Node classification is to predict the labels of the unlabeled nodes in a graph, which is useful for various applications of social network and biological information analysis. To measure the uncertainty of structural ...
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Meta-path-based methods for measuring the similarities between nodes in Heterogeneous information Networks (HINs) have attracted attention from researchers due to excellent performance. However, these methods suffer f...
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Node classification on heterogeneous graphs with multiple node types and relationships has been widely used in commodity classification, friend recommendation, and so on. Most of the existing models need to define the...
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Recent studies have shown that DNNs can be compromised by backdoor attacks crafted at training time. A backdoor attack installs a backdoor into the victim model by injecting a backdoor pattern into a small proportion ...
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Most existing quality of service (QoS) control algorithms of Web applications take into account Web Server or database connections which can be released immediately. However, many applications are deployed on virtual ...
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In Unsupervised Neural Machine Translation (UNMT) tasks, the lack of extensive parallel corpora makes it challenging for the model to directly optimize the correspondence between the source and target languages. UNMT ...
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With the continuous deepening of international anti-terrorism movement,the anti-terrorism has entered a new stage,and it is facing new *** of the new challenges is to extract useful and valuable information from massi...
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ISBN:
(数字)9781728158556
ISBN:
(纸本)9781728158563
With the continuous deepening of international anti-terrorism movement,the anti-terrorism has entered a new stage,and it is facing new *** of the new challenges is to extract useful and valuable information from massive data *** anti-terrorism system model based on local shallow information is imperfect,which is not conducive to obtaining accurate prediction *** shortcomings of existing research are the lack of comprehensive analysis and deeper mining of *** order to improve the efficiency and accuracy of the present anti-terrorism system,we propose an effective method for risk assessment and prediction based on machine learning by using Global Terrorism Database(GTD).There are four basic steps:first,we reduce the data dimension through correlation calculation and Singular Value Decomposition(SVD),then,the function is established to rank the harmfulness of terrorist attacks;second,the cascaded network with attention mechanism is used to predict suspects;third,k-means is used to cluster the regions of terrorist attacks,and then we establish a generalized linear regression model to predict the situation of terrorist *** verify the feasibility of the model by comparing with the real *** experimental results show that the proposed method can analyze and predict the information related to terrorist attacks comprehensively and accurately.
Mobile devices are widely used for data access,communications and ***,storing a private key for signature and other cryptographic usage on a single mobile device can be challenging,due to its computational ***,a numbe...
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Mobile devices are widely used for data access,communications and ***,storing a private key for signature and other cryptographic usage on a single mobile device can be challenging,due to its computational ***,a number of(t,n)threshold secret sharing schemes designed to minimize private key from leakage have been proposed in the ***,existing schemes generally suffer from key reconstruction *** this paper,we propose an efficient and secure two-party distributed signing protocol for the SM2 signature *** latter has been mandated by the Chinese government for all electronic commerce *** proposed protocol separates the private key to storage on two devices and can generate a valid signature without the need to reconstruct the entire private *** prove that our protocol is secure under nonstandard ***,we implement our protocol using MIRACL Cryptographic SDK to demonstrate that the protocol can be deployed in practice to prevent key disclosure.
Speech Emotions recognition has become the active research theme in speech processing and in applications based on human-machine interaction. In this work, our system is a two-stage approach, namely feature extraction...
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In a cloudcomputing environment, datacenter consists of number of servers, cooling and power delivery equipment's that require enormous measure of computational energy to drive complex frameworks. Due to the risi...
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