It was tried to prepare the microcapsules containing grape polyphenol with the spray drying method followed by the layer-by-layer method. As grape polyphenol was water soluble, the spray drying method was adopted to o...It was tried to prepare the microcapsules containing grape polyphenol with the spray drying method followed by the layer-by-layer method. As grape polyphenol was water soluble, the spray drying method was adopted to obtain the higher content. As the shell material of the first microcapsules prepared by the spray drying method, palmitic acid with the melting point of 60°C was adopted in order to prevent grape polyphenol from dissolution into water. As the shell material of the second microcapsules prepared by the layer-by-layer method, chitosan was used to coat the first microcapsules and to give the microcapsules alcohol resistance. In the experiment, the spray drying conditions such as the inlet temperature and the spraying pressure, the oil soluble surfactant species and the chitosan concentration were changed. The mean diameters of microcapsules could be controlled in the range from 5 μm to 35 μm by changing the spraying pressure and the inlet temperature. The yield of microcapsules and the microencapsulation efficiency over 50% could be obtained under the conditions of P = 1.0 kgf/cm2 and Tin = 100°C. Furthermore, the microencapsulation efficiency could be increased by adding the oil soluble surfactant with the larger HLB value. Coating with chitosan could considerably increase alcohol resistance.展开更多
The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more prominent.The K-anonymity algorithm is an eff...The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more prominent.The K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big data.However,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data availability.In addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be reduced.Based on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data usability.Specifically,we construct a new information loss function based on the information quantity theory.Considering that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss function.In addition,to reduce information loss,we improve K-anonymity in two ways.First,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering algorithm.In addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of mass.Meanwhile,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information loss.Finally,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.展开更多
The reduced basis methods (RBM) have been demonstrated as a promising numerical technique for statics problems and are extended to structural dynamic problems in this paper. Direct step-by-step integration and mode su...The reduced basis methods (RBM) have been demonstrated as a promising numerical technique for statics problems and are extended to structural dynamic problems in this paper. Direct step-by-step integration and mode superposition are the most widely used methods in the field of the finite element analysis of structural dynamic response and solid mechanics. Herein these two methods are both transformed into reduced forms according to the proposed reduced basis methods. To generate a reduced surrogate model with small size, a greedy algorithm is suggested to construct sample set and reduced basis space adaptively in a prescribed training parameter space. For mode superposition method, the reduced basis space comprises the truncated eigenvectors from generalized eigenvalue problem associated with selected sample parameters. The reduced generalized eigenvalue problem is obtained by the projection of original generalized eigenvalue problem onto the reduced basis space. In the situation of direct integration, the solutions of the original increment formulation corresponding to the sample set are extracted to construct the reduced basis space. The reduced increment formulation is formed by the same method as mode superposition method. Numerical example is given in Section 5 to validate the efficiency of the presented reduced basis methods for structural dynamic problems.展开更多
During the past decade, increasing attention has been given to the development of meshless methods using radial basis functions for the numerical solution of Partial Differential Equations （PDEs）. A level set method...During the past decade, increasing attention has been given to the development of meshless methods using radial basis functions for the numerical solution of Partial Differential Equations （PDEs）. A level set method is a promising design tool for tracking, modelling and simulating the motion of free boundaries in fluid mechanics, combustion, computer animation and image processing. In the conventional level set methods, the level set equation is solved to evolve the interface using a capturing Eulerian approach. The solving procedure requires an appropriate choice of the upwind schemes, reinitialization, etc. Our goal is to include Multiquadric Radial Basis Functions （MQ RBFs） into the level set method to construct a more efficient approach and stabilize the solution process with the adaptive greedy algorithm. This paper presents an alternative approach to the conventional level set methods for solving moving-boundary problems. The solution was compared to the solution calculated by the exact explicit lime integration scheme. The examples show that MQ RBFs and adaptive greedy algorithm is a very promising calculation scheme.展开更多
