In propositional normal default logic, given a default theory(?, D) and a well-defined ordering of D, there is a method to construct an extension of(?, D) without any injury. To construct a strong extension of(?, D) g...
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In propositional normal default logic, given a default theory(?, D) and a well-defined ordering of D, there is a method to construct an extension of(?, D) without any injury. To construct a strong extension of(?, D) given a well-defined ordering of D, there may be finite injuries for a default δ∈ D. With approximation deduction ?s in propositional logic, we will show that to construct an extension of(?, D) under a given welldefined ordering of D, there may be infinite injuries for some default δ∈ D.
In many realistic scenarios,such as political election and viral marketing,two opposite opinions,i.e.,positive opinion and negative opinion,spread simultaneously in the same social networks[1,2].Consequently,to achiev...
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In many realistic scenarios,such as political election and viral marketing,two opposite opinions,i.e.,positive opinion and negative opinion,spread simultaneously in the same social networks[1,2].Consequently,to achieve good word-of-mouth effect,it is desired to maximize the spread of posi-
Performance degradation or system resource exhaustion can be attributed to inadequate computing resources as a result of software *** the real world,the workload of a web server varies with time,which will cause a non...
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Performance degradation or system resource exhaustion can be attributed to inadequate computing resources as a result of software *** the real world,the workload of a web server varies with time,which will cause a nonlinear aging *** nonlinear property often makes analysis and modelling *** is one of the important factors influencing the speed of *** paper quantitatively analyzes the workload-aging relation and proposes a framework for aging control under varying *** addition,this paper proposes an approach that employs prior information of workloads to accurately forecast incoming system *** workload data are used as a threshold to divide the system resource usage data into multiple sections,while in each section the workload data can be treated as a *** section is described by an individual autoregression(AR)*** with other AR models,the proposed approach can forecast the aging process with a higher accuracy.
A B4-valued propositional logic will be proposed in this paper which there are three unary logical connectives ～1, ～2, ┐ and two binary logical connectives A, v, and a Gentzen-typed deduction system will be given s...
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A B4-valued propositional logic will be proposed in this paper which there are three unary logical connectives ～1, ～2, ┐ and two binary logical connectives A, v, and a Gentzen-typed deduction system will be given so that the system is sound and complete with B4-valued semantics, where B4 is a Boolean algebra.
Based on local algorithms,some parallel finite element(FE)iterative methods for stationary incompressible magnetohydrodynamics(MHD)are *** approaches are on account of two-grid skill include two major phases:find the ...
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Based on local algorithms,some parallel finite element(FE)iterative methods for stationary incompressible magnetohydrodynamics(MHD)are *** approaches are on account of two-grid skill include two major phases:find the FE solution by solving the nonlinear system on a globally coarse mesh to seize the low frequency component of the solution,and then locally solve linearized residual subproblems by one of three iterations(Stokes-type,Newton,and Oseen-type)on subdomains with fine grid in parallel to approximate the high frequency *** error estimates with regard to two mesh sizes and iterative steps of the proposed algorithms are *** numerical examples are implemented to verify the algorithm.
Deep learning methods can enhance the efficiency of tumor segmentation in breast ultrasound (BUS) images. However, noise interference, small tumors, and blurred boundaries can reduce segmentation accuracy. We design a...
Deep learning methods can enhance the efficiency of tumor segmentation in breast ultrasound (BUS) images. However, noise interference, small tumors, and blurred boundaries can reduce segmentation accuracy. We design a three-branch challenge-aware U-net (CAU-net) to address these main challenges in BUS images. Our CAU-net extracts the features from three challenge-aware encoders in parallel first. Secondly, we propose an adaptive aggregation layer (AAL) to merge the multi-scale features of three challenging branches, enabling the network to adaptively handle different breast lesion samples with these main challenges. To further enhance the accuracy of segmentation, we introduce the graph reasoning module (GRM) to the network to model the correlation between the channels of the features and acquire the global information in the features. The result of our experiment on two datasets demonstrates the superiority of CAU-net over the advanced medical image segmentation methods. Our code can be downloaded from https://***/tzz-ahu .
In this paper, we propose a method to improve localization algorithm of maximum likelihood estimation;the localization scheme relies on the distance threshold. In order to suppress effectively the effects of received ...
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ISBN:
(纸本)9781509038237;9781509038220
In this paper, we propose a method to improve localization algorithm of maximum likelihood estimation;the localization scheme relies on the distance threshold. In order to suppress effectively the effects of received signal strength error to node localization precision. This paper presents an indoor localization algorithm based on received signal strength to select anchor nodes. Compared with the traditional localization algorithm, this scenario not only improve the localization accuracy, but also reduce the calculation complexity of nodes. The simulation results show that the average error of the proposed method is less than 0.15 m. Moreover, when there are a large number of anchor nodes, the computational complexity is effectively reduced. Verification result verifies the effectiveness and reliability of the algorithm.
Although SnO_2-based nanomaterials used to be considered as being extraordinarily versatile for application to nanosensors,microelectronic devices, lithium-ion batteries, supercapacitors and other devices, the functio...
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Although SnO_2-based nanomaterials used to be considered as being extraordinarily versatile for application to nanosensors,microelectronic devices, lithium-ion batteries, supercapacitors and other devices, the functionalities of SnO_2-based nanomaterials are severely limited by their intrinsic vulnerabilities. Facile electrospinning was used to prepare SnO_2 nanofibers coated with a protective carbon layer. The mechanical properties of individual core-shell-structured SnO_2@C nanofibers were investigated by atomic force microscopy and the finite element method. The elastic moduli of the carbon-coated SnO_2 nanofibers remarkably increased, suggesting that coating SnO_2 nanofibers with carbon could be an effective method of improving their mechanical properties.
Dear editor,Rectilinear Steiner minimal tree(RSMT)has been widely used in several modern very large scale integration(VLSI)circuit design *** of its importance,it has been fully studied in the past *** addition,the de...
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Dear editor,Rectilinear Steiner minimal tree(RSMT)has been widely used in several modern very large scale integration(VLSI)circuit design *** of its importance,it has been fully studied in the past *** addition,the density of modern VLSI chips has increased *** today’s VLSI designs,there are increasingly more obstacles,such as IP blocks and pre-routed nets,these
The traditional double-threshold endpoint detection method has the phenomenon of missing detection. Therefore, the speech recognition(SR) system based on vector quantization(VQ) in this paper proposes an improved algo...
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ISBN:
(纸本)9781509038237;9781509038220
The traditional double-threshold endpoint detection method has the phenomenon of missing detection. Therefore, the speech recognition(SR) system based on vector quantization(VQ) in this paper proposes an improved algorithm for this phenomenon, which effectively avoids the problem of missing detection. Then, Mel Frequency Cepstral Coefficients(MFCC) is used to extract the characteristic parameters of the speech signal, and the multistage vector quantization is used to quantify the characteristic parameters. Experimental results show that, the proposed algorithm improves the recognition rate of the text-independent speaker recognition system by 8.7%, and it also confirms that the longer the training speech is, the higher the recognition rate will be.
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