Abstruct-A small plastic scintillator bonded to an optical fiber has several characteristics that make it promising as a brachytherapy dosimeter. In these dosimeters, scintillation light represents signal, whereas Cerenkov and luminescence light from the optical fiber stem is noise that must be subtracted. The dosimeter accuracy can be improved by optically filtering part of the fiber stem light. Spectral measurements were performed to guide the choice of scintillator, fiber, and filter. Spectral signatures and total luminescence of three scintillators and five different silica optical fibers, excited by a 8 Ci I9'Ir source, were measured. The total radiation-induced light from the various optical fibers differed by up to a factor of 5.6. The percentage of fiber-produced light due to luminescence varied between 15 and 79%. A fiber with weak emission was used in the dosimeter with BC408S, a scintillator with minimum emission wavelength of 400 nm. A 400-nm cutoff UV filter gave a factor of two increase in signal-to-noise. The dosimeter response was linear for dose rates varying by at least three orders of magnitude, representing source-to-probe distances of 0.2-10 cm. Measurement errors of the dosimeter compare favorably with other brachytherapy dosimeters.

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In order to cope with the increasing energy demand, microgrids emerged as a potential solution which allows the designer a lot of flexibility. The optimization of the controller parameters of a microgrid ensures a stable and environment friendly operation. Non-dominated Sorting Sine Cosine Algorithm (NSSCA) is a hybrid of Sine Cosine Algorithm and Non-dominated Sorting technique. This algorithm is applied to optimize the control parameters of a microgrid which incorporates both static and dynamic load. The obtained results are compared with the results of the established Non-dominated Sorting Genetic Algorithm-II (NSGA-II) in order to justify the proposal of the NSSCA. The average time needed to converge in NSSCA is 7.617s whereas NSGA-II requires an average of 10.660s. Moreover, the required number of iterations for NSSCA is 2 which is significantly less in comparison to the 12 iterations in NSGA-II.