机组排班计划是航空公司运营管理计划的重要组成部分,因其NP-hard特性常面临组合爆炸而难以求解。针对这一问题,提出一种基于航班环的优化模型。在第一阶段考虑执勤时空衔接约束与执勤始发终到约束,构建了航班间的航班环模型;在第二阶...机组排班计划是航空公司运营管理计划的重要组成部分,因其NP-hard特性常面临组合爆炸而难以求解。针对这一问题,提出一种基于航班环的优化模型。在第一阶段考虑执勤时空衔接约束与执勤始发终到约束,构建了航班间的航班环模型;在第二阶段设计了结合改进的深度优先搜索算法(depth-first search,DFS)以及贪心算法完成对模型的求解。此外,提出了列生成算法下受限主问题模型(restricted master problem model,RMP),并运用该模型完成实验验证算例的求解。展开更多
文摘It was tried to prepare the microcapsules containing grape polyphenol with the spray drying method followed by the layer-by-layer method. As grape polyphenol was water soluble, the spray drying method was adopted to obtain the higher content. As the shell material of the first microcapsules prepared by the spray drying method, palmitic acid with the melting point of 60°C was adopted in order to prevent grape polyphenol from dissolution into water. As the shell material of the second microcapsules prepared by the layer-by-layer method, chitosan was used to coat the first microcapsules and to give the microcapsules alcohol resistance. In the experiment, the spray drying conditions such as the inlet temperature and the spraying pressure, the oil soluble surfactant species and the chitosan concentration were changed. The mean diameters of microcapsules could be controlled in the range from 5 μm to 35 μm by changing the spraying pressure and the inlet temperature. The yield of microcapsules and the microencapsulation efficiency over 50% could be obtained under the conditions of P = 1.0 kgf/cm2 and Tin = 100°C. Furthermore, the microencapsulation efficiency could be increased by adding the oil soluble surfactant with the larger HLB value. Coating with chitosan could considerably increase alcohol resistance.
基金Foundation of National Natural Science Foundation of China(62202118)Scientific and Technological Research Projects from Guizhou Education Department([2023]003)+1 种基金Guizhou Provincial Department of Science and Technology Hundred Levels of Innovative Talents Project(GCC[2023]018)Top Technology Talent Project from Guizhou Education Department([2022]073).
文摘The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more prominent.The K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big data.However,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data availability.In addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be reduced.Based on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data usability.Specifically,we construct a new information loss function based on the information quantity theory.Considering that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss function.In addition,to reduce information loss,we improve K-anonymity in two ways.First,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering algorithm.In addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of mass.Meanwhile,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information loss.Finally,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.
文摘The reduced basis methods (RBM) have been demonstrated as a promising numerical technique for statics problems and are extended to structural dynamic problems in this paper. Direct step-by-step integration and mode superposition are the most widely used methods in the field of the finite element analysis of structural dynamic response and solid mechanics. Herein these two methods are both transformed into reduced forms according to the proposed reduced basis methods. To generate a reduced surrogate model with small size, a greedy algorithm is suggested to construct sample set and reduced basis space adaptively in a prescribed training parameter space. For mode superposition method, the reduced basis space comprises the truncated eigenvectors from generalized eigenvalue problem associated with selected sample parameters. The reduced generalized eigenvalue problem is obtained by the projection of original generalized eigenvalue problem onto the reduced basis space. In the situation of direct integration, the solutions of the original increment formulation corresponding to the sample set are extracted to construct the reduced basis space. The reduced increment formulation is formed by the same method as mode superposition method. Numerical example is given in Section 5 to validate the efficiency of the presented reduced basis methods for structural dynamic problems.
文摘During the past decade, increasing attention has been given to the development of meshless methods using radial basis functions for the numerical solution of Partial Differential Equations （PDEs）. A level set method is a promising design tool for tracking, modelling and simulating the motion of free boundaries in fluid mechanics, combustion, computer animation and image processing. In the conventional level set methods, the level set equation is solved to evolve the interface using a capturing Eulerian approach. The solving procedure requires an appropriate choice of the upwind schemes, reinitialization, etc. Our goal is to include Multiquadric Radial Basis Functions （MQ RBFs） into the level set method to construct a more efficient approach and stabilize the solution process with the adaptive greedy algorithm. This paper presents an alternative approach to the conventional level set methods for solving moving-boundary problems. The solution was compared to the solution calculated by the exact explicit lime integration scheme. The examples show that MQ RBFs and adaptive greedy algorithm is a very promising calculation scheme.
文摘机组排班计划是航空公司运营管理计划的重要组成部分,因其NP-hard特性常面临组合爆炸而难以求解。针对这一问题,提出一种基于航班环的优化模型。在第一阶段考虑执勤时空衔接约束与执勤始发终到约束,构建了航班间的航班环模型;在第二阶段设计了结合改进的深度优先搜索算法(depth-first search,DFS)以及贪心算法完成对模型的求解。此外,提出了列生成算法下受限主问题模型(restricted master problem model,RMP),并运用该模型完成实验验证算例的求解。
