高校机构知识库灰色文献质量控制研究

分析高校机构知识库中灰色文献的特点以及存在的质量控制问题,并提出一种灰色文献质量控制的方法．通过构建灰色文献的评价指标体系及其权重和用户可信度评价指标体系及其权重,从而获得灰色文献的评价权值．根据评价权值以及分组标准将文献进行分组,再对不同的分组赋予不同的访问权限,从而完成机构知识库灰色文献质量控制机制的构建．     

THE JANUS TEST: A HIERARCHICAL ALGORITHM FOR COMPUTING DIRECTION AND DISTANCE VECTORS (EXTENDED VERSION)*

For a compiler, dependence direction vectors are the key structure for many loop parallelizing transformations. More powerful transformations require knowing the values of the associated distances. However, this generally involves solving many problems. In this paper, we consider a hierarchical set of problems which differ only in direction vectors, as in the framework introduced by Burke and Cytron. Firstly, we solve the basic problem of the existence of a dependence without direction constraints, using a fast and exact algorithm composed of a pre-processing phase of reduction and of an integer simplex resolution. We propose a new “basic” algorithm. Secondly, if a solution exists, we define three new problems, each of them being obtained by adding a constraint associated with one of the three possible direction vectors relative to the first loop index. For each of these problems, if a solution exists, we define three enlarged similar problems involved by the second loop index, and so forth until the last index. The amount of computation for each new problem is very low. Information on the values of the distances is provided. The Janus Test, implemented at INRIA, has been embedded in the parallelizer built within the esprit project Compare and in the PARTITA tool of the EUREKA project EUROTOPS. Due to its robustness, it could be applied to more complex problems in data dependence and data flow analysis.     

数据驱动的智能车辆目标检测能力测试评价方法

本文针对智能车辆目标检测能力测评存在的指标体系不完整、量化程度和测评实时性低等问题,聚焦智能车辆目标检测能力中的目标分类和目标识别,在这两个测评项目上提出了一套量化的评价指标体系,并用TOPSIS方法进行综合的评价.然后在此指标体系的基础上搭建数据驱动的智能车辆目标检测能力测评平台,平台可满足对智能车辆目标检测能力测评的实时性要求.最后采用了若干组车辆检测算法对指标体系进行验证.     

Symmetric positive solutions of fourth order integral BVP for an increasing homeomorphism and homomorphism with sign-changing nonlinearity on time scales

In this paper, we consider the eigenvalue problems for fourth order integral boundary value problems on time scales for an increasing homeomorphism and homomorphism with sign changing nonlinearities. By using a fixed point index theorem, we give the existence of eigenvalue intervals in which there exist one symmetric positive solution to the problem. An example is also given to demonstrate the main results.     

Computing Prime Factorization And Discrete Logarithms: From Index Calculus To Xedni Calculus

The integer factorization problem (IFP), the finite field discrete logarithm problem (DLP) and the elliptic curve discrete logarithm problem (ECDLP) are essentially the only three mathematical problems that the practical public-key cryptographic systems are based on. For example, the most famous RSA cryptosystem is based on IFP, the US government's Digital Signature Standard, DSS, is based on DLP, whereas the ECC (Elliptic Curve Cryptography) and Elliptic Curve Digital Signature Algorithm (ECDSA) are based on ECDLP. The security of such cryptographic systems relies on the computational intractability of these three mathematical problems. In this paper, we shall present a survey of various methods for solving the IFP/DLP and particularly the ECDLP problems. More specifically, we shall first discuss how the index calculus as well as quantum algorithms can be used to solve IFP/DLP. Then we shall show why the index calculus cannot be used to solve ECDLP. Finally, we shall introduce a new method, xedni calculus , due to Joseph Silverman, for attack ECDLP; some open problems and new research directions, will also be addressed.     

