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de Oliveira Pegado de Noronha E Távora, Luís Miguel
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- Experimental measurement of the mobilities of atomic, Ne+, and dimer, Ne2+, ions in NePublication . Garcia, A. N. C.; Trindade, A. M. F.; Oliveira, T. D. P.; Neves, P. N. B.; Barata, J. A. S.; Távora, L. M. N.; Dias, T. H. V. T.; Borges, F. I. G. M.; Conde, C. A. N.We measured the reduced mobilities of the atomic, Ne+, and dimer, Ne2+, ions in Ne, under different pressures and reduced electric fields, at 300 K. The value obtained for the atomic ion, 4.1 cm2V1 s1, is in good agreement with other values published in the scientific literature. The value obtained for the mobility of the dimer ion, 7.3 cm2 V1 s1, is not in accordance with other published data. We discuss the most probable sources of error.
- Photopeak shift effects due to the drift electric field in high pressure xenon detectorsPublication . Neves, P. N. B.; Barata, J. A. S.; Távora, L. M. N.; Dias, T. H. V. T.; Borges, F. I. G. M.; Conde, C. A. N.The photopeak shift in High Pressure Xe (HPXe) gamma ray detectors due to the energy acquired/lost by the photoelectric and Compton electrons, from the electric field applied in the drift region, is calculated using the PENELOPE code for gamma rays from several radioactive sources. The implications of this effect in HPXe detectors are discussed, namely for TPCs for double beta decay of 136 Xe studies.
- Experimental measurement of the mobilities of atomic and dimer Ar, Kr, and Xe ions in their parent gasesPublication . Neves, P. N. B.; Conde, C. A. N.; Távora, L. M. N.A new experimental technique for measuring the mobilities of positive ions in their parent gases is presented. The technique was applied to the rare gases, Ar, Kr, and Xe, and, for pressures typically below 10 Torr, two different types of positive ions were observed. The reduced mobilities of these ions in their parent gases were measured as a function of E/N, the ratio of the electric field strength to the gas number density, at a temperature of 300±1 K. The results were compared with others available in the literature and the two ions were identified as being the atomic and the dimer rare gas ions. The results are in good agreement with those from other authors. Space charge and impurities effects are discussed.
- Drift field limitations to the energy resolution in Time Projection Chambers for 136Xe neutrino-less double beta decay searchPublication . Neves, P.N.B.; Conde, C.A.N.; de Oliveira Pegado de Noronha E Távora, Luís MiguelThe effect of drift electric field in the degradation of the energy resolution of gaseous xenon Time Projection Chambers for the search of neutrino-less double beta decay of 136Xe is calculated with the PENELOPE code. Calculations are presented first for single electron emission with energies from 0.2 to 3 MeV and reduced electric fields in the 0.1–2 V cm−1 Torr−1 range, showing energy resolution degradations by as much as 12% (FWHM). Calculations are also presented for neutrino-less double beta decay of 136Xe assuming two decay mechanisms, the mass mechanism (MM) and the right-handed current due to the λ parameter (RHCλ) mechanism, for reduced drift electric fields in the 0.03–0.8 V cm−1 Torr−1 range. It is shown that the drift field degrades the energy resolution of the two electrons sum peak (2457.8 keV) by an amount that is significant even for reduced fields as low as 0.1 V cm−1 Torr−1. It is concluded that to reach the experimental target of 1% (FWHM) for the energy resolution of TPCs set-ups (like the NEXT collaboration set-up) the drift electric field should be weaker than about 0.1 V cm−1 Torr−1.
- The X++2X→X2++X reaction rate constant for Ar, Kr and Xe, at 300 KPublication . Neves, P. N. B.; Conde, C. A. N.; Távora, L. M. N.The X++2X → X+2X- reaction rate constants were measured for Ar, Kr and Xe, at 300 K, using a new experimental technique. The results for Ar, kAr=(1.2 ± 0.2) × 10 -31 cm6 Kr, kKr=(2.1 ± 0.9) × 10-31 cm and Xe, kxe=(1.48 ± 0.18) x 10 -31 cm6S-1 are discussed and compared with those of other authors using different techniques.
- Skin lesion classification enhancement using border-line features – The melanoma vs nevus problemPublication . Pereira, Pedro M. M.; Fonseca-Pinto, Rui; Paiva, Rui Pedro; Assuncao, Pedro A. A.; Tavora, Luis M. N.; Thomaz, Lucas A.; Faria, Sergio M. M.Machine learning algorithms are progressively assuming an important role as a computational tool to support clinical diagnosis, namely in the classification of pigmented skin lesions. The current classification methods commonly rely on features derived from shape, colour, or texture, obtained after image segmentation, but these do not always guarantee the best results. To improve the classification accuracy, this work proposes to further exploit the border-line characteristics of the lesion segmentation mask, by combining gradients with local binary patterns (LBP). In the proposed method, these border-line features are used together with the conventional ones to enhance the performance of skin lesion classification algorithms. When the new features are combined with the classical ones, the experimental results show higher accuracy, which impacts positively the overall performance of the classification algorithms. As the medical image datasets usually present large class imbalance, which results in low sensitivity for the classifiers, the border-line features have a positive impact on this classification metric, as evidenced by the experimental results. Both the features’ usefulness and their impact are assessed in regard to the classification results, which in turn are statistically tested for completeness, using three different classifiers and two medical image datasets.
