The major aspect of the paper is to understand the recurring traffic congestion and suggest a precautionary measure to the society. This implication of widening the existing roads or building new one by acquiring the ...
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The way Data Science and Machine Learning have set modern trends for automation. It is thoughtful to simplify our day to day activities which are related to these domains. One such task is the repetitive submission of...
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In today's environment, research into the implementation of Machine Learning Algorithms in the VLSI sector has increased dramatically. One of the most important requirements for these designs was the employment of...
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The innovative Smart Soil system, carefully crafted using OMNeT++, marks a significant breakthrough in precision farming as it seamlessly incorporates the advanced capabilities of Power Aware Multi Access Signaling (P...
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Solar energy stands out as a highly reliable renewable technology with global applicability. The growing integration of solar photovoltaic systems worldwide emphasizes the need for sustaining peak performance and maxi...
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Coconut farming is an essential agricultural practice that contributes significantly to the global economy by providing valuable products such as coconut water, oil, and meat. However, the management of coconut planta...
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Among closed places like cities, apartments, and multistory buildings, parking of the different vehicles is quite problematic, and the main problem is the space, which is not enough, and the staff must be used, which ...
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Hand gestures are the most common way of interaction among humans in the physical world. Gestures are used in everyday life to interact with objects around us. Hand gesture is becoming the most comfortable alternative...
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Separated transmit and receive antennas are employed to improve transmit-receive isolation in conventional short-range radars, which greatly increases the antenna size and misaligns of the transmit/receive radiation p...
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Separated transmit and receive antennas are employed to improve transmit-receive isolation in conventional short-range radars, which greatly increases the antenna size and misaligns of the transmit/receive radiation patterns. In this paper,a dual circularly polarized(CP) monostatic simultaneous transmit and receive(MSTAR) antenna with enhanced isolation is proposed to alleviate the problem. The proposed antenna consists of one sequentially rotating array(SRA), two beamforming networks(BFN), and a combined decoupling structure. The SRA is shared by the transmit and receive to reduce the size of the antenna and to obtain a consistent transmit and receive *** BFN achieve right-hand CP for transmit and left-hand CP for receive. By exploring the combined decoupling structure of uniplanar compact electromagnetic band gap(UC-EBG) and ringshaped defected ground structure(RS-DGS), good transmitreceive isolation is achieved. The proposed antenna prototype is fabricated and experimentally characterized. The simulated and measured results show good agreement. The demonstrate transmit/receive isolation is height than 33 dB, voltage standing wave ratio is lower than 2, axial ratio is lower than 3 dB, and consistent radiation for both transmit and receive is within4.25-4.35 GHz.
In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh env...
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In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.
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