An algebraic framework for temporal attribute characteristics

Most real-world database applications manage temporal data, i.e., data with associated time references that capture a temporal aspect of the data, typically either when the data is valid or when the data is known. Such applications abound in, e.g., the financial, medical, and scientific domains. In contrast to this, current database management systems offer preciously little built-in query language support for temporal data management. This situation persists although an active temporal database research community has demonstrated that application development can be simplified substantially by built-in temporal support. This paper's contribution is motivated by the observation that existing temporal data models and query languages generally make the same rigid assumption about the semantics of the association of data and time, namely that if a subset of the time domain is associated with some data then this implies the association of any further subset with the data. This paper offers a comprehensive, general framework where alternative semantics may co-exist. It supports so-called malleable and atomic temporal associations, in addition to the conventional ones mentioned above, which are termed constant. To demonstrate the utility of the framework, the paper defines a characteristics-enabled temporal algebra, termed CETA, which defines the traditional relational operators in the new framework. This contribution demonstrates that it is possible to provide built-in temporal support while making less rigid assumptions about the data and without jeopardizing the degree of the support. This moves temporal support closer to practical applications.     

Symbolic computation and the cyclicity problem for singularities

We show how methods of computational commutative algebra are employed to investigate the local 16th Hilbert Problem, which is to find an upper bound on the number of limit cycles that can bifurcate from singularities in families of polynomial systems of differential equations on R²${\mathbb{R}}^2$, and is one step in a program for solving the full 16th Hilbert Problem. We discuss an extension of a well-known theorem, and illustrate the concepts and methods with concrete examples.     

Formalization of interrelations between operators and data within the framework of an extended algebra of algorithms

A system of algorithmic algebras is considered whose basic concepts are newly interpreted to formalize the interrelation between operators and data of such a system. A modified formal instrument is constructed that extends the possibilities of design and transformation of regular schemes of algorithms. Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 170–182, November–December 2008.     

移动机器人最优路径的表示、对称性及算法

针对由两个轮子独立驱动的移动机器人，从最优速度模式的角度寻求最优路径，利用极大值原理和Hamilton算子得出一种结构简单的最优路径表示形式，并解决了其跟踪控制问题．通过对不同转弯模式下的最优路径进行分析和比较，给出了基于路径长度和转动角度准则的最优路径实现算法，并提出了最优路径的对称性及其跟踪控制算法．该方法大大降低了设计和计算的复杂性，简单实用．     

二进制数据流通用翻译框架及实现

为了辅助xDSL Modem开发人员做好固件程序的测试工作,提出了一个通用的二进制数据流翻译方案。它能够根据某个协议标准将Modem产生的二进制数据流转换成人们容易理解的形式,从而帮助开发人员快速判定Modem中的固件程序是否符合那个协议标准。同时,为了保证翻译程序不受协议版本变动的影响,将协议标准的内容以协议规则的形式存于外部文件。不同于现有的描述方式,提出了一个灵活且完备的协议规则描述方式,指出了协议规则应具备的10个属性。最后,实现了一个原型系统,并以国际通信联盟标准事业部的G.994.1协议标准为例验证了该翻译方案的有效性。     

多路径测试数据自动生成方法及应用

以程序结构测试自动生成为研究背景,提出了一种重叠路径结构用以描述程序路径,并以此为基础设计了一种多路径测试数据生成适应值算法,实现了一次搜索完成多条路径的测试数据生成。算法通过目标路径间共享遗传算法产生的中间个体减少单一路径搜索始于随机产生的无序个体的初期迭代,从而加快搜索收敛的速度。应用于常用的基准程序和取自实际项目的程序,该算法与典型的分支谓词距离算法相比平均消耗时间缩短了70.6%。     

Medical image segmentation, volume representation and registration using spheres in the geometric algebra framework

This paper presents an algorithm to model volumetric data and other one for non-rigid registration of such models using spheres formulated in the geometric algebra framework. The proposed algorithm for modeling, as opposite to the Union of Spheres method, reduces the number of entities (spheres) used to model 3D data. Our proposal is based in marching cubes idea using, however, spheres, while the Union of Spheres uses Delaunay tetrahedrization. The non-rigid registration is accomplished in a deterministic annealing scheme. At the preprocessing stage we segment the objects of interest by a segmentation method based on texture information. This method is embedded in a region growing scheme. As our final application, we present a scheme for surgical object tracking using again geometric algebra techniques.     

