Vol 60, No 5 (2017)

This article provides examples that illustrate the search for different two-layer metamaterials that provide rotation of the polarization plane (“optical activity”). Selected objects show a twenty-year history of the search for a new principle of creation of polarization rotators based on planar metamaterials that were implemented in the form of thin-layered periodic structures. The manifestation of optical activity, presence or absence of satisfactory or perfect matching, the possibility of a multiband phenomena, the role of high spatial harmonics in “electromagnetics” of this effect are explained by the features of the eigen-oscillations that are excited in the gap of the multilayer structure.

The authors propose the method for data coding in wireless sensor networks (WSN) based on the transformation of the residue number system and multipath routing. It enables to utilize efficiently the bandwidth of communication channels as well as reduce message delivery time. It is explored the ant algorithm to search an optimal route of data transmission in the wireless sensor network. There is introduced a limitation for the communication radius of the wireless unit that shorts a number of the search decision modes and improves the accuracy of the wireless network simulation. The correspondent software is designed, it allowes exploring the dynamics of finding the optimal transmission path in WSN in case of different algorithm settings, and exploring the impact of the elite ants on the accuracy of the found path.

This paper considers the topic of two-dimensional object localization using radio frequency identification (RFID) technology. One of the important problems that arise during the development of RFID positioning systems is choosing a localization algorithm and a type of measurement data. Usually developers try to find such a combination of an algorithm and measurement type that allows to achieve maximal localization accuracy for a particular scenario. However, in some situations there can be several combinations of algorithms and measurements with equally high accuracy. In order to simplify the choosing problem and to additionally increase accuracy it is developed a combinational localization method. The method is based on averaging position estimates formed by several point-based and zone-based algorithms that process different measurements. In our work there are used three point-based and three zone-based algorithms: a k nearest neighbors algorithm, trilateration, intersectional algorithm, the methods of support vector machine, artificial neural networks, and a naive Bayes classifier. As an input for the algorithms we utilized received signal strength, read rate, and proximity measurements. During the experiments we found that our method decreases the mean error by 15% and the maximum error by 14% compared to the best single algorithm.