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The purpose of this paper is to gain a better understanding on how metasurfaces behave, in terms of currents in each unit cell. A better knowledge of their behavior could lead to an ad-hoc design for specific applications.

The methodology used is both theoretical and numerical; it is based on circuit theory and on an optimization procedure.

The results show that when the knowledge of the current in each unit cell of a metasurface is needed, the most common approximations currently used are often not accurate. Furthermore, a procedure for the termination of a metasurface, with application-driven goals, is given.

This paper investigates the distribution of the currents in a 2D metamaterial realized with magnetically coupled resonant coils. Different models for the analysis of these structures are illustrated, and the effects of the approximations they introduce on the current values are shown and discussed. Furthermore, proper terminations of the resonators on the boundaries have been investigated by implementing a numerical optimization procedure with the purpose of achieving a uniform distribution of the resonator currents. The results show that the behavior of a metasurface (in terms of currents in each single resonator) depends on different properties; as a consequence, their design is not a trivial task and is dependent on the specific applications they are designed for. A design strategy, with lumped impedance termination, is here proposed.

This paper aims to investigate the corrosion resistance of two types of coatings – one is ceria sol coating and the other is ceria sol coating modified by ZnO nanoparticles on 7075 aluminum alloy in 3.5% NaCl solution.

Aluminum alloys were dipped into ceria sol and ceria sol modified by ZnO nanoparticles separately and removed after 10 min from the solutions and dried at 110°C for 30 min and heated at 500 °C for 30 min to form the coatings. The coatings have been characterized by using field emission scanning electron microscopy (FE-SEM), electrochemical impedance spectroscopy (EIS), X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS). The EIS tests were performed in a corrosive solution of 3.5% NaCl.

The results showed that the coating of ceria sol modified by ZnO nanoparticles has higher corrosion resistance than the ceria sol coating and the bare sample. Also, the best efficiency is related to aluminum sample immersion after 1 h in NaCl corrosive solution for coating modified by ZnO nanoparticles.

In this research, the modification of ceria sol coating by ZnO nanoparticles had an effect on improving the corrosion behavior of aluminum alloy. It is also understood that modification of coatings is an effective parameter on corrosion resistance.

Static inverters are very important for the emergency energy distribution system of aircraft and similar machines. At the same time, the electrical energy produced at high frequency for electrical devices is used to reduce the weight of the cables in the aircraft and spacecraft because of the skin effect. In the high-frequency system, a thinner cable cross-section is used, and a great weight reduction occurs in the aircraft. So, fuel economy, less and late wear of the materials (landing gear, etc.) can be obtained with decreasing weight. This paper aims to present the development of a functional multilevel inverter (FMLI) with fractional sinus pulse width modulation (FSPWM) and a reduced number of switches to provide high-frequency and quality electrical energy conversion.

After the production of FSPWM for FMLI with a reduced component, which, to the best of the authors’ knowledge, is presented for the first time in this study, is explained step by step, and eight operating states are given according to different FSPWMs operating the circuit. The designed inverter and modulation technique are compared by testing the conventional modular multilevel inverter on different loads.

According to application results, it is seen that there is a 50% reduction in cross-section from 100 Hz to 400 Hz with the skin effect. At 1000 Hz, there is a 90% cross-section reduction. The decrease can be in cable weights that may occur in aircraft from 10 kg to 100 kg according to different frequencies. It causes less harmonic distortion than conventional converters. This supports the safer operation of the system. Compared to the traditional system, the proposed system provides more amplitude in converting the source to alternating voltage and increases the efficiency.

FSPWM is developed for multilevel inverters with reduced components at the high frequency and cascaded switching studies in the power electronics of aircraft.

Although the proposed system has less current and power loss as mentioned in the previous sections, it contains fewer power elements than conventional inverters that are equivalent for different hardware levels. This not only reduces the cost of the system but also provides ease of maintenance. To reduce the cable load in aircraft and create more efficient working conditions, 400 Hz alternative voltage is used. The proposed system causes less losses and lower harmonic distortions than traditional systems. This will reduce possible malfunctions and contribute to aircraft reliability for passengers and cargo. As technology develops, it is revealed that the proposed inverter system will be more efficient than traditional inverters when devices operating at frequencies higher than 400 Hz are used. With the proposed inverter, safer operation will be ensured, while there will be less energy loss, less fuel consumption and less carbon emissions to the environment.