Possibilistic and probabilistic fuzzy clustering: unification within the framework of the non-extensive thermostatistics

Fuzzy clustering algorithms are becoming the major technique in cluster analysis. In this paper, we consider the fuzzy clustering based on objective functions. They can be divided into two categories: possibilistic and probabilistic approaches leading to two different function families depending on the conditions required to state that fuzzy clusters are a fuzzy c-partition of the input data. Recently, we have presented in Menard and Eboueya (Fuzzy Sets and Systems, 27, to be published) an axiomatic derivation of the Possibilistic and Maximum Entropy Inference (MEI) clustering approaches, based upon an unifying principle of physics, that of extreme physical information (EPI) defined by Frieden (Physics from Fisher information, A unification, Cambridge University Press, Cambridge, 1999). Here, using the same formalism, we explicitly give a new criterion in order to provide a theoretical justification of the objective functions, constraint terms, membership functions and weighting exponent m used in the probabilistic and possibilistic fuzzy clustering. Moreover, we propose an unified framework including the two procedures. This approach is inspired by the work of Frieden and Plastino and Plastino and Miller (Physics A 235, 577) extending the principle of extremal information in the framework of the non-extensive thermostatistics. Then, we show how, with the help of EPI, one can propose extensions of the FcM and Possibilistic algorithms.     

大气再分析产品应用平台通用框架及组件设计

大气再分析产品涵盖了历史一段时期内的大气温度、压强、湿度、风速风向等变量的四维格点化信息,可以广泛应用到气候变化、武器装备设计等多个领域。针对再分析产品的数据格式及应用特点,再分析产品应用平台通用框架采用经典MVC三层模型,基于第三方软件开发和集成了解码、统计分析、可视化等应用组件和标准化的IO接口。以往ASCII格点数据需要用户导出GRIB格式数据,利用拼接软件拼接产生,耗时且十分麻烦。点面结合的混合数据管理,能实现对PB级再分析产品的高效管理,具有高扩展、低延迟等特点。场单元及点单元的点面结合管理方式可满足不同时空跨度的数据检索应用需求。     

Determining the prices of remanufactured products,capacity of internal workstations and the contracting strategy within queuing framework

This paper studies a remanufacturing facility with several types of incoming nonconforming products and different independent remanufacturing workstations. The workstations have limited capacities so that an outsourcing strategy can be practiced. Each workstation is modeled with an M/M/1/k queuing system considering k as a decision variable. Additionally, a binary decision variable is taken into account to determine the contracting strategy along with some decision variables for the prices of remanufactured products. Thus, a bi-objective mixed-integer nonlinear programming is built to obtain optimal values of the decision variables. The first objective attempts to maximize the total profit and the second minimizes the average length of queuing at workstations. To solve the complex bi-objective mixed-integer nonlinear programming problem, the best out of six multi-objective decision-making (MODM) methods is selected in order to make the bi-objective optimization problem a single-objective one. Afterward, a genetic algorithm (GA) is developed to find a near-optimum solution of the single-objective problem. Besides, all of the important parameters of the algorithm are calibrated using regression analysis. To validate the results obtained, the solutions of some test problems are compared to the ones obtained by the GAMS software. The applicability of the proposed model and the solution procedure are shown with an illustrative example.     

Benchmarking within a DEA framework: setting the closest targets and identifying peer groups with the most similar performances

Data envelopment analysis (DEA) is widely used as a benchmarking tool for improving performance of organizations. For that purpose, DEA analyses provide information on both target setting and peer identification. However, the identification of peers is actually a by-product of DEA. DEA models seek a projection point of the unit under evaluation on the efficient frontier of the production possibility set, which is used to set targets, while peers are identified simply as the members of the so-called reference sets, which consist of the efficient units that determine the projection point as a combination of them. In practice, the selection of peers is crucial for benchmarking, because organizations need to identify a peer group in their sector or industry that represents actual performances from which to learn. In this paper, we argue that DEA benchmarking models should incorporate into their objectives criteria for the selection of suitable benchmarks among peers, in addition to considering the setting of appropriate targets (as usual). Specifically, we develop models having two objectives: setting the closest targets and selecting the most similar reference sets. Thus, we seek to establish targets that require the least effort from organizations for their achievement in addition to identifying peer groups with the most similar performances, which are potential benchmarks to emulate and improve.     

基于Hadoop及出租车历史轨迹的乘客推荐算法

针对智慧城市中乘客打车策略的推荐算法效率不高的问题,使用古典概率学统计历史轨迹中该时间该路段有空车的天数占数据集总天数比例,作为乘客等到空车概率;使用最小二乘法拟合时间与到达空车数曲线,预测乘客等到空车时间,以提高推荐效率。同时,使用Hadoop作为数据存储和计算平台以提高数据处理能力;提出一种基于地图栅格化的路网存储结构来提高搜索地图速度;改进一种基于计算几何的地图匹配算法提高匹配准确率。实验结果显示,空车概率推荐算法正确率约87%,等待时间推荐算法正确率达88.4%,表明挖掘轨迹数据为乘客提供推荐服务的可行性。     

