Mustafa Berkan Biçer

Simple Formulas for Calculating Resonant Frequencies of C and H Shaped Compact Microstrip Antennas Obtained by Using Artificial Bee Colony Algorithm

Accurate and simple formulas are presented for effective length in determining the resonant frequency of C and H shaped compact microstrip antennas (CMAs) operating on UHF band. For this purpose, 144 C-shaped CMAs and 216 H-shaped CMAs having different physical dimensions and various relative dielectric constants were simulated by packaged software called XFDTD based on finite difference time domain (FDTD) method. The physical and electrical parameters of the antennas and their respective resonant frequency values were given as inputs to artificial bee colony (ABC) algorithm to determine unknown coefficients of the effective length expression which provides the best fit to the resonant frequency. The resonant frequency results of the effective length expressions were compared with the different measurement, simulation and calculation results published earlier in the literature. It was shown that our results are in very good agreement with the simulated and measured results as compared to those of calculated by the other suggestions reported elsewhere. Moreover, C and H shaped CMAs were fabricated in this work and then the accuracy and validity of proposed expressions were tested and verified. Major benefit of the formulation proposed here is that it provides accurate results without necessitating any other calculations.

A Novel Microstrip-Fed Monopole Antenna For WLAN/WiMAX Applications

Abstract A new microstrip-fed printed monopole antenna which is simple in design and compact in size is presented for simultaneously satisfying wireless local area network (WLAN) and worldwide interoperability for microwave access (WiMAX) bands. A simulation software package, CST Microwave Studio, has been used to model the proposed antenna, whose electrical characteristics and radiation performance are thoroughly analyzed as well. The proposed antenna, with small size of 28 × 51 mm2 on Rogers RT/Duroid® 5870 substrate with permittivity 2.33, was designed and fabricated. It was demonstrated that the measured 10 dB bandwidth for return loss is from 1.76 to 2.59 GHz, 3.44 to 3.89 GHz and 5.18 to 5.99 GHz, covering all the 2.4/5.2/5.8 GHz WLAN and 2.5/3.5/5.5 GHz WiMAX bands.

A novel and simple expression to accurately calculate the resonant frequency of annular-ring microstrip antennas

This paper proposes a novel and simple expression for effective radius of annular-ring microstrip antennas (ARMAs) obtained using a recently emerged optimization algorithm of artificial bee colony (ABC) in calculating the resonant frequency at dominant mode (TM 11 ). A total of 80 ARMAs having different parameters related to antenna dimensions and dielectric constants was simulated in terms of the resonant frequency with the help of an electromagnetic simulation software called IE3D™ based on method of moment. The effective radius expression was constructed and the unknown coefficients belonging to the expression were then optimally determined with the use of ABC algorithm. The proposed expression was verified through comparisons with the methods of resonant frequency calculation reported elsewhere. Also, it was further validated on an ARMA fabricated in this study. The superiority of the presented approach over the other methods proposed in the literature is that it does not need any sophisticated computations while achieving the most accurate results in the resonant frequency calculation of ARMAs.

ANFIS model for determining resonant frequency of rectangular ring compact microstrip antennas

In this work, a model constructed with the adaptive neuro - fuzzy inference system (ANFIS) for estimating the resonant frequency of rectangular ring compact microstrip antennas (RRCMAs) in UHF band is proposed. A total of 108 RRCMAs having different parameters related to the antenna dimensions and dielectric substrate were simulated with the help of electromagnetic packaged software IE3D TM based on method of moment (MoM) to generate the data pool for training and test processes of the ANFIS model. While 96 RRCMAs were employed for training, the remainders were used for test the ANFIS model. The resonant frequencies were computed with the average percentage errors (APE) as 0.014% and 0.666% for training and test, respectively. The accuracy of proposed model was successfully demonstrated by comparing with the results of a method over the simulated data previously published in the literature. Further to inspect the validity of the ANFIS model, a RRCMA operating at 2.44 GHz was designed and fabricated for this work, and the accurate results concerning the resonant frequency were achieved.

ANN surface roughness prediction of AZ91D magnesium alloys in the turning process

Abstract This contribution presents an approach for the modeling and prediction of surface roughness in the turning of AZ91D magnesium alloys using an artificial neural network. The experiments were conducted with CCGT, DCGT and VCGT cutting tools under minimum quantity lubrication and dry machining conditions. AZ91D alloys were machined at different cutting speeds and feed rates, and the depth of cut was kept constant. 15 out of 18 experimental data points were used for the training of the artificial neural network model and the remaining 3 were used for the testing process. The average percentage error was calculated as 0.000815 % and 0.663 % for training and testing, respectively. The model and target results were found to have extremely low error rates.

Design of Butterworth and Chebyshev low-pass filter with heuristic algorithms

Heuristic algorithms which are artificial bee colony (ABC), differential evolution algorithm (DEA) and particle swarm optimization (PSO) algorithms are powerful evolutionary computation techniques for electronic circuit design. In this work, usage of ABC, FGA and PSO algorithms in the design of tenth orders Butterworth, and 1-dB Chebyshev low-pass filters are investigated and the obtained comparative results are presented. PSO algorithm obtained the effective and efficient design parameter results for Butterworth and 1-dB Chebyshev low-pass filters.

Breast cancer detection using inverse radon transform with microwave image technique

Cancer is listed to be the second cause of death after cardiovascular diseases. Meanwhile, breast cancer ranks the first cause of cancer related deaths among women. The possibility of uncontrollable proliferation of cancer cells and propagation to other healthy tissues increase the significance of early diagnosis. In breast cancer imaging, many methods including x-ray mammography, magnetic resonance imaging and ultrasound imaging techniques have been applied. The use of x-rays and applying pressure to the breast region in x-ray mammography; high cost of magnetic resonance imaging and also applying pressure in in ultrasound imaging are the main disadvantages of these methods. Microwave imaging; however, have the has the potential to eliminate the disadvantages of the other methods with various advantageous properties including operating at lower frequencies and lower power when compared to x-ray mammography, the ability to make measurements with low cost, not applying any pressure to the tissue. In this study, a breast tissue containing either one or two tumours, formed in the numerical simulation environment as point scatterers, and the scattered electric field data are processed using two-dimensional inverse synthetic aperture radar (ISAR) method. The images similar to the initially assumed scenarios were obtained by implementing the inverse radon transform to the collected data.