Magnetic bearing motors are in high demand due to their ability to operate in special environments without mechanical friction and lubrication, effectively avoiding wear and contamination. To overcome the complexity a...
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The paper proposes a novel checkpoint management method for a real-time system with a quintuple modular redundancy (QMR) structure wherein multiple fault detections are performed between checkpoints. If the detected f...
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In response to the evolving landscape of modern military operations, where drone technology now constitutes an estimated 70% of Indian military missions, as evidenced by recent statistics, our proposed AI-based Visual...
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Radiomics represents a specialized branch of medical imaging where quantitative features are extracted from images. Performing a classification using radiomics means solving two common problems: the imbalanced setting...
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A prevalent issue with missing or expired vehicle paperwork has prompted the development of a digital service utilizing QR codes within the documentation. This innovation allows Rapid Transport Office (RTO) officers t...
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Suspect identification can be challenging for forensic investigations since standard procedures are time-consuming and prone to mistakes. This calls for the creation of novel approaches utilizing developments in machi...
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ISBN:
(纸本)9798350379136
Suspect identification can be challenging for forensic investigations since standard procedures are time-consuming and prone to mistakes. This calls for the creation of novel approaches utilizing developments in machine learning (ML) and artificial intelligence (AI). In order to overcome these obstacles, the proposed Face Generation and Recognition in Forensic Science will make use of sophisticated recognition algorithms and AI-based face generation models. Fully trained Stable Diffusion model is applied to generate high-quality face images from textual descriptions. Image Generation, Text Guided Image Manipulation using Denoising Diffusion Probabilistic Models (DDPMs), and Dataset Matching are the three primary components of the process. Using a stable diffusion model, Image Generation quickly creates high-resolution images from word prompts by combining an autoencoder (VAE), U-Net, and text encoder. With the introduction of an alternate noise space for DDPMs, Text Guided picture Manipulation makes it possible to do meaningful picture altering tasks in response to text prompts. VGG-16 , a convolutional neural network architecture is used in dataset matching to extract features and calculate similarity, which makes dataset alignment and comparison easier. The suggested methodology gives law enforcement authorities effective tools for identifying suspects, which represents a substantial development in forensic investigations. The project intends to increase the efficiency of criminal investigations, accelerate the matching process with large datasets, and enhance the accuracy of facial sketches by utilizing AI and ML approaches. The approach's ability to produce coherent and contextually relevant face images is validated by experimental results, which also show the approach's potential for speeding up the conclusion of criminal cases, particularly unsolved cold cases. All things considered, Face Generation and Recognition in Forensic Science is a promising step in st
Pulsed current cathodic protection(PCCP) could be more effective than direct current cathodic protection(DCCP)for mitigating corrosion in buried structures in the oil and gas industries if appropriate pulsed parameter...
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Pulsed current cathodic protection(PCCP) could be more effective than direct current cathodic protection(DCCP)for mitigating corrosion in buried structures in the oil and gas industries if appropriate pulsed parameters are chosen. The purpose of this research is to present the corrosion prevention mechanism of the PCCP technique by taking into account the effects of duty cycle as well as frequency, modeling the relationships between pulse parameters(frequency and duty cycle) and system outputs(corrosion rate, protective current and pipe-to-soil potential) and finally identifying the most effective protection conditions over a wide range of frequency(2–10 kHz) and duty cycle(25%-75%). For this, pipe-to-soil potential, pH, current and power consumption, corrosion rate, surface deposits and investigation of pitting corrosion were taken into account. To model the input-output relationship in the PCCP method, a data-driven machine learning approach was used by training an artificial neural network(ANN). The results revealed that the PCCP system could yield the best protection conditions at 10 kHz frequency and 50% duty cycle, resulting in the longest protection length with the lowest corrosion rate at a consumption current 0.3 time that of the DCCP method. In the frequency range of 6–10 kHz and duty cycles of 50%-75%, SEM images indicated a uniform distribution of calcite deposits and no pits on cathode surface.
Vision is a crucial aspect for both artificial intelligence and automated robots. In the case of an automated coconut harvesting machine, a computerized system linked to the machine plays a key role in real-time ident...
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In urban areas, traffic congestion is a major problem causing increased travel times, higher consumption of fuel, and environmental pollution. The traditional traffic control systems cannot adapt to dynamic traffic co...
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