TLS 1.3 is widely used to realize secure communication over the Internet. Existing security analyses of TLS 1.3 primarily focus on its handshake protocol which is indeed an authenticated key exchange (AKE) protocol, a...
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It plays a central role in intelligent agent systems to model agents’epistemic states and their *** plays a key role in distributed systems,in which the messages transmitted may not be received instantly by the *** c...
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It plays a central role in intelligent agent systems to model agents’epistemic states and their *** plays a key role in distributed systems,in which the messages transmitted may not be received instantly by the *** characterize asynchronous communications,Asynchronous Announcement Logic(AAL)has been presented,which focuses on the logic laws of the change of epistemic state after receiving *** AAL does not involve the interactive behaviours between an agent and its *** interactions can change agents’epistemic states,while the latter will affect the *** enriching the well-known-calculus by adding the operators for passing basic facts and applying the well-known action model logic to describe agents’epistemic states,this paper presents the ecalculus to model epistemic interactions between agents with epistemic *** e-calculus can be adopted to characterize synchronous and asynchronous communications between *** capture the asynchrony,a buffer pool is constructed to store the basic facts announced and each agent reads these facts from this buffer pool in some *** on the transmission of link names,the e-calculus is able to realize reading from this buffer pool in different *** paper gives two examples:one is to read in the order in which the announced basic facts are sent(First-in-first-out,FIFO),and the other is in an arbitrary order.
The detection of skin cancer holds paramount importance worldwide due to its impact on global health. While deep convolutional neural networks (DCNNs) have shown potential in this domain, current approaches often stru...
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Oil temperature is an important index to reflect the state of transformer and predict the fault and remaining useful life of transformer. However, the oil temperature of the transformer is affected by various factors ...
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Deploying models on resource-constrained edge devices remains always a critical challenge for the application of neural network. Quantization is one of the most popular methods to compress the model for meeting the pe...
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RagaMoodSync presents an innovative framework for personalized music therapy through Hindustani Raga recommendations based on facial emotion recognition. Utilizing a Fusion-DenseNet (FusDenseNet) architecture with adv...
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Aiming at the nonlinear and dynamic characteristics of data in automotive engine systems, a fault detection method based on canonical variate analysis combined with Bhattacharyya distance (CVA-BD) is proposed in this ...
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The increasing use of cloud-based image storage and retrieval systems has made ensuring security and efficiency crucial. The security enhancement of image retrieval and image archival in cloud computing has received c...
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The increasing use of cloud-based image storage and retrieval systems has made ensuring security and efficiency crucial. The security enhancement of image retrieval and image archival in cloud computing has received considerable attention in transmitting data and ensuring data confidentiality among cloud servers and users. Various traditional image retrieval techniques regarding security have developed in recent years but they do not apply to large-scale environments. This paper introduces a new approach called Triple network-based adaptive grey wolf (TN-AGW) to address these challenges. The TN-AGW framework combines the adaptability of the Grey Wolf Optimization (GWO) algorithm with the resilience of Triple Network (TN) to enhance image retrieval in cloud servers while maintaining robust security measures. By using adaptive mechanisms, TN-AGW dynamically adjusts its parameters to improve the efficiency of image retrieval processes, reducing latency and utilization of resources. However, the image retrieval process is efficiently performed by a triple network and the parameters employed in the network are optimized by Adaptive Grey Wolf (AGW) optimization. Imputation of missing values, Min–Max normalization, and Z-score standardization processes are used to preprocess the images. The image extraction process is undertaken by a modified convolutional neural network (MCNN) approach. Moreover, input images are taken from datasets such as the Landsat 8 dataset and the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset is employed for image retrieval. Further, the performance such as accuracy, precision, recall, specificity, F1-score, and false alarm rate (FAR) is evaluated, the value of accuracy reaches 98.1%, the precision of 97.2%, recall of 96.1%, and specificity of 917.2% respectively. Also, the convergence speed is enhanced in this TN-AGW approach. Therefore, the proposed TN-AGW approach achieves greater efficiency in image retrieving than other existing
This paper presents an ultra-low power RFID with an embedded CMOS temperature sensor. The thermometry working flow of the Query01-Query00-Ack sequence is introduced, which is compatible with the EPC GEN-2 standard. A ...
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Quantum computers may solve some computing tasks more efficiently than classical computers, but to do so requires the design of appropriate quantum circuits. However, it is hard to design even simple quantum programs....
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