Search results for "machine learning."

Analysis of the Pre and Post-COVID-19 Lockdown Use of Smartphone Apps in Spain

2021

The global pandemic of COVID-19 has changed our daily habits and has undoubtedly affected our smartphone usage time. This paper attempts to characterize the changes in the time of use of smartphones and their applications between the pre-lockdown and post-lockdown periods in Spain, during the first COVID-19 confinement in 2020. This study analyzes data from 1940 participants, which was obtained both from a survey and from a tracking application installed on their smartphones. We propose manifold learning techniques such as clustering, to assess, both in a quantitative and in a qualitative way, the behavioral and social effects and implications of confinement in the Spanish population. We al…

PIECEWISE ANOMALY DETECTION USING MINIMAL LEARNING MACHINE FOR HYPERSPECTRAL IMAGES

2021

Abstract. Hyperspectral imaging, with its applications, offers promising tools for remote sensing and Earth observation. Recent development has increased the quality of the sensors. At the same time, the prices of the sensors are lowering. Anomaly detection is one of the popular remote sensing applications, which benefits from real-time solutions. A real-time solution has its limitations, for example, due to a large amount of hyperspectral data, platform’s (drones or a cube satellite) constraints on payload and processing capability. Other examples are the limitations of available energy and the complexity of the machine learning models. When anomalies are detected in real-time from the hyp…

PAN-AFRICAN MOBILE BELTS AS EVIDENCE FOR A TRANSITIONAL TECTONIC REGIME FROM INTRAPLATE OROGENY TO PLATE MARGIN OROGENY

1979

Pan-African belts of the African mainland and the Arabian-Nubian Shield exhibit evolutionary features which are either compatible with intracontinental ensialic development or with plate margin and Wilson cycle tectonics. Some of these belts are discussed and, considered together, they appear to reflect variations in crustal mobility during a transitional tectonic regime from intraplate to plate margin orogeny which lasted some 50. Ma from ca. 1000 Ma to ca. 500 Ma ago.

An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks

2020

Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a…

Weights Space Exploration Using Genetic Algorithms for Meta-classifier in Text Document Classification

2012

Development of an Automatic Pollen Classification System Using Shape, Texture and Aperture Features

2015

International audience; Automatic detection and classification of pollen species has value for use inside of palynologic allergen studies. Traditional labeling of different pollen species requires an expert biologist to classify particles by sight, and is therefore time-consuming and expensive. Here, an automatic process is developed which segments the particle contour and uses the extracted features for the classification process. We consider shape features, texture features and aperture features and analyze which are useful. The texture features analyzed include: Gabor Filters, Fast Fourier Transform, Local Binary Patterns, Histogram of Oriented Gradients, and Haralick features. We have s…

Sähköä ja alkemiaa: Tekoälydiskurssit Yleisradion verkkoartikkeleissa

2021

Tässä artikkelissa tarkastelemme sitä, millaisena ja miten tekoäly esitetään suomalaisessa julkisessa keskustelussa, ja ketkä tekoälystä suurelle yleisölle kertovat. Aineistona olemme käyttäneet Yleisradion verkkosivujen tekoälyä käsitteleviä artikkeleja. Tulosten perusteella tekoälystä pääsevät kertomaan useimmin talouden ja teollisuuden aloilla työskentelevät miehet. Aineistossa esiintyneet tekoälytulevaisuuskuvaukset pitäytyvät pitkälti nykyisen länsikeskeisen kapitalistisen maailmankuvan sisällä. Toisin sanoen, ne eivät haastaneet tai ylittäneet vallitsevaa status quoa, vaan näkivät tulevaisuuden pikemminkin lineaarisena kehityksenä nykytilasta. Aiemman tutkimuksen perusteella yleinen k…

On the impact of forgetting on learning machines

1995

People tend not to have perfect memories when it comes to learning, or to anything else for that matter. Most formal studies of learning, however, assume a perfect memory. Some approaches have restricted the number of items that could be retained. We introduce a complexity theoretic accounting of memory utilization by learning machines. In our new model, memory is measured in bits as a function of the size of the input. There is a hierarchy of learnability based on increasing memory allotment. The lower bound results are proved using an unusual combination of pumping and mutual recursion theorem arguments. For technical reasons, it was necessary to consider two types of memory : long and sh…

Movie Script Similarity Using Multilayer Network Portrait Divergence

2020

International audience; This paper addresses the question of movie similarity through multilayer graph similarity measures. Recent work has shown how to construct multilayer networks using movie scripts, and how they capture different aspects of the stories. Based on this modeling, we propose to rely on the multilayer structure and compute different similarities, so we may compare movies, not from their visual content, summary, or actors, but actually from their own storyboard. We propose to do so using “portrait divergence”, which has been recently introduced to compute graph distances from summarizing graph characteristics. We illustrate our approach on the series of six Star Wars movies.

Supervised learning of time-independent Hamiltonians for gate design

2018

We present a general framework to tackle the problem of finding time-independent dynamics generating target unitary evolutions. We show that this problem is equivalently stated as a set of conditions over the spectrum of the time-independent gate generator, thus transforming the task to an inverse eigenvalue problem. We illustrate our methodology by identifying suitable time-independent generators implementing Toffoli and Fredkin gates without the need for ancillae or effective evolutions. We show how the same conditions can be used to solve the problem numerically, via supervised learning techniques. In turn, this allows us to solve problems that are not amenable, in general, to direct ana…