https://ojs.trp.org.in/index.php/ajes/issue/feed Asian Journal of Electrical Sciences 2021-09-11T15:25:27+0530 Dr.K.S.Shivraj info@trp.org.in Open Journal Systems <p>Asian Journal of Electrical Sciences is a half-yearly, peer-reviewed scholarly journal in the field of electrical engineering and electronics that aims to publish the most complete and reliable source of information on the discoveries and current developments in the mode of research articles, review articles, case reports, short communications, etc.</p> https://ojs.trp.org.in/index.php/ajes/article/view/2794 Performance Analysis of a High Gain LUO Converter-Based Hybrid PV-Wind System 2021-07-15T11:21:51+0530 N. Amutha Priya a.amazing13@gmail.com M. Aswin a.amazing13@gmail.com S. J. Azis Shane a.amazing13@gmail.com Y. Blessing Dino a.amazing13@gmail.com D. Dagul a.amazing13@gmail.com <p>This project is aimed at the implementation of a fuzzy logic algorithm based maximum power point tracking in transformer less grid connected PV system along with reactive power compensation. A single diode model is used for PV array and its simulation is performed using MATLAB. In fuzzy logic controller, voltage and current are taken as inputs and the effective value of A.C current corresponding to the maximum power point is obtained as output. Thus, in addition to supplying voltage by the inverter without transformer for compensating the reactive power not exceeding its power rating. This results in utilization of PV system at night and at periods of low irradiation. Rules relating the input and output of fuzzy logic controller are written and simulation is performed. A LUO Converter is used for maintaining DC input to the inverter at various conditions of irradiation and temperature. Gating pulses to the inverter are generated by proportional-integral controller. Hardware model of a10W solar panel is developed and results are obtained with fuzzy logic controller for different irradiation and temperature conditions. Results show the effectiveness of the proposed method in utilizing the PV system. This project is implemented using DSPIC30F2010 controller.</p> 2021-05-15T00:00:00+0530 Copyright (c) 2021 https://ojs.trp.org.in/index.php/ajes/article/view/2833 Utilization of Chabot in an Educational System 2021-09-11T14:58:40+0530 Beenu santoshdgc@gmail.com Harsh Jindal santoshdgc@gmail.com Rakesh Kumar santoshdgc@gmail.com Meghul Kumar Kushawaha santoshdgc@gmail.com Santosh Kumar santoshdgc@gmail.com <p>Chabot are recently being utilized in a variety of online applications such as education, marketing, supporting systems, cultural heritage and industry from e-commerce to travel. It provides several benefits, such as availability, personalization, etc. Chabot is appeared in very large numbers at the start of the present decade. In a present day, the usage of Chabot is increasing day by day in large scale of the application that is providing better intelligence to the user. In fact, to speed up the assistance these systems are equipped with Chatbots which can interpret the user questions and provide the right answers, in a quick and proper manner. Hence, it is not a part of virtual assistants, but it can be utilized for governments as well as organizations on websites, applications and instant messaging platforms to develop the products, ideas or services. This paper presents the realization of a chatbot in the educational system. In addition, the authors present the historical development, types of chatbot, applications and their future in education sector is described.</p> 2021-05-15T00:00:00+0530 Copyright (c) 2021 https://ojs.trp.org.in/index.php/ajes/article/view/2834 Defect Identification and Classification of Tomato Leaf Using Convolutional Neural Network 2021-09-11T15:25:27+0530 S. Shargunam shargunamguna@gmail.com G. Rajakumar gmanly12@gmail.com <p>Tomatoes are the most commonly grown crop globally, and they are used in almost every kitchen. India holds second place in the production of tomatoes. Due to the various kinds of diseases, the quantity and quality of tomato crop go down. Identifying the diseases in the earlier stage is very important and will help the farmers save the crop. The first initial step is pre-processing, for the Canny edge detection method is used for detecting the edges in the tomato leaves. The classification of tomato leaves is to be carried out by extracting the features like color, shape, and texture. Extracted features from segmented images are fed into classification. The convolutional neural network algorithm will be used, which will give a better accuracy to classify the diseases in the tomato leaves.</p> 2021-05-15T00:00:00+0530 Copyright (c) 2021