A tree-structured index allocation method with replication over multiple broadcast channels in wireless environments

Broadcast has often been used to disseminate frequently requested data efficiently to a large volume of mobile units over single or multiple channels. Since mobile units have limited battery power, the minimization of the access and tuning times for the broadcast data is an important problem. There have been many research efforts that focus on minimizing access and tuning times by providing indexes on the broadcast data. We have studied an efficient index allocation method for broadcast data with skewed access frequencies over multiple physical channels which cannot be coalesced into a single high bandwidth channel. Previously proposed index allocation techniques have one of two problems. The first problem is that they require equal size for both index and data. The second problem is that their performance degrades when the number of given physical channels is not enough. These two problems result in an increased average access time for the broadcast data. To cope with these problems, we propose a tree-structured index allocation method. Our method minimizes the average access time by broadcasting the hot data and their indices more frequently than the less hot data and their indexes over the dedicated index and data channels. We present an in-depth experimental and theoretical analysis of our method by comparing it with other similar techniques. Our performance analysis shows that it significantly decreases the average access and tuning times for the broadcast data over existing methods.     

混合性能指标优化问题的进化优化方法及应用

针对混合性能指标优化问题的普遍性及其处理过程中的特点,提出一种混合性能指标优化问题的进化优化方法,首先给出混合性能指标优化问题的定义;然后．确定不同类型和标度的性能指标的转换策略、混合性能指标的个体适应度的赋值方法、以及混合性能指标优化问题的进化优化流程;最后．通过服装设计这一典型的混合性能指标优化问题的仿真验证了算法的有效性．     

基于BSC-AHP的绩效评估模型研究与实现

为了解决企业战略目标执行难的问题,提升绩效评估合理性。笔者在深入研究现存理论和方法的基础上,采用平衡记分卡理论从企业战略目标中提取关键评估指标,并提出了用分解矩阵的方法将评估指标分解到各评估对象。最后引用层次分析法确定各指标权重。建立了引导、鼓励员工工作向有利于企业战略的执行与控制的绩效评估指标体系和评价模型。开发的系统在某印刷企业得到应用并取得良好效果,有效证明了模型的可行性和科学性。     

FoxBASE^＋数据库操作使用中的问题

本文论述了ＦＯＸＢＡＳＥ＋被据库操作使用中组合索引、ＭＮＤ和ＳＥＥＫ命令组合查找中的某些问题，并给出了正确的操作与使用方法．     

索引算法及其在图像多尺度变换中的应用

给出了几种索引算法模型,然后分析了整数提升小波变换的性质,针对其索引算法的索引矩阵存储空间问题,对5/3小波变换进行改造,提出了一个新的图像多尺度变换,该变换后得到高频系数和低频系数的动态范围与原始图像像素值的动态范围相同,从而可实现多级可逆索引算法。实验结果显示,基于索引算法的图像多尺度变换的速度较普通方法有显著提高。     

Guaranteed cost control of uncertain nonlinear systems via polynomial lyapunov functions

In this paper, we consider the problem of guaranteed cost control for a class of uncertain nonlinear systems. We derive linear matrix inequality conditions for the regional robust stability and performance problems based on Lyapunov functions which are polynomial functions of the state and uncertain parameters. The performance index is calculated over a set of initial conditions. Also, we discuss the synthesis problem for a class of affine control systems. Numerical examples illustrate our method.     

Vertex-Edge Degree Based Indices of Honey Comb Derived Network

Chemical graph theory is a branch of mathematics which combines graph theory and chemistry. Chemical reaction network theory is a territory of applied mathematics that endeavors to display the conduct of genuine compound frameworks. It pulled the research community due to its applications in theoretical and organic chemistry since 1960. Additionally, it also increases the interest the mathematicians due to the interesting mathematical structures and problems are involved. The structure of an interconnection network can be represented by a graph. In the network, vertices represent the processor nodes and edges represent the links between the processor nodes. Graph invariants play a vital feature in graph theory and distinguish the structural properties of graphs and networks. In this paper, we determined the newly introduced topological indices namely, first -degree Zagreb index, first -degree Zagreb index, second -degree Zagreb index, -degree Randic index, -degree atom-bond connectivity index, -degree geometric-arithmetic index, -degree harmonic index and -degree sum-connectivity index for honey comb derived network. In the analysis of the quantitative structure property relationships (QSPRs) and the quantitative structureactivity relationships (QSARs), graph invariants are important tools to approximate and predicate the properties of the biological and chemical compounds. Also, we give the numerical and graphical representation of our outcomes.     

