Search results for "feature"

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…

Testing Three Theories of Cognitive Dysfunction in Problem Alcohol Use

2014

- Objectives : many hypotheses concerning the cognitive functions affected by chronic alcoholism have been advanced. The aim of this study was to test cognitive performance in a sample of alcoholics and to examine results comparing three different models: the frontal lobe hypothesis, the lateralization hypothesis and the diffuse brain hypothesis. - Methods : 51 patients who refer to alcoholism service have been included in this study. Cognitive functions were assessed by trained psychologist with a specific neuropsychological battery. -Results : our results show a ranking of impairment degrees in different cognitive functions and different influence of clinical features. In our sample the f…

Soil, pasture and animal products quality

2013

The management of pasture, through the use of appropriate stocking rates and grazing systems, influences the feeding behaviour of the animals. The impact of animal behaviour on vegetation can be of great importance for the sustainability of pastures and mantaining their biodiversity. Indeed, a different response in terms of quality of animal products is mediated by the ability of animals to concentrate or transform grass components, according to the characteristics of the soil. The herbage ingested by animals provides them with compounds with aromatic characteristics, such as terpenes, and with functional properties beneficial for human health, such as carotenoids, vitamins, polyphenols and…

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…

Preattentive detection of rare audiovisual feature conjunctions by the human brain as reflected by the mismatch negativity

2007

Application of a Knowledge Discovery Process to Study Instances of Capacitated Vehicle Routing Problems

2020

Vehicle Routing Problems (VRP) are computationally challenging, constrained optimization problems, which have central role in logistics management. Usually different solvers are being developed and applied for different kind of problems. However, if descriptive and general features could be extracted to describe such problems and their solution attempts, then one could apply data mining and machine learning methods in order to discover general knowledge on such problems. The aim then would be to improve understanding of the most important characteristics of VRPs from both efficient solution and utilization points of view. The purpose of this article is to address these challenges by proposi…

A Methodological Approach to Determine Sound Response Modalities to Coastal Erosion Processes in Mediterranean Andalusia (Spain)

2020

Human occupation along coastal areas has been greatly increasing in recent decades and, in many places, human activities and infrastructures are threatened by erosion processes that can produce relevant economic and human losses. In order to reduce such impacts and design sound management strategies, which can range from the &ldquo

Coseismic extension recorded within the damage zone of the Vado di Ferruccio Thrust Fault, Central Apennines, Italy

2018

Recent high resolution hypocentral localisation along active fault systems in the Central Apennines illuminates the activation of seismogenic volumes dipping at low angle (<30°) in extensional settings overprinting contractional deformations affecting the continental crust of the Adria microplate. Individuation of the geological structures and of the fault processes associated with these seismic patterns will contribute to the interpretation of seismic sequence evolution, and seismic hazard studies.Here we report field and microstructural evidence of seismogenic extensional faults localized within pre-existing thrust fault zones. The Vado di Ferruccio Thrust Fault (VFTF) is a narrow …

Social media overload, exhaustion, and use discontinuance : Examining the effects of information overload, system feature overload, and social overlo…

2020

While users’ discontinuance of use has posed a challenge for social media in recent years, there is a paucity of knowledge on the relationships between different dimensions of overload and how overload adversely affects users’ social media discontinuance behaviors. To address this knowledge gap, this study employed the stressor–strain–outcome (SSO) framework to explain social media discontinuance behaviors from an overload perspective. It also conceptualized social media overload as a multidimensional construct consisting of system feature overload, information overload, and social overload. The proposed research model was empirically validated via 412 valid questionnaire responses collecte…

Ensemble feature selection with the simple Bayesian classification

2003

Abstract A popular method for creating an accurate classifier from a set of training data is to build several classifiers, and then to combine their predictions. The ensembles of simple Bayesian classifiers have traditionally not been a focus of research. One way to generate an ensemble of accurate and diverse simple Bayesian classifiers is to use different feature subsets generated with the random subspace method. In this case, the ensemble consists of multiple classifiers constructed by randomly selecting feature subsets, that is, classifiers constructed in randomly chosen subspaces. In this paper, we present an algorithm for building ensembles of simple Bayesian classifiers in random sub…