Rosa Rodriguez-Sánchez

Information theoretic measure for visual target distinctness

It is of great benefit to have advance knowledge of human visual target acquisition performance for targets or other relevant objects. However, search performance inherently shows a large variance and depends strongly on prior knowledge of the perceived scene. A typical search experiment therefore requires a large number of observers to obtain statistically reliable data. Moreover, measuring target acquisition performance in field situations is usually impractical and often very costly or even dangerous. The paper presents a method for characterizing information of a target relative to its background. The resultant computational measures are then applied to quantify the visual distinctness of targets in complex natural backgrounds from digital imagery. A generalization of the Kullback-Leibler joint information gain of various random variables is shown to correlate strongly with visual target distinctness as estimated by human observers. Bootstrap methods for assessing statistical accuracy were used to produce this inference.

Mapping citation patterns of book chapters in the Book Citation Index

In this paper we provide the reader with a visual representation of relationships among the impact of book chapters indexed in the Book Citation Index using information gain values and published by different academic publishers in specific disciplines. The impact of book chapters can be characterized statistically by citations histograms. For instance, we can compute the probability of occurrence of book chapters with a number of citations in different intervals for each academic publisher. We predict the similarity between two citation histograms based on the amount of relative information between such characterizations. We observe that the citation patterns of book chapters follow a Lotkaian distribution. This paper describes the structure of the Book Citation Index using ‘heliocentric clockwise maps’ which allow the reader not only to determine the grade of similarity of a given academic publisher indexed in the Book Citation Index with a specific discipline according to their citation distribution, but also to easily observe the general structure of a discipline, identifying the publishers with higher impact and output.

Mapping academic institutions according to their journal publication profile: Spanish universities as a case study

We introduce a novel methodology for mapping academic institutions based on their journal publication profiles. We believe that journals in which researchers from academic institutions publish their works can be considered as useful identifiers for representing the relationships between these institutions and establishing comparisons. However, when academic journals are used for research output representation, distinctions must be introduced between them, based on their value as institution descriptors. This leads us to the use of journal weights attached to the institution identifiers. Since a journal in which researchers from a large proportion of institutions published their papers may be a bad indicator of similarity between two academic institutions, it seems reasonable to weight it in accordance with how frequently researchers from different institutions published their papers in this journal. Cluster analysis can then be applied to group the academic institutions, and dendrograms can be provided to illustrate groups of institutions following agglomerative hierarchical clustering. In order to test this methodology, we use a sample of Spanish universities as a case study. We first map the study sample according to an institutions overall research output, then we use it for two scientific fields (Information and Communication Technologies, as well as Medicine and Pharmacology) as a means to demonstrate how our methodology can be applied, not only for analyzing institutions as a whole, but also in different disciplinary contexts.

Performance of the Kullback-Leibler information gain for predicting image fidelity

This paper presents a new method for characterizing information of a compressed image relative to the original one. We show how the Kullback-Leibler information gain is based on three basic postulates which are natural for image processing and thus desirable. As an example of the proposed measure, we analyze the effects of lossy compression on the identification of breast cancer microcalcifications. We also show the comparative results of the Kullback-Leibler information gain and various quantitative measures for predicting image fidelity in the sense of diagnostic usefulness.

The author---editor game

This paper provides a formal study on manuscript quality control in peer review. Within this analysis, a biased editor is defined operationally as an editor that exerts a higher (lower) level of quality control. Here we show that if the editor is more biased than the manuscript’s author then the author undertakes the type of revision that the editor prefers instead of following his or her own opinion. Moreover, authors with a strong belief about the required level of quality control will be very motivated under editors who agree with them. By contrast, when authors do not undertake the revision type that the editor prefers, they will be very demotivated under editors that exert a different level of quality control and more so as the associate editor is more biased. The effects of editors’ bias on authors’ satisfaction and motivation cause sorting in the authors who submit manuscripts to scholarly journals, and therefore, match authors and journals with similar quality standards. It will decrease the demotivating effect that editors’ bias had on some authors, so that bias becomes more effective at the peer review stage. Moreover, some journals will be forced to lower the quality standards in order to be able to compete with journals of more biased editors. This paper also shows that, under fairly weak conditions, it is optimal for the Editor-in-Chief to assign manuscripts to an editor that exerts a quality control higher than the journal’s standard, against the competing journal whose editor holds the journal’s standard.

