Search results for " mining"
showing 10 items of 1548 documents
What explains the resilience of SMEs? Ambidexterity capability and strategic consistency
2020
Abstract The ability to be resilient, to recover and bounce back when confronted with a threatening and stressful external event, such as the most recent global economic crisis, is an important issue for strategic management research, particularly for small and medium-sized enterprises (SMEs). Research studies on firm level antecedents of resilience offer contradictory propositions, some of which stress the need for experimentation, while others suggest focusing on reliability. To disentangle this controversy and face this gap, our study proposes that for SMEs to achieve resilience, it is necessary that these companies are able to efficiently respond to the changing environments through amb…
Literature, social media and questionnaire surveys identify relevant conservation areas for Carcharhinus species in the Mediterranean Sea
2023
Sharks support ecosystems’ health, but their populations are facing severe declines worldwide. Knowledge gaps on shark distribution and the negative human perception of them still represent a barrier to the implementation of effective conservation measures. Here we carried out a regional-scale analysis in the Mediterranean Sea using data on requiem shark catches and sightings available in the scientific literature and on social media platforms to: 1) depict the distribution of Carcharhinus species across the basin, 2) identify potentially relevant areas for their conservation, and 3) evaluate people’s attitude toward shark protection. In addition, we administered 112 questionnaires in one o…
Remote Sensing Image Classification with Large Scale Gaussian Processes
2017
Current remote sensing image classification problems have to deal with an unprecedented amount of heterogeneous and complex data sources. Upcoming missions will soon provide large data streams that will make land cover/use classification difficult. Machine learning classifiers can help at this, and many methods are currently available. A popular kernel classifier is the Gaussian process classifier (GPC), since it approaches the classification problem with a solid probabilistic treatment, thus yielding confidence intervals for the predictions as well as very competitive results to state-of-the-art neural networks and support vector machines. However, its computational cost is prohibitive for…
Core of communities in bipartite networks
2017
We use the information present in a bipartite network to detect cores of communities of each set of the bipartite system. Cores of communities are found by investigating statistically validated projected networks obtained using information present in the bipartite network. Cores of communities are highly informative and robust with respect to the presence of errors or missing entries in the bipartite network. We assess the statistical robustness of cores by investigating an artificial benchmark network, the co-authorship network, and the actor-movie network. The accuracy and precision of the partition obtained with respect to the reference partition are measured in terms of the adjusted Ran…
Cross-Sensor Adversarial Domain Adaptation of Landsat-8 and Proba-V images for Cloud Detection
2021
The number of Earth observation satellites carrying optical sensors with similar characteristics is constantly growing. Despite their similarities and the potential synergies among them, derived satellite products are often developed for each sensor independently. Differences in retrieved radiances lead to significant drops in accuracy, which hampers knowledge and information sharing across sensors. This is particularly harmful for machine learning algorithms, since gathering new ground truth data to train models for each sensor is costly and requires experienced manpower. In this work, we propose a domain adaptation transformation to reduce the statistical differences between images of two…
A probabilistic estimation and prediction technique for dynamic continuous social science models: The evolution of the attitude of the Basque Country…
2015
In this paper, a computational technique to deal with uncertainty in dynamic continuous models in Social Sciences is presented.Considering data from surveys,the method consists of determining the probability distribution of the survey output and this allows to sample data and fit the model to the sampled data using a goodness-of-fit criterion based the χ2-test. Taking the fitted parameters that were not rejected by the χ2-test, substituting them into the model and computing their outputs, 95% confidence intervals in each time instant capturing the uncertainty of the survey data (probabilistic estimation) is built. Using the same set of obtained model parameters, a prediction over …
Helminth Microbiota Profiling Using Bacterial 16S rRNA Gene Amplicon Sequencing: From Sampling to Sequence Data Mining
2021
Symbiont microbial communities play important roles in animal biology and are thus considered integral components of metazoan organisms, including parasitic worms (helminths). Nevertheless, the study of helminth microbiomes has thus far been largely overlooked, and symbiotic relationships between helminths and their microbiomes have been only investigated in selected parasitic worms. Over the past decade, advances in next-generation sequencing technologies, coupled with their increased affordability, have spurred investigations of helminth-associated microbial communities aiming at enhancing current understanding of their fundamental biology and physiology, as well as of host-microbe intera…
Constrained Role Mining
2013
Role Based Access Control (RBAC) is a very popular access control model, for long time investigated and widely deployed in the security architecture of different enterprises. To implement RBAC, roles have to be firstly identified within the considered organization. Usually the process of (automatically) defining the roles in a bottom up way, starting from the permissions assigned to each user, is called {\it role mining}. In literature, the role mining problem has been formally analyzed and several techniques have been proposed in order to obtain a set of valid roles. Recently, the problem of defining different kind of constraints on the number and the size of the roles included in the resu…
Transfer Learning with Convolutional Networks for Atmospheric Parameter Retrieval
2018
The Infrared Atmospheric Sounding Interferometer (IASI) on board the MetOp satellite series provides important measurements for Numerical Weather Prediction (NWP). Retrieving accurate atmospheric parameters from the raw data provided by IASI is a large challenge, but necessary in order to use the data in NWP models. Statistical models performance is compromised because of the extremely high spectral dimensionality and the high number of variables to be predicted simultaneously across the atmospheric column. All this poses a challenge for selecting and studying optimal models and processing schemes. Earlier work has shown non-linear models such as kernel methods and neural networks perform w…
Multi-label Methods for Prediction with Sequential Data
2017
The number of methods available for classification of multi-label data has increased rapidly over recent years, yet relatively few links have been made with the related task of classification of sequential data. If labels indices are considered as time indices, the problems can often be seen as equivalent. In this paper we detect and elaborate on connections between multi-label methods and Markovian models, and study the suitability of multi-label methods for prediction in sequential data. From this study we draw upon the most suitable techniques from the area and develop two novel competitive approaches which can be applied to either kind of data. We carry out an empirical evaluation inves…