Search results for "Machine"
showing 10 items of 2592 documents
Accelerometry - Simple, but challenging
2017
Des machines dans les vignes. L’acclimatation lente de la vapeur à Dijon et en Côte d’or (1820-1865)
2018
International audience
Analisi di test di Immunofluorescenze indiretta per il supporto alla diagnosi di Malattie Autoimmuni basata su Deep Learning.
2019
La diagnosi delle malattie autoimmuni rappresenta un problema molto importante in medicina. Il test più utilizzato a questo scopo è il test anticorpo antinucleo, un test indiretto di immunofluorescenza. Il metodo proposto affronta tale problema sfruttando le metodologie del Machine Learning. In particolare, fa uso di reti neurali pre-addestrate in grado di classificare i pattern auto anticorpali collegati alle patologie autoimmuni. Gli strati delle reti pre-addestrate e vari parametri di sistema sono stati valutati al fine di ottimizzare il processo. Le prestazioni del sistema sono state valutate in termini di accuratezza in un processo di cross validation, mostrando efficienza e robustezza.
Discriminating and simulating actions with the associative self-organising map
2015
We propose a system able to represent others’ actions as well as to internally simulate their likely continuation from a partial observation. The approach presented here is the first step towards a more ambitious goal of endowing an artificial agent with the ability to recognise and predict others’ intentions. Our approach is based on the associative self-organising map, a variant of the self-organising map capable of learning to associate its activity with different inputs over time, where inputs are processed observations of others’ actions. We have evaluated our system in two different experimental scenarios obtaining promising results: the system demonstrated an ability to learn discrim…
Harmonic Balance Method and Stability of Discontinuous Systems
2019
The development of the theory of discontinuous dynamical systems and differential inclusions was not only due to research in the field of abstract mathematics but also a result of studies of particular problems in mechanics. One of first methods, used for the analysis of dynamics in discontinuous mechanical systems, was the harmonic balance method developed in the thirties of the 20th century. In our work the results of analysis obtained by the method of harmonic balance, which is an approximate method, are compared with the results obtained by rigorous mathematical methods and numerical simulation. peerReviewed
A Deep Learning Model for Automatic Sleep Scoring using Multimodality Time Series
2021
Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. Automatic sleep scoring is crucial and urgent to help address the increasing unmet need for sleep research. Therefore, this paper aims to develop an end-to-end deep learning architecture using raw polysomnographic recordings to automate sleep scoring. The proposed model adopts two-dimensional convolutional neural networks (2D-CNN) to automatically learn features from multi-modality signals, together with a "squeeze and excitation" block for recalibrating channel-wise feature responses. The learnt representations are finally fed to a softmax classifier to generate predictions for each sleep stage. The model pe…
Endotyping allergic rhinitis in children: A machine learning approach.
2021
Introduction: The diversity of allergic rhinitis (AR) phenotypes is particularly evident in childhood, suggesting the need to analyze and identify new approaches to capture such clinical heterogeneity. Nasal cytology (NC) is a very useful diagnostic tool for identifying and quantifying nasal inflammation. Data-driven approaches such as latent class analysis (LCA) assign subjects to classes based on their characteristics. We hypothesized that LCA based on NC, including the assessment of neutrophils, eosinophils, and mast cells, may be helpful for identifying AR endotypes in children. Methods: A total of 168 children were enrolled. Sociodemographic characteristics and detailed medical history…
A novel pilot study of automatic identification of EMF radiation effect on brain using computer vision and machine learning
2020
Abstract Electromagnetic field (EMF) radiations from mobile phones and cell tower affect brain of humans and other organisms in many ways. Exposure to EMF could lead to neurological changes causing morphological or chemical changes in the brain and other internal organs. Cellular level analysis to measure and identify the effect of mobile radiations is an expensive and long process as it requires preparing the cell suspension for the analysis. This paper presents a novel pilot study to identify changes in brain morphology under EMF exposure considering drosophila melanogaster as a specimen. The brain is automatically segmented, obtaining microscopic images from which discriminatory geometri…
Robust Automated Assessment of Human Blastocyst Quality using Deep Learning
2018
AbstractMorphology assessment has become the standard method for evaluation of embryo quality and selecting human blastocysts for transfer inin vitro fertilization(IVF). This process is highly subjective for some embryos and thus prone to human bias. As a result, morphological assessment results may vary extensively between embryologists and in some cases may fail to accurately predict embryo implantation and live birth potential. Here we postulated that an artificial intelligence (AI) approach trained on thousands of embryos can reliably predict embryo quality without human intervention.To test this hypothesis, we implemented an AI approach based on deep neural networks (DNNs). Our approac…
On the Influence of Grammars on Crossover in Grammatical Evolution
2021
Standard grammatical evolution (GE) uses a one-point crossover (“ripple crossover”) that exchanges codons between two genotypes. The two resulting genotypes are then mapped to their respective phenotypes using a Backus-Naur form grammar. This article studies how different types of grammars affect the resulting individuals of a ripple crossover. We distinguish different grammars based on the expected number of non-terminals chosen when mapping genotype codons to phenotypes, \(B_{avg}\). The grammars only differ in \(B_{avg}\) but can express the same phenotypes. We perform crossover operations on the genotypes and find that grammars with \(B_{avg} > 1\) lead to high numbers of either very sm…