Dynamique des lasers à fibre dopée à I’erbium

The dynamics of the erbium doped fiber laser is analysed both experimentally and theoretically. This laser operates spontaneously in self-pulsing, in sinusoidal or in CW regime. Experiments have allowed to determine the control parameters : the cavity losses, the pumping rate and the ion pairs concentration. An antiphase dynamics is observed when the laser operates simultaneously at 1.55 µn and 1.536 µm. The self-pulsing behavior is attributed to a fast energy transfer which occurs between two neighboring ions (pair induced quenching). A simple model considering the active medium as a mixture of isolated ions and ions pairs is developped and leads to a good qualitative agreement with the experimental results.     

Digital sound broadcasting: Satellites or Terrestrial Networks?

When European laboratories decided to develop a digital sound broadcasting system (DSB), they specified three main conditions to fulfil:

• quality improvement up to the level of ‘CD’ sound, even in difficult reception conditions (mobile vehicles, etc)
• additional significant digital data transmissions in order to transform sound broadcasting into a really new service
• the possibility of a common system for satellite and terrestrial transmissions.

It is on these bases that the European project ‘Eureka 147’ defined the system called DAB (digital audio broadcasting). In 1992, the ITU Conference WARC 92 allocated 40 MHz to DSB in the L-band in the configuration of complementary terrestrial and satellite networks; nevertheless, the present state of technical possibilities makes such mixed networks almost unfeasible and the lack of available spectrum in VHF bands led a significant number of countries to envisage L-band for T-DAB. The situation could turn to a competition between terrestrial and satellite networks, especially because the bandwidth in L-band is not that large! France belongs to the countries facing this problem. L-band alone is intended to be used by T-DAB, and broadcasters taking part in the work of ‘Club DAB’ estimated that 20 MHz would be a minimum to ensure the success of T-DAB introduction. It is half of the DSB band. Splitting this band into two parts has already been decided by CEPT, but in the proportion of 1/3 for T-DAB. This organization intends to arrange a European planning meeting for T-DAB in July 1995, and, shortly after, several countries are ready to start the implementation of the terrestrial networks. At the same time, international broadcasters wonder whether satellite transmission could present an alternative to HF.     

Impact of white-matter mask selection on DTI histogram-based metrics as potential biomarkers in cerebral small vessel disease

Magnetic Resonance Materials in Physics, Biology and Medicine - Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small...     

Evolutionary design of neural network architectures: a review of three decades of research

We present a comprehensive review of the evolutionary design of neural network architectures. This work is motivated by the fact that the success of an Artificial Neural Network (ANN) highly depends on its architecture and among many approaches Evolutionary Computation, which is a set of global-search methods inspired by biological evolution has been proved to be an efficient approach for optimizing neural network structures. Initial attempts for automating architecture design by applying evolutionary approaches start in the late 1980s and have attracted significant interest until today. In this context, we examined the historical progress and analyzed all relevant scientific papers with a special emphasis on how evolutionary computation techniques were adopted and various encoding strategies proposed. We summarized key aspects of methodology, discussed common challenges, and investigated the works in chronological order by dividing the entire timeframe into three periods. The first period covers early works focusing on the optimization of simple ANN architectures with a variety of solutions proposed on chromosome representation. In the second period, the rise of more powerful methods and hybrid approaches were surveyed. In parallel with the recent advances, the last period covers the Deep Learning Era, in which research direction is shifted towards configuring advanced models of deep neural networks. Finally, we propose open problems for future research in the field of neural architecture search and provide insights for fully automated machine learning. Our aim is to provide a complete reference of works in this subject and guide researchers towards promising directions.

     

Hierarchical classification of data streams: a systematic literature review

The classification task usually works with flat and batch learners, assuming problems as stationary and without relations between class labels. Nevertheless, several real-world problems do not assume these premises, i.e., data have labels organized hierarchically and are made available in streaming fashion, meaning that their behavior can drift over time. Existing studies on hierarchical classification do not consider data streams as input of their process, and thus, data is assumed as stationary and handled through batch learners. The same can be said about works on streaming data, as the hierarchical classification is overlooked. Studies concerning each area individually are promising, yet, do not tackle their intersection. This study analyzes the main characteristics of the state-of-the-art works on hierarchical classification for streaming data concerning five aspects: (i) problems tackled, (ii) datasets, (iii) algorithms, (iv) evaluation metrics, and (v) research gaps in the area. We performed a systematic literature review of primary studies and retrieved 3,722 papers, of which 42 were identified as relevant and used to answer the aforementioned research questions. We found that the problems handled by hierarchical classification of data streams include mainly classification of images, human activities, texts, and audio; the datasets are mostly created or synthetic data; the algorithms and evaluation metrics are well-known techniques or based on those; and research gaps are related to dynamic context, data complexity, and computational resources constraints. We also provide implications for future research and experiments to consider common characteristics shared amongst hierarchical classification and data stream classification.

     

Psychosocial aspects of children and families treated with hemodialysis

Introduction: The aim of this study was to analyze the selected psychosocial aspects of chronic kidney disease in children treated with hemodialysis (HD). Methods: The study included 25 children treated with HD aged 2 to 18 years and their parents. Data concerning the illness and socio‐demographic parameters was collected. We used the Paediatric Quality of Life Inventory (PedsQL) for patients and for their parents the PedsQL‐proxy version, General Health Questionnaire (GHQ‐12), Berlin Social Support Scales (BSSS), and the Caregivers Burden Scale (CBS) to evaluate health‐related quality of life (QoL) of HD children and their primary caregivers. Findings: In the PedsQL test, the QoL of HD children was lower than in healthy children. Children treated with HD assessed their QoL on the PedsQL questionnaire higher than the primary caregivers, on all subscales as well as an overall health‐related QoL. Scoring below 2 on the GHQ‐12 test was reported in 56% of mothers, which may indicate that psychological symptoms have intensified. There was no correlation between BSSS, CBS, and GHQ‐12. Discussion: The assessment of QoL in pediatric patients would allow for the earliest possible identification of their nonsomatic problems and irregularities. This could, consequently, contribute to improving QoL in both children with chronic kidney disease and their families.