The partial differential equation(PDE)solution of the telegrapher is a promising fault location method among time-domain and model-based *** research works have shown that the leap-frog process is superior to other ex...
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The partial differential equation(PDE)solution of the telegrapher is a promising fault location method among time-domain and model-based *** research works have shown that the leap-frog process is superior to other explicit methods for the PDE ***,its implementation is challenged by determining the initial conditions in time and the boundary conditions in *** letter proposes two implicit solution methods for determining the initial conditions and an analytical way to obtain the boundary conditions founded on the signal *** results show that the proposal gives fault location accuracy superior to the existing leap-frog scheme,particularly in the presence of harmonics.
The work presented in this paper has great significance in improving electromagnetic models based on the strong coupling between the magnetic and electric fields transient equations while considering a realistic rando...
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All wireless communication systems are moving towards higher and higher frequencies day by day which are severely attenuated by rains in outdoor environment. To design a reliable RF system, an accurate prediction meth...
Distance and size estimation of objects of interests is an inevitable task for many navigation and obstacle avoidance algorithms mainly used in autonomus and robotic systems. Stereo vision systems, inspired by human v...
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Semi-supervised learning techniques utilize both labeled and unlabeled images to enhance classification performance in scenarios where labeled images are limited. However, challenges such as integrating unlabeled imag...
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Semi-supervised learning techniques utilize both labeled and unlabeled images to enhance classification performance in scenarios where labeled images are limited. However, challenges such as integrating unlabeled images with incorrect pseudo-labels, determining appropriate thresholds for the pseudo-labels, and label prediction fluctuations on low-confidence unlabeled images, hinder the effectiveness of existing methods. This research introduces a novel framework named Interpolation Consistency for Bad Generative Adversarial Networks (IC-BGAN) that utilizes a new loss function. The proposed model combines bad adversarial training, fusion techniques, and regularization to address the limitations of semi-supervised learning. IC-BGAN creates three types of image augmentations and label consistency regularization in interpolation of bad fake images, real and bad fake images, and unlabeled images. It demonstrates linear interpolation behavior, reducing fluctuations in predictions, improving stability, and facilitating the identification of decision boundaries in low-density areas. The regularization techniques boost the discriminative capability of the classifier and discriminator, and send a better signal to the bad generator. This improves the generalization and the generation of diverse inter-class fake images as support vectors with information near the true decision boundary, which helps to correct the pseudo-labeling of unlabeled images. The proposed approach achieves notable improvements in error rate from 2.87 to 1.47 on the Modified National Institute of Standards and Technology (MNIST) dataset, 3.59 to 3.13 on the Street View House Numbers (SVHN) dataset, and 12.13 to 9.59 on the Canadian Institute for Advanced Research, 10 classes (CIFAR-10) dataset using 1000 labeled training images. Additionally, it reduces the error rate from 22.11 to 18.40 on the CINIC-10 dataset when using 700 labeled images per class. The experiments demonstrate the IC-BGAN framework outp
Identifying influential nodes has attracted the attention of many researchers in recent years. Because of the weak tradeoff between accuracy and running time, and ignoring the community structure by the proposed algor...
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Considering the expansion of the Internet of Things (IoT) and the volume of data and user requests, Mobile Edge Computing (MEC) is considered a novel and efficient solution that puts decentralized servers at the netw...
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The significant increase in civil aircraft traffic has led to frequent congestion and various negative outcomes within the terminal area. To mitigate these challenges, addressing and studying the aircraft landing prob...
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In recent years, airport runways have become a more critical bottleneck in airports, and it is very unusual to use only one runway to solve the Aircraft Landing Problem (ALP). The ALP includes the aircraft's landi...
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The capability of a system to fulfill its mission promptly in the presence of attacks,failures,or accidents is one of the qualitative definitions of *** this paper,we propose a model for survivability quantification,w...
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The capability of a system to fulfill its mission promptly in the presence of attacks,failures,or accidents is one of the qualitative definitions of *** this paper,we propose a model for survivability quantification,which is acceptable for networks carrying complex traffic *** network traffic is considered as general multi-rate,heterogeneous traffic,where the individual bandwidth demands may aggregate in complex,nonlinear *** probability is the chosen measure for survivability *** study an arbitrary topology and some other known topologies for the *** and dependent failure scenarios as well as deterministic and random traffic models are ***,we provide survivability evaluation results for different network *** results show that by using about 50%of the link capacity in networks with a relatively high number of links,the blocking probability remains near zero in the case of a limited number of failures.
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