e. feli

In this research, creative techniques have been applied on the surface of polymer optical fiberto observ new optical effects in the production of luminous textiles and their further application in designing luminous clothing. Accordingly, optical fibers of three different thicknesses (0.25, 0.5, and 0.75 mm) were subjected to secondary operations using techniques such as knotting, pulling, grinding the surface with sandpaper, melting, and creating scratches with a cutter, and were exposed to LED to evaluate their luminescence. The result showed that the light emitted from fibers with greater thickness shined more than the similar samples in fibers with less thickness. Additionally, a thicker fiber has been proven to be less flexible than a thinner fiber. Thinner plastic fibers revealed faster melting and weremore fragile and more sensitive to heat. In the knotting and melting methods, the obtained light was appeared in the form of a three-dimensional spotlight. In the melting method, the resulting light was appeared brighter than other samples due to the formation of a spherical shape in the fiber tip. On the other hand, the light emitted from the samples exposed to sanding and pulling scatter appeareduniformly due to the fiber transparency and linear processing. The conducted research declaredthe high potential of optical fibers for the production of luminous textiles with unique design capabilities and their high efficiency in the fashion and clothing industry.

In Vitro Fertilization (IVF) is one of the scientifically known methods of infertility treatment. This study aimed at improving the performance of predicting the success of IVF using machine learning and its optimization through evolutionary algorithms. The Multilayer Perceptron Neural Network (MLP) were proposed to classify the infertility dataset. The Genetic algorithm was used to improve the performance of the Multilayer Perceptron Neural Network model. The proposed model was applied to a dataset including 594 eggs from 94 patients undergoing IVF, of which 318 were of good quality embryos and 276 were of lower quality embryos. For performance evaluation of the MLP model, an ROC curve analysis was conducted, and 10-fold cross-validation performed. The results revealed that this intelligent model has high efficiency with an accuracy of 96% for Multi-layer Perceptron neural network, which is promising compared to counterparts methods.