1,721,037 research outputs found
Malagasy Dialects and the Peopling of Madagascar
No full textServa M, Petroni F, Volchenkov D, Wichmann S. Malagasy Dialects and the Peopling of Madagascar. Interface. Journal of the Royal Society. 2012;9(66):54-67
Analysis of urban complex networks
Full text linkVolchenkov D. Analysis of urban complex networks. In: Condensed Matter Physics. Condensed Matter Physics. Vol 11. Institute for Condensed Matter Physics; 2008: 331-340.We analyze the dual graph representation of urban textures by the methods of complex network theory and spectral graph theory. We present the empirical diagrams of distributions of the nearest and far-away neighbors in the several European compact urban patterns and the spectra of normalized Laplace operator defined on their dual graphs
Geometric representations of language taxonomies
Full text linkBlanchard P, Petroni F, Serva M, Volchenkov D. Geometric representations of language taxonomies. Computer Speech & Language. 2011;25(3):679-699.A Markov chain analysis of a network generated by the matrix of lexical distances allows for representing complex relationships between different languages in a language family geometrically, in terms of distances and angles. The fully automated method for construction of language taxonomy is tested on a sample of fifty languages of the Indo-European language group and applied to a sample of fifty languages of the Austronesian language group. The Anatolian and Kurgan hypotheses of the Indo-European origin and the 'express train' model of the Polynesian origin are thoroughly discussed. (C) 2010 Elsevier Ltd. All rights reserved
Stochastic and Discrete Time Models of Long-Range Turbulent Transport in the Scrape-Off Layer
No full textVolchenkov D, Lima R. Stochastic and Discrete Time Models of Long-Range Turbulent Transport in the Scrape-Off Layer. International Journal of Modern Physics B. 2005;19(28):4195-4218
Malagasy dialects and the peopling of Madagascar
No full textThe origin of Malagasy DNA is half African and half Indonesian, nevertheless the Malagasy language, spoken by the entire population, belongs to the Austronesian family. The language most closely related to Malagasy is Maanyan (Greater Barito East group of the Austronesian family), but related languages are also in Sulawesi, Malaysia and Sumatra. For this reason, and because Maanyan is spoken by a population which lives along the Barito river in Kalimantan and which does not possess the necessary skill for long maritime navigation, the ethnic composition of the Indonesian colonizers is still unclear. There is a general consensus that Indonesian sailors reached Madagascar by a maritime trek, but the time, the path and the landing area of the first colonization are all disputed. In this research, we try to answer these problems together with other ones, such as the historical configuration of Malagasy dialects, by types of analysis related to lexicostatistics and glottochronology that draw upon the automated method recently proposed by the authors. The data were collected by the first author at the beginning of 2010 with the invaluable help of Joselina Soafara Nere and consist of Swadesh lists of 200 items for 23 dialects covering all areas of the island
From Indonesia to Madagascar: in search of the origins of the Malagasy language
No full textMadagascar exhibits a strong linguistic uniformity since all dialects are regional variants of the same language, which belongs
to the Greater Barito East group of the Austronesian family [Houtman, 1603]. This was firmly established a long time ago in
[Tuuk, 1864], while, more recently, [Dahl, 1951] pointed out a particularly close relationship between Malagasy and Maanyan
of south-eastern Kalimantan [Dyen, 1953]. Nevertheless, Malagasy also bears similarities to languages in Sulawesi, Malaysia,
Sumatra and Philippines, including loanwords from Malay, Javanese, and one (or more) language(s) of south Sulawesi
[Adelaar, 2009] and Philippines. On the contrary, the east-African contribution to the vocabulary seems to be limited to few
faunal names [Blench and Walsh, 2009].
Because of these linguistic relationships, it is widely accepted that the island was settled by Indonesian sailors after a
maritime trek but dates and place of landing are still debated and it is also not clear whether there were multiple settlements
or just a single one. The linguistic composition of the Austronesian settlers is also debated as well its consequences on the
vocabulary of Malagasy dialects.
In this paper we review our research [Serva et al, 2012, Serva, 2012], which tries to shed new light on these problems.
The key point is the application of a new quantitative methodology [Serva and Petroni, 2008, Petroni and Serva, 2008,
Bakker et al, 2009] which is able to find out the kinship relations among languages (or dialects). New techniques are
also introduced in order to extract the maximum information from these relations concerning time and space patterns
[Blanchard et al, 2010a, Wichmann et al, 2010a]. We consider 23 Malagasy dialects plus Malay and Maanyan. The data
concerning Madagascar were collected by one of the authors (M.S.) at the beginning of 2010 and consist of Swadesh lists of
200 items for each of the 23 dialects covering all areas of the island
Levenstein’s distance for measuring lexical evolution rates
No full textThe relationships between languages molded by extremely complex so-
cial, cultural and political factors are assessed by an automated method, in which
the distance between languages is estimated by the average normalized Levenshtein
distance between words from the list of 200 meanings maximally resistant to change.
A sequential process of language classification described by random walks on the
matrix of lexical distances allows to represent complex relationships between lan-
guages geometrically, in terms of distances and angles. We have tested the method
on a sample of 50 Indo-European and 50 Austronesian languages. The geometric
representations of language taxonomy allow for making accurate interfaces on the
most significant events of human history by tracing changes in language families
through time. The Anatolian and Kurgan hypothesis of the Indo-European origin
and the “express train” model of the Polynesian origin are thoroughly discussed
Geometric representations of language taxonomies
No full textA Markov chain analysis of a network generated by the matrix of lexical distances allows for representing complex relationships between different languages in a language family geometrically, in terms of distances and angles. The fully automated method for construction of language taxonomy is tested on a sample of fifty languages of the Indo-European language group and applied to a sample of fifty languages of the Austronesian language group. The Anatolian and Kurgan hypotheses of the Indo-European origin and the 'express train' model of the Polynesian origin are thoroughly discussed. (C) 2010 Elsevier Ltd. All rights reserved
We Speak Up the Time, and Time Bespeaks Us
No full textWe have presented the first study integrating the analysis of temporal patterns of interaction, interaction preferences and the local vs. global structure of communication in networks of agents. We analyzed face-to-face interactions in two organizations over a period of three weeks. Data on interactions among ca 140 individuals have been collected through a wearable sensors study carried on two start-up organizations in the North-East of Italy. Our results suggest that simple principles reflecting interaction propensities, time budget and institutional constraints underlie the distribution of interaction events. Both data on interaction duration and those on intervals between interactions respond to a common logic, based on the propensities of individuals to interact with each other, the cost of interrupting other activities to interact, and the institutional constraints over behavior. These factors affect the decision to interact with someone else. Our data suggest that there are three regimes of interaction arising from the organizational context of our observations: casual, spontaneous (or deliberate) and institutional interaction. Such regimes can be naturally expressed by different parameterizations of our models. © 2016 L&H Scientific Publishing, LLC. All rights reserved
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