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The suggested antenna has a switched mechanism among the successive elements of the radiating patch. The purpose of this paper is to develop high gain and less interference at higher frequencies.

The design geometry of the suggested high gain switched beam Yagi-Uda antennas. The constructed antenna has been developed with Rogers Substrate, relative permittivity (ε_r) of 4.4, tangent of loss 0.0009 and with height of 1.6 mm. The proposed antenna has an input impedance of 50, and it is connected to input feed line with 2 mm.

In forthcoming life, the antennas play key role in all the wireless devices, because these devices perform with high gain and high efficacy.

The pivotal principle of this paper is to accomplish the gain as high, high directivity and interference is low at higher frequencies. Therefore, it is more applicable to 5G mobile communications and millimeter wave communications.

The purpose of this paper is to describe a modified Hilbert‐based fractal antenna for ultra wideband (UWB) wireless applications. Simulation results show excellent multi‐band characteristics for UWB wireless applications.

A Hilbert curve‐based fractal is optimised for self‐replicating, space‐filling and self‐avoiding properties. In the proposed design, the Hilbert curve is applied to a rectangle as an initial iteration and maintained for the later iterations. Additionally, a Yagi‐like strip is removed from the second iteration of the Hilbert patch and a hexagonal portion is removed from the substrate to achieve good optimization. The antenna feed is created through a micro‐strip line with a feeding section. Finally, a partial ground plane technique is used for improved impedance matching characteristics. A finite element method (FEM) is used to simulate the modified Hilbert model with commercially available Ansoft HFSS software.

The proposed antenna is miniaturized (39 mm length×30 mm width) and has multi‐band characteristics. The simulation results show that the antenna has a reflection coefficient characteristic of <−10 dB, a linear phase reflection coefficient, better than 65 percent radiation efficiency, 2.2‐4 dBi antenna gain and nearly omni‐directional radiation pattern properties over the UWB bandwidth (3.1‐10.6 GHz).

The antenna shows promising characteristics for the full 7.5 GHz UWB bandwidth. In addition, the performance is achieved by using laceration techniques on the Hilbert patch and substrate, respectively. A partial ground plane ensures impedance matching of 50 over full UWB bandwidth. The simulation analysis of the modified Hilbert fractal antenna design constitutes the main contribution of the paper.

The purpose of this paper is to propose an algorithm that combines the particle swarm optimization (PSO) with the biogeography-based optimization (BBO) algorithm.

The BBO and the PSO algorithms are jointly used in to order to combine the advantages of both algorithms. The efficiency of the proposed algorithm is tested using some selected standard benchmark functions. The performance of the proposed algorithm is compared with that of the differential evolutionary (DE), genetic algorithm (GA), PSO, BBO, blended BBO and hybrid BBO-DE algorithms.

Experimental results indicate that the proposed algorithm outperforms the BBO, PSO, DE, GA, and the blended BBO algorithms and has comparable performance to that of the hybrid BBO-DE algorithm. However, the proposed algorithm is simpler than the BBO-DE algorithm since the PSO does not have complex operations such as mutation and crossover used in the DE algorithm.

The proposed algorithm is a generic algorithm that can be used to efficiently solve optimization problems similar to that solved using other popular evolutionary algorithms but with better performance.

This paper aims to present the design development and measurement of two aerodynamic slotted X-bands back-to-back planer substrate-integrated rectangular waveguide (SIRWG/SIW) to Microstrip (MS) line transition for satellite and RADAR applications. It facilitates the realization of nonplanar (waveguide-based) circuits into planar form for easy integration with other planar (microstrip) devices, circuits and systems. This paper describes the design of a SIW to microstrip transition. The transition is broadband covering the frequency range of 8–12 GHz. The design and interconnection of microwave components like filters, power dividers, resonators, satellite dishes, sensors, transmitters and transponders are further aided by these transitions. A common planar interconnect is designed with better reflection coefficient/return loss (RL) (S₁₁/S₂₂ ≤ 10 dB), transmission coefficient/insertion loss (IL) (S₁₂/S₂₁: 0–3.0 dB) and ultra-wideband bandwidth on low profile FR-4 substrate for X-band and Ku-band functioning to interconnect modern era MIC/MMIC circuits, components and devices.

Two series of metal via (6 via/row) have been used so that all surface current and electric field vectors are confined within the metallic via-wall in SIW length. Introduced aerodynamic slots in tapered portions achieve excellent impedance matching and tapered junctions with SIW are mitered for fine tuning to achieve minimum reflections and improved transmissions at X-band center frequency.

Using this method, the measured IL and RLs are found in concord with simulated results in full X-band (8.22–12.4 GHz). RLC T-equivalent and p-equivalent electrical circuits of the proposed design are presented at the end.

The measurement of the prototype has been carried out by an available low-cost X-band microwave bench and with a Keysight E4416A power meter in the microwave laboratory.

The transition is fabricated on FR-4 substrate with compact size 14 mm × 21.35 mm × 1.6 mm and hence economical with IL lie within limits 0.6–1 dB and RL is lower than −10 dB in bandwidth 7.05–17.10 GHz. Because of such outstanding fractional bandwidth (FBW: 100.5%), the transition could also be useful for Ku-band with IL close to 1.6 dB.

The purpose of this paper is to investigate the strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup.

Formulation of the multi-objective design problem-oriented toward execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploits variable fidelity modeling, physics- and approximation-based representation of the structure and model correction techniques. The considered approach is suitable for handling various problems pertinent to the design of microwave and antenna structures. Numerical case studies are provided demonstrating the feasibility of the segmentation-based framework for the design of real-world structures in setups with two and three objectives.

