2010
Authors
Rodrigues, PP; Gama, J;
Publication
KNOWLEDGE DISCOVERY FROM SENSOR DATA
Abstract
Sensor data is usually represented by streaming time series. Current state-of-the-art systems for visualization include line plots and three-dimensional representations, which most of the time require screen resolutions that are not available in small transient mobile devices. Moreover, when data presents cyclic behaviors, such as in the electricity domain, predictive models may tend to give higher errors in certain recurrent points of time, but the human-eye is not trained to notice this cycles in a long stream. In these contexts, information is usually hard to extract from visualization. New visualization techniques may help to detect recurrent faulty predictions. En this paper we inspect visualization techniques in the scope of a real-world sensor network, quickly dwelling into future trends in visualization in transient mobile devices. We propose a simple dense pixel display visualization system, exploiting the benefits that it may represent on detecting and correcting recurrent faulty predictions. A case study is also presented, where a simple corrective strategy is studied in the context of global electrical load demand, exemplifying the utility of the new visualization method when compared with automatic detection of recurrent errors.
2010
Authors
Gaber, MM; Vatsavai, RR; Omitaomu, OA; Gama, J; Chawla, NV; Ganguly, AR;
Publication
KDD Workshop on Knowledge Discovery from Sensor Data
Abstract
2010
Authors
Gama, J; Rodrigues, PP; Spinosa, EJ; Carvalho, ACPLFd;
Publication
Web Intelligence and Security - Advances in Data and Text Mining Techniques for Detecting and Preventing Terrorist Activities on the Web
Abstract
2010
Authors
Vatsavai, RR; Omitaomu, OA; Gama, J; Chawla, NV; Gaber, MM; Ganguly, AR;
Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
2010
Authors
Vieira, J; Ferreira, PG; Aguiar, B; Fonseca, NA; Vieira, CP;
Publication
BMC EVOLUTIONARY BIOLOGY
Abstract
Background: Within Rosaceae, the RNase based gametophytic self-incompatibility (GSI) system has been studied at the molecular level in Maloideae and Prunus species that have been diverging for, at least, 32 million years. In order to understand RNase based GSI evolution within this family, comparative studies must be performed, using similar methodologies. Result: It is here shown that many features are shared between the two species groups such as levels of recombination at the S-RNase ( the S-pistil component) gene, and the rate at which new specificities arise. Nevertheless, important differences are found regarding the number of ancestral lineages and the degree of specificity sharing between closely related species. In Maloideae, about 17% of the amino acid positions at the S-RNase protein are found to be positively selected, and they occupy about 30% of the exposed protein surface. Positively selected amino acid sites are shown to be located on either side of the active site cleft, an observation that is compatible with current models of specificity determination. At positively selected amino acid sites, non-conservative changes are almost as frequent as conservative changes. There is no evidence that at these sites the most drastic amino acid changes may be more strongly selected. Conclusions: Many similarities are found between the GSI system of Prunus and Maloideae that are compatible with the single origin hypothesis for RNase based GSI. The presence of common features such as the location of positively selected amino acid sites and lysine residues that may be important for ubiquitylation, raise a number of issues that, in principle, can be experimentally addressed in Maloideae. Nevertheless, there are also many important differences between the two Rosaceae GSI systems. How such features changed during evolution remains a puzzling issue.
2010
Authors
Santos, JS; Fonseca, NA; Vieira, CP; Vieira, J; Casares, F;
Publication
DEVELOPMENTAL DYNAMICS
Abstract
The tshz genes comprise a family of evolutionarily conserved transcription factors. However, despite the major role played by Drosophila tsh during the development of the fruit fly, the expression and function of other tshz genes have been analyzed in a very limited set of organisms and, therefore, our current knowledge of these genes is still fragmentary. In this study, we perform detailed phylogenetic analyses of the tshz genes, identify the members of this gene family in zebrafish and describe the developmental expressions of two of them, tshz2 and tshz3b, and compare them with meis1, meis2.1, meis2.2, pax6a, and pax6b expression patterns. The expression patterns of these genes define a complex set of coexpression domains in the developing zebrafish brain where their gene products have the potential to interact. Developmental Dynamics 239:1010-1018, 2010. (C) 2010 Wiley-Liss, Inc.
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