D. Kampitaki

Thinned Planar Array Design Using Boolean PSO With Velocity Mutation

The design of thinned planar microstrip arrays under specific constraints concerning the impedance-matching condition of the array elements and the radiation pattern is presented. The radiation characteristics of the structure are extracted by applying the method-of-moments. The array design is based on a novel optimization method, which is a modified version of the boolean particle swarm optimization that employs velocity mutation (BPSO-vm). Apart from the optimization of the array geometry, the proposed method is applicable to other discrete-variable optimization problems. Moreover, the planar array design is coped with by means of other techniques, namely, a binary coded Genetic Algorithm, the binary Particle Swarm Optimization, and the Boolean PSO. The comparison of the above methods and the BPSO-vm shows the efficiency of the proposed technique.

Pareto Optimal Design of Dual-Band Base Station Antenna Arrays Using Multi-Objective Particle Swarm Optimization With Fitness Sharing

The design of dual-band base station antennas under constraints for mobile communications is addressed in this paper. Given the antenna geometry, the method of moments (MoM) is used to compute the antenna characteristics. Two distinct multi-objective evolutionary algorithms are applied in order to find the Pareto front of the feasible solutions that satisfy the design constraints. In the present work, the Multi-Objective Particle Swarm Optimization with fitness sharing (MOPSO-fs) is compared with the Nondominated Sorting Genetic Algorithm-II (NSGA-II) in order to optimize the antenna geometry. Two design cases are presented. The first case is a five-element array operating in GSM1800/UMTS frequency bands. The second base station antenna array consists of six elements operating in UMTS/WLAN (2.4 GHz) frequency bands.

A web-based melanoma image diagnosis support system using topic map and AJAX technologies

The design and implementation of a web-based diagnostic support tool for melanoma dermatological images and related diagnostic data is presented. The proposed system is semantic web-based and is driven by exploiting the combination of AJAX framework and topic map technology. A novel client/server architecture was developed that enables several clients to interact online with the topic map-based system. Users have the ability to access the system anywhere and anytime via a simple Internet browser. Additionally, an ABCD application has been developed for automated calculation of ABCD parameters and consequently embedded in the proposed TM-based system.