The intense and extreme rains in southeastern Brazil are spatially and temporally dynamic, corroborating their substantial complexity regarding understanding and associations. Therefore, the present study aimed at determining threshold values for events of intense and extreme rainfall in the region of São Carlos/SP using a climatic index, as well as temporal and spatial observations. The RClimdex script, Rnn index, and the detection of outliers were employed in order to mark and establish intense and extreme rainfall thresholds for the region. Values of 10 mm and 20 mm of rain were considered typical and of greater recurrence, and their incidence over a period of 24 hours did not necessarily denote intense events. In turn, values of 35, 46, and 60 mm indicate pluviometric rates that impact on significant disasters, as verified in the IPMET/UNESP natural disasters database. It is important to emphasize that values below 60 mm of daily rainfall may also indicate disaster contexts. However, they do not exclude the necessity to verify the intensity, duration, and frequency of intense rain events, and can delineate thresholds for territorial management organizations in their planning.

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This study examines the development of a system that assists in planning flight activities of the Academia da Força Aérea (AFA) so that meteorological data can be used to predict the occurrence of fog. This system was developed in MATLAB 8.0 by applying multilayer perceptron-type artificial neural networks and using an error correction algorithm called backpropagation. The methodology used to implement the network comprises eight input variables, five neurons in the intermediary layer, and one neuron in the output layer, which corresponds to the presence or absence of fog. The fog phenomenon is very important for the study and definition of flight strategic planning. Data taken from 1989 to 2008 and related to the input variables were used for the training and validation of the proposed network. Consequently, the multilayer perceptron network has a 95% reliability compared with the data collected. This high level of reliability is an exceptional result for the management, planning, and decision making team of the AFA strategic group. Thus, it can be concluded that the proposed system is efficient and will subsidize, with good safety margin, AFA's flight activity planning and could also be applied to other air activities in Brazil.

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This article presents a survey of the state of art of the mechanisms to provide security to the Wireless Sensor Networks. Over the principal schemes, are the key management and cryptography, the authentica-tion protocols and the mechanisms of clone or intrusion detection.