The sugar composition of fruits in the diet of spider monkeys (Ateles geoffroyi) in tropical humid forest in Costa Rica

Spider monkeys (Ateles geoffroyi) detect sucrose at a threshold lower than any primate yet tested and prefer sucrose to glucose or fructose in laboratory tests. This preferential selection of sucrose led to the hypothesis that such acute discrimination is related to a diet of sucrose-rich fruits. Furthermore, it has been suggested that fruit sugars may be related to distinct guilds of vertebrate seed-dispersers. The objectives of this study were: (1) to test if spider monkeys select sucrose-rich fruits both within and among plant species and (2) to test the hypothesis that sugar concentration is related to bird, bat or monkey seed-dispersal syndromes. Data were collected from one troop of spider monkeys in south-western Costa Rica. Interspecific comparison of ingested fruits shows that spider monkeys consumed species with significantly higher concentrations of glucose and fructose than sucrose. Similarly, at the intraspecific level, food-fruits had significantly more fructose and glucose than non-food fruits, but no difference was found for sucrose. The three different sugar types were not correlated with the importance of the species in the diet based on the amount of time they spent consuming each species. Although sucrose concentrations were significantly higher in primate-dispersed species compared with those dispersed by other vertebrates, soluble carbohydrates in primate-dispersed fruits were principally composed of glucose and fructose. Neither fructose nor glucose concentrations showed significant differences across the three categories of seed dispersal.published_or_final_versio

Pyramidal Stochastic Graphlet Embedding for Document Pattern Classification

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordDocument pattern classification methods using graphs have received a lot of attention because of its robust representation paradigm and rich theoretical background. However, the way of preserving and the process for delineating documents with graphs introduce noise in the rendition of underlying data, which creates instability in the graph representation. To deal with such unreliability in representation, in this paper, we propose Pyramidal Stochastic Graphlet Embedding (PSGE). Given a graph representing a document pattern, our method first computes a graph pyramid by successively reducing the base graph. Once the graph pyramid is computed, we apply Stochastic Graphlet Embedding (SGE) for each level of the pyramid and combine their embedded representation to obtain a global delineation of the original graph. The consideration of pyramid of graphs rather than just a base graph extends the representational power of the graph embedding, which reduces the instability caused due to noise and distortion. When plugged with support vector machine, our proposed PSGE has outperformed the state-of-The-art results in recognition of handwritten words as well as graphical symbols.European Union Horizon 2020Ministerio de Educación, Cultura y Deporte, SpainRamon y Cajal FellowshipCERCA Program/Generalitat de Cataluny

Hierarchical stochastic graphlet embedding for graph-based pattern recognition

This is the final version. Available on open access from Springer via the DOI in this recordDespite being very successful within the pattern recognition and machine learning community, graph-based methods are often unusable with many machine learning tools. This is because of the incompatibility of most of the mathematical operations in graph domain. Graph embedding has been proposed as a way to tackle these difficulties, which maps graphs to a vector space and makes the standard machine learning techniques applicable for them. However, it is well known that graph embedding techniques usually suffer from the loss of structural information. In this paper, given a graph, we consider its hierarchical structure for mapping it into a vector space. The hierarchical structure is constructed by topologically clustering the graph nodes, and considering each cluster as a node in the upper hierarchical level. Once this hierarchical structure of graph is constructed, we consider its various configurations of its parts, and use stochastic graphlet embedding (SGE) for mapping them into vector space. Broadly speaking, SGE produces a distribution of uniformly sampled low to high order graphlets as a way to embed graphs into the vector space. In what follows, the coarse-to-fine structure of a graph hierarchy and the statistics fetched through the distribution of low to high order stochastic graphlets complements each other and include important structural information with varied contexts. Altogether, these two techniques substantially cope with the usual information loss involved in graph embedding techniques, and it is not a surprise that we obtain more robust vector space embedding of graphs. This fact has been corroborated through a detailed experimental evaluation on various benchmark graph datasets, where we outperform the state-of-the-art methods.European Union Horizon 2020Ministerio de Educación, Cultura y Deporte, SpainGeneralitat de Cataluny

Graph-Based Deep Learning for Graphics Classification

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordGraph-based representations are a common way to deal with graphics recognition problems. However, previous works were mainly focused on developing learning-free techniques. The success of deep learning frameworks have proved that learning is a powerful tool to solve many problems, however it is not straightforward to extend these methodologies to non euclidean data such as graphs. On the other hand, graphs are a good representational structure for graphical entities. In this work, we present some deep learning techniques that have been proposed in the literature for graph-based representations and we show how they can be used in graphics recognition problems.European Union Horizon 2020FPUMinisterio de Educación, Cultura y Deporte, SpainRamon y Cajal FellowshipCERCA Program/Generalitat de Cataluny

