对比模式挖掘是序列模式挖掘的一个重要分支,带有密度约束的对比模式有助于生物学家发现生物序列中的特殊因子的分布情况。为此,文中提出了MPDG(Mining distinguishing sequence Patterns based on Density and Gap constraint)算法,该...对比模式挖掘是序列模式挖掘的一个重要分支,带有密度约束的对比模式有助于生物学家发现生物序列中的特殊因子的分布情况。为此,文中提出了MPDG(Mining distinguishing sequence Patterns based on Density and Gap constraint)算法,该算法应用网树结构挖掘满足密度约束和间隙约束的对比模式,在仅需扫描一遍序列库的情况下,该算法可计算当前模式的所有超模式的支持度,从而提高挖掘效率。最后,在真实蛋白质数据集上进行实验,实验结果验证了MPDG算法的有效性。展开更多
序列模式挖掘是从序列数据中发现用户感兴趣的模式。对比模式挖掘是其中的一类挖掘方法,其特点是在两类或多类别的序列库中找到特征信息,在实际的生活和生产中应用十分广泛。随着数据规模的不断增加,算法的挖掘效率显得尤为重要,但是当...序列模式挖掘是从序列数据中发现用户感兴趣的模式。对比模式挖掘是其中的一类挖掘方法,其特点是在两类或多类别的序列库中找到特征信息,在实际的生活和生产中应用十分广泛。随着数据规模的不断增加,算法的挖掘效率显得尤为重要,但是当前对比模式挖掘仍存在挖掘速度太慢的问题。为了快速挖掘满足密度约束和间隙约束的对比模式,文中提出了一种近似求解算法ADMD(Approximately Distinguishing Patterns Mining Based on Density Constraint),该算法在模式的挖掘过程中允许存在小部分的模式丢失,从而换取挖掘速度的大幅提升。该算法采用网树的特殊结构来计算模式的支持数;采用模式拼接的方式来生成候选模式;采用预判式剪枝策略对模式进行剪枝,以避免大量冗余模式的生成。但由于在剪枝过程中可能会剪掉一部分非冗余模式,造成挖掘结果并非完备,因此该算法是一种近似求解算法。在ADMD算法的基础上,通过在剪枝策略中设定参数k的方式来得到ADMD-k算法,该算法可以通过设定k的取值来调整剪枝程度,从而在挖掘效率和准确率方面取得平衡。最后在真实的蛋白质数据集上将所提算法与其他算法从挖掘的对比模式数量和挖掘速度方面进行对比实验。实验结果表明,在k=1.5的情况下,所提算法仅用不到原来13%的时间,就可以挖掘到99%以上的模式,具有近似度高、速度快的特点。展开更多
针对单类分类器设计中的密度方法,采用以任务为导向的设计思想,通过人为指定核密度估计的密度函数上界,增强了边界低密度区域数据敏感性,同时也有效降低了密度估计的计算复杂度。进一步最大化全体样本的核密度估计函数并采用线性规划,...针对单类分类器设计中的密度方法,采用以任务为导向的设计思想,通过人为指定核密度估计的密度函数上界,增强了边界低密度区域数据敏感性,同时也有效降低了密度估计的计算复杂度。进一步最大化全体样本的核密度估计函数并采用线性规划,可快速得到相应的稀疏解,因而称之为最大化约束密度单类分类器(Maximum constrained density based one-class classifier,MCDOCC)。为充分利用单类数据中可能出现的极少量异常数据,进一步提出了带负类的最大化约束密度分类器(MCDOCC with negative data,NMCDOCC),通过挖掘异常数据的先验信息来修正仅有正常类的数据描述边界,可提高分类器泛化能力。UCI数据集上的实验结果表明,MCDOCC的泛化能力与单类支持向量机相当,NMCDOCC较之则有所提高,从而能够更高效地估计目标类数据概率密度。展开更多
We propose a new clustering algorithm that assists the researchers to quickly and accurately analyze data. We call this algorithm Combined Density-based and Constraint-based Algorithm (CDC). CDC consists of two phases...We propose a new clustering algorithm that assists the researchers to quickly and accurately analyze data. We call this algorithm Combined Density-based and Constraint-based Algorithm (CDC). CDC consists of two phases. In the first phase, CDC employs the idea of density-based clustering algorithm to split the original data into a number of fragmented clusters. At the same time, CDC cuts off the noises and outliers. In the second phase, CDC employs the concept of K-means clustering algorithm to select a greater cluster to be the center. Then, the greater cluster merges some smaller clusters which satisfy some constraint rules. Due to the merged clusters around the center cluster, the clustering results show high accuracy. Moreover, CDC reduces the calculations and speeds up the clustering process. In this paper, the accuracy of CDC is evaluated and compared with those of K-means, hierarchical clustering, and the genetic clustering algorithm (GCA) proposed in 2004. Experimental results show that CDC has better performance.展开更多
