6,820 research outputs found
Modeling complex living systems via signal processing and deep learning
No full textThe original abstract was too long for uniweb.
A copy can be read here https://github.com/jesus-333/phd_thesis/blob/main/Sources/Abstract.tex
or directly inside the thesis
Modeling Value of Information in remote sensing from correlated sources
No full textThis paper investigates data correlation in remote sensing networks and how it can be characterized through diverse models quantifying the Value of Information (VoI), a metric that describes how informative the data transmitted by the sensors are. For each sensor, the VoI evaluations comprise the average node-specific Age of Information (AoI), the average cost spent for sending updates, and the AoI of neighbor nodes, assumed to be correlated sources of information and therefore benefiting the VoI of other sensors nearby. We discuss how this metric can be tracked through a two-dimensional Markov chain, but we also show how this representation can be simplified by including the impact of neighbor nodes within the transition probabilities, so as to obtain a simpler model that gives the same insight in terms of VoI evaluations
[Poesia] Três poemas de Alberto Secama
No full textThree poems by Alberto Secama. About the author: Alberto Secama is an Angolan poet who has poems published on many websites and on facebook:https://www.facebook.com/Xungurra/abouthttp://www.pordentrodaafrica.com/cultura/africa-em-verso-rio-kwanza-por-alberto-secamahttp://www.pordentrodaafrica.com/cultura/africa-em-verso-zong-por-alberto-secamahttp://www.pordentrodaafrica.com/cultura/coluna-africa-em-verso-o-sol-la-fora-por-alberto-secamaTres poemas de Alberto Secama. Sobre el autor: Alberto Secama es un poeta angoleño que tiene poemas publicados en varios sitios y en el facebook:https://www.facebook.com/Xungurra/abouthttp://www.pordentrodaafrica.com/cultura/africa-em-verso-rio-kwanza-por-alberto-secamahttp://www.pordentrodaafrica.com/cultura/africa-em-verso-zong-por-alberto-secamahttp://www.pordentrodaafrica.com/cultura/coluna-africa-em-verso-o-sol-la-fora-por-alberto-secamaTrês poemas de Alberto Secama. Sobre o autor: Alberto Secama é um poeta angolano que possui poemas publicados em vários sites e no facebook:https://www.facebook.com/Xungurra/abouthttp://www.pordentrodaafrica.com/cultura/africa-em-verso-rio-kwanza-por-alberto-secamahttp://www.pordentrodaafrica.com/cultura/africa-em-verso-zong-por-alberto-secamahttp://www.pordentrodaafrica.com/cultura/coluna-africa-em-verso-o-sol-la-fora-por-alberto-secam
vEEGNet: learning latent representations to reconstruct EEG raw data via variational autoencoders
No full textElectroencephalografic (EEG) data are complex multi-dimensional time-series which are very useful in many different applications, i.e., from diagnostics of epilepsy to driving brain-computer interface systems. Their classification is still a challenging task, due to the inherent within- and between-subject variability as well as their low signal-to-noise ratio. On the other hand, the reconstruction of raw EEG data is even more difficult because of the high temporal resolution of these signals. Recent literature has proposed numerous machine and deep learning models that could classify, e.g., different types of movements, with an accuracy in the range 70% to 80% (with 4 classes). On the other hand, a limited number of works targetted the reconstruction problem, with very limited results. In this work, we propose vEEGNet, a DL architecture with two modules, i.e., an unsupervised module based on variational autoencoders to extract a latent representation of the multi-channel EEG data, and a supervised module based on a feed-forward neural network to classify different movements. Furthermore, to build the encoder and the decoder of VAE we exploited the well-known EEGNet network, specifically designed since 2016 to process EEG data. We implemented two slightly different architectures of vEEGNet, thus showing state of the art classification performance, and the ability to reconstruct both low frequency and middle-range components of the raw EEG. Although preliminary, this work is promising as we found out that the low-frequency reconstructed signals are consistent with the so-called motor-related cortical potentials, very specific and well-known motor-related EEG patterns and we could improve over previous literature by reconstructing faster EEG components, too. Further investigations are needed to explore the potentialities of vEEGNet in reconstructing the full EEG data, to generate new samples, and to study the relationship between classification and reconstruction performance
hvEEGNet: a novel deep learning model for high-fidelity EEG reconstruction
