1,720,962 research outputs found
Experimental validation of machine-learning based spectral-spatial power evolution shaping using Raman amplifiers
We experimentally validate a real-time machine learning framework, capable of
controlling the pump power values of Raman amplifiers to shape the signal power
evolution in two-dimensions (2D): frequency and fiber distance. In our setup,
power values of four first-order counter-propagating pumps are optimized to
achieve the desired 2D power profile. The pump power optimization framework
includes a convolutional neural network (CNN) followed by differential
evolution (DE) technique, applied online to the amplifier setup to
automatically achieve the target 2D power profiles. The results on achievable
2D profiles show that the framework is able to guarantee very low maximum
absolute error (MAE) (<0.5 dB) between the obtained and the target 2D profiles.
Moreover, the framework is tested in a multi-objective design scenario where
the goal is to achieve the 2D profiles with flat gain levels at the end of the
span, jointly with minimum spectral excursion over the entire fiber length. In
this case, the experimental results assert that for 2D profiles with the target
flat gain levels, the DE obtains less than 1 dB maximum gain deviation, when
the setup is not physically limited in the pump power values. The simulation
results also prove that with enough pump power available, better gain deviation
(less than 0.6 dB) for higher target gain levels is achievable
Spectral and spatial power evolution design with machine learning-enabled Raman amplification
We present a machine learning (ML) framework for designing desired signal
power profiles over the spectral and spatial domains in the fiber span. The
proposed framework adjusts the Raman pump power values to obtain the desired
two-dimensional (2D) profiles using a convolutional neural network (CNN)
followed by the differential evolution (DE) technique. The CNN learns the
mapping between the 2D profiles and their corresponding pump power values using
a data-set generated by exciting the amplification setup. Nonetheless, its
performance is not accurate for designing 2D profiles of practical interest,
such as a 2D flat or a 2D symmetric (with respect to the middle point in
distance). To adjust the pump power values more accurately, the DE fine-tunes
the power values initialized by the CNN to design the proposed 2D profile with
a lower cost value. In the fine-tuning process, the DE employs the direct
amplification model which consists of 8 bidirectional propagating pumps,
including 2 second-order and 6 first order, in an 80 km fiber span. We evaluate
the framework to design broadband 2D flat and symmetric power profiles, as two
goals for wavelength division multiplexing (WDM) system performing over the
whole C-band. Results indicate the framework's ability to achieve maximum power
excursion of 2.81 dB for a 2D flat, and maximum asymmetry of 14% for a 2D
symmetric profile
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
Author-wise bibliometric analysis based on entropy.</p
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