Formulation of appropriate design problem enables identification of the search space region containing Pareto front, which can be further divided into a set of compartments characterized by small combined volume. Approximation model of each segment can be constructed using a small number of training samples and then optimized, at a negligible computational cost, using population-based metaheuristics. Introduction of segmentation mechanism to multi-objective design framework is important to facilitate low-cost optimization of many-parameter structures represented by numerically expensive computational models. Further reduction of the design cost can be achieved by enforcing equal-volumes of the search space segments.

The study summarizes recent advances in low-cost multi-objective design of microwave and antenna structures. The investigated techniques exceed capabilities of conventional design approaches involving direct evaluation of physics-based models for determination of trade-offs between the design objectives, particularly in terms of reliability and reduction of the computational cost. Studies on the scalability of segmentation mechanism indicate that computational benefits of the approach decrease with the number of search space segments.

The proposed design framework proved useful for the rapid multi-objective design of microwave and antenna structures characterized by complex and multi-parameter topologies, which is extremely challenging when using conventional methods driven by population-based metaheuristics algorithms. To the authors knowledge, this is the first work that summarizes segmentation-based approaches to multi-objective optimization of microwave and antenna components.

The purpose of this paper is to present a modified version of the non-dominated sorted genetic algorithm with an application in the design optimization of a power inductor for magneto-fluid hyperthermia (MFH).

The proposed evolutionary algorithm is a modified version of migration-non-dominated sorting genetic algorithms (M-NSGA) that now includes the self-adaption of migration events- non-dominated sorting genetic algorithms (SA-M-NSGA). Moreover, a criterion based on the evolution of the approximated Pareto front has been activated for the automatic stop of the computation. Numerical experiments have been based on both an analytical benchmark and a real-life case study; the latter, which deals with the design of a class of power inductors for tests of MFH, is characterized by finite element analysis of the magnetic field.

The SA-M-NSGA substantially varies the genetic heritage of the population during the optimization process and allows for a faster convergence.

The proposed SA-M-NSGA is able to find a wider Pareto front with a computational effort comparable to a standard NSGA-II implementation.

By investigating the thermal-mechanical interaction between the through silicon via (TSV) and the Cu pad, this study aimed to determine the effect of electroplating defects on the upper surface protrusion and internal stress distribution of the TSV at various temperatures and to provide guidelines for the positioning of TSVs and the optimization of the electroplating process.

A simplified model that consisted of a TSV (100 µm in diameter and 300 µm in height), a covering Cu pad (2 µm thick) and an internal drop-like electroplating defect (which had various dimensions and locations) was developed. The surface overall deformation and stress distribution of these models under various thermal conditions were analyzed and compared.

The Cu pad could barely suppress the upper surface protrusion of the TSV if the temperature was below 250 ?. Interfacial delamination started at the collar of the TSV at about 250 ? and became increasingly pronounced at higher temperatures. The electroplating defect constantly experienced the highest level of strain and stress during the temperature increase, despite its geometry or location. But as its radius expanded or its distance to the upper surface increased, the overall deformation of the upper surface and the stress concentration at the collar of the TSV showed a downward trend.

Previous studies have not examined the influence of the electroplating void on the thermal behavior of the TSV. However, with the proposed methodology, the strain and stress distribution of the TSV under different conditions in terms of temperature, dimension and location of the electroplating void were thoroughly investigated, which might be beneficial to the positioning of TSVs and the optimization of the electroplating process.

In this work, the multi-objective optimization shuffled complex evolution is proposed. The algorithm is based on the extension of shuffled complex evolution, by incorporating two classical operators into the original algorithm: the rank ordering and crowding distance. In order to accelerate the convergence process, a Local Search strategy based on the generation of potential candidates by using Latin Hypercube method is also proposed.

The multi-objective optimization shuffled complex evolution is used to accelerate the convergence process and to reduce the number of objective function evaluations.

In general, the proposed methodology was able to solve a classical mechanical engineering problem with different characteristics. From a statistical point of view, we demonstrated that differences may exist between the proposed methodology and other evolutionary strategies concerning two different metrics (convergence and diversity), for a class of benchmark functions (ZDT functions).

The development of a new numerical method to solve multi-objective optimization problems is the major contribution.

The purpose of this paper is to validate methodologies for expedited multi-objective design optimization of complex antenna structures both numerically and experimentally.

The task of identifying the best possible trade-offs between the antenna size and its electrical performance is formulated as multi-objective optimization problem. Algorithmic frameworks are described for finding Pareto-optimal designs using auxiliary surrogate models and two alternative approaches to design refinement: response correction techniques and co-kriging. Numerical and experimental case studies are provided to demonstrate feasibility of solving real-world and complex antenna design tasks.

It is possible, through appropriate combination of the surrogate modeling techniques (both data driven and physics based) and response correction methods, to find the set of alternative designs representing the best possible trade-offs between conflicting design objectives, here, electrical performance and size. Design optimization can be performed at practically feasible computational costs.

The study demonstrates feasibility of automated multi-objective design optimization of antennas at low computational cost. The presented techniques reach beyond the commonly used design approaches based on parameter sweeps and similar hands-on methods, particularly in terms of automation, reliability and reduction of the computational costs of the design processes.

Multi-objective design of antenna structures is very challenging when high-fidelity electromagnetic simulations are utilized for performance evaluation of the structure at hand. The proposed design framework permits rapid optimization of complex structures (here, MIMO antenna), which is hardly possible using conventional methods.