Semantic Communication (SemCom) is a promising new paradigm for next-generation communication systems, emphasizing the transmission of core information, particularly in environments characterized by uncertainty, noise...
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This paper presents a novel method that integrates the Algebraic Connectivity Strength of Point(ACSP) and Scoring Criteria to identify genes associated with tumor ***,for each gene,the ACSP is used to identify reliabl...
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This paper presents a novel method that integrates the Algebraic Connectivity Strength of Point(ACSP) and Scoring Criteria to identify genes associated with tumor ***,for each gene,the ACSP is used to identify reliable expression levels of the gene in all the *** informative genes are then selected using Scoring Criteria based on these reliable expression ***,the Support Vector Machine(SVM) classifier is used to classify the two datasets of gene expression *** results show that the informative genes selected by the proposed method have higher credibility than those selected by Scoring Criteria alone.
In this paper, we design an algorithm to address the challenges of expensive multi-objective optimization problems by improving the surrogate model and sampling criterion. Firstly, we introduce a combined model which ...
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In this paper, we design an algorithm to address the challenges of expensive multi-objective optimization problems by improving the surrogate model and sampling criterion. Firstly, we introduce a combined model which aims to enhance the impact of points that do not play a negative role, thus improving prediction accuracy. Subsequently, we develop two complementary indicators to accommodate various shapes of Pareto frontiers to better balance convergence and diversity in the sampling criterion. Experimental results on several benchmarks show that our proposed method is highly competitive in solving expensive multi-objective optimization problems compared to other state-of-the-art algorithms.
MicroRNAs(miRNAs)are closely related to numerous complex human diseases,therefore,exploring miRNA-disease associations(MDAs)can help people gain a better understanding of complex disease *** increasing number of compu...
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MicroRNAs(miRNAs)are closely related to numerous complex human diseases,therefore,exploring miRNA-disease associations(MDAs)can help people gain a better understanding of complex disease *** increasing number of computational methods have been developed to predict ***,the sparsity of the MDAs may hinder the performance of many *** addition,many methods fail to capture the nonlinear relationships of miRNA-disease network and inadequately leverage the features of network and neighbor *** this study,we propose a deep matrix factorization model with variational autoencoder(DMFVAE)to predict potential *** first decomposes the original association matrix and the enhanced association matrix,in which the enhanced association matrix is enhanced by self-adjusting the nearest neighbor method,to obtain sparse vectors and dense vectors,***,the variational encoder is employed to obtain the nonlinear latent vectors of miRNA and disease for the sparse vectors,and meanwhile,node2vec is used to obtain the network structure embedding vectors of miRNA and disease for the dense ***,sample features are acquired by combining the latent vectors and network structure embedding vectors,and the final prediction is implemented by convolutional neural network with channel *** evaluate the performance of DMFVAE,we conduct five-fold cross validation on the HMDD v2.0 and HMDD v3.2 datasets and the results show that DMFVAE performs ***,case studies on lung neoplasms,colon neoplasms,and esophageal neoplasms confirm the ability of DMFVAE in identifying potential miRNAs for human diseases.
The limit behaviors of computations have not been fully *** is necessary to consider such limit behaviors when we consider the properties of infinite objects in computer science,such as infinite logic programs,the sym...
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The limit behaviors of computations have not been fully *** is necessary to consider such limit behaviors when we consider the properties of infinite objects in computer science,such as infinite logic programs,the symbolic solutions of infinite polynomial ***,we can use finite objects to approximate infinite objects,and we should know what kinds of infinite objects are approximable and how to approximate them effectively.A sequence {Rκ:κω}of term rewriting systems has the well limit behavior if under the condition that the sequence has the Set-theoretic limit or the distance-based limit,the sequence {Th(Rκ):κ∈ω} of corresponding theoretic closures of Rκ has the set-theoretic or distance-based limit,and limκ→∞ Th(Rκ) is equal to the theoretic closure of the limit of {Rκ:κ∈ω).Two kinds of limits of term rewriting systems are considered:one is based on the set-theoretic limit,the other is on the distance-based *** is proved thatgiven a sequence {Rκ:κ∈ω) of term rewriting systems Rκ,if there is a well-founded ordering (-<) on terms such that every Rκ is (-<)-well-founded,and the set-theoretic limit of {Rκ:κ∈ω).exists,then {Rκ:κ∈ω).has the well limit behavior;and if (1) there is a well-founded ordering(-<)on terms such that every Rκ is(-<-well-founded,(2) there is a distance d on terms which is closed under substitutions and contexts and (3) {Rκ:κ∈ω).is Cauchy under d then {Rκ:κ∈ω).has the well limit *** results are used to approximate the least Herbrand models of infinite Horn logic programs and real Horn logic programs,and the solutions and Cr(o)bner bases of (infinite) sets of real polynomials by sequences of (finite) sets of rational polynomials.
In this paper, an improved multi-strategy ontology mapping method is proposed to improve the accuracy of the ontology mapping. The structural characteristics of ontology and the effect of instance mapping upon the sim...
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Traditional secret sharing scheme generally exists two shortages:each participant's sub-secret key is distributed by the certification center;the sub-secret keys can not be repeated to use. Both shortages brought ...
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According to the functional demand of intelligent Test Paper system, we have designed four functional modules: examination database, test paper-generation, grade analysis and system setup. Test paper generation module...
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A novel image auto-annotation method is presented based on probabilistic latent semantic analysis(PLSA) model and multiple Markov random fields(MRF).A PLSA model with asymmetric modalities is first constructed to esti...
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A novel image auto-annotation method is presented based on probabilistic latent semantic analysis(PLSA) model and multiple Markov random fields(MRF).A PLSA model with asymmetric modalities is first constructed to estimate the joint probability between images and semantic concepts,then a subgraph is extracted served as the corresponding structure of Markov random fields and inference over it is performed by the iterative conditional modes so as to capture the final annotation for the *** novelty of our method mainly lies in two aspects:exploiting PLSA to estimate the joint probability between images and semantic concepts as well as multiple MRF to further explore the semantic context among keywords for accurate image *** demonstrate the effectiveness of this approach,an experiment on the Corel5 k dataset is conducted and its results are compared favorably with the current state-of-the-art approaches.
Click-through rate (CTR) prediction aims to estimate the probability of a user clicking on a particular item, making it one of the core tasks in various recommendation platforms. In such systems, user behavior data ar...
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