Evolutionary algorithms for optimization problems with uncertainties and hybrid indices

Many optimization problems in real-world applications contain both explicit (quantitative) and implicit (qualitative) indices that usually contain uncertain information. How to effectively incorporate uncertain information in evolutionary algorithms is one of the most important topics in information science. In this paper, we study optimization problems with both interval parameters in explicit indices and interval uncertainties in implicit indices. To incorporate uncertainty in evolutionary algorithms, we construct a mathematical uncertain model of the optimization problem considering the uncertainties of interval objectives; and then we transform the model into a precise one by employing the method of interval analysis; finally, we develop an effective and novel evolutionary optimization algorithm to solve the converted problem by combining traditional genetic algorithms and interactive genetic algorithms. The proposed algorithm consists of clustering of a large population according to the distribution of the individuals and estimation of the implicit indices of an individual based on the similarity among individuals. In our experiments, we apply the proposed algorithm to an interior layout problem, a typical optimization problem with both interval parameters in the explicit index and interval uncertainty in the implicit index. Our experimental results confirm the feasibility and efficiency of the proposed algorithm.     

Optimal control for unstructured nonlinear differential-algebraic equations of arbitrary index

We study optimal control problems for general unstructured nonlinear differential-algebraic equations of arbitrary index. In particular, we derive necessary conditions in the case of linear-quadratic control problems and extend them to the general nonlinear case. We also present a Pontryagin maximum principle for general unstructured nonlinear DAEs in the case of restricted controls. Moreover, we discuss the numerical solution of the resulting two-point boundary value problems and present a numerical example. This research was supported through the Research-in-Pairs Program at Mathematisches Forschungsinstitut Oberwolfach. V. Mehrmann’s research was supported by Deutsche Forschungsgemeinschaft, through Matheon, the DFG Research Center “Mathematics for Key Technologies” in Berlin.     

Pythagorean Fuzzy Clustering Analysis: A Hierarchical Clustering Algorithm with the Ratio Index‐Based Ranking Methods

The Pythagorean fuzzy set introduced by R. R. Yager in 2014 is a useful tool to model imprecise and ambiguous information appearing in decision and clustering problems. In this study, we present a general type of distance measure for Pythagorean fuzzy numbers (PFNs) and propose a novel ratio index‐based ranking method of PFNs. The novel ranking method of PFNs has more powerful ability to discriminate the magnitude of PFNs than the existing ranking methods for PFNs, which is further extended to compare the magnitude of interval‐valued Pythagorean fuzzy numbers (IVPFNs). The IVPFN is a new extension of PFN, which is parallel to interval‐valued intuitionistic fuzzy number. We introduce a general type of distance measure for IVPFNs. Afterwards, we study a kind of clustering problems in Pythagorean fuzzy environments in which the evaluation values are expressed by PFNs and/or IVPFNs and develop a novel Pythagorean fuzzy agglomerative hierarchical clustering approach. In the proposed clustering method, we define the concept of the dissimilarity degree between two clusters for each criterion and introduce the clustering procedure in the criteria level. To take all the criteria into account, we also introduce the overall clustering procedure, which is based on the overall dissimilarity degrees for a fixed aggregation operator such as the commonly used weighted arithmetic average operator or the ordered weighted averaging operator. In the overall clustering process, (1) we present a deviation degree‐based method to derive the weights of criteria and further obtain the overall clustering results if the weights of criteria are completely unknown; (2) we employ the ratio index‐based ranking method of IVPFNs to obtain the overall clustering results if the weights of criteria are given in advance and are expressed by IVPFNs. The salient feature of the proposed clustering method is that it not only can address the clustering problems in which the weights of criteria are not given precisely in advance but also can manage simultaneously the PFNs and IVPFNs data.     

