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We demonstrate a cellphone based contact microscopy platform, termed Contact Scope, which can image highly dense or connected samples in transmission mode. Weighing approximately 76 grams, this portable and compact microscope is installed on the existing camera unit of a cellphone using an opto-mechanical add-on, where planar samples of interest are placed in contact with the top facet of a tapered fiber-optic array. This glass-based tapered fiber array has ∼9 fold higher density of fiber optic cables on its top facet compared to the bottom one and is illuminated by an incoherent light source, e.g., a simple light-emitting-diode (LED). The transmitted light pattern through the object is then sampled by this array of fiber optic cables, delivering a transmission image of the sample onto the other side of the taper, with ∼3× magnification in each direction. This magnified image of the object, located at the bottom facet of the fiber array, is then projected onto the CMOS image sensor of the cellphone using two lenses. While keeping the sample and the cellphone camera at a fixed position, the fiber-optic array is then manually rotated with discrete angular increments of e.g., 1-2 degrees. At each angular position of the fiber-optic array, contact images are captured using the cellphone camera, creating a sequence of transmission images for the same sample. These multi-frame images are digitally fused together based on a shift-and-add algorithm through a custom-developed Android application running on the smart-phone, providing the final microscopic image of the sample, visualized through the screen of the phone. This final computation step improves the resolution and also gets rid of spatial artefacts that arise due to non-uniform sampling of the transmission intensity at the fiber optic array surface. We validated the performance of this cellphone based Contact Scope by imaging resolution test charts and blood smears.

Abstract:In determination of electric energy price, most price information coming from bilateral contracts is effective, but the importance of the spot market (pool market) price cannot be ignored. Forecasting the spot market price is very crucial, especially for companies actively participating in the spot market and giving purchase and sale bids. An artificial neural network is a way frequently used for price forecasting research. In this study, simulation studies about price modeling via artificial neural networks and proper artificial neural network configurations are examined. After selection of different network topologies and parameters, attempts are made to observe network performance by error rates and find the best suitable configuration. Moreover, a time series model is made and it is compared with the artificial neural network's error performance.

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A wideband chirped fiber Bragg grating (FBG) dispersion compensator operating in C band is designed theoretically by numerically solving the coupled mode equations. The power reflectivity spectrum and dispersion characteristics of the chirped fiber Bragg gratings are analysed. In order to achieve wideband dispersion compensation with a low insertion loss, grating length, average refractive index change, apodization profile and chirp parameter of the grating should be precisely optimized. The chirped FBG designs achieved in this study have resulted in a negative dispersion of 4.95 ps/nm for a grating length of L = 10 mm and a negative dispersion of 9.76 ps/nm for a grating length of L = 20 mm with 16 nm bandwidth at around 1550 nm.