Utilização do mapa espacial de radiação e dose acumulada como ferramenta para otimização de doses em pacientes e trabalhadores nas clínicas de medicina nuclear

This study has as general aim to propose a spatial map of doses as an auxiliary tool in assessing the need for optimization of the workplace in nuclear medicine services. As specific aims, we assessed the workers individual dosimetry; we analyzed the facilities of the nuclear medicine services; and we evaluated environment exposure rates. The research is characterized as a case study, with an exploratory and explanatory nature. It was conducted in three Nuclear Medicine Services, all established in the Northwest of the Paraná State. Results indicated that the evaluated dose rates and workers dosimetry, in all the dependencies of the surveyed services, are within the limits of annual doses. However some exceeded the limits recommended in the standard CNEN-NN 3:01 (2014). It was concluded that the spatial map dose is an important tool for nuclear medicine services because it facilitates the visualization of areas with highest concentration of radiation, and also helps in the constant review of these measures and resources, aiding in the identification of any failures and shortcomings, providing resources to correct any issues and prevent their repetition. The spatial map dose is also important for the regular inspection, evaluating if the radiation protection objectives are being met.

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.