多指标决策中隶属度转换算法及其应用

隶属度转换涉及了众多应用领域, 但是, 目前已有的隶属度转换算法仍然存在如下问题: 给出的转换算法不能揭示指标隶属度中哪部分对目标分类有用, 从而导致了指标隶属度中原本对目标分类不起作用的冗余数值也被用于计算目标隶属度. 针对已有隶属度转换算法中存在的冗余数据问题, 本文从对目标分类的角度设计了一种滤波器, 可以识别对目标分类不起作用的冗余的指标隶属度和指标隶属度中的冗余数值, 并从指标隶属度中分离出对目标分类起作用的``有效值', 参与计算目标隶属度; 最终建立实现由指标隶属度到目标隶属度转换的一般算法. 应用实例说明了转换的全过程.     

On compatibility of uncertain additive linguistic preference relations based on the linguistic COWA operator

We develop a new compatibility for the uncertain additive linguistic preference relations and study its properties which are very suitable to deal with group decision making (GDM) problems involving uncertain additive linguistic preference relations. Based on the linguistic continuous ordered weighted averaging (LCOWA) operator, we present some concepts of the compatibility degree and compatibility index for the two uncertain additive linguistic preference relations. Then, we study some desirable properties including the property that the synthetic uncertain linguistic preference relation is of acceptable compatibility under the condition that uncertain additive linguistic preference relations given by experts are all of acceptable compatibility with the ideal uncertain linguistic preference relation, which provides a theoretic basis for the application of the uncertain additive linguistic preference relations in GDM. In order to determine the weights of experts, we construct an optimal model based on the criterion of minimizing the compatibility index in GDM. Finally, we propose a new approach based on the compatibility index and the expected additive linguistic preference relation to GDM and develop an application of the optimal weights approach compared with the equal weights approach where we analyze a GDM regarding the evaluation of schools in a university.     

On optimal output regulation for linear systems

The classical output regulation problem formulation for linear systems has a number of shortcomings; among them a primary one is that it does not take into account the transient response. Although this problem has been studied since the 1970s, a complete picture has not emerged yet. We formulate and study here a number of output regulation problems which incorporate the notion of transient performance into them. By defining a performance index that involves transient response, we define optimal and suboptimal control problems which are constrained by the steady state output regulation requirement. Such constrained optimal and suboptimal control problems for a given system are studied by transforming them to unconstrained optimal and suboptimal control problems for certain auxiliary systems. Several issues such as obtaining expressions for the infimal performance measure, solvability conditions, regulator construction are studied in detail. Both state and measurement feedback controllers are considered.     

Efficient storage and retrieval of probabilistic latent semantic information for information retrieval

Probabilistic latent semantic analysis (PLSA) is a method for computing term and document relationships from a document set. The probabilistic latent semantic index (PLSI) has been used to store PLSA information, but unfortunately the PLSI uses excessive storage space relative to a simple term frequency index, which causes lengthy query times. To overcome the storage and speed problems of PLSI, we introduce the probabilistic latent semantic thesaurus (PLST); an efficient and effective method of storing the PLSA information. We show that through methods such as document thresholding and term pruning, we are able to maintain the high precision results found using PLSA while using a very small percent (0.15%) of the storage space of PLSI.     

Conditions for generic normality in optimal control

Optimal control problems in which the necessary conditions of Pontryagin's maximum principle do not involve the cost or performance index are called abnormal. In this paper we study normality through perturbations of the endpoint set. It is known that normality holds for all problems obtained by translating the original endpoint set in directions belonging to a dense set. When the equations of motion are linear in the state variable, we enlarge this set of directions to a full (Lebesgue) measure set, showing that its complement is contained in the relative boundary of a convex set. For nonlinear systems we show that by enlarging the endpoint set, instead of translating it, normality is also guaranteed almost everywhere.