75Se - A promising alternative to 192Ir for potential use in the skin cancer brachytherapy: A Monte Carlo simulation study using FLUKA code.

This study aimed to evaluate the possibility of utilizing the HDR 75Se source for skin cancer brachytherapy. In this work, based on the BVH-20 skin applicator, two cup-shaped applicators, without and with the flattening filter, were modeled. To obtain the optimal flattening filter shape, an approach based on the MC simulation in combination with an analytical estimation was used. Then, the dose distributions for 75Se-applicators were generated using MC simulations in water, and their dosimetric characterizations such as flatness, symmetry, and penumbra were evaluated. Furthermore, the radiation leakage in the backside of the applicators was estimated by additional MC simulation. Finally, to evaluate the treatment times, calculations were performed for two 75Se-applicators assuming 5 Gy per fraction. The flatness, symmetry, and penumbra values for the 75Se-applicator without the flattening filter were estimated to be 13.7%, 1.05, and 0.41 cm respectively. The corresponding values for 75Se-applicator with the flattening filter were estimated to be 1.6%, 1.06, and 0.10 cm respectively. The radiation leakage value at a distance of 2 cm from the applicator surface was calculated to be 0.2% and 0.4% for the 75Se-applicator without and with the flattening filter respectively. Our results showed that the treatment time for the 75Se-applicator is comparable with that of the 192Ir-Leipzig applicator. The findings revealed that the dosimetric parameters of the 75Se applicator are comparable with the 192Ir skin applicator. Overall, the 75Se source can be an alternative to 192Ir sources for HDR brachytherapy of skin cancer.

A data fusion method in wireless sensor networks.

The success of a Wireless Sensor Network (WSN) deployment strongly depends on the quality of service (QoS) it provides regarding issues such as data accuracy, data aggregation delays and network lifetime maximisation. This is especially challenging in data fusion mechanisms, where a small fraction of low quality data in the fusion input may negatively impact the overall fusion result. In this paper, we present a fuzzy-based data fusion approach for WSN with the aim of increasing the QoS whilst reducing the energy consumption of the sensor network. The proposed approach is able to distinguish and aggregate only true values of the collected data as such, thus reducing the burden of processing the entire data at the base station (BS). It is also able to eliminate redundant data and consequently reduce energy consumption thus increasing the network lifetime. We studied the effectiveness of the proposed data fusion approach experimentally and compared it with two baseline approaches in terms of data collection, number of transferred data packets and energy consumption. The results of the experiments show that the proposed approach achieves better results than the baseline approaches.