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Analysis of institutional authors

Tejedor Noguerales, JavierCorresponding Author
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Review

Machine Learning Methods for Pipeline Surveillance Systems based on Distributed Acoustic Sensing: A Review.

Publicated to:Applied Sciences-Basel. 7 (8): - 2017-08-16 7(8), DOI: 10.3390/app7080841

Authors: Tejedor, Javier; Macias-Guarasa, Javier; Martins, Hugo F.; Pastor-Graells, Juan; Corredera, Pedro; Martin-Lopez, Sonia;

Affiliations

CSIC, Inst Opt, E-28006 Madrid, Spain      CSIC - Instituto de Optica (Daza de Valdes)    Consejo Superior de Investigaciones Cientificas (CSIC) - Author
FOCUS SL, Madrid 28004, Spain - Author
Univ Alcala De Henares, Dept Elect, Alcala De Henares 28801, Spain.      Universidad de Alcala - Author
Univ Alcala De Henares, Dept Elect, Alcala De Henares 28801, Spain      Universidad de Alcala       - Author
Univ CEU San Pablo, Dept Informat Technol, Madrid 28003, Spain      San Pablo CEU University - Author
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Abstract

© 2017 by the authors. There is an increasing interest in researchers and companies on the combination of Distributed Acoustic Sensing (DAS) and a Pattern Recognition System (PRS) to detect and classify potentially dangerous events that occur in areas above fiber optic cables deployed along active pipelines, aiming to construct pipeline surveillance systems. This paper presents a review of the literature in what respect to machine learning techniques applied to pipeline surveillance systems based on DAS+PRS (although its scope can also be extended to any other environment in which DAS+PRS strategies are to be used). To do so, we describe the fundamentals of the machine learning approaches when applied to DAS systems, and also do a detailed literature review of the main contributions on this topic. Additionally, this paper addresses the most common issues related to real field deployment and evaluation of DAS+PRS for pipeline threat monitoring, and intends to provide useful insights and recommendations in what respect to the design of such systems. The literature review concludes that a real field deployment of a PRS based on DAS technology is still a challenging area of research, far from being fully solved.

Keywords
Distributed acoustic sensingF-otdrFiber optic systemsPattern recognition systemsPipeline integrity threat monitoringReview

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Applied Sciences-Basel due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2017, it was in position , thus managing to position itself as a Q2 (Segundo Cuartil), in the category Computer Science Applications. Notably, the journal is positioned en el Cuartil Q3 for the agency WoS (JCR) in the category Physics, Applied.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 1.84. This indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: ESI Nov 14, 2024)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Weighted Average of Normalized Impact by the Scopus agency: 6.14 (source consulted: FECYT Feb 2024)
  • Field Citation Ratio (FCR) from Dimensions: 24.64 (source consulted: Dimensions May 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-05-17, the following number of citations:

  • WoS: 71
  • Scopus: 121
  • Europe PMC: 2
  • OpenCitations: 89
Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-17:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 135.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 135 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 12.95.
  • The number of mentions on the social network X (formerly Twitter): 6 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (TEJEDOR NOGUERALES, JAVIER) .

the author responsible for correspondence tasks has been TEJEDOR NOGUERALES, JAVIER.