The proposed inverter structure shows that it can provide energy transmission for electrical devices in space and aircraft by using the skin effect. It also contains less power elements than the traditional inverters, which are equivalent for different levels of hardware.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

This paper aims to explore the influence of corrosion-deformation interactions (CDI) on the corrosion behavior and mechanisms of 316LN under applied tensile stresses.

Corrosion of metals would be aggravated by CDI under applied stress. Notably, the presence of nitrogen in 316LN austenitic stainless steel (SS) would enhance the corrosion resistance compared to the nitrogen-absent 316L SS. To clarify the CDI behaviors, electrochemical corrosion experiments were performed on 316LN specimens under different applied stress levels. Complementary analyses, including three-dimensional morphological examinations by KH-7700 digital microscope and scanning electron microscopy coupled with energy dispersive spectroscopy, were conducted to investigate the macroscopic and microscopic corrosion morphology and to characterize the composition of corrosion products within pits. Furthermore, ion chromatography was used to analyze the solution composition variations after immersion corrosion tests of 316LN in a 6 wt.% FeCl₃ solution compared to original FeCl₃ solution. Electrochemical experiment results revealed the linear decrease in free corrosion potential with increasing applied stress. Electrochemical impedance spectroscopy results indicated that high tensile stress level damaged the integrity of passivation film, as evidenced by the remarkable reduction in electrochemical impedance. Ion chromatography analyses proved the concentrations increase of NO₃⁻ and NH₄⁺ ion concentrations in the corrosion media after corrosion tests.

The enhanced corrosion resistance of 316LN SS is attributable to the presence of nitrogen.

The scope of this study is confined to the influence of tensile stress on the electrochemical corrosion of 316LN at ambient temperatures; it does not encompass the potential effects of elevated temperatures or compressive stress.

The resistance to stress electrochemical corrosion in SS may be enhanced through nitrogen alloying.

This paper presents a systematic investigation into the stress electrochemical corrosion of 316LN, marking the inaugural study of its impact on corrosion behaviors and underlying mechanisms.

This case requires students to evaluate alternative dual-share-class corporate structures that allow companies and entrepreneurs to pursue profit with purpose. The case explores Impact Makers, an IT consulting company based in Richmond, Virginia. While original founders of the firm hold all voting rights, the cash flow rights belong to two nonprofits setting the stage for a Newman's Own model of management consulting. The case discusses whether and how the alternative corporate structure aids the firm's overall strategy to attract top-quality employees, pay them competitive salaries, and provide superior service to its clients while donating 100% of its lifetime value to charitable causes, largely through partnerships with various nonprofit organizations. More importantly, the case asks students to evaluate how such a dual-share-class and dual-purpose company can raise capital to fund continued growth.

The case opens with CEO Michael Pirron reminding himself of all the questions he had run through to execute a strategy to further grow Impact Makers' consulting business both through expanding a menu of services and through conquering new geographical markets. To do either, or both, the company needed a cash infusion. Internal cash was limited, as up to 40% of it flowed to charitable partners, demonstrating Impact Makers' commitment to its mission. Raising debt for a company without fixed assets was challenging and time consuming. Complicating it all was that being structured as a nonstock corporation rendered equity raising difficult. Could Impact Makers raise money to grow and stay true to community values at the same time?

The rapid development of urban areas in Sleman District, Indonesia, has created new challenges for firefighting response services. One of the primary challenges is to identify the optimal locations for new fire stations, to improve service quality and maximize service coverage within the specified time.

This paper proposes a method for precisely calculating travel time that integrates delay time caused by traffic lights, intersections and congestion. The study highlights the importance of precise calculation of travel time in order to provide a more accurate understanding of the service area covered by the fire stations. The proposed method utilizes network analysis in ArcGIS, the analytical hierarchy process (AHP) and simple additive weighting (SAW) to accurately calculate travel time and to identify the best locations for new fire stations. The identification of new site was based on service safety, service quality, service costs and demographic factors and applied to the Sleman district in Indonesia.

The results showed that the total area covered by old and new fire stations decreased from 61% to 31.8% of the study area when the adjusted default speed scenario was implemented.

The results indicated that the default speed scenario could provide misleading information about the service area, while the adjusted default speed scenario improved service quality and maximized service coverage.

The proposed method provides decision-makers with an effective tool to make informed decisions on optimal locations for new fire stations and thus enhance emergency response and public safety.

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.