The high-frequency electromagnetic waves of ground-penetrating radar(GPR)attenuate severely when propagated in an underground attenuating medium owing to the influence of resistivity,which remarkably decreases the res...The high-frequency electromagnetic waves of ground-penetrating radar(GPR)attenuate severely when propagated in an underground attenuating medium owing to the influence of resistivity,which remarkably decreases the resolution of reverse time migration(RTM).As an effective high-resolution imaging method,attenuation-compensated RTM(ACRTM)can eff ectively compensate for the energy loss caused by the attenuation related to media absorption under the influence of resistivity.Therefore,constructing an accurate resistivity-media model to compensate for the attenuation of electromagnetic wave energy is crucial for realizing the ACRTM imaging of GPR data.This study proposes a resistivity-constrained ACRTM imaging method for the imaging of GPR data by adding high-density resistivity detection along the GPR survey line and combining it with its resistivity inversion profile.The proposed method uses the inversion result of apparent resistivity data as the GPR RTM-resistivity model for imposing resistivity constraints.Moreover,the hybrid method involving image minimum entropy and RTM is used to estimate the medium velocity at the diff raction position,and combined with the distribution characteristics of the reflection in the GPR profile,a highly accurate velocity model is built to improve the imaging resolution of the ACRTM.The accuracy and eff ectiveness of the proposed method are verified using the ACRTM test of the GPR simulated data of a typical attenuating media model.On this basis,the GPR and apparent resistivity data were observed on a field survey line,and use the GPR resistivity-constrained ACRTM method to image the observed data.A comparison of the proposed method with the conventional ACRTM method shows that the proposed method has better imaging depth,stronger energy,and higher resolution,and the obtained results are more conducive for subsequent data analysis and interpretation.展开更多
We determine the dependence of key inertial confinement fusion （ICF） hot spot properties on the deuterium-tritium （DT） fuel adiabat accomplished by addition of heat to the cold shell. Our main result is to observe...We determine the dependence of key inertial confinement fusion （ICF） hot spot properties on the deuterium-tritium （DT） fuel adiabat accomplished by addition of heat to the cold shell. Our main result is to observe that variation of this parameter reduces the simulation to experiment discrepancy in several experimentally inferred quantities. Simulations are continued from capsule only l D simulations using the Lawrence Livermore National Laboratory ICF code, HYDRA. The continuations employ the high energy density physics （HEDP） University of Chicago code, FLASH, and a hydro only code, FronTier, modified with a radiation equation of state （EOS） model. Hot spot densities, burn-weighted ion temperatures and pressures show a decreasing trend, while the hot spot radius shows an increasing trend in response to added heat to the cold shell. Instantaneous quantities are assessed at the time of maximum neutron production within each simulation.展开更多