- Integer DCT Approximation With Arbitrary Size and Adjustable PrecisionPublication . Thomaz, Lucas A.; Assunção, Pedro A. A.; Tavora, Luis M. N.; Faria, Sérgio M. M. deThis letter proposes a method to obtain integer reversible discrete cosine transforms for generic transform-based coding schemes. The novelty of the proposed method, which is based on decomposition of the DCT-II matrix into two triangular and one diagonal matrices, is twofold: (i) the new matrices can be of arbitrary size, i.e., any square N\times N dimension, thus suitable for applications where non power-of-2 dimensions are required; (ii) they can be designed with adjustable precision in a trade-off with the number of representation bits. Furthermore, improvements are also proposed over the base scheme to avoid numerical issues when working with large matrices and to obtain more reliable approximations. The performance evaluation demonstrate the effectiveness of the proposed transforms to approximate the coding gain capabilities of the original DCT-II.
- Machine Learning in MRI Brain Imaging: A Review of Methods, Challenges, and Future DirectionsPublication . Ottoni, Martyna; Kasperczuk, Anna; Tavora, Luis M. N.In recent years, machine learning (ML) has been increasingly used in many fields, including medicine. Magnetic resonance imaging (MRI) is a non-invasive and effective diagnostic technique; however, manual image analysis is time-consuming and prone to human variability. In response, ML models have been developed to support MRI analysis, particularly in segmentation and classification tasks. This work presents an updated narrative review of ML applications in brain MRI, with a focus on tumor classification and segmentation. A literature search was conducted in PubMed and Scopus databases and Mendeley Catalog (MC)—a publicly accessible bibliographic catalog linked to Elsevier’s Scopus indexing system—covering the period from January 2020 to April 2025. The included studies focused on patients with primary or secondary brain neoplasms and applied machine learning techniques to MRI data for classification or segmentation purposes. Only original research articles written in English and reporting model validation were considered. Studies using animal models, non-imaging data, lacking proper validation, or without accessible full texts (e.g., abstract-only records or publications unavailable through institutional access) were excluded. In total, 108 studies met all inclusion criteria and were analyzed qualitatively. In general, models based on convolutional neural networks (CNNs) were found to dominate current research due to their ability to extract spatial features directly from imaging data. Reported classification accuracies ranged from 95% to 99%, while Dice coefficients for segmentation tasks varied between 0.83 and 0.94. Hybrid architectures (e.g., CNN-SVM, CNN-LSTM) achieved strong results in both classification and segmentation tasks, with accuracies above 95% and Dice scores around 0.90. Transformer-based models, such as the Swin Transformer, reached the highest performance, up to 99.9%. Despite high reported accuracy, challenges remain regarding overfitting, generalization to real-world clinical data, and lack of standardized evaluation protocols. Transfer learning and data augmentation were frequently applied to mitigate limited data availability, while radiomics-based models introduced new avenues for personalized diagnostics. ML has demonstrated substantial potential in enhancing brain MRI analysis and supporting clinical decision-making. Nevertheless, further progress requires rigorous clinical validation, methodological standardization, and comparative benchmarking to bridge the gap between research settings and practical deployment.
- Lossless light-field compression using reversible colour transformationsPublication . Santos, Joao M.; Pedro A. A. Assuncao; Cruz, Luis A. da Silva; Luís Távora; Fonseca-Pinto, Rui; Sergio M. M. FariaRecent advances in Light Field acquisition and rendering are pushing research efforts towards increasingly efficient methods to encode this particular type of data. Light Field image compression is of the utmost importance, not only due to the large amount of data required for its representation but also due to quality requirements of many applications and computational photography methods. This paper presents a research study about the impact of reversible colour transformations and alternative data arrangements in Light Field lossless coding. The experimental results indicate that the RCT reversible transform consistently achieves the highest compression performance across all data arrangements and lossless encoders. In particular, the best results are obtained with MRP when encoding the stack of sub-aperture images using a spiral scan order, achieving 6.41 bpp, on average.
- Complexity Estimation for Load Balancing of 360-Degree Intra Versatile Video CodingPublication . Filipe, Jose N.; Monteiro Carreira, João Filipe; Tavora, Luis M. N.; Faria, Sergio; Navarro, Antonio; Assuncao, Pedro A. A.The ever increasing demand for image and video content poses new requirements to support higher resolutions and richer representation formats, creating new challenges in coding algorithms. The forthcoming Versatile Video Coding (VVC) standard aims to increase the coding efficiency of existing algorithms and it is particularly suitable for Ultra-High Definition (UHD) resolutions and 360° video. However, since coding efficiency gains are obtained at the cost of increased complexity, fast computational approaches are needed to cope with realtime requirements, such as parallel processing. Thus, this work presents a contribution towards efficient parallel encoding of 360° video, based on coding complexity estimation and nonuniform data-level splitting (slice-based) for load balancing across multiple processors. A machine learning approach is proposed to estimate the complexity of intra coding VVC, using uncorrelated features, obtained through Principal Component Analysis (PCA) and Extremely Randomised Trees (ERT). Then, a complexity-balanced slice partition is devised, taking advantage of the clustered complexity inherent to Equirectangular Projection (ERP). It is shown that coding complexity is estimated with an accuracy of 92.25%, and the encoding time is reduced by 8.50%, when compared to the case where the 360° frames are evenly split.
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