The electroencephalogram (EEG) signals are a big data which are frequently corrupted by motion artifacts. As human neural diseases, diagnosis and analysis need a robust neurological signal. Consequently, the EEG artifacts’ eradication is a vital step. In this research paper, the primary motion artifact is detected from a single-channel EEG signal using support vector machine (SVM) and preceded with further artifacts’ suppression. The signal features’ abstraction and further detection are done through ensemble empirical mode decomposition (EEMD) algorithm. Moreover, canonical correlation analysis (CCA) filtering approach is applied for motion artifact removal. Finally, leftover motion artifacts’ unpredictability is removed by applying wavelet transform (WT) algorithm. Finally, results are optimized by using Harris hawks optimization (HHO) algorithm. The results of the assessment confirm that the algorithm recommended is superior to the algorithms currently in use.

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A Machine Learning-Based Big EEG Data Artifact Detection and Wavelet-Based Removal: An Empirical Approach

During data transmission, a decentralised Mobile Ad Hoc Network (MANET) might result in high Energy Consumption (EC) and a short Network Lifetime (NLife). To address these difficulties, an on-demand Power and Load-Aware multipath node-disjoint source routing is presented based on the Enhanced Opportunistic Routing (PLAEOR) protocol. This unique protocol aims at using power, load, and latency to manage routing costs depending on control packet flooding from the destination node. However, the exchange of control packets from the target to all nodes may impact network efficiency. As a result, the PLAEOR is designed with a Multichannel Cooperative Neighbor Discovery (MCND) protocol to locate the nearby cooperative nodes for each node in the routing path during control packet transmission. Furthermore, when the packet rate of CBR is 20 packets/sec, the simulated results show that the PLAEOR-MCND achieves 120 sec of NLife and 20 J of EC than the state-of-the-art protocols.

Delay-Driven Opportunistic Routing with Multichannel Cooperative Neighbor Discovery for Industry 4.0 Wireless Networks Based on Power and Load Awareness

Three-phase induction motors are becoming increasingly popular for electric cars and industrial uses because of their improved efficiency and simplicity of production, among other things. Many enterprises and industries use induction motors in several rotating applications. However, it is a difficult talent to master when it comes to controlling the speed of an induction motor for various purposes. This study examines the performance of a three-phase induction motor using approaches such as field-oriented control and direct torque control. This work utilized the fractional order Darwinian particle swarm optimization (FODPSO) method in fuzzy methodology to optimize a motor’s performance. Field-oriented control (FOC) and Direct torque control (DTC) methods are regulated by FODPSO, which is compared to standard FOC and DTC methods. MATLAB-Simulink was used to compare the outcomes of each system’s simulation model to determine which one performed the best. The support vector machine-direct torque control (SVM-DTC) technology is famous for its rapid dynamic response and decreased torque ripples. Using torque and settling time and rising time reduction, the suggested technique is proved to be superior to the present way.

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Hybrid Optimization Approach for Energy Control in Electric Vehicle Controller for Regulation of Three-Phase Induction Motors

The participation of women Lifestyle of poor women in self-help groups and has had the greatest impact on style and Them not only as individuals, but also as family Them not only as individuals, but also as family Has also improved as a member. Community and community. Their common through self-help and mutual aid. They come together for the purpose of solving problems. The most attractive project with the least effort is the "Self Help Group" (SHGs). It is also about poverty alleviation and women entrepreneurship in India and is also a tool for improving financial assistance. Current Study Self Help Groups in Tamil Naduby itself into the study of women's empowerment Controls. The main objective of the study isthe impact of self-help groups on women's empowerment which is carried out in Kaveripattinam, Krishnagiri District, Tamil Nadu, and India. The result shows that there is a positive impact of self-help group son women's empowerment.

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The Impact of Self-help Groups on the Women Empowerment in Tamil Nadu

In this paper we used WPM method; it is a unique combination of weight sum model and weight product model. Due to its mathematical simplicity and ability to deliver more Compared with WSM and WPM Accurate results. As an effective decision-making tool Now widely accepted methods. In decision-making theory, Weighted Sum Model (WSM), Weighted Linear Combination (WLC) or Also known as Simple Admission Waiting (SAW) is used to evaluate multiple alternatives based on a list of weighted objectives (WOT) criteria used to rank different alternatives. Weighted linear composition is an analytical method used when making multiple attribute decisions (MADM) or considering multiple attributes. The weighted average is the average type calculated by multiplying the weight (or probability) associated with a particular event or effect by its relative magnitude effect. The WPM methods is the most ideal solution Short-distance and negative-best the solution with the longest distance from the solution Determines, but the comparison of these distances Does not consider importance. From the result it is seen that Salem is got the first rank whereas is the Madurai is having the lowest rank.

Exploring the Possibility of Urban Agriculture Farn

Data processing with multiple domains is an important concept in any platform; it deals with multimedia and textual information. Where textual data processing focuses on a structured or unstructure...

Rachana Dubey

Papers

Review of video compression techniques based on fractal transform function and swarm intelligence