The efficient utilization of metallic lithium(Li)is the key to enable application of Li metal full-cell with low amount of excess Li,contributing to higher safety and energy density.Herein,we report an extraordinary L...The efficient utilization of metallic lithium(Li)is the key to enable application of Li metal full-cell with low amount of excess Li,contributing to higher safety and energy density.Herein,we report an extraordinary Li metal full-cell with only 20%excess Li,which demonstrated significantly improved reversibility and high Coulombic efficiency.Ingenious simulated missile guidance and confinement system(SMGCS)was designed to guide and confine Li deposition through constructing compatible silver lithiophilic sites and nitrate layer.Silver sites act as effective Li nuclei to attract Li ions and direct the initial nucleation.The generated nitrate layer affords an interfacial environment favorable for confined and uniform deep Li deposition,which is theoretically verified by molecular dynamics(MD)simulations.The two combined merits offer a robust and dendrite-free Li deposition,enabling the application of Li metal full-cell with slight excess Li.They also result in an outperformed Li cycling efficiency of ca.99%for over 300 cycles along with deep cycling at a high capacity of 10 mA h cm^(-2)in carbonate electrolytes.The unprecedented high degree of Li utilization opens a new avenue for the future development of highly efficient Li metal full-cells.展开更多
文摘对比模式挖掘是序列模式挖掘的一个重要分支,带有密度约束的对比模式有助于生物学家发现生物序列中的特殊因子的分布情况。为此,文中提出了MPDG(Mining distinguishing sequence Patterns based on Density and Gap constraint)算法,该算法应用网树结构挖掘满足密度约束和间隙约束的对比模式,在仅需扫描一遍序列库的情况下,该算法可计算当前模式的所有超模式的支持度,从而提高挖掘效率。最后,在真实蛋白质数据集上进行实验,实验结果验证了MPDG算法的有效性。
文摘序列模式挖掘是从序列数据中发现用户感兴趣的模式。对比模式挖掘是其中的一类挖掘方法,其特点是在两类或多类别的序列库中找到特征信息,在实际的生活和生产中应用十分广泛。随着数据规模的不断增加,算法的挖掘效率显得尤为重要,但是当前对比模式挖掘仍存在挖掘速度太慢的问题。为了快速挖掘满足密度约束和间隙约束的对比模式,文中提出了一种近似求解算法ADMD(Approximately Distinguishing Patterns Mining Based on Density Constraint),该算法在模式的挖掘过程中允许存在小部分的模式丢失,从而换取挖掘速度的大幅提升。该算法采用网树的特殊结构来计算模式的支持数;采用模式拼接的方式来生成候选模式;采用预判式剪枝策略对模式进行剪枝,以避免大量冗余模式的生成。但由于在剪枝过程中可能会剪掉一部分非冗余模式,造成挖掘结果并非完备,因此该算法是一种近似求解算法。在ADMD算法的基础上,通过在剪枝策略中设定参数k的方式来得到ADMD-k算法,该算法可以通过设定k的取值来调整剪枝程度,从而在挖掘效率和准确率方面取得平衡。最后在真实的蛋白质数据集上将所提算法与其他算法从挖掘的对比模式数量和挖掘速度方面进行对比实验。实验结果表明,在k=1.5的情况下,所提算法仅用不到原来13%的时间,就可以挖掘到99%以上的模式,具有近似度高、速度快的特点。
文摘针对单类分类器设计中的密度方法,采用以任务为导向的设计思想,通过人为指定核密度估计的密度函数上界,增强了边界低密度区域数据敏感性,同时也有效降低了密度估计的计算复杂度。进一步最大化全体样本的核密度估计函数并采用线性规划,可快速得到相应的稀疏解,因而称之为最大化约束密度单类分类器(Maximum constrained density based one-class classifier,MCDOCC)。为充分利用单类数据中可能出现的极少量异常数据,进一步提出了带负类的最大化约束密度分类器(MCDOCC with negative data,NMCDOCC),通过挖掘异常数据的先验信息来修正仅有正常类的数据描述边界,可提高分类器泛化能力。UCI数据集上的实验结果表明,MCDOCC的泛化能力与单类支持向量机相当,NMCDOCC较之则有所提高,从而能够更高效地估计目标类数据概率密度。
文摘We propose a new clustering algorithm that assists the researchers to quickly and accurately analyze data. We call this algorithm Combined Density-based and Constraint-based Algorithm (CDC). CDC consists of two phases. In the first phase, CDC employs the idea of density-based clustering algorithm to split the original data into a number of fragmented clusters. At the same time, CDC cuts off the noises and outliers. In the second phase, CDC employs the concept of K-means clustering algorithm to select a greater cluster to be the center. Then, the greater cluster merges some smaller clusters which satisfy some constraint rules. Due to the merged clusters around the center cluster, the clustering results show high accuracy. Moreover, CDC reduces the calculations and speeds up the clustering process. In this paper, the accuracy of CDC is evaluated and compared with those of K-means, hierarchical clustering, and the genetic clustering algorithm (GCA) proposed in 2004. Experimental results show that CDC has better performance.
