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For high-power, high-voltage applications, multilevel inverters have gained widespread acceptance. Due to its rising advantages. In this paper a new circuit multilevel inverter, comparatively speaking to traditional inverters, this design requires less components as well as fewer gate drives and carrier signals. Because of this, both the total expense and complexity are drastically decreased, especially for higher output voltage levels. This circuit consists by two components one is level generation part contain by four switches and other one is polarity generation part comprise by H-bridge inverter that make up output voltage as a seven level. The portion that generates levels employs high frequency switches to produce various levels, and the part that generates the polarity of the output voltage is at line frequency. Additionally, it is more effective due to an inverter component that uses line frequency to operate switching power devices. As a result, there is no requirement for all switches to operate at high frequency, resulting in easier and more dependable management of the inverter. Here multicarrier Phase Disposition Sinusoidal Pulse Width Modulation (PDSPWM) technique regulates the operation of the inverter.It consists by three carrier signals instead of six carrier signal and it provide less THD of output voltage and current compare to other multicarrier sinusoidal pulse width modulation techniques. The design, analysis and control of the seven level inverter is demonstrated with the help of MATLAB/Simulink tool.

Based on economic, controllability and total harmonic distortion (THD) Multilevel inverters are more rising devices in many applications compare to other traditional inverters. Hence here a novel multilevel inverter (MLI) is designed and analysed with less count of switches and diodes. Generally (L-1) switches are required for conventional L level inverters like flying capacitor, diode clamped, and cascaded multilevel inverters but here a H-bridge inverter with additional two legs having less no of switches is introduced. The converter’s controllability plays a crucial role in enhancing the THD of the output voltage and efficiency. Here a level shifted sinusoidal pulse width modulation technique is implemented i.e Phase Opposition Disposition SPWM (PODSPWM) method, because of it gives better THD over other level shifted SPWM techniques like PDSPWM, APODSPWM,COSPWM,VFSPWM and Phase shift SPWM techniques. The Design and analysis of thisseven level inverter is evaluated with the tool of MATLAB/SIMULINK.

This paper presents a method for measuring a wind turbine's MPP (Maximum Power Point) with a three-bladed VSWT that is driven by a DFIG (Double-Fed Induction Generator) (Variable Speed Wind Turbine). The rotor incorporates a DFIG with successive PWM voltage-source converters within its integrated rotor integrated circuit. Grid-side converters generate and establish sinusoidal currents while independently managing the active and reactive power drawn from the grid supply using vector control techniques. The rotor-side converter needs to be vector controlled in order for the speed range to function. The vector approach manages the permit circuit optimally to maximize the amount of wind energy gathered. The control needs of the permit circuit take this into account. Such a system is analyzed using MATLAB software

In the current work, the morphological and mechanical features of a hybrid epoxy matrix composite created by hand layup and reinforced with fibers from rice husk, sisal, and kenaf are predicted by using Watershed segmentation algorithm. To forecast the effect of coating composition on physical performance of a composite, Tensile and hardness tests were used to define the resulting hybrid composites' mechanical characteristics. The objective of the empirical investigation presented in this work is to understand the mechanical behavior of hybrid natural fiber composites. The production of rose husk-sisal-kenaf-epoxy hybrid samples is done by hand layup, with the planned plies being alternately stacked and the weight of the matrix and fibers being kept between 40% and 60%. Samples are sliced from a laminate that has been manufactured in accordance with ASTM specifications in order to undertake various experiments. Dog bone and flat bar shapes were used to cut specimens for tensile test & flexural test. Tensile strength and flexural strength were measured following execution of experiment under UTM and contrasted with base values of used epoxy polymer to identify constant change in strength.

