Levent Seyfi

A novel software for an energy efficient GPR

In this paper, a simulator software based on MATLAB environment has been developed so that an energy efficient ground penetrating radar (GPR) can be modelled. Thus, applications of the radar in practice will easily be performed. In the software, the output power of GPR has been assumed as variable in order to reduce energy consumption. Power values have been computed in simulations with the proposed software for two different models which have comprised mediums with horizontal sublayer and inclined sublayer. Compared with common algorithm, power savings (PS) of 43% for the horizontal situation and 22% for the inclined one have been obtained.

A comparative study on parameters of leaf-shaped patch antenna using hybrid artificial intelligence network models

This study proposes a very compact coaxial-fed planar antenna for X band applications. The antenna design includes a tulip-shaped radiator on the FR4 dielectric substrate. The antenna parameters, such as return losses, bandwidth and operating frequency, have close relationships with patch geometry. In order to obtain desired antenna parameters for X band application, patch dimension is necessary to be optimized. In this article, four different hybrid artificial intelligence network models are suggested for optimization. These are particle swarm optimization, differential evolution, grey wolf optimizer and vortex search algorithm. Also, they are combined with artificial neural network for the purpose of estimating dimension of patch. Therefore, the comparison of different proposed algorithms is analyzed to obtain higher characteristics for antenna design. Their results are compared with each other in HFSS 13.0 software. The antenna with the most suitable return loss, bandwidth and operating frequency is selected to be used in antenna design.

SAR Values in a Homogenous Human Head Model

The purpose of this chapter is to present how to determine and reduce specific absorption rate (SAR) on mobile phone user. Both experimental measurement technique and a numerical computing method are expressed here. Furthermore, an application on reduction of SAR value induced in human head is carried out with numerical computing. Mobile phone working at 900 MHz frequency shielded with copper is considered in order to furnish reduction of SAR in simulations which are conducted to calculate the maximum SAR values in Matlab programming language using two dimensional (2D) Finite Difference Time Domain (FDTD) method. Calculations are separately made for both 1 g and 10 g. Head model structure is assumed uniform.

Deep dictionary learning application in GPR B-scan images

This paper introduces GPR B-scan database which contains 180 labelled images to facilitate research in developing presentation algorithm for this challenging scenario. Along with GPR B-scan images, there are several other detections of buried objects that are explored in the literature. The next contribution of this research is a novel multilevel deep dictionary learning-based presentation buried object detection algorithm that can discern different kinds of materials. An efficient layer by layer training approach is formulated to learn the deep dictionaries followed by different classifiers as types of shape for buried objects. By changing the number of layers in proposed algorithm, performances in different classifiers are compared. It is possible to integrate the proposed algorithm with real-time systems because it is supervised and has high classification accuracy with 94.4%.