Elimination of noise on transcranial Doppler signal using IIR filters designed with artificial bee colony – ABC-algorithm

Biomedical signals are usually contaminated by noise generated from sources such as power line interference and disturbances produced by the movement of the recording electrodes. Also the signal-to-noise ratio of biomedical signals is usually quite low. In addition, biomedical signals often interfere with each other. Therefore, the filters employed for eliminating noise and interference are significant in the medical practice. Digital infinite impulse response (IIR) filters have shorter filter length than the finite impulse response (FIR) filters with the same frequency characteristic. Therefore, in this work, an approach based on digital IIR filters are described for the elimination of noise on transcranial Doppler by using artificial bee colony (ABC) which is a popular swarm based optimization algorithm introduced recently. Moreover, the performance of the proposed approach is compared to particle swarm optimization algorithm.     

A comparative study of multi-objective optimization algorithms for sparse signal reconstruction

The development of the efficient sparse signal recovery algorithm is one of the important problems of the compressive sensing theory. There exist many types of sparse signal recovery methods in compressive sensing theory. These algorithms are classified into several categories like convex optimization, non-convex optimization, and greedy methods. Lately, intelligent optimization techniques like multi-objective approaches have been used in compressed sensing. Firstly, in this paper, the basic principles of the compressive sensing theory are summarized. And then, brief information about multi-objective algorithms, local search methods, and knee point selection methods are given. Afterward, multi-objective sparse recovery methods in the literature are reviewed and investigated in accordance with their multi-objective optimization algorithm, the local search method, and the knee point selection method. Also in this study, examples of multi-objective sparse reconstruction methods are designed according to the existing studies. Finally, the designed algorithms are tested and compared by using various types of sparse reconstruction test problems.

     

A generic framework for optimizing performance metrics by tuning parameters of clustering protocols in WSNs

Wireless Networks - Wireless sensor network (WSN) is a key technology trend in emerging internet of things paradigms which are commonly used for application areas such as smart-cities, smart-grids,...     

Antenna array pattern nulling by controlling both amplitude and phase using modified touring ant colony optimization algorithm

This paper presents an efficient method, based on the modified touring ant colony optimization algorithm, for null steering of linear antenna arrays by controlling both the amplitude and the phase of array elements. The maximum sidelobe level, the null depth level and the dynamic range ratio are taken into account in the pattern synthesis. Simulation results for Chebyshev patterns with the imposed single, multiple and broad nulls are given to show the effectiveness of the proposed method.     

Fixed and dynamic bandwidth allocation strategies for wireless mobile integrated services networks

Performance evaluation of two bandwidth allocation strategies in wireless mobile integrated services networks is carried out. Performances of the proposed strategies are compared with those of the traditional guard channels and threshold strategies. In the study, a single wireless cell which is accessed by voice and non-voice traffic types producing, respectively narrowband and wideband calls is considered. In the proposed strategies a number of channels are reserved in a fixed or dynamic fashion for the use of originating wideband calls in addition to the guard channels allocated for the handoff calls. The results indicate that the two strategies have comparable advantages and by manipulating the number of reserved channels, desired performance levels can be achieved. The dynamic reservation based strategy makes the system fairer for the originating wideband calls while maintaining low handoff dropping probability and acceptable channel utilization levels. On the other hand, the fixed reservation strategy provides a lower handoff call dropping at comparable channel utilization levels. The tradeoff is between improving the handoff call dropping versus the originating wideband call blocking. Both strategies provide better performance for the originating wideband calls compared with that provided by the traditional guard channels strategy.

Microstructure and Transport Properties of Compaction-Modified In Situ Fe/MgB<Subscript>2</Subscript> Wires

This study has shown the effect of excessive mechanical deformation by pressing and consecutive heat treatment, respectively, on the microstructure and transport properties of mono-core sintered in situ Fe/MgB₂ wires. These wires were pressed into short tapes under 1 GPa uniaxial pressure. Transport properties like critical temperature, transition width and engineering critical current density of the same samples were determined before and after pressing and after annealing. Phase formation and grain size of the samples were studied with XRD. The SEM analysis indicated that the mechanical deformation reduced initial voids to a large extent but caused cracks, increased the number of grain boundaries and introduced weak links. The subsequent heat treatment on the pressed samples improved the microstructure and the grain connectivity. Possibility of a final densification of the reacted in situ wires was discussed in terms of transport properties.     

A survey: algorithms simulating bee swarm intelligence

Swarm intelligence is an emerging area in the field of optimization and researchers have developed various algorithms by modeling the behaviors of different swarm of animals and insects such as ants, termites, bees, birds, fishes. In 1990s, Ant Colony Optimization based on ant swarm and Particle Swarm Optimization based on bird flocks and fish schools have been introduced and they have been applied to solve optimization problems in various areas within a time of two decade. However, the intelligent behaviors of bee swarm have inspired the researchers especially during the last decade to develop new algorithms. This work presents a survey of the algorithms described based on the intelligence in bee swarms and their applications.     

The parameter extraction of the thermally annealed Schottky barrier diode using the modified artificial bee colony

In this paper, a new method based on the modified artificial bee colony (MABC) algorithm to determine the main characteristic parameters of the Schottky barrier diode such as barrier height, ideality factor and series resistance. For this model, the Ni/n-GaAs/In Schottky barrier diode was produced and annealed at different temperature in a laboratory. The performance of the modified ABC method was compared to that of the basic artificial bee colony (ABC), particle swarm optimization (PSO), differential evolution (DE), genetic algorithm (GA) and simulated annealing (SA). From the results, it is concluded that the modified ABC algorithm is more flexible and effective for the parameter determination than the other algorithms.