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The aim of this paper is to introduce a novel microinverter design that is based on the DC/DC converter, Buck. This structure is intended to provide a sinusoidal voltage to low-power autonomous loads embedded in vehicles, which require excellent waveform quality. In the first part, the paper presents the new topology, its modeling, and the control strategies employed. Two control strategies are discussed, including the classical control with a PI regulator and the sliding mode control with the step function. The dimensioning is carried out using the Ziegler-Nichols method, and the stability is ensured using the Lyapunov method. In the second part, the paper comments on the results obtained from different simulations in terms of harmonic distortion (THD), efficiency and control robustness with different sources, such as battery and photovoltaic panel. [ABSTRACT FROM AUTHOR]

This paper focuses on the hybridization of two renewable energy sources (i.e., PV Panel and Bi-Cycle Dynamo) and the use of a Multi-Input SEPIC converter for highly efficient output from them. This paper has also presented the comparative assessment between the conventional Single-Input Single Output SEPIC (Single Ended Primary Inductor Converter) and Multi-Input SEPIC converter based on performance analysis. Both the Multi-Input SEPIC that is designed in this literature powered by the hybrid architecture of power sources and the Single-Input SEPIC are run in boost mode. The project is mainly developed with a view to facilitating the isolated rural islands and regions detached from the on-grid connections. The findings and assessments of this study are corroborated by the MATLAB/Simulink simulation results and optimally designed prototype built for miniature applications. The Multi-Input SEPIC topology has been developed in such a way that it is functional with an input voltage of 12.1V exactly and gives an output voltage of DC 53V approximately at the output terminal. To get the maximum voltage at the output from the designed circuit, the duty cycle of the converter recorded is almost 81.49%. The renewable energy sources (RES) that are used to build the prototype are Photovoltaic Panel and Bi-Cycle Dynamo. Due to the limitations of the PV Panels to generate power during the night and gloomy weather, the Bi-Cycle dynamo works as the backup power source. In performing the hardware and software analyses, various intermittent situations, solar irradiation, seasonal change, day-night phase, and other parameters are taken into consideration on the input terminal of the converter. An efficiency of 91.6% is obtained from the proposed hardware field-test analysis. [ABSTRACT FROM AUTHOR]

This paper deals with the problems related to power stability issues in the isolated wind-solar based renewable energy system. The stability issues in such system are produced mainly due to unbalanced loading, distortion of load current and intermittent nature of renewable energy sources. To overcome these problems, A voltage source converter (VSC) is used in proposed literature. The VSC is driven using a time domain-based signal decomposition algorithm consisting a 3-phase dual reduced order generalized integrators frequency Locked loop (DROGI-FLL). The 3 phase DROGI FLL has the inherent abilities of noise rejection and error tracking, which improves the system stability and maintains the voltage and frequency of the system constant under transient conditions. The transient conditions are simulated by varying the loading condition, solar irradiance and wind speed in the system. Apart from stability issues this system also deals with the issues related to reactive composition, natural current compensation and operation of SPV system at maximum power point (MPP). A perturb and observe (P&O) maximum power point tracking (MPPT) is employed for the working of solar photovoltaic systems (SPV) system at MPP and to maximize the utilization of renewable energy. The neutral current compensation is achieved by using a star-double delta transformer. This entire system is developed and tested in the MATLAB/SIMULINK environment.. [ABSTRACT FROM AUTHOR]

In terms of applications and research, VANET (Vehicular Ad-hoc Networks) communication is becoming more popular. Existing VANET communication protocols try to improve network performance but fail to consider security issues. Attackers exploit the vulnerabilities of VANET communication protocols. Providing security to the VANET is still a challenging task because of the vehicles' mobility and their short communication range. Based on our study, we found that wormhole attacks are the most common type of attack on VANET communication. The existing security solutions are inadequate to prevent or detect external wormhole attacks on VANET communication because these solutions do not consider important parameters such as vehicle mobility, neighboring ratio, and node mobility to detect the wormhole attack. To address external wormhole attacks in VANETs, we propose a two-level fast and efficient distance based external wormhole detection and prevention system in this paper. In our proposed solution, we consider the vehicles' mobility, geographical location, and distance parameters to identify and isolate external wormhole attacker nodes. For effective monitoring of wormhole attacks, we use a dynamic threshold value for suspecting external wormhole attack links and then use the hop count metric to detect and prevent it. We used SUMO with NS2 simulators to compare our proposed system with existing works, and our simulations show that our proposed security solution outperforms existing works in terms of throughput, PDR, and jitter in a wormhole attack VANET environment. [ABSTRACT FROM AUTHOR]

In this paper, benzene-core photonic crystal fibers (B-PCFs) with non-uniform air holes for the square lattice are studied by controlling the air-filling factor of the air holes in the first ring and increasing those up to a maximum for external holes. Commercial Mode Solutions software is used to study the influence of structural parameters on the nonlinear coefficient, dispersion, effective mode area, and attenuation. It can be seen that this design affects the linear and nonlinear properties at the same time. In other words, it has a crucial effect on either the near-zero flatness of dispersion or going up the nonlinearity and falling the loss of the B-PCFs. The above benefits make the optimized fibers suitable for supercontinuum (SC) generation applications. [ABSTRACT FROM AUTHOR]