Improving Information Retrieval in Multiwriter Scenario by Exploiting the Similarity Graph of Document Terms

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordInformation Retrieval (IR) is the activity of obtaining information resources relevant to a questioned information. It usually retrieves a set of objects ranked according to the relevancy to the needed fact. In document analysis, information retrieval receives a lot of attention in terms of symbol and word spotting. However, through decades the community mostly focused either on printed or on single writer scenario, where the state-of-The-art results have achieved reasonable performance on the available datasets. Nevertheless, the existing algorithms do not perform accordingly on multiwriter scenario. A graph representing relations between a set of objects is a structure where each node delineates an individual element and the similarity between them is represented as a weight on the connecting edge. In this paper, we explore different analytics of graphs constructed from words or graphical symbols, such as diffusion, shortest path, etc. to improve the performance of information retrieval methods in multiwriter scenario.European Union Horizon 2020Ministerio de Educación, Cultura y Deporte, SpainFPUCERCA Programme/Generalitat de Cataluny

Table Detection in Invoice Documents by Graph Neural Networks

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Tabular structures in documents offer a complementary dimension to the raw textual data, representing logical or quantitative relationships among pieces of information. In digital mail room applications, where a large amount of administrative documents must be processed with reasonable accuracy, the detection and interpretation of tables is crucial. Table recognition has gained interest in document image analysis, in particular in unconstrained formats (absence of rule lines, unknown information of rows and columns). In this work, we propose a graph-based approach for detecting tables in document images. Instead of using the raw content (recognized text), we make use of the location, context and content type, thus it is purely a structure perception approach, not dependent on the language and the quality of the text reading. Our framework makes use of Graph Neural Networks (GNNs) in order to describe the local repetitive structural information of tables in invoice documents. Our proposed model has been experimentally validated in two invoice datasets and achieved encouraging results. Additionally, due to the scarcity of benchmark datasets for this task, we have contributed to the community a novel dataset derived from the RVL-CDIP invoice data. It will be publicly released to facilitate future research.European Unio

Indigenous artifacts of Adi tribe in Arunachal Pradesh: Are they waning amidst thewaves of globalization?

The tribals lead the life with natural simplicity relying on primal truths reinforced by eternal values. The strength of the tribes is that they are able to successfully cling to the primal skills and natural simplicity. Their creations speak of evolutions over time, and the arts and crafts created by them have timeless appeal. The primal instinct in all of us is evoked whenever we come across the crudest tribal handicrafts. The present case study was conducted during August and September 2019 and the study included combination of methods such as research viz., household survey of 44 Adi families, followed by a focused group discussion was adopted and also documented the artifacts of Adi tribe in East Siang district of Arunachal Pradesh, India. Further, the study also aimed at unearthing the kinds of possible threats that arise due to globalization which may affect traditional craftsmanship. Multitudinal sets of traditional artifacts created out of indigenous wisdom have beendocumented which affirm that the life of the Adi is intertwined with the forest products especially bamboo, canes and their products. However, the prevailing trend of globalization, with characteristics of immense, unexpected emphasis on capital, labour and information, is having growing influence on material culture and in this scenario, especially new generationprefers more of plastic products in their day to day lifestyle. On the contrary, traditional artifacts of Adi could offer innovative and sustainable solutions which can act as alternatives to plastic products

Indigenous artifacts of Adi tribe in Arunachal Pradesh: Are they waning amidst the waves of globalization?

277-283The tribals lead the life with natural simplicity relying on primal truths reinforced by eternal values. The strength of the tribes is that they are able to successfully cling to the primal skills and natural simplicity. Their creations speak of evolutions over time, and the arts and crafts created by them have timeless appeal. The primal instinct in all of us is evoked whenever we come across the crudest tribal handicrafts. The present case study was conducted during August and September 2019 and the study included combination of methods such as research viz., household survey of 44 Adi families, followed by a focused group discussion was adopted and also documented the artifacts of Adi tribe in East Siang district of Arunachal Pradesh, India. Further, the study also aimed at unearthing the kinds of possible threats that arise due to globalization which may affect traditional craftsmanship. Multitudinal sets of traditional artifacts created out of indigenous wisdom have been documented which affirm that the life of the Adi is intertwined with the forest products especially bamboo, canes and their products. However, the prevailing trend of globalization, with characteristics of immense, unexpected emphasis on capital, labour and information, is having growing influence on material culture and in this scenario, especially new generation prefers more of plastic products in their day to day lifestyle. On the contrary, traditional artifacts of Adi could offer innovative and sustainable solutions which can act as alternatives to plastic products