It became a bottleneck for the Machine Learning (ML) researchers to select/develop a sustainable model for a particular problem. Hence, there is a need for an approach to prepare a model with all constraints of the software system. The proposed approach is based on Object Constraint Language (OCL) which is a declarative language for writing constraints on software artifacts, it is widely used for effective representation of Functional Requirements (FR’s) and Non-Functional Requirements (NFR’s). In the proposed system, the paddy leaf disease identification system is considered and proposed Leaf Identification Constraints (LIC) and Leaf Disease Identification Constraints (LDIC) based on OCL, for the proposed constraints the Convolutional Neural Network (CNN) is chosen, as it can handle diverse range of input data and large volume of concurrent requests. To satisfy other constraints of the system, the Auto encoders are used along with CNN and the input data was take in the form of thermal imaging. This system was evaluated with test data and validation data and obtained the accuracy of 90.6%. And 84.8 was attained by earlier researchers before this approach.

Nowadays, industry 4.0 plays a tremendous role in the manufacturing industries for increasing the amount of data and accuracy in modern manufacturing systems. Thanks to artificial intelligence, particularly machine learning, big data analytics have dramatically amended, and manufacturers easily exploit organized and unorganized data. This study utilized hybrid optimization algorithms to find friction stir welding and optimal hardness value at the nugget zone. A similar AA 6262 material was used and welded in a butt joint configuration. Tool rotational speed (RPM), tool traverse speed (mm/min), and the plane depth (mm) are used as controllable parameters and optimized using Taguchi L9, Random Forest, and XG Boost machine learning tools. Analysis of variance was also conducted at a 95% confidence interval for identifying the significant parameters. The result indicated that the coefficient of determination from Taguchi L9 orthogonal array is 0.91 obtained while Random Forest and XG Boost algorithm imparted 0.62 and 0.65 respectively. Keywords: Friction Stir Welding; Taguchi; Machine Learning; Hardness; Nugget Zone and Random Forest.

Internet of Things (IoT) innovation is one of the fastest growing fields in various regions or aspects which include irrigation. IoT works on the character of our lives by way of bringing and cultivating modifications in many fields of exercises to motive them to come to be convenient, savvy and enriched with the aid of adequate guy-made recognition. As a result of this innovation, smart cultivating frameworks recognize a social trade towards current agri-business that is more useful, consumes less water, and is extraordinarily less luxurious. The primary goal of this paper is to make use of IoT within the agribusiness subject to accumulate facts right away (soil Moister, temperature), with a purpose to help one with staring at a few climate situations distantly, effectively and improve massively the creation and thus the pay of ranchers. The modern version is created utilizing NodeMCU innovation, which contains express sensors, and a Wifi module that assists with amassing moment records on the internet. It is worth concentrating on the testing of this model created, profoundly precise data in light of the fact that any herbal changes were outstanding in a flash and taking into consideration to decide. This paper speculating about integrating the IoT with different other technologies.

In this paper we introduce and study a new subclass of meromorphically uniformly convex functions with positive coefficients defined by a differential operator and obtain coefficient estimates, growth and distortion theorem, radius of convexity, integral transforms, convex linear combinations, convolution properties and δ-neighborhoods for the class σ p (α).

Biosorption of lead onto Fallen Coffee Plant leaves (FCPL) powder from an aqueous solution was studied in the present study. The characterization of FCPL powder was done by FTIR, XRD, SEM and BET. The equilibrium agitation time for lead biosorption is 60 min. The optimum pH and dosage values are 5.2 and 20 g/L respectively. In the range of variables studied, percentage biosorption is increased from 75.1 to 95.5 %. The maximum uptake capacity of 3.664 mg/g is obtained at 303 K. In the present investigation the equilibrium data was well explained by Langmuir, Redlich-Peterson with a correlation coefficient of 0.99, and followed by Temkin and Freundlich isotherms. The kinetic studies reveal that the biosorption system obeyed the pseudo second order kinetic model by considering the correlation coefficient value as 0.99. From the values of ∆S, ∆H and ∆G it is observed that the biosorption of lead onto Fallen coffee plant leaves(FCPL) powder was irreversible, endothermic and spontaneous.