Deep learning is an emerging area in current scenario. Mostly, Convolutional Neural Network (CNN) and Deep Belief Network (DBN) are used as the model in deep learning. It is termed as Deep Neural Network (DNN). The use of DNN is widely spread in many applications, exclusively for detection and classification purpose. In this paper, authors have used the same network for signal enhancement purpose. Speech is considered for the input signal with noise. The model of DNN is used with two layers. It has been compared with the ADALINE model to prove its efficacy.
Low energy 125I-brachytherapy sources are used for the treatment of retinoblastoma and many other forms of eye cancer. Such sources were prepared by adsorption of 125I on palladium coated silver rods and were critically evaluated for safety aspects, as per AERB standards. In order to attain low leachability and to facilitate leak free laser encapsulation of sources within titanium capsules of size 0.8 mm (f) ´ 4.75 mm (l), the radioactive source core was coated with polystyrene. With a view to study the radiation stability of such sources over a period of three weeks, both polymer coated radioactive sources and inactive source cores were separately subjected to an integrated gamma dose of ~(17.85 ´ 104) Gy (17.85 MRad), which is the dose expected to be received in three weeks from a source containing ~ 111 MBq of 125I. This was carried out to test their suitability for reuse within such period. SEM pictures of inactive source cores were taken to observe the effect of gamma radiation on palladium coating. Post-irradiation leachability and uniformity of activity of radioactive sources were evaluated and found to be satisfactory. The sources were found to be reusable safely, for repeated brachytherapy procedures over a practically useful time of at least three weeks.
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