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This work systematically investigates the oxidation of extra virgin olive oil (EVOO) under accelerated storage conditions with UV absorption and total fluorescence spectroscopy. With the large amount of data collected, it proposes a method…

Machine Learning · Computer Science 2023-09-25 Francesca Venturini , Silvan Fluri , Manas Mejari , Michael Baumgartner , Dario Piga , Umberto Michelucci

Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud, for example through adulteration, creates new challenges…

The olive oil sector produces a substantial impact in the Mediterranean's economy and lifestyle. Many studies exist which try to optimize the different steps in the olive oil's production process. One of the main challenges for olive oil…

This dataset encompasses fluorescence spectra and chemical parameters of 24 olive oil samples from the 2019-2020 harvest provided by the producer Conde de Benalua, Granada, Spain. The oils are characterized by different qualities: 10 extra…

Quantitative Methods · Quantitative Biology 2023-01-12 Francesca Venturini , Michela Sperti , Umberto Michelucci , Arnaud Gucciardi , Vanessa M. Martos , Marco A. Deriu

The easy and accurate identification of varieties is fundamental in agriculture, especially in the olive sector, where more than 1200 olive varieties are currently known worldwide. Varietal misidentification leads to many potential problems…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Hristofor Miho , Giulio Pagnotta , Dorjan Hitaj , Fabio De Gaspari , Luigi V. Mancini , Georgios Koubouris , Gianluca Godino , Mehmet Hakan , Concepcion Muñoz Diez

Background: Classification of volatile organic compounds (VOCs) is of interest in many fields. Examples include but are not limited to medicine, detection of explosives, and food quality control. Measurements collected with electronic noses…

Star-galaxy separation is a crucial step in creating target catalogues for extragalactic spectroscopic surveys. A classifier biased towards inclusivity risks including spurious stars, wasting fibre hours, while a more conservative…

Feature engineering plays a critical role in handling hyperspectral data and is essential for identifying key wavelengths in food fraud detection. This study employs Bayesian Additive Regression Trees (BART), a flexible machine learning…

Applications · Statistics 2025-10-20 Mengxiang Zhu , Riccardo Rastelli

Recently proposed new method "Ethanol as Internal Standard" for determination of volatile compounds in alcohol products by gas chromatography (GC) is investigated from different sides including method testing on prepared standard solutions…

An NUV-optical diagram made for sources from the secend Galaxy Evolution Explorer (GALEX) Ultraviolet Variability (GUVV-2) Catalog provide us a method to tentatively classify the unknown GUVV2 sources by their NUV-optical magnitudes. On the…

Solar and Stellar Astrophysics · Physics 2015-05-27 Y. Li , J. Wang , J. Y. Wei , X. T. He

Selection of extragalactic point sources, e.g. QSOs, is often hampered by significant selection effects causing existing samples to have rather complex selection functions. We explore whether a purely astrometric selection of extragalactic…

High Energy Astrophysical Phenomena · Physics 2015-06-19 Kasper E. Heintz , Johan P. U. Fynbo , Erik Høg

Recently proposed new method "Ethanol as Internal Standard" for determination of volatile compounds in alcohol products by gas chromatography is investigated from different sides. Results of experimental study from three different…

Hot subdwarf stars are faint, blue objects, and are the main contributors to the far-UV excess observed in elliptical galaxies. They offer an excellent laboratory to study close and wide binary systems, and to scrutinize their interiors…

Solar and Stellar Astrophysics · Physics 2016-08-14 R. Oreiro , C. Rodríguez-López , E. Solano , A. Ulla , R. Østensen , M. García-Torres

A novel method based on Fast Neutron Resonance Transmission Radiography is proposed for non-destructive, quantitative determination of the weight percentages of oil and water in cores taken from subterranean or underwater geological…

State-of-the-art techniques to identify H\alpha emission line sources in narrow-band photometric surveys consist of searching for H\alpha excess with reference to nearby objects in the sky (position-based selection). However, while this…

Astrophysics of Galaxies · Physics 2022-11-16 M. Fratta , S. Scaringi , M. Monguió , A. F. Pala , J. E. Drew , C. Knigge , K. A. Iłkiewicz , P. Gandhi

Deep generative models have been demonstrated as problematic in the unsupervised out-of-distribution (OOD) detection task, where they tend to assign higher likelihoods to OOD samples. Previous studies on this issue are usually not…

Machine Learning · Computer Science 2024-01-04 Zezhen Zeng , Bin Liu

In this paper, we demonstrate the potential of applying Variational Autoencoder (VAE) [10] for anomaly detection in skin disease images. VAE is a class of deep generative models which is trained by maximizing the evidence lower bound of…

Machine Learning · Computer Science 2018-07-26 Yuchen Lu , Peng Xu

Most of the sources detected in the extreme ultraviolet (EUV; 100 Ang to 600 Ang) by the Rosat WFC and EUVE all-sky surveys have been identified with active late-type stars and hot white dwarfs that are near enough to escape absorption by…

Astrophysics · Physics 2015-06-24 Dan Maoz , Eran Ofek , Amotz Shemi

This study explores a data-driven approach to discovering novel clinical and genetic markers in ovarian cancer (OC). Two main analyses were performed: (1) a nonlinear examination of an OC dataset using autoencoders, which compress data into…

Out-of-Distribution (OOD) detection under long-tailed distributions is a highly challenging task because the scarcity of samples in tail classes leads to blurred decision boundaries in the feature space. Current state-of-the-art (sota)…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Ningkang Peng , Qianfeng Yu , Yuhao Zhang , Yafei Liu , Xiaoqian Peng , Peirong Ma , Yi Chen , Peiheng Li , Yanhui Gu
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