125,086 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Clustering of waveforms based on FPCA direction
No full textLooking for curves similarity could be a complex issue characterized by
subjective choices related to continuous transformations of observed discrete data
(Chiodi, 1989). Waveforms correlation techniques have been introduced to charac-
terize the degree of seismic event similarity (Menke, 1999) and in facilitating more
accurate relative locations within similar event clusters by providing more precise
timing of seismic wave (P and S) arrivals (Phillips, 1997).
In this paper functional analysis (Ramsey, and Silverman, 2006) is considered to
highlight common characteristics of waveforms-data and to summarize these charac-
teristics by few components, by applying a variant of a classical clustering method to
rotated data (Sangalli et al., 2010) according to the direction of maximum variance
(i.e. based on PCA rotation of data)
Dispelling the Myths Behind First-author Citation Counts
No full textWe 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
Oxo-rhenium-catalyzed Biomimetic Cyclizations and Late-stage Electrochemical C–H Oxidation of Unactivated C(sp3)–H Bonds
No full textPart A: Oxo-rhenium-catalyzed Biomimetic Cyclization
Biomimetic cyclizations are remarkable tools because a significant increase in molecular complexity can be obtained in a single step. In the first part of my PhD, a new method to promote biomimetic cyclizations of terpenoid-like starting materials using an oxo-rhenium complex as a catalyst is described. This proof of concept, if further explored, will give access to useful building blocks that can be employed for the total synthesis of natural products.
Part B: Electrochemical C–H Oxidation
The site-specific oxidation of “strong”, non-acidic C(sp3)–H bonds is a rewarding, yet difficult topic in organic synthesis. In the second part of my PhD, N-ammonium ylides are described as tunable, electrochemically driven oxidants for site-specific, chemoselective C(sp3)–H oxidation. This ylide-based approach to C–H oxidation exhibits a unique selectivity relative to other classes of chemical oxidants and can be applied to real-world problems.Part A: Oxo-rhenium-catalyzed Biomimetic Cyclization
Biomimetic cyclizations are remarkable tools because a significant increase in molecular complexity can be obtained in a single step. In the first part of my PhD, a new method to promote biomimetic cyclizations of terpenoid-like starting materials using an oxo-rhenium complex as a catalyst is described. This proof of concept, if further explored, will give access to useful building blocks that can be employed for the total synthesis of natural products.
Part B: Electrochemical C–H Oxidation
The site-specific oxidation of “strong”, non-acidic C(sp3)–H bonds is a rewarding, yet difficult topic in organic synthesis. In the second part of my PhD, N-ammonium ylides are described as tunable, electrochemically driven oxidants for site-specific, chemoselective C(sp3)–H oxidation. This ylide-based approach to C–H oxidation exhibits a unique selectivity relative to other classes of chemical oxidants and can be applied to real-world problems
Clustering of Waveforms Based on FPCA Direction
No full textAbstract. Looking for curves similarity could be a complex issue characterized by
subjective choices related to continuous transformations of observed discrete data
(Chiodi, 1989). Waveforms correlation techniques have been introduced to charac-
terize the degree of seismic event similarity (Menke, 1999) and in facilitating more
accurate relative locations within similar event clusters by providing more precise
timing of seismic wave (P and S) arrivals (Phillips, 1997).
