Técnicas de manejo agropecuário sustentável

The competitiveness in the rural sector and the need to make viable and sustainable property, direct the farmer to seek new production strategies. In this sense, the book Techniques of sustainable agricultural management has as objective contributed information on concepts, management practices, technological innovations, which are applicable in the agricultural production. The same is composed of 13 chapters, topics covered in aquaculture production, management and dairy production, as general aspects of hematology fish; dynamics of decision-making and adaptive flow dairy production systems; importance of performance measures and body biometrics in small ruminants; milk production in beef cows; parasitism in beef cattle; performance of dairy cows in production; efficiency of cross beef cattle in finishing phase; development of Marchangus: five years; and, bovine growth efficiency. In vegetable production area are addressed matters relating on management and olive cultivation, species of great economic importance and diversification as alternative on the property; functional foods in fruit and vegetables; influence of environmental factors, harvesting and drying in the production and composition of essential oils of Mentha spp; and, implication of the contamination of corn grain by mycotoxins in livestock production. At the end of the book, the expectation of the authors is to have contributed with relevant themes of Brazilian agriculture, which could reflect positively on knowledge, values and quality of available material.

Protocolo de roteamento para redes oportunistas utilizando otimização por enxame de partículas

In this research work, a new routing protocol for Opportunistic Networks is presented. The proposed protocol is called PSONET (PSO for Opportunistic Networks) since the proposal uses a hybrid system composed of a Particle Swarm Optimization algorithm (PSO). The main motivation for using the PSO is to take advantage of its search based on individuals and their learning adaptation. The PSONET uses the Particle Swarm Optimization technique to drive the network traffic through of a good subset of forwarders messages. The PSONET analyzes network communication conditions, detecting whether each node has sparse or dense connections and thus make better decisions about routing messages. The PSONET protocol is compared with the Epidemic and PROPHET protocols in three different scenarios of mobility: a mobility model based in activities, which simulates the everyday life of people in their work activities, leisure and rest; a mobility model based on a community of people, which simulates a group of people in their communities, which eventually will contact other people who may or may not be part of your community, to exchange information; and a random mobility pattern, which simulates a scenario divided into communities where people choose a destination at random, and based on the restriction map, move to this destination using the shortest path. The simulation results, obtained through The ONE simulator, show that in scenarios where the mobility model based on a community of people and also where the mobility model is random, the PSONET protocol achieves a higher messages delivery rate and a lower replication messages compared with the Epidemic and PROPHET protocols.