Published in IJEER

Special Issue on Innovations and Trends in role of Electrical, and Electronics Engineering in IT Revolution: Bridging the Digital Frontier


Multiple Power Quality Issues Reorganization Analysis and Feature Extraction with the Discrete Wavelet Transform

Now a day’s utilization of the power is very important concept in term of the quality. Utilization of the power is very effective as compared to the generation, at the end point of the different issues are occurs when the power is uses these issues are affect the quality of power so in this paper present about the application of the wavelet for determination of the different power quality issues in the system. In this series first issues determination play very important role. For the determination of the quality issue different soft computational techniques can be apply.

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Development of Smart Agriculture to detect the Arabica Coffee Leaf Disease using IAFSA based MSAB with Channel and Spatial Attention Network

Plant diseases provide challenges for the agriculture sector, notably to produce Arabica coffee. Recognising issues on Arabica coffee leaves is a first step in avoiding and curing illnesses to prevent crop loss. With the extraordinary advancements achieved in convolutional neural networks (CNN) in recent years, Arabica coffee leaf damage can now be identified without the aid of a specialist. However, the local characteristics that convolutional layers in CNNs record are typically redundant and unable to make efficient use of global data to support the prediction process. The proposed Hybrid Attention UNet, also known as CMSAMB-UNet due to its feature extraction and global modelling capabilities, integrates both the Channel and Spatial Attention Module (CSAM) as well as the Multi-head Self-Attention Block (MSAB).

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Dynamic Monitoring and Analysis of Dual-Axis movement of SPV Power Plant Parameters under various Atmospheric Conditions

This research paper presents comprehensive insight into the testing of a 1 KW sun tracking photovoltaic (PV) performance. The study uses a state-of-the-art real-time string monitoring system to allow this analysis while covering an extensive variety of atmospheric conditions. The design of the 1 KW solar tracker system incorporates a tracking sensor circuit, motor driver circuit, string monitoring system, and solar tracker control circuit. Solar tracking systems boost energy generation by adjusting the angle of PV panels to optimum sunlight exposure. The effectiveness of such devices can, however, be severely impacted by atmospheric changes. In a photovoltaic (PV) facility, we have successfully developed and placed into use a real-time system for monitoring certain strings.

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Filtering based Image Decomposition and Restoration Approach

In image processing, most of the time it is required to process the image by partitioning or decomposing it in different parts or representing it by mean of different features. Also, the quality of an acquired or received image is very much important from the further processing point of view. The partitioning or decomposition of the image and reconstruction of the original image from the distorted image are the prime areas of research when deals with the image filtering. Presented research work deals with the decomposition of the distorted color image and the restoration of the original color image. Average filtering is used for the decomposition of each grey level planes of the image in three components and later, the average and median filters are used to reconstruct the color image from these decomposed components of each grey level planes.

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Taming Misinformation: Fake Review Detection on Social Media platform using Hybrid Ensemble Technique

In today's digital world, we witness exponential growth in the generation of textual content on a daily basis. However, the widespread dissemination of information through social media, online forums, and news websites has given rise to the proliferation of fake views, opinions, and reviews, posing a significant challenge in the battle against misinformation and manipulation. Machine Learning has become increasingly integral to real-world online activities, particularly in the area of Artificial Intelligence. Traditional methods often struggle to keep pace with the relentless creation of internet data. Consequently, short text processing has emerged as a new domain for the application of Machine Learning.

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Flexible and Wearable Antenna Design for Bluetooth and Wi-Fi Application

The emergence of wearable technology has revolutionized the way we interact with electronic devices, integrating them into our daily routines. From fitness trackers, smart watches to augmented reality glasses and medical monitoring devices, wearable have become increasingly prevalent. Among the most commonly employed wireless technologies within wearables are Bluetooth and Wi-Fi. The design of efficient and reliable antennas for Bluetooth and Wi-Fi applications in wearable is of paramount importance to ensure optimal performance and user satisfaction. In this paper presented a flexible and wearable antenna design for Bluetooth and Wi-Fi application utilizing the Rogers RT5880 flexible substrate, characterized by a dielectric constant of 2.2 and a thickness of 20mil.

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Empowering Health and Well-being: IoT-Driven Vital Signs Monitoring in Educational Institutions and Elderly Homes Using Machine Learning

IoT-based EHRs use machine learning technology to automate real-time patient-centered records more securely for authorized users. (1) Background: In this era of pandemics, predictive healthcare systems are necessary for private and public healthcare delivery to predict early cancer, COVID-19, hypertension, and fever in Educational Institutions and Elderly Homes. IoT-Based EHRs bring healthcare delivery to the doorsteps of educational home facilities users, thereby reducing the time required to access healthcare and minimizing direct physical interaction between individuals seeking healthcare and their providers. (2) Method:

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A Novel Approach for Islanding Detection in Distributed Wind Energy Generators within Renewable Energy-Integrated Smart Grid using the 3-Parameter Sine Fit Algorithm

This paper introduces a novel islanding detection method employing the 3 Parameter Sine Fit (3PSF) algorithm, which accurately estimates the angle between voltage and current at Distributed Generators (DGs). The method improves islanding identification in a test system consisting three Wind Energy Generators (WEGs) and an Emergency Diesel Engine Generator (EDEG). To demonstrate the efficacy of suggested novel strategy, the assessment is done under variety of situations such as islanding, load shedding and distribution line loss.

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