetic Algorithms, Cultural Algorithms, and Artificial Immune Systems, with an emphasis on parameter tuning to optimize the reduced thermal model correlation. Results indicate that these heuristic methods can achieve high-accuracy correlations, with transient simulations exhibiting temperature differences below 3 °C, thereby validating the hypothesis that heuristic methods can effectively navigate complex parameter optimizations. Moreover, a comparative analysis of fitness function performance across various optimization methods underscores both the potential and computational challenges inherent in these approaches. The findings suggest that while heuristic global optimization provides a robust framework for thermal model reduction and correlation, further refinement—particularly in scaling to larger, more complex models and adaptive parameter tuning—is necessary. Overall, this work contributes to the theoretical understanding and practical application of advanced optimization strategies in aerospace thermal analysis, paving the way for improved predictive reliability and more efficient engineering processes.
- How different are conventional and biofuel sprays applied to aviation? An infodynamic comparative analysisPublication . Ferrão, Inês Alexandra dos Santos ; Panão, Miguel Rosa Oliveira; Mendes, Miguel; Moita, Ana Sofia Oliveira Henriques; Silva, André Resende Rodrigues daThe transition from fossil to sustainable and alternative fuels is imperative to address environmental concerns and meet energy requirements. Thus, the implementation of alternative fuels requires a deeper investigation of spray behavior. This study explores conventional jet fuel (Jet A-1) and hydrotreated vegetable oil (HVO) in terms of breakup length and spray dynamics over a wide range of operating conditions. The normalized mean breakup length was measured, and an empirical correlation was developed based on the experimental data. Focusing on the droplet sizes in fuel sprays, which are critical for optimizing combustion, an informational perspective for comparative analysis was explored. The terms informature, infotropy, and infosensor were introduced to quantify and capture the non-deterministic nature of physical systems. The results revealed similar drop size distributions for HVO and Jet A-1, with the Gamma function effectively characterizing the distributions. Both fuels exhibit spray evolution toward higher complexity states, emphasizing the role of aerodynamic forces and minimum development distance in atomization. The new lexicon of infodynamics views sprays as networks of information flow, with infotropy indicating that both fuels produce sprays with similar degrees of transformation. HVO is endorsed as a viable alternative with broader implications for sustainable aviation solutions and understanding complex engineering processes.
- Mitigating Dynamic Stall with a Movable Leading-Edge: the NACA0012-IK30 WingPublication . Camacho, Emanuel António Rodrigues ; Silva, André Resende Rodrigues da ; Marques, Flávio D.One major problem that affects rotor blade aerodynamics is dynamic stall, characterized by a series of events where transient vortex shedding negatively affects drag and lift, leading to abrupt changes in the wing’s pitching moment. The present work focuses on the mitigation of such effects by using a modified NACA0012 airfoil: the NACA0012-IK30 airfoil, used previously for thrust enhancement in flapping propulsion. An experimental rig is designed and built to study the advantages of a time-varying pitching leading edge on a plunging wing, more specifically its influence on the aerodynamic coefficients over time. Results indicate that when the wing is not experiencing significant stall, the movable leading edge does not hold considerable influence on drag or lift. However, it can reduce the pitching moment intensity by indirectly shifting the pressure center. Contrarily, when the wing is under proper dynamic stall, the movable leading edge truly improves the aerodynamic characteristics while operating at smaller effective angles of attack. This study contributes to the long-standing discussion on how to mitigate the adverse effects of dynamic stall by providing an innovative yet simple solution.
- Predicting airfoil dynamic stall loads using neural networksPublication . Camacho, Emanuel António Rodrigues ; Silva, André Resende Rodrigues da ; Marques, Flávio D.Dynamic stall is an aerodynamic regime characterized by loss of airfoil lift, drag increment, and abrupt changes in the pitching moment. Such effects can couple with structural dynamics where perturbations can be easily amplified, making this a critical phenomenon that jeopardizes operational safety. Hence, there is always the need to constantly study the basics of dynamic stall and provide newer predictive models that can take advantage of the current interest peak in artificial intelligence. The present work builds upon that need, exploring the ability of a simple feed-forward network to predict the oscillation cycle of a pitching airfoil experiencing from light to deep stall of a NACA0012 airfoil close to a Reynolds number of approximately 1.1x10^6. The proposed neural network uses the angle of attack and its rate of change as inputs, then estimates the whole aerodynamic cycle at once, outputting an aggregated vector of drag, lift, and pitching moment coefficients. The training phase was conducted using a database containing several conditions obtained from experimental tests, with a strict convergence criterion of R^2=0.99 for both training and test datasets. Results show that the neural network, even in the least-performing conditions, can capture the aerodynamics and overall tendencies, even if some dynamics are underrepresented in the training dataset. The present work brings down the complexity of methodology while demonstrating that a simplistic architecture can still offer an accurate dynamic stall model.