The electrical energy storage system faces numerous obstacles as green usage rises. demand for electric vehicles (EVs) is growing in tandem with the technological advance of EV range on a single charge. To tackle low-range problem, an effective device necessary. Traditionally, have been powered by source power, which insufficient to handle EV’s dynamic demand. As result, unique medium necessary meet load characteristics high-energy density and high-power density. This made up two...

In power system to optimized PMUs is a critical task ensure maximum network observability while minimizing installation costs. This study presents comparative analysis of three optimization techniques: Teaching-Learning-Based Optimization (TLBO), Particle Swarm (PSO), and hybrid TLBO-PSO approach, focusing on their efficiency in determining the best PMU placements. Individual methods, such as TLBO PSO, are often limited by longer computation times requirement for higher number achieve full...

Integration of RE sources to the utility grid offers technical and operational challenges causing problems PQ, stability, identification events, etc. This article presents an algorithm identify events including islanding, integration, outage solar PV WG plants in using a ST. Islanding event may occur presence any kind plant. Processing negative sequence component voltage is performed by utilizing ST based multiresolution analysis at test node output matrix evaluated. The features (F1–F4), VI...

To judge the ability of convolutional neural networks (CNNs) to effectively and efficiently transfer image representations learned on ImageNet dataset task recognizing COVID-19 in this work, we propose analyze four approaches. For purpose, use VGG16, ResNetV2, InceptionResNetV2, DenseNet121, MobileNetV2 CNN models pre-trained extract features from X-ray images COVID Non-COVID patients. Simulations study performed by us reveal that these have a different level representation. We find...

The broad application area and accompanying challenges make machine learning-based recognition of handwritten scripts a demanding field. Individuals' writing practices inherent variations in the size, shape, tilt characters may increase difficulty level. Deep convolutional neural network (DCNN) models have been successful solving pattern problems, but at expense considerable number trainable parameters heavy computational loads. proposed work addresses these problems by using shifted window...

Abstract Given the vast range of factors, including shape, size, skew, and orientation handwritten numerals, their machine-based recognition is a difficult challenge for researchers in pattern field. Due to abundance curves resembling shapes symbols, Devnagari numerals can leverage difficulty level recognition. The suggested low-classification-cost method obtaining fine features from given numeral images used benchmark deep learning models, VGG-16Net, VGG-19Net, ResNet-50, Inception-v3,...

This paper introduces a power quality (PQ) detection and categorization algorithm actuated by multiple signal processing techniques rule-based decision tree (RBDT). is aimed to recognize PQ events of simple nature higher order multiplicity with less computational time using hybridization the techniques. A voltage waveform event (PQE) processed Stockwell transform (ST) compute index (SPDI). The also Hilbert (HT) (HPDI). decomposed Discrete Wavelet (DWT) classification feature (CFI) [CFI1...

This paper has introduced an algorithm for the identification of islanding events in remotely located distribution grid with renewable energy (RE) sources using voltage signals. Voltage signal is processed Stockwell transform (ST) to compute median-based recognition factor (MIRF). The rate change root mean square (RMS) computed by differentiating RMS respect time (VRCIRF). proposed voltage-based (IRFV) multiplying MIRF and VRCIRF element element. event discriminated from faulty operational...

Embedded memory yield dominates manufacturing of the chip and enhancement techniques for embedded memories are important entire SoC increases. Lasers fuses anti two commonly used mechanisms hard repair they consume a lot area. Analysis based upon prediction methods as well silicon database shows that putting fuse to all on is not worth expense, when only few bits needed. In this paper, authors present background reduction (cost analysis) propose methodology compress total number such cost...

Power consumption during test can be significantly higher than normal functional mode. This paper presents a low power Automated Test Pattern Generation (ATPG) flow for managing capture in today's critical designs. It introduces novel method sequentially enabling the on-chip clock controllers to generate accurate ATPG patterns respecting specifications of design. The effectiveness is demonstrated on several industrial designs that show up issues

This paper presents a technique using hybrid features extracted from current signals Stockwell and Hilbert Transforms for detecting the islanding events operational of renewable energy generators loads. The study is performed on power system test network incorporating wind solar generators. Results are computed MATLAB/Simulink software variety case studies. Through applied successfully identified discriminated events.

In high speed applications, ratio of total jitter to clock period is critical. It necessitates accurate measurement Jitter. this paper we describe an on- chip methodology measure in time domain, with resolutions up 0.1 ps.

Embedded memory yield dominates manufacturing of the chip and enhancement techniques for embedded memories are important entire SoC increase. Laser fuses anti two commonly used mechanisms hard repair they consume a lot area. Analysis based upon prediction methods as well silicon database shows that putting fuse to all on is not worth expense, when only few bits needed. In this paper, we present background reduction (cost analysis) propose methodology compress total number such cost through...

Hindi is the official language of India and used by a large population for several public services like postal, bank, judiciary, surveys. Efficient management these needs language-based automation. The proposed model addresses problem handwritten character recognition using machine learning approach. pre-trained DCNN models namely; InceptionV3-Net, VGG19-Net, ResNet50 were extraction salient features from characters’ images. A novel approach fusion adopted in work; DCNN-based are fused with...

This paper delves into enhancing short-term solar energy predictions using advanced machine learning techniques. Solar power production, affected by weather, time, and location, demands accurate forecasts. The study fills a literature gap thoroughly assessing Support Vector Machine (SVM), XGBoost, Decision Tree, Random Forest, AdaBoost models in this context. Accurate are vital for grid stability, efficient management, smooth integration. Research goals include comparing modelperformance,...

This research paper designed a system protection scheme (SPS) for two 400kV/220kV interlinking transformer (ILT) installed on thermal power plant (TPP) of practical utility grid to make these ILTs N-1 compliant. Two SPS logic are avoid tripping from the overload conditions and one ILT when another is tripped fault. achieved by load curtailment nearby 220 kV Grid-substation (GSS) in region. The command taken over-load/over-current relay trip 86-master transmitted over line carrier...