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This work proposes the charge optimization strategy for the electric vehicle is in order to utilize the maximum charger available in renewable energy resource and to minimize the utilization of charge available in charger grids. Also while driving the electric vehicle, the decision making algorithm will continuously checks the limit of charger generated by the alternator and the solar cell incorporated in the E-Vehicle and switches over the battery charging to the maximum charger available resource. [ABSTRACT FROM AUTHOR]

Wind energy conversions are growing rapidly as a renewable energy source. A new method of interconnected wind power production that utilizes a doubly fed induction generator coupled to a quality Analyst matrix converter is described in this study. The aims of this project include Doubly-fed induction generator modeling and simulation The rotor current is controlled via a space vector modulated matrix converter. This strategy is aimed directly at the converter-based rotor current regulation. The system enhances the ideal speed tracking for wind energy collection to maximize energy extraction, while also implementing power-control strategies that apply to the RST regulator. The findings obtained for different operating points are evaluated, and they indicate the excellent control capabilities of the system. [ABSTRACT FROM AUTHOR]

The popular Z-source DC connection was extended by the Z-Source network, which was first designed to enhance the power output of power semiconductor inverters. The following research article covers how the aforementioned concept is taken further, using 3 indirect matrix converters. This is done via an ultra-sparse matrix architecture that is characterised by a low number of semiconductor switches. The Z-source network is positioned on the positive or negative rail between both the three-switch input rectifier stage and the six-switch output inverter stage. A short on-and-off condition causes the voltage to increase. Higher boosting capacity of the converter with minimal switching losses is achieved by using an ideal pulse width modulation strategy. A comparison was made between matrix converters that use Z-source networks (Z may be an unbalanced or balanced one), one of which uses a series network and the other a typical cascade network. The series Z-source matrix converter's capabilities include reductions in inrush current and the Z-source capacitor's voltage. The same conclusion is further supported by the rapid Fourier transformation study of the output current, which indicates that perhaps the series Z-source converter is better than the cascaded one. [ABSTRACT FROM AUTHOR]

This paper focuses on the design of semi-autonomous agricultural mobile robot. It is able to perform efficient ploughing and spraying water or fertilizer function. The uttermost tedious tasks to perform in the indoor agriculture field are ploughing operation and also spraying water or fertilizing above on crops. Ploughing is the first step in farming. By ploughing it means a plough tool will be utilized which will have spikes like structure at the end and it will be able to turn the upper layer of soil down. Another crucial feature of this semi-autonomous agricultural mobile robot is storing-bin, which is used to store water or fertilizer while on spraying above crops. This semi-autonomous agricultural mobile robot is utilized to monitor and control through a developed app with IOT included. Due to this user was able to easily navigate this agricultural mobile robot and also monitor data like water or fertilizer range. [ABSTRACT FROM AUTHOR]

This paper presents a new machine vision based technique for self-navigation of agricultural mobile robots in the agriculture field. The proposed method for staunch detection of incessant crop rows based on mask region based enhanced self-navigation technique. It utilizes a camera module to self-navigate this mobile robot in a structured agricultural field by following incessant crop rows. First, a camera was fixed in the proper location of the mobile robot to obtain optimized navigation orientation. Second, enhanced image processing techniques were utilized to acquire optimized navigation base lines. Finally, an optimized navigation base line was extracted from the mask region based enhanced self-navigation technique. This self-navigation technique was utilized to perform operations like spraying water, fertilizing, weeding etc. The proposed technique requires 160ms to detect the masked area of crop rows. Experimented results shows, this technique can instantly and preciously find the incessant crop rows even under various light conditions. [ABSTRACT FROM AUTHOR]

Coronavirus, Corona Virus Disease-2019, brought about by an original Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2). A compelling screening of this infection can empower speedy and proficient finding of COVID-19 can diminish the weight on the medical care framework. A nitty gritty examination gave dataset can assemble unique and different kinds of AI calculations, which their exhibition could be processed and further assessed. This paper proposed a mixture information mining method that coordinated Random Forest with SVM (Support Vector Machines). The accompanying case proposed model is to beat the wide range of various Machine Learning models like SVM, Decision Tree, KNN and Logistic Regression. [ABSTRACT FROM AUTHOR]

