Tutorial para uso do sistema ISE BM&FBovespa (2011)

Tutorial para envio do questionário 2011

New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM)

LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Tangibilidade, classe de ativos e estrutura de capital das empresas listadas na BM&FBOVESPA

This study aims to investigate the influence of the asset class and the breakdown of tangibility as determinant factors of the capital structure of companies listed on the BM & FBOVESPA in the period of 2008-2012. Two current assets classes were composed and once they were grouped by liquidity, they were also analyzed by the financial institutions for credit granting: current resources (Cash, Bank and Financial Applications) and operations with duplicates (Stocks and Receivables). The breakdown of the tangible assets was made based on its main components provided as warrantees for loans like Machinery & Equipment and Land & Buildings. For an analysis extension, three metrics for leverage (accounting, financial and market) were applied and the sample was divided into economic sectors, adopted by BM&FBOVESPA. The data model in dynamic panel estimated by a systemic GMM of two levels was used in this study due its strength to problems of endogenous relationship as well as the omitted variables bias. The found results suggest that current resources are determinants of the capital structure possibly because they re characterized as proxies for financial solvency, being its relationship with debt positive. The sectorial analysis confirmed the results for current resources. The tangibility of assets has inverse proportional relationship with the leverage. As it is disintegrated in its main components, the significant and negative influence of machinery & equipment was more marked in the Industrial Goods sector. This result shows that, on average, the most specific assets from operating activities of a company compete for a less use of third party resources. As complementary results, it was observed that the leverage has persistence, which is linked with the static trade-off theory. Specifically for financial leverage, it was observed that the persistence is relevant when it is controlled for the lagged current assets classes variables. The proxy variable for growth opportunities, measured by the Market -to -Book, has the sign of its contradictory coefficient. The company size has a positive relationship with debt, in favor of static trade-off theory. Profitability is the most consistent variable in all the performed estimations, showing strong negative and significant relationship with leverage, as the pecking order theory predicts