No full textIntroductionModeling multi-channel electroencephalographic (EEG) time-series is a challenging tasks, even for the most recent deep learning approaches. Particularly, in this work, we targeted our efforts to the high-fidelity reconstruction of this type of data, as this is of key relevance for several applications such as classification, anomaly detection, automatic labeling, and brain-computer interfaces.MethodsWe analyzed the most recent works finding that high-fidelity reconstruction is seriously challenged by the complex dynamics of the EEG signals and the large inter-subject variability. So far, previous works provided good results in either high-fidelity reconstruction of single-channel signals, or poor-quality reconstruction of multi-channel datasets. Therefore, in this paper, we present a novel deep learning model, called hvEEGNet, designed as a hierarchical variational autoencoder and trained with a new loss function. We tested it on the benchmark Dataset 2a (including 22-channel EEG data from 9 subjects).ResultsWe show that it is able to reconstruct all EEG channels with high-fidelity, fastly (in a few tens of epochs), and with high consistency across different subjects. We also investigated the relationship between reconstruction fidelity and the training duration and, using hvEEGNet as an anomaly detector, we spotted some data in the benchmark dataset that are corrupted and never highlighted before.DiscussionThus, hvEEGNet could be very useful in several applications where automatic labeling of large EEG dataset is needed and time-consuming. At the same time, this work opens new fundamental research questions about (1) the effectiveness of deep learning models training (for EEG data) and (2) the need for a systematic characterization of the input EEG data to ensure robust modeling
Plasma cortisol concentration following breakfasts of different composition in healthy subjects
No full textWe measured plasma cortisol concentrations following breakfasts of different fat:carbohydrate ratio in 23 healthy subjects. A meal-related peak of plasma cortisol concentration was not found, as well as any difference in plasma cortisol levels following the two meals. Since the two meals elicited plasma glucose and plasma insulin levels which were significantly different, it is suggested that plasma cortisol is not acutely affected by ambient glucose and insulin concentrations. The same results were found when the study group was subdivided in nonobese (n = 13) and obese (Body Mass Index greater than n = 10), thus confirming the previous statement in the presence of different body weights
Orizzonti mantovani. Spunti e dinamiche paesaggistiche ne L'Illustrissimo di Alberto Cantoni
No full textIn the literary production of Alberto Cantoni, short story writer and novelist between the nineteenth and twentieth centuries, the novel L'Illustrissimo is highly important both because it is the last publication of the author, from Pomponesco, a small town a few kilometers south of Mantua, both because it summarizes in a single text the different nuances and different directions that his writing has taken over the course of his literary career, also due to a writing and processing time that embraces the entire span of years of his career itself. In the foreground, in addition to the numerous and brilliant characters, one of the protagonists is the Mantuan landscape which, not a simple background, becomes a true literary parameter which in different and significant ways affects the purposes and mechanisms of the novel
The Leather Industry: A Chemistry Insight Part I: an Overview of the Industrial Process
No full textA panoramic overview of the leather world market is given. The industrial tanning process is schematically
explained giving a general outline of how an animal skin is transformed into a durable material having many
different characteristics according to its specific future use. All the tanning industrial steps are overviewed starting
from soaking, liming and after various steps ending up with finishing. An insight of collagen chemistry is also given
Plenary Session: Luis Alberto Urrea
No full texta) Plenary Session: Luis Alberto Urrea, Mexican American Chicago Writer
Luis Alberto Urrea is a 2005 Pulitzer Prize finalist for non-fiction and member of the Latino Literature Hall of Fame. He is a prolific and acclaimed writer who has used his dual-culture life border experiences to explore the complex and interconnected Mexican-US American reality. The critically acclaimed and best-selling Mexican-born author of 13 books, Urrea has won numerous awards for his poetry, fiction and essays.
Moderator: Dr. Héctor García, Loyola University Chicag
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