查看更多>>摘要：The Blaschke-Minkowski homomorphisms was defined by Schuster.Recently,Wang extended its concept to Lp version.In this paper,we obtain affirmative and negative forms of the Shephard type problems for Lp geominimal surface areas with respect to the Lp Blaschke-Minkowski homomorphisms.
查看更多>>摘要：An H-covering(resp.decomposition) of a graph G is a set of subgraphs of G,{H1,H2,…,Hk } such that Hi is isomorphic to H for each i,and each edge of G belongs to at least (resp.ex actly) one of the subgraphs Hi,for 1 ≤ i ≤ k.An H-covering (resp.decomposition) of a graph G is a magic H-covering (resp.decomposition) if there is a bijection f:V(G)UE(G)→{1,…,|V(G)|+|E(G) |} such that the sum of labels of edges and the vertices of each copy of H in the decomposition is a constant.IfG admits a unique H-covering H and H is a magic H-covering of G,then G is H-magic.In this paper,we show that ifG admits a magic H-covering (resp.decomposition),and satisfies some other conditions,then a union ofk vertex joint graph G,kG,and a graph obtained from kG,Gk admit a magic H-covering or decomposition.
查看更多>>摘要：A fractal square F is essentially a planar self-similar set satisfying the set equation F=(F+D)/n with n≥2 and D (C) {0,1,...,n-1}2.In this paper,we study the topological classification of fractal squares in the case of n=4 and |D| =4.
查看更多>>摘要：In order to solve the problem that the krill herd (KH) algorithm is premature due to the decrease of population diversity,a new hybrid vortex search KH (VSKH) algorithm has been developed to deal with the global optimization problem.The improvement is that a new hybrid vortex search (HVS) operator is added into the updating process of the krill for the purpose of dealing with optimization problems more efficiently.Using 20 benchmark functions for comparison experiments,the results show that the VSKH algorithm has higher accuracy.
查看更多>>摘要：With the rapid development of social network in recent years,a huge number of social information has been produced.As traditional recommender systems often face data sparsity and cold-start problem,the use of social information has attracted many researchers' attention to improve the prediction accuracy of recommender systems.Social trust and social relation have been proven useful to improve the performance of recommendation.Based on the classic collaborative filtering technique,we propose a PCCTTF recommender method that takes the rating time of users,social trust among users,and item tags into consideration,then do the item recommending.Experimental results show that the PCCTTF method has better prediction accuracy than classical collaborative filtering technique and the state-of-the-art recommender methods,and can also effectively alleviate data sparsity and cold-start problem.Furthermore,the PCCTTF method has better performance than all the compared methods while counting against shilling attacks.
查看更多>>摘要：Rust is a system-level programming language that provides thread and memory safety guarantee through a suite of static compiler checking rules and prevents segmentation errors.However,since compiler checking is too strict to confine Rust's programmability,the developers prefer to use the keyword "unsafe" to bypass compiler checking,through which the caller could interact with OS directly.Unfortunately,the code block with "unsafe" would easily lead to some serious bugs such as memory safety violation,race condition and so on.In this paper,to verify memory and concurrency safety of Rust programs,we present RSMC (Safety Model Checker for Rust),a tool based on Smack to detect concurrency bugs and memory safety errors in Rust programs,in which we combine concurrency primitives model checking and memory boundary model checking.RSMC,with an assertion generator,can automatically insert assertions and requires no programmer annota tions to verify Rust programs.We evaluate RSMC on two categories of Rust programs,and the result shows that RSMC can effectively fmd concurrency bugs and memory safety errors in vulnerable Rust programs,which include unsafe code.
查看更多>>摘要：A Certificateless Aggregate Signature (CLAS) scheme was proposed by Qu and Mu recently,which was published in "Int.J.Electronic Security and Digital Forensics,2018,10 (2)".They used discrete logarithm to ensure the scheme's security.However,we show by formulating an attack that their CLAS scheme cannot defend against Type I adversary.Furthermore,we point out an error that exists in the signature simulation of their security proof.After that we give a correct signature simulation for the security proof.Finally,to resist the Type Ⅰ attack,we present two methods for improving Qu et al's CLAS scheme.Moreover,the second improving method can elevate the trust level of Qu et al's CLAS scheme to the highest trust level:Level 3.
查看更多>>摘要：As one of the underlying technologies of the blockchain,the consensus algorithm plays a vital role in ensuring security and efficiency.As a consensus algorithm for the private blockchain,Raft has better performance than the rest of the consensus algorithms,and it does not cause problems such as the concentrated hashing power,resource waste and fork.However,Raft can only be used in a non-byzantine environment with a small network size.In order to enable Raft to be used in a large-scale network with a certain number of byzantine nodes,this paper combines Raft and credit model to propose a Raft blockchain consensus algorithm based on credit model CRaft.In the node credit evaluation phase,RBF-based support vector machine is used as the anomaly detection method,and the node credit evaluation model is constructed.Then the Trust Nodes List (TNL) mechanism is introduced to make the consensus phase in a creditable network environment.Finally,the common node is synchronized to the consensus node to update the blockchain of the entire network.Experiments show that CRaft has better throughput and lower latency than the commonly used consortium blockchain consensus algorithm PBFT (Practical Byzantine Fault Tolerance).
查看更多>>摘要：With the development of the Internet of Things (IoT)technique,sensitive information collected by sensors may be leaked.In recent years,many authentication schemes have been proposed.Banerjee et al proposed a biometric based user authentication scheme in wireless sensor networks using smart cards in 2019.But we found that Banerjee et al's authentication scheme is vulnerable to impersonation attacks.In order to overcome the weaknesses of Banerjee et al's scheme,we propose a new authentication scheme.In our proposed scheme,we only use the exclusive-or operation and one-way Hash function for the efficiency,which can reduce the computation burden for the IoT devices.In the authentication and session key agreement phase,the secret registration parameter is not used for the authentication,and the session key is given for the all entities.In the Devol-Yao threat model,the security analysis demonstrates that our proposed authentication scheme can resist well-known attacks.
查看更多>>摘要：In order to find out the special cognitive emotional information to reach good accuracy in the recognition of anger emotions,the brain emotional oscillatory activity induced by relaxation and anger affective pictures is investigated in the amplitude measurement.A visual evoked affective experiment is designed and carried out to collect the electroencephalogram (EEG)data labeled with anger and relaxation emotion states.Twenty-one healthy college students (female 9,male 12) are employed to stimulate emotion by different affective pictures.Event-Related Spectral Perturbation (ERSP) is used to discover the pronounced features of anger tendency prediction in the time-frequency domain.ERSP maps exhibit that there is a difference between the female and male group,which is statistically significant within the 150-250 ms and 350-450 ms time range of alpha band.The male group is more susceptible to anger than female group,while the female group is faster in emotional regulation than the male group.These feature values could be used to identify the tendency of angry emotion,which can provide certain reference basis for further research on the predict the tendency of aggressive behavior.
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