Search results for "NETWORK"

Betweenness Centrality for Networks with Non-Overlapping Community Structure

2018

Evaluating the centrality of nodes in complex networks is one of the major research topics being explored due to its wide range of applications. Among the various measures that have been developed over the years, Betweenness centrality is one of the most popular. Indeed, it has proved to be efficient in many real-world situations. In this paper, we propose an extension of the Betweenness centrality designed for networks with nonoverlapping community structure. It is a linear combination of the so-called “local” and “global” Betweenness measures. The Local measure takes into account the influence of a node at the community level while the global measure depends only on the interactions betwe…

2020

Hierarchy and centrality are two popular notions used to characterize the importance of entities in complex systems. Indeed, many complex systems exhibit a natural hierarchical structure, and centrality is a fundamental characteristic allowing to identify key constituents. Several measures based on various aspects of network topology have been proposed in order to quantify these concepts. While numerous studies have investigated whether centrality measures convey redundant information, how centrality and hierarchy measures are related is still an open issue. In this paper, we investigate the association between centrality and hierarchy using several correlation and similarity evaluation mea…

A comparison between nine laboratories performing triangle tests

2012

WOS: 000299451400001; International audience; Fifteen groups of participants in nine laboratories performed triangle tests with two pairs of soft drinks. Groups differed in practice level with triangle tests: eight groups of 60 consumers who were not used to triangle test, three groups of qualified assessors who have already performed a few triangle tests, and four groups of trained assessors with a more extensive practice of triangle tests; qualified and trained groups included 9 or 18 assessors. The soft drinks were made from syrups at two levels of dilution in order to achieve about 55% of correct responses to test for difference and about 40% of correct responses to test for similarity.…

A Review of the State-of-the-Art of Assistive Technology for People with ASD in the Workplace and in Everyday Life

2019

Part 8: Digital Divide and Social Inclusion; International audience; Autism, also known as autism spectrum disorder (ASD), is an incurable brain-based disorder that refers to a wide range of complex neurodevelopment disorders characterised by marked difficulties in communication and social skills, repetitive behaviour, highly focused interests and sensory sensitivity. Autism can present challenges for affected people at the work environment and in everyday life. The barrier for individuals with ASD increases further with changing environmental situations. Individuals with ASD have limited abilities to isolate their Five senses and often experience over- or under-sensitivity to sounds, touch…

The social networks of young people with intellectual disabilities during the On-Campus supported adult education programme

2016

<p>This article describes the social networks of four young people with intellectual disabilities in supported adult education, focusing on their inclusion in school and leisure environments. A multiple case study approach with content analysis was used. Data were collected through interviews with young people and their family members, relationship maps, observation journals and notes from Personal Futures Planning meetings. Relationships with family members, other relatives and neighbours were close. One participant had a friend of her own age with no disabilities. The other three had varying, superficial peer relationships and friends of the family. All the participants had heteroge…

Improving Speaker-Independent Lipreading with Domain-Adversarial Training

2017

We present a Lipreading system, i.e. a speech recognition system using only visual features, which uses domain-adversarial training for speaker independence. Domain-adversarial training is integrated into the optimization of a lipreader based on a stack of feedforward and LSTM (Long Short-Term Memory) recurrent neural networks, yielding an end-to-end trainable system which only requires a very small number of frames of untranscribed target data to substantially improve the recognition accuracy on the target speaker. On pairs of different source and target speakers, we achieve a relative accuracy improvement of around 40% with only 15 to 20 seconds of untranscribed target speech data. On mul…

Deep Neural Network Frontend for Continuous EMG-Based Speech Recognition

2016

Financial contagion through space-time point processes

2020

AbstractWe propose to study the dynamics of financial contagion by means of a class of point process models employed in the modeling of seismic contagion. The proposal extends network models, recently introduced to model financial contagion, in a space-time point process perspective. The extension helps to improve the assessment of credit risk of an institution, taking into account contagion spillover effects.

Investigating the moderating effect of information sources on cruise tourist behaviour in a port of call

2015

The aim of the study is to examine how destination knowledge acquired by cruisers through different information sources (online versus others) can moderate destination image formation and the relationship of image–satisfaction–behavioural intentions in a port of call. A multiple group analysis with partial least square method was carried out using data collected from a major tourism destination in Spain: Valencia. The findings revealed knowledge acquired through different information sources is a moderator of the image–satisfaction and satisfaction–behavioural intention relationships. The destination image formation is also significantly different from one group to the other. The findings o…

Cell state prediction through distributed estimation of transmit power

2019

Determining the state of each cell, for instance, cell outages, in a densely deployed cellular network is a difficult problem. Several prior studies have used minimization of drive test (MDT) reports to detect cell outages. In this paper, we propose a two step process. First, using the MDT reports, we estimate the serving base station’s transmit power for each user. Second, we learn summary statistics of estimated transmit power for various networks states and use these to classify the network state on test data. Our approach is able to achieve an accuracy of 96% on an NS-3 simulation dataset. Decision tree, random forest and SVM classifiers were able to achieve a classification accuracy of…