In this paper functional analysis (Ramsey, and Silverman, 2006) is considered to
highlight common characteristics of waveforms-data and to summarize these charac-
teristics by few components, by applying a variant of a classical clustering method to
rotated data (Sangalli et al., 2010) according to the direction of maximum variance
(i.e. based on PCA rotation of data).PublishedKarlsruhe (Germany)ope
Too True to Be Good. Il problema della somiglianza nell’arte contemporanea
No full textThe last forty years have witnessed an ever-growing production of three-dimensional realistic images in art. Artists such as Paul Thek, Bruce Nauman, Duane Hanson and, more recently, Maurizio Cattelan, Huang Yong Ping, Robert Gober, Charles Ray, John Isaacs, Ron Mueck, Tomoaki Suzuki, Sun Yuan and Peng Yu, have been using traditional (wax) or innovative materials (silicone, fiberglass, and polyester resins) and techniques, as well as taxidermized animals, to create sculptures and installations showing an extreme albeit ambiguous resemblance to their models. Such a trend has become a key feature of two-dimensional images as well, blurring the border between painting, photography and digital art. This new kind of “hyper-realism” seems to combine the tradition of mimetic sculpture, the sideshow fascination of wax figures, and the current attraction for photo-realistic manipulations, in a way that defies established critical criteria. This particular kind of deceptive images challenges the traditional ideas of «mimesis» and «representation», which are both based on the possibility of drawing a distinction between copies and originals; it moreover addresses the very status of the “image”, which can be called image only insofar it is distinguishable from its referent. Nevertheless – as both the continental and the analytical aesthetics have effectively underlined –, similarity and resemblance are far from being obvious and self-evident notions: they are on the contrary highly problematic concepts. This issue of «Piano B» wants to critically explore this constellation of problems, inviting scholars to investigate the different issues connected with the extensive use of mimetic strategies in the contemporary art practices
Kernel intensity for space-time point processes with application to seismological problems
No full textDealing with data coming from a space-time inhomogeneous process,
there is often the need of semi-parametric estimates of the conditional intensity
function; isotropic or anisotropic multivariate kernel estimates can be used, with windows sizes h. The properties of the intensities estimated with this choice of h
are not always good for specific fields of application; we could try to choose h in
order to have good predictive properties of the estimated intensity function. Since a
direct ML approach cannot be followed, we propose an estimation procedure, computationally intensive, based on the subsequent increments of likelihood obtained
adding an observation at time. The first results obtained are very encouraging. Some
application in statistical seismology is presented
Functional Principal Components direction to cluster earthquake
No full textLooking for curves similarity could be a complex issue characterized by subjective choices related to continuous
transformations of observed discrete data (Chiodi, 1989).
In this paper we combine the aim of finding clusters from a set of individual curves to the functional nature of data,
applying a variant of a k-means algorithm based on the principal component rotation of data. We apply a classical
clustering method to rotated data, according to the direction of maximum variance.
A k-means clustering algorithm based on PCA rotation of data is proposed, as an alternative to methods that
require previous interpolation of data based on splines or linear fitting (García-Escudero and Gordaliza (2005),
Tarpey (2007), Sangalli et al. (2008)).PublishedVienna (Austria)ope
Functional Principal Components direction to cluster earthquake
No full textLooking for curves similarity could be a complex issue characterized by subjective choices related to continuous
transformations of observed discrete data (Chiodi, 1989).
In this paper we combine the aim of finding clusters from a set of individual curves to the functional nature of data,
applying a variant of a k-means algorithm based on the principal component rotation of data. We apply a classical
clustering method to rotated data, according to the direction of maximum variance.
A k-means clustering algorithm based on PCA rotation of data is proposed, as an alternative to methods that
require previous interpolation of data based on splines or linear fitting (García-Escudero and Gordaliza (2005),
Tarpey (2007), Sangalli et al. (2008)).PublishedVienna (Austria)ope
A penalized approach to covariate selection through quantile regression coefficient models
No full textThe coefficients of a quantile regression model are one-to-one functions of the order of the quantile. In standard quantile regression (QR), different quantiles are estimated one at a time. Another possibility is to model the coefficient functions parametrically, an approach that is referred to as quantile regression coefficients modeling (QRCM). Compared with standard QR, the QRCM approach facilitates estimation, inference and interpretation of the results, and generates more efficient estimators. We designed a penalized method that can address the selection of covariates in this particular modelling framework. Unlike standard penalized quantile regression estimators, in which model selection is quantile-specific, our approach permits using information on all quantiles simultaneously. We describe the estimator, provide simulation results and analyse the data that motivated the present article. The proposed approach is implemented in the qrcmNP package in R
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