On first quartile journals which are not of highest impact

Here we study the relationship between journal quartile rankings of ISI impact factor (at the 2010) and journal classification in four impact classes, i.e., highest impact, medium highest impact, medium lowest impact, and lowest impact journals in subject category computer science artificial intelligence. To this aim, we use fuzzy maximum likelihood estimation clustering in order to identify groups of journals sharing similar characteristics in a multivariate indicator space. The seven variables used in this analysis are: (1) Scimago Journal Ranking (SJR); (2) H-Index (H); (3) ISI impact factor (IF); (4) 5-Year Impact Factor (5IF); (5) Immediacy Index (II); (6) Eigenfactor Score (ES); and (7) Article Influence Score (AIS). The fuzzy clustering allows impact classes to overlap, thereby accommodating for uncertainty related to the confusion about the impact class attribution for a journal and vagueness in impact classes definition. This paper demonstrates the complex relationship between quartiles of ISI impact factor and journal impact classes in the multivariate indicator space. And that several indicators should be used for a distinct analysis of structural changes at the score distribution of journals in a subject category. Here we propose it can be performed in a multivariate indicator space using a fuzzy classifier.

The principal‐agent problem in peer review

In economics, the principal‐agent problem is the difficulty in motivating one party (the agent), to act in the best interests of another (the principal) rather than in his own interests. We consider the example of a journal editor (the principal) wondering whether his or her reviewer (the agent) is recommending rejection of a manuscript because it does not have enough quality to be published or because the reviewer dislikes effort and he/she must work to acquire in‐depth knowledge of the content of the manuscript. The reviewers effort provides him or her with superior information about a manuscripts quality. If this information is not correctly communicated, the reviewer has more information when compared with the journal editor. This inherently leads to an encouragement of moral hazard, where the editor will not know whether the reviewer has done his or her job in accordance to the editors interest. Prescriptions need to be given as to how the journal editor should control the reviewers to curb self‐interest. Besides the associate editors monitoring the peer‐review process, incentives can be employed to limit moral hazard on the part of the reviewer. Drawing on agency theory, we examine the incentives motivating the reviewers to expend effort to generate information about the quality of submissions. This model predicts that for reviewers early in their careers, promotion‐based incentives may mean there is no need for within‐job incentives, but also that within‐job rewards for a referees performance should depend on individual differences in ability and promotion opportunities.

Ranking of the subject areas of Scopus

Here, we show a longitudinal analysis of the ranking of the subject areas of Elseviers Scopus. To this aim, we present three summary measures based on the journal ranking scores for academic journals in each subject area. This longitudinal study allows us to analyze developmental trends over times in different subject areas with distinct citation and publication patterns. We evaluate the relative performance of each subject area by using the overall prestige for the most important journals with ranking score above a given threshold (e.g., in the first quartile) as well as the overall prestige gap for the less important journals with ranking score below a given threshold (e.g., below the top 10 journals). Thus, we propose that it should be possible to study different subject areas by means of appropriate summary measures of the journal ranking scores, which provide additional information beyond analyzing the inequality of the whole ranking-score distribution for academic journals in each subject area. It allows us to investigate whether subject areas with high levels of overall prestige for the first quartile journals also tended to achieve low levels of overall prestige gap for the journals below the top 10.

The role of integral features for perceiving image discriminability

Abstract The computational model we propose deals with the measurement of image discriminability in such a way that the comparison of a pair of images is performed by matching the corresponding integral features registered within the same fixation point which a spatial sensitivity function directs about the images.

Ranking of research output of universities on the basis of the multidimensional prestige of influential fields: Spanish universities as a case of study

A university may be considered as having dimension-specific prestige in a scientific field (e.g., physics) when a particular bibliometric research performance indicator exceeds a threshold value. But a university has multidimensional prestige in a field of study only if it is influential with respect to a number of dimensions. The multidimensional prestige of influential fields at a given university takes into account that several prestige indicators should be used for a distinct analysis of the influence of a university in a particular field of study. After having identified the multidimensionally influential fields of study at a university their prestige scores can be aggregated to produce a summary measure of the multidimensional prestige of influential fields at this university, which satisfies numerous properties. Here we use this summary measure of multidimensional prestige to assess the comparative performance of Spanish Universities during the period 2006–2010.