基金supported by the National Natural Science Foundation of China (No.41604102)the Guangxi Natural Science Foundation project (No.2020GXNSFAA159121).
文摘The high-frequency electromagnetic waves of ground-penetrating radar(GPR)attenuate severely when propagated in an underground attenuating medium owing to the influence of resistivity,which remarkably decreases the resolution of reverse time migration(RTM).As an effective high-resolution imaging method,attenuation-compensated RTM(ACRTM)can eff ectively compensate for the energy loss caused by the attenuation related to media absorption under the influence of resistivity.Therefore,constructing an accurate resistivity-media model to compensate for the attenuation of electromagnetic wave energy is crucial for realizing the ACRTM imaging of GPR data.This study proposes a resistivity-constrained ACRTM imaging method for the imaging of GPR data by adding high-density resistivity detection along the GPR survey line and combining it with its resistivity inversion profile.The proposed method uses the inversion result of apparent resistivity data as the GPR RTM-resistivity model for imposing resistivity constraints.Moreover,the hybrid method involving image minimum entropy and RTM is used to estimate the medium velocity at the diff raction position,and combined with the distribution characteristics of the reflection in the GPR profile,a highly accurate velocity model is built to improve the imaging resolution of the ACRTM.The accuracy and eff ectiveness of the proposed method are verified using the ACRTM test of the GPR simulated data of a typical attenuating media model.On this basis,the GPR and apparent resistivity data were observed on a field survey line,and use the GPR resistivity-constrained ACRTM method to image the observed data.A comparison of the proposed method with the conventional ACRTM method shows that the proposed method has better imaging depth,stronger energy,and higher resolution,and the obtained results are more conducive for subsequent data analysis and interpretation.
文摘We determine the dependence of key inertial confinement fusion （ICF） hot spot properties on the deuterium-tritium （DT） fuel adiabat accomplished by addition of heat to the cold shell. Our main result is to observe that variation of this parameter reduces the simulation to experiment discrepancy in several experimentally inferred quantities. Simulations are continued from capsule only l D simulations using the Lawrence Livermore National Laboratory ICF code, HYDRA. The continuations employ the high energy density physics （HEDP） University of Chicago code, FLASH, and a hydro only code, FronTier, modified with a radiation equation of state （EOS） model. Hot spot densities, burn-weighted ion temperatures and pressures show a decreasing trend, while the hot spot radius shows an increasing trend in response to added heat to the cold shell. Instantaneous quantities are assessed at the time of maximum neutron production within each simulation.
基金the National Natural Science Foundation of China(51622208,21703149,and 51872193)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)。
文摘The efficient utilization of metallic lithium(Li)is the key to enable application of Li metal full-cell with low amount of excess Li,contributing to higher safety and energy density.Herein,we report an extraordinary Li metal full-cell with only 20%excess Li,which demonstrated significantly improved reversibility and high Coulombic efficiency.Ingenious simulated missile guidance and confinement system(SMGCS)was designed to guide and confine Li deposition through constructing compatible silver lithiophilic sites and nitrate layer.Silver sites act as effective Li nuclei to attract Li ions and direct the initial nucleation.The generated nitrate layer affords an interfacial environment favorable for confined and uniform deep Li deposition,which is theoretically verified by molecular dynamics(MD)simulations.The two combined merits offer a robust and dendrite-free Li deposition,enabling the application of Li metal full-cell with slight excess Li.They also result in an outperformed Li cycling efficiency of ca.99%for over 300 cycles along with deep cycling at a high capacity of 10 mA h cm^(-2)in carbonate electrolytes.The unprecedented high degree of Li utilization opens a new avenue for the future development of highly efficient Li metal full-cells.
