With the rapid development of software industry, a variety of new technologies are produced. Research and development in cloud computing, big data, artificial intelligence, the Internet of Things, blockchain, and othe...
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As the deployment,supporting,and stability mechanisms of satellite antennas,space-deployable mechanisms play a key role in the field of *** order to design truss deployable antenna supporting mechanisms with large fol...
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As the deployment,supporting,and stability mechanisms of satellite antennas,space-deployable mechanisms play a key role in the field of *** order to design truss deployable antenna supporting mechanisms with large folding rate,high accuracy,easy deployment and strong stability,aiming at the geometric division of the parabolic reflector,a novel method based on symmetric hexagonal division and its corresponding modular truss deployable antenna mechanism is proposed,and the original method based on asymmetric triangular division and its corresponding mechanisms are presented for comparative ***,the screw theory is employed to analyze the mobility of different ***,the improved three-dimensional mesh method is used to divide the reflector surface of a large parabolic antenna designed by the two different methods,and the profile accuracy and the type of links are taken as the evaluation indexes to quantitatively analyze the division ***,a three-dimensional model of the modular deployable mechanism based on the symmetric hexagonal design is developed,and the deployable mechanisms with different configurations based on the two design methods are compared and analyzed from the mechanical *** research results provide a good theoretical reference for the design of deployable truss antenna mechanisms and their application in the aerospace field.
An efficient massively parallel computing program for shock wave propagation named Shock3d is developed for shock wave damage mechanism in complex scenes. With the finite volume method, the program is built upon JASMI...
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Accurate prediction of gene regulation rules is important for understanding complex life processes. Existing computational algorithms designed for bulk transcriptome datasets typically require a large number of time p...
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ISBN:
(纸本)9781450396868
Accurate prediction of gene regulation rules is important for understanding complex life processes. Existing computational algorithms designed for bulk transcriptome datasets typically require a large number of time points to infer gene regulatory networks (GRNs), are suitable for a small number of genes, and cannot efficiently detect potential regulatory relationships. We propose an approach based on a deep learning framework to reconstruct GRNs from bulk transcriptome datasets, assuming that the expression levels of transcription factors involved in gene regulation are strong predictors of the expression of their target genes. The algorithm uses multilayer perceptrons to infer the regulatory relationship between multiple transcription factors and a gene, and uses genetic algorithms to search for the best regulatory gene combination. The results show that our approach is more accurate than other methods for reconstructing gene regulatory networks on real-world and simulated bulk transcriptome gene expression datasets.
This article proposes a relay deployment method that uses UAVs to provide communication services to ground users, especially for emergency communication scenarios in disaster ***, a two-layer network communication mod...
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Seeking effective numerical approximations for partial differential equations (PDEs) is a major challenge in modern science and technology. Recently, AI-inspired data-driven solvers, such as neural operators, have ach...
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Federated Learning (FL) has emerged as a promising training framework that enables a server to effectively train a global model by coordinating multiple devices, i.e., clients, without sharing their raw data. Keeping ...
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Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decode...
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Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.
Because of the increasing number of threats in the IoT cloud, an advanced security mechanism is needed to guard data against hacking or attacks. A user authentication mechanism is also required to authenticate the use...
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Because of the increasing number of threats in the IoT cloud, an advanced security mechanism is needed to guard data against hacking or attacks. A user authentication mechanism is also required to authenticate the user accessing the cloud services. The conventional cryptographic algorithms used to provide security mechanisms in cloud networks are often vulnerable to various cyber-attacks and inefficient against new attacks. Therefore,developing new solutions based on different mechanisms from traditional cryptography methods is required to protect data and users' privacy from attacks. Different from the conventional cryptography method, we suggest a secure mutual authentication protocol based on the visual cryptography technique in this paper. We use visual cryptography to encrypt and decrypt the secret images. The mutual authentication is based on two secret images and *** user requests the ticket from the authentication server(AS) to obtain the permission for accessing the cloud services. Three shared secret keys are used for encrypting and decrypting the authentication process. We analyze the protocol using the Barrows-Abadi-Needham(BAN)-logic method and the results show that the protocol is robust and can protect the user against various attacks. Also, it can provide a secure mutual authentication mechanism.
In this paper,we focus on the Line-of-sight(LOS) information estimation for missiles with censored multi-dimensional *** this end,we first construct the nonlinear dynamic relative model between the missile and the tar...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In this paper,we focus on the Line-of-sight(LOS) information estimation for missiles with censored multi-dimensional *** this end,we first construct the nonlinear dynamic relative model between the missile and the target in 3D space to describe the correlated LOS ***,we build the measurement model including the censored measurement,which results from view limit constraints and uncensored measurement obtained from the geometric relationship or ***,an Improved Tobit Kalman filter is proposed to realize the measurement with two censoring limits and then the Improved Tobit Kalman filter is combined with the fifth-degree cubature Kalman filter to handle the nonlinearity of the dynamic ***,numerical simulations are given to demonstrate the effectiveness of our proposed algorithm.
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