Medical services are the quickest developing space that expects to give the fitting therapy to postpone the sickness movement. Medical services space comprises of the most significant subdomain called sickness forecast which needs an effective procedure to anticipate the infection in beginning phases. Information digging gives proficient procedures to early infection forecast. This work utilizes Hybrid characterization procedures which incorporates Support Vector Machines (SVM) and K-Nearest Neighbor (KNN) to assemble the danger forecast model for early expectation of diabetes. This danger model predicts the chance of the patient influenced by diabetes after the age of 40. The dataset comprises of set of retinal pictures of high nearsightedness and Central Serous Retinopathy of PCOS, pancreatitis and way of life issue. This work likewise clarifies the relationship of illnesses like PCOS and pancreatic malignant growth with diabetes. Characterization strategies like Adaboost, Gradient boosting, Decision tree, Navies Bayes, Logistic relapse and neural organization are contrasted with discover a calculation with high exactness. [ABSTRACT FROM AUTHOR]

The field which encompasses predictive data analysis known as machine learning is quickly developing. Agricultural outcomes have been improved due to its suitability in automation, weather prediction, and share market applications. This article covers the latest on using machine learning to various fields in agriculture. The broad variety of machine learning methods applicable for said predictive modeling within important agricultural It is a great difficulty to be living in a densely populated nation, since one must meet the requirements of everyone. Agriculture ranks ahead of almost everything else when it comes to moving our nation forward. Machine learning makes the system adaptive to various environmental conditions by reducing human involvement. This article talks about the many algorithms for choosing the best for the application. [ABSTRACT FROM AUTHOR]

Bicycles have always been a wonderful transport that is used all over the world. In this automatic world, bicycles can also be automated by designing controllers. Bicycles are highly non-linear; the controller design can be found very difficult. The smart controllers such as Firefly Algorithm (FFA), Bacterial Foraging Optimization (BFO) algorithm, and Ant Colony Optimization (ACO) algorithm are used to design PID controllers and comparable to each other to achieve the best results for a bicycle. The error values are compared by the ANOVA test and the ACO PID results are better. [ABSTRACT FROM AUTHOR]

Each optimal idea for distributing mini-rides as well as confined loads in remote regions is modern hybrid electrical technologies combining traditional but sustainable energy conversion systems, characterized by complex interlocking systems but instead increased control dependency for optimized use of resources available, particularly PV cells and wind energy. Providing reliable, cheap energy is an important problem for industrial growth and the associated rise in living standards. Renewable energy sources chosen properly will substantially reduce consumption for fossil fuel, thus improving energy supply sustainability. Under harsh environmental conditions, conventional sources assist renewable sources, which improve the reliability and stability of electricity systems. Combined with environmental and ecological limitations, increasing demand for energy confronts system designers with numerous problems. With the liberalization of energy utilities, sure those customers tend to be viewed as electricity transmission routes from wherever accessible to places, depending on the price that varies with daytime. This research suggests a stand-alone hybrid system. Solar system (SPS) management MPPT is achieved by perturbation and observation methodology and the TSR control method was used to develop WECS MPPT control and field-oriented MSC system control mechanism, which enables the WECS to extract optimum power. A stand-alone rechargeable battery wind-solar system was investigated, Simulation for modelling & analytical models. [ABSTRACT FROM AUTHOR]

In recent decades, the bioinformatics, biology and biotechnology plays a major role in accumulation of numerous biomedical data, which offers an in-depth analysis. On other hand, with the advent of data mining research leads to the development of scalable and efficient models for mining some interesting data pattern in case of small or large databases. It is hence essential to bridge bioinformatics with data mining models for successful implementation of finding the meaning pattern in case of biological data. In this paper, we present a comprehensive survey on various data mining models that helps in analyzing the chemical bonding and its structured index in case of sequential pattern mining. [ABSTRACT FROM AUTHOR]