On-chip optical-interconnect technology emerges as an attractive approach due to its ultra-large bandwidth and ultra-low power consumption. Silicon-on-insulator (SOI) wire waveguides, on the other hand, have been identified to potentially replace copper wires for intra-chip communication. To take advantage of the wide bandwidth of SOI waveguides, wavelengthdivision multiplexing (WDM) has been implemented. However, WDM have inherent drawbacks. Mode-division multiplexing (MDM) is a viable alternative to WDM in MIMO photonic circuits on SOI as it requires only one carrier wavelength to operate. In this vein, mode converters are key components in on-chip MDM systems. The goal of this paper is to introduce a transverse electric mode converter. The suggested device can convert fundamental transverse electric modes to first-order transverse electric ones and vice versa. It is based on small material perturbation which introduces gradual coupling between different modes. This device is very simple and highly compact; the size of which is 3 μm2. Mathematical expressions for both the insertion loss and crosstalk are derived and optimized for best performance. In addition, three-dimensional finite-difference time-domain (3D-FDTD) simulations are performed in order to verify the mathematical model of the device. Our numerical results reveal that the proposed device has an insertion loss of 1.2 dB and a crosstalk of 10.1 dB. The device’s insertion loss can be decreased to 0.95 dB by adding tapers to its material perturbation.

Automatic car license plate recognition (LPR) is widely used nowadays. It involves plate localization in the image, character segmentation and optical character recognition. In this paper, a set of descriptors of image segments (characters) was proposed as well as a technique of multi-stage classification of letters and digits using cascade of neural network and several parallel Random Forest or classification tree or rule list classifiers. The proposed solution was applied to automated recognition of number plates which are composed of capital Latin letters and Arabic numerals. The paper presents an analysis of the accuracy of the obtained classifiers. The time needed to build the classifier and the time needed to classify characters using it are also presented.

The field experiment carried out in Winna Góra compared the efficacy of fungicide programs applied in accordance with the NegFry and Routine systems. The results of2002 validation achieved in Winna Góra showed that NegFry model forecasting the late blight occurrence is useful in Polish climatic conditions. Compared with routine treatment schemes, NegFry recommended fewer treatments without significant reduction of yield thus potato protection according to NegFry was more cost-effective than according to Routine system. Basing on these facts the NegFry decision support system can be recommended for Polish climatic conditions.