An authentication code can be constructed with a family of $\epsilon$ -Almost strong universal ( $\epsilon$ -ASU) hash functions, with the index of hash functions as the authentication key. This paper considers the pe...
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An authentication code can be constructed with a family of $\epsilon$ -Almost strong universal ( $\epsilon$ -ASU) hash functions, with the index of hash functions as the authentication key. This paper considers the performance of authentication codes from $\epsilon$ -ASU, when the authentication key is only partially secret. We show how to apply the result to privacy amplification against active attacks in the scenario of two independent partially secret strings shared between a sender and a receiver.
Choreographic programming is an emerging programming paradigm for concurrent and distributed systems, where developers write the communications that should be enacted and a compiler then automatically generates a dist...
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A nevertheless-emerging generation called cloud computing permits customers to pay for services on a usage-based foundation. Internet-primarily based IT offerings are supplied through cloud computing, at the same time...
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We focus on a planning problem based on Plotting, a tile-matching puzzle video game published by Taito. The objective of the game is to remove at least a certain number of coloured blocks from a grid by sequentially s...
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Latest advancements in the integration of camera sensors paves a way for newUnmannedAerialVehicles(UAVs)applications such as analyzing geographical(spatial)variations of earth science in mitigating harmful environment...
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Latest advancements in the integration of camera sensors paves a way for newUnmannedAerialVehicles(UAVs)applications such as analyzing geographical(spatial)variations of earth science in mitigating harmful environmental impacts and climate *** have achieved significant attention as a remote sensing environment,which captures high-resolution images from different scenes such as land,forest fire,flooding threats,road collision,landslides,and so on to enhance data analysis and decision *** scene classification has attracted much attention in the examination of earth data captured by *** paper proposes a new multi-modal fusion based earth data classification(MMF-EDC)*** MMF-EDC technique aims to identify the patterns that exist in the earth data and classifies them into appropriate class *** MMF-EDC technique involves a fusion of histogram of gradients(HOG),local binary patterns(LBP),and residual network(ResNet)*** fusion process integrates many feature vectors and an entropy based fusion process is carried out to enhance the classification *** addition,the quantum artificial flora optimization(QAFO)algorithm is applied as a hyperparameter optimization *** AFO algorithm is inspired by the reproduction and the migration of flora helps to decide the optimal parameters of the ResNet model namely learning rate,number of hidden layers,and their number of ***,Variational Autoencoder(VAE)based classification model is applied to assign appropriate class labels for a useful set of feature *** proposedMMF-EDCmodel has been tested using UCM and WHU-RS *** proposed MMFEDC model attains exhibits promising classification results on the applied remote sensing images with the accuracy of 0.989 and 0.994 on the test UCM and WHU-RS dataset respectively.
The popularity of cloud computing in scheduling work processes, particularly logical work processes, is growing. The cloud computing environment may encounter significant issues with execution time and cost during res...
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Procedural activities are sequences of key-steps aimed at achieving specific goals. They are crucial to build intelligent agents able to assist users effectively. In this context, task graphs have emerged as a human-u...
ISBN:
(纸本)9798331314385
Procedural activities are sequences of key-steps aimed at achieving specific goals. They are crucial to build intelligent agents able to assist users effectively. In this context, task graphs have emerged as a human-understandable representation of procedural activities, encoding a partial ordering over the key-steps. While previous works generally relied on hand-crafted procedures to extract task graphs from videos, in this paper, we propose an approach based on direct maximum likelihood optimization of edges' weights, which allows gradient-based learning of task graphs and can be naturally plugged into neural network architectures. Experiments on the CaptainCook4D dataset demonstrate the ability of our approach to predict accurate task graphs from the observation of action sequences, with an improvement of +16.7% over previous approaches. Owing to the differentiability of the proposed framework, we also introduce a feature-based approach, aiming to predict task graphs from key-step textual or video embeddings, for which we observe emerging video understanding abilities. Task graphs learned with our approach are also shown to significantly enhance online mistake detection in procedural egocentric videos, achieving notable gains of + 19.8% and +7.5% on the Assembly101-O and EPIC-Tent-O datasets. Code for replicating the experiments is available at https://***/fpv-iplab/Differentiable-Task-Graph-Learning.
Inadequate rainfall causes reduced harvesting, reduced availability of water, economic losses, environmental degradation, public health problems, decreased power generation, social unrest, and infrastructure destructi...
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Images for social media are an essential component of any blog or social media post. As we now live in the age of the ‘camera in everyone’s pocket’, a new dynamic era of image creation and content has emerged. Howe...
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The problem of achieving performance-guaranteed finite-time exact tracking for uncertain strict-feedback nonlinear systems with unknown control directions is addressed. A novel logic switching mechanism with monitorin...
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