Percorrer por autor "Oliveira, Francisco"
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- Development and benchmarking of sensing technologies for Tenebrio molitor dead pupae identificationPublication . Oliveira, Francisco; Tinoco, Vítor; Rodrigues, Leandro; Santos, Filipe N.; Cunha, Mário; Vieira, Inês; Santos, Marisa V.The production of insects for both human and animal consumption has seen an interest increase in recent years. Tenebrio molitor, a beetle species whose larval stage was considered by the European Commission safe for human consumption, represents a promising candidate for large-scale production. Efficient production of T. molitor requires the separation of its different metamorphic stages to optimize productivity and reduce cannibalism. Additionally, dead pupae must be removed to prevent contamination and ensure the healthy development of the remaining individuals. Currently, the identification of dead pupae relies primarily on visual inspection based on colour changes, as dead individuals tend to exhibit surface melanization. However, this method becomes inefficient in large-scale operations. This study presents a benchmark of hyperspectral imaging (HSI) and thermal imaging as alternative sensing technologies for automated dead pupae identification. Hyperspectral data acquired in the near-infrared range (900–1700 nm) enabled accurate discrimination between dead and live pupae using both a PLS-DA and a Logistic Regression model, achieving F1-Scores above 90 % for both classes. Furthermore, key wavelengths (903 nm and 1259 nm) were identified and used to develop a normalized difference index (NDI) capable of distinguishing pupae health status using only two spectral bands. Thermal imaging revealed consistent temperature differences, with dead pupae presenting approximately 1–3 % lower temperatures than live pupae. The proven reliability and precision of the proposed sensing technologies validate their use in contributing to the development of scalable and reliable solutions for quality control in the insect farming industry.
- Development of new analytical tools for monitoring of cardiovascular disease markers – towards the detection of homocysteine-thiolactonePublication . Monteiro, Tiago; Oliveira, Francisco; Silveira, Célia M.; Pereira, Sofia A.; Almeida, M. Gabriela
- New PON1-based biosensor for the detection of homocysteine-thiolactone in human plasmaPublication . Monteiro, Tiago; Oliveira, Francisco; Silveira, Célia M.; Pereira, Sofia A.; Almeida, M. Gabriela
- The BioVisualSpeech corpus of words with sibilants for speech therapy games developmentPublication . Cavaco, Sofia; Guimarães, Isabel; Ascensão, Mariana; Abad, Alberto; Anjos, Ivo; Oliveira, Francisco; Martins, Sofia; Marques, Nuno; Eskenazi, Maxine; Magalhães, João; Grilo, Ana MargaridaAbstract: In order to develop computer tools for speech therapy that reliably classify speech productions, there is a need for speech production corpora that characterize the target population in terms of age, gender, and native language. Apart from including correct speech productions, in order to characterize the target population, the corpora should also include samples from people with speech sound disorders. In addition, the annotation of the data should include information on the correctness of the speech productions. Following these criteria, we collected a corpus that can be used to develop computer tools for speech and language therapy of Portuguese children with sigmatism. The proposed corpus contains European Portuguese children’s word productions in which the words have sibilant consonants. The corpus has productions from 356 children from 5 to 9 years of age. Some important characteristics of this corpus, that are relevant to speech and language therapy and computer science research, are that (1) the corpus includes data from children with speech sound disorders; and (2) the productions were annotated according to the criteria of speech and language pathologists, and have information about the speech production errors. These are relevant features for the development and assessment of speech processing tools for speech therapy of Portuguese children. In addition, as an illustration on how to use the corpus, we present three speech therapy games that use a convolutional neural network sibilants classifier trained with data from this corpus and a word recognition module trained on additional children data and calibrated and evaluated with the collected corpus.