Plant phenotyping is one of the recent research areas that play an essential role to develop a better understanding of plant traits, genotypes, stresses, and other related features. It is regarded as essential concept as it facilitates development in several fields such as botany, agronomy, and genetics. Plant phenotype helps in acquiring relevant information about plant organs and whole features that allows the farmers to make informed plant cropping decisions. It includes the use of Deep Learning (DL) which is part of a machine learning technique that makes use of several processing layers to provide reliable outcomes from abstraction. DL-based approaches are highly useful in providing a sufficient amount of data related to plant strapping, stresses, and growth indices. Deep learning approaches are highly efficient in analysing plant phenotype and characterizing the phenotyping aspects by classifying the plant stress datasets into open, labelled, and broad-spectrum. In this paper, a review work makes an attempt to explore the efficiency of deep learning and filtering approaches in plant phenotyping. The recent works related to the DL principles have been utilized for digital image–based plant stress phenotyping. Then a comparative assessment of DL tools against other existing techniques, with respect to decision accuracy, data size requirement, and applicability in various scenarios. Therefore, it is strongly recommended in the study to use the imaging data process so that there is the attainment of accurate information from training datasets by using high-throughput systems like UAVs and other autonomous systems. [ABSTRACT FROM AUTHOR]

This paper aims to provide a comprehensive examination of the Brain-Computer Interface and the more scientific discoveries that have resulted from it. The ultimate goal of this review is to provide extensive research in BCI systems while also focusing on artifact removal techniques or methods that have recently been used in BCI and important aspects of BCIs. In its pre-processing, artifact removal methodologies were critical. Furthermore, the review emphasizes the applicability, practical challenges, and outcomes associated with BCI advancements. This has the potential to accelerate future progress in this field. This critical evaluation examines the current state of BCI technology as well as recent advancements. It also identifies various BCI technology application areas. This detailed study shows that, while progress is being made, significant challenges remain for user advancement A comparison of EEG artifact removal methods in BCI was done, and their usefulness in real-world EEG-BCI applications was talked about. Some directions and suggestions for future research in this area were also made based on the results of the review and the existing artifact removal methods. [ABSTRACT FROM AUTHOR]

This paper presents the engineering design of an unmanned aerial vehicle (UAV)/drone hexacopter and optimizes the PID (Proportional-Integral-Derivate) values for the Pixhawk 2.4.8 (PX4) flight controller. The design phase begins with component selection and identification, with the goal that the drone can carry loads up to 3 kg. Then install the main components and test the construction results. An analysis of the experimental results of the PID PX4 controller with no load and with load was performed. Results from direct field experiments with a home-built hexacopter show that the default PID must be tuned to be able to lift a load with a specific target. [ABSTRACT FROM AUTHOR]

In this paper, the problem of model-based finite-time bounded event-triggered control for distributed fuzzy T-S systems is presented. For this purpose, the whole network model is embedded locally in both the controller and the remote telemetry unit. In order to estimate the states of the plant between two consecutive events, a fuzzy observer has been used. Model-based state estimation reduces the state error and consequently leads to reduction of data transmission instants. By the network model and event triggering block which are placed locally in each remote telemetry unit, the time of data transmission on the distributed network is determined. Finally, the finite-time boundedness of the closed-loop system has been investigated using MATLAB software for a centralized and a distributed system, respectively. [ABSTRACT FROM AUTHOR]

In order to connect two binary and quaternary systems, it is necessary to use binary-to-quaternary (B2Q) and quaternary-to-binary (Q2B) converters. These converters convert numbers from logic 2 to 4 and vice versa. In this paper, we designed a new binary-to-quaternary converter circuit using CNT transistors. In this circuit, the Power Delay Product (PDP) has been reduced to14.59% and 15.39% compared to best previous works (Ref [22] and Ref [23]). Also, this circuit has better driving ability and temperature stability than best previous works. The simulation results using Stanford's 32 nm CNTFET model in HSPICE software are at a voltage of 0.9 V. [ABSTRACT FROM AUTHOR]

Kingship verification is a process that two or more people has a family relation such as father and son or other family relation. Numerous studies have been presented to investigate the relationship between people. Kingship verification can be done based on image of face. Most of the methods presented on face images work well on face data sets recorded under controlled conditions. However, due to the complex nature of environments, rapidly and accurately examining human kinship in real-world unrestricted or wild-type scenarios is still a challenging research. In this paper, in order to overcome the aforementioned challenges, an efficient and new method is presented. In the proposed method, a method is used to launch the operation to create a map. The created feature map is stable against deformation, transition, scaling, direction and Dilation in wild images. Group-Face and TSK in Face databases are used for simulation. In order to evaluate the evaluation of the proposed method, average recall of 94.1, precision 94.6, accuracy 94.7, specificity 93.8, and finally F_Measure 95.0 were used. The superiority of the proposed method in all comparisons shows the effectiveness of the proposed method in diagnosing kinship. [ABSTRACT FROM AUTHOR]