101 research outputs found

    Equation-free analysis of a dynamically evolving multigraph

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    In order to illustrate the adaptation of traditional continuum numerical techniques to the study of complex network systems, we use the equation-free framework to analyze a dynamically evolving multigraph. This approach is based on coupling short intervals of direct dynamic network simulation with appropriately-defined lifting and restriction operators, mapping the detailed network description to suitable macroscopic (coarse-grained) variables and back. This enables the acceleration of direct simulations through Coarse Projective Integration (CPI), as well as the identification of coarse stationary states via a Newton-GMRES method. We also demonstrate the use of data-mining, both linear (principal component analysis, PCA) and nonlinear (diffusion maps, DMAPS) to determine good macroscopic variables (observables) through which one can coarse-grain the model. These results suggest methods for decreasing simulation times of dynamic real-world systems such as epidemiological network models. Additionally, the data-mining techniques could be applied to a diverse class of problems to search for a succint, low-dimensional description of the system in a small number of variables

    Extraction of cartographic objects in high resolution satellite images for object model generation

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    The aim of this study is to detect man-made cartographic objects in high-resolution satellite images. New generation satellites offer a sub-metric spatial resolution, in which it is possible (and necessary) to develop methods at object level rather than at pixel level, and to exploit structural features of objects. With this aim, a method to generate structural object models from manually segmented images has been developed. To generate the model from non-segmented images, extraction of the objects from the sample images is required. A hybrid method of extraction (both in terms of input sources and segmentation algorithms) is proposed: A region based segmentation is applied on a 10 meter resolution multi-spectral image. The result is used as marker in a "marker-controlled watershed method using edges" on a 2.5 meter resolution panchromatic image. Very promising results have been obtained even on images where the limits of the target objects are not apparent

    Visualizing clickstream data with multidimensional scaling

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    We visualize a a web server log by means of multidimensionalscaling. To that end, a so-called dissimilarity metric is introduced inthe sets of sessions and pages respectively. We interpret the resultingvisualizations and find some interesting patterns.

    Language classification from bilingual word embedding graphs

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    We study the role of the second language in bilingual word embeddings in monolingual semantic evaluation tasks. We find strongly and weakly positive correlations between down-stream task performance and second language similarity to the target language. Additionally, we show how bilingual word embeddings can be employed for the task of semantic language classification and that joint semantic spaces vary in meaningful ways across second languages. Our results support the hypothesis that semantic language similarity is influenced by both structural similarity as well as geography/contact.Comment: To be published at Coling 201

    Aljabar Hipergraf Dan Aplikasinya

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    Dalam makalah ini telah dibangun pohon filogenetik untuk menentukan kedekatan hubungan kekerabatan dari 16 organisme, dengan menggunakan pendekatan Aljabar hipergraf. Langkah pertama adalah menggunakan hipergraf berarah untuk merepresentasikan siklus asam sitrat sebagai jaringan metabolik kemudian menghitung jarak antara 2 jaringan metabolik dengan menggunakan operasi‐operasi aljabar seperti dalam penelitian sebelumnya[8] sehingga diperoleh matrik jarak. Selanjutnya program Matlab R2007b digunakan untuk membangun pohon filogenetik dengan Algoritma Neighbor Joining (Neighbor Joining Algorithm). Kemudian telah dibangun pula pohon filogenetik pembanding yang diperoleh berdasarkan urutan nukleotida gen 16S rRNA pada masing‐masing organisme yang sama. Dari penelitian ini diperoleh bahwa, terdapat sepasang organisme pada kedua pohon filogenetik yang dihasilkan, yang memiliki kekerabatan dekat berdasarkan urutan gen 16S rRNA tetapi memiliki kekerabatan yang jauh berdasarkan jaringan metaboliknya ataupun sebaliknya. Kata kunci: Filogenetik, aljabar hipergraf, jaringan metabolic, algoritma neighbor joining, siklus asam sitrat, urutan nukleotida, gen 16S rRNA

    Accurate recognition of large number of hand gestures

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    A hierarchical gesture recognition algorithm is introduced to recognise a large number of gestures. Three stages of the proposed algorithm are based on a new hand tracking technique to recognise the actual beginning of a gesture using a Kalman filtering process, hidden Markov models and graph matching. Processing time is important in working with large databases. Therefore, special cares are taken to deal with the large number of gestures, which are partially similar
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