Dry band formation on the surface of outdoor insulators is one of the main reasons leading to flashover and power outages. In this paper, a dynamic arc model is proposed for single and multiple dry bands configuration to predict the critical flashover voltage for silicone rubber outdoor insulators. An arc is modelled as a time dependent impedance consisting of a Resistor Inductor Capacitor (RLC) circuit. The effect of dry band location and existence of multiple dry bands on critical flashover voltage is investigated. To validate the proposed model, experiments were conducted in a climate chamber under controlled environmental conditions on rectangular silicone rubber sheets polluted using improved solid layer method based on IEC 60,507. Tests were conducted at different dry band configurations and pollution severity levels. A good correlation was found between experimental results and simulation results. This model can provide a good foundation for the development of mathematical models for station post insulators having multiple dry and clean bands and can be used in the design and selection of outdoor insulators for polluted conditions.

With the advent of high-speed and parallel computing, the applicability of computational optimization in engineering problems has increased, with greater validation than conventional methods. Pitch angle is an effective variable in extracting maximum wind power in a wind turbine system (WTS). The pitch angle controller contributes to improve the output power at different wind speeds. In this paper, the pitch angle controller with proportional (P) and proportional-integral (PI) controllers is used. The parameters of the controllers are tuned by computational optimization techniques for a doubly-fed induction generator (DFIG)-based WTS. The study is carried out on a 9 MW DFIG based WTS model in MATLAB/SIMULINK. Two computational optimization techniques: particle swarm optimization (PSO), a swarm intelligence algorithm, and a genetic algorithm (GA), an evolutionary algorithm, are applied. A multi-objective, multi-dimensional error function is defined and minimized by selecting an appropriate error criterion for each objective of the function which depicts the relative magnitude of each objective in the error function. The results of the output power flow and the dynamic response of the optimized P and PI controllers are compared with the conventional P and PI controller in three different cases. It is revealed that the PSO-based controllers performed better in comparison with both the conventional controllers and the GA-based controllers.

Gait recognition is an active research area that uses a walking theme to identify the subject correctly. Human Gait Recognition (HGR) is performed without any cooperation from the individual. However, in practice, it remains a challenging task under diverse walking sequences due to the covariant factors such as normal walking and walking with wearing a coat. Researchers, over the years, have worked on successfully identifying subjects using different techniques, but there is still room for improvement in accuracy due to these covariant factors. This paper proposes an automated model-free framework for human gait recognition in this article. There are a few critical steps in the proposed method. Firstly, optical flow-based motion region estimation and dynamic coordinates-based cropping are performed. The second step involves training a fine-tuned pre-trained MobileNetV2 model on both original and optical flow cropped frames; the training has been conducted using static hyperparameters. The third step proposed a fusion technique known as normal distribution serially fusion. In the fourth step, a better optimization algorithm is applied to select the best features, which are then classified using a Bi-Layered neural network. Three publicly available datasets, CASIA A, CASIA B, and CASIA C, were used in the experimental process and obtained average accuracies of 99.6%, 91.6%, and 95.02%, respectively. The proposed framework has achieved improved accuracy compared to the other methods.

This article presents a new technique for determining accurate values of resonant frequency and quality factor pertaining to the split-ring resonator. Different conducting shield materials have been used around a copper split-ring. The split-ring has been designed to operate at about 2.1 GHz. Various equations were worked out earlier to determine the values of resonant frequency and quality factor. However, these equations yielded different solutions. Therefore, simulations were used to obtain the values of the resonant frequency and quality factor of the split-ring resonator with different five-shield materials, using High-Frequency Structure Simulator (HFSS) software. In this work, a novel method has been introduced for obtaining values of resonant frequency which provides results with negligible error. An optimal technique, namely time-varying particle swarm optimization (TVPSO), was then performed to obtain two sets of equations for resonant frequency and quality factor. The two sets of equations, optimized using TVPSO, were compared for their effectiveness in matching the actual frequency and quality factor for each of the five materials. It was found that the TVPSO was significant in achieving the frequency and quality factor regression equation to accurately resemble the actual values portrayed by the low mean absolute error.

Ultra‐wideband (UWB) antennas play a crucial role in biomedical and microwave imaging applications because they provide accurate imaging and diagnostics with a wide frequency range, high resolution, and reliable signal integrity. This study presents a coplanar waveguide (CPW)‐fed Helm‐shaped printed antenna with UWB characteristics for biomedical and microwave imaging applications. The antenna is compact and has total dimensions of 30 × 25 mm ² and demonstrates an impressive UWB with a fractional bandwidth (FBW) of 122.15%, covering the frequency range from 2.9 to 12 GHz. Additionally, it achieves a peak gain of 4.8 dBi @ 11 GHz and has stable radiation characteristics across the operating bandwidth. The proposed antenna is developed in the form of a prototype, and measured results are obtained using in‐house facilities. It is observed that the measured performance is agreed well with simulations. The time domain analysis of the proposed structure is also conducted, and it is observed that the group delay is <1 ns for both side‐by‐side (SbS) and face‐to‐face configurations. Through the obtained results, it is worth mentioning that the proposed antenna design is suitable for biomedical, microwave imaging, and hyperthermia treatment applications.