测试向量转换中波形数据格式及其压缩编码算法

为了实现由芯片设计仿真出来的测试向量到测试设备的测试程序转换，在分析了不断变化的测试需求后，提出了一种类-STIL的波形数据格式。针对该波形数据格式，实现了一种基于测试向量特点的动态无损的压缩编码算法, 从而解决了测试向量的大容量问题。实验结果表明，在该波形格式基础上的测试向量转换，不仅在速度上得到优化，同时针对大容量的测试向量集合，也获得了较高的压缩结果。     

管道燃气快烤装置燃烧过程数值仿真及结构参数影响分析

快烤试验装置作为快烤试验的重要组成部分,其产生的火焰温度对试验结果有很大的影响。为设计管道燃气快烤装置,利用Fluent软件、采用SST k-ω湍流模型和非预混燃烧模型,开展管道燃气装置燃烧过程仿真和关键结构参数对火焰温度及其均匀性的影响规律研究。选择三个关键参数即管道间距h1、火孔孔径Φ、火孔孔距h2,设计了三因素三水平正交试验进行仿真。研究结果表明:在管道直径确定的条件下,管道间距是影响管道燃烧器火焰温度均匀性的最主要因素,其次是火孔间距,火孔孔径是影响火焰温度均匀性的最次要因素;管道燃烧器上方不同高度处火焰温度均匀性对应的最佳结构参数并不相同。     

Comparisons of metaheuristic algorithms and fitness functions on software test data generation

Cost of testing activities is a major portion of the total cost of a software. In testing, generating test data is very important because the efficiency of testing is highly dependent on the data used in this phase. In search-based software testing, soft computing algorithms explore test data in order to maximize a coverage metric which can be considered as an optimization problem. In this paper, we employed some meta-heuristics (Artificial Bee Colony, Particle Swarm Optimization, Differential Evolution and Firefly Algorithms) and Random Search algorithm to solve this optimization problem. First, the dependency of the algorithms on the values of the control parameters was analyzed and suitable values for the control parameters were recommended. Algorithms were compared based on various fitness functions (path-based, dissimilarity-based and approximation level + branch distance) because the fitness function affects the behaviour of the algorithms in the search space. Results showed that meta-heuristics can be effectively used for hard problems and when the search space is large. Besides, approximation level + branch distance based fitness function is generally a good fitness function that guides the algorithms accurately.     

A simulation study using EFA and CFA programs based the impact of missing data on test dimensionality

This study examines the impact of missing rates and data imputation methods on test dimensionality. We consider how missing rate levels (10%, 20%, 30%, and 50%) and the six missed data imputation methods (Listwise, Serial Mean, Linear Interpolation, Linear Trend, EM, and Regression) affect the structure of a test. A simulation study is conducted using the SPSS 15.0 EFA and CFA programs. The EFA results for the six methods are similar, and all results obtained two factors. The CFA results also fit the hypothesized two factor structure model for all six methods. However, we observed that the EM method fits the EFA results relatively well. When the percentage of missing data is less than 20%, the impact of the imputation methods on test dimensionality is not statistically significant. The Serial Mean and Linear Trend methods are suggested for use when the percentage of missing data is greater than 30%.     

The sign test and the signed-rank test for interval-valued data

Two versions of the generalized sign test and the signed-rank test for interval-valued data (both for one-sample and paired two-sample problem) are proposed. These two versions correspond to different possible views on the interval outcomes of the experiment—either the epistemic or the ontic one. Each view yields its own approach to data analysis which results in different test construction and the way of carrying on the statistical inference.     

基于DSP的彩色图像三基色重建算法及实现

分析一种由CCD像感器和数字信号处理器DSP所组成的视频信号帧存储方式，数据采集系统的彩色图像三基色重建算法及实现。该算法针对Bayer滤色器的色信号特性，采用邻边点色彩补偿法去重建图像三基色。用该算法重建的彩色图像清晰、平滑，且利用DSP来实现上述算法，提高了彩色图像重建的运算速度。     

多主体框架下结合最大期望值和遗传算法的SAR图像分割

目的 SAR图像中固有的相干斑噪声增加了图像分割的困难.为此,提出一种分布式SAR图像分割算法.方法 首先假设图像中同质区域内像素满足同一独立的Gamma分布,依此建立SAR图像模型;为了刻画SAR图像中像素的类属性,建立标号场的MRF(Markov Random Field)模型;在Bayesian理论框架下建立图像分割模型;在多主体系统(MAS)框架下,结合MRF模型和遗传算法(GA)模拟分割模型.MAS结构由分割主体和协调主体组成,其中分割主体利用最大期望值( EM)算法估计MRF模型参数,从而实现全局分割;协调主体利用GA实现全局最优.结果 为了验证提出方法的有效性,分别对模拟和RADARSAT-I/II SAR图像进行实验,并与EM和RJMCMC算法比较.本文算法的用户精度、产品精度、总精度及kappa系数均高于EM算法.定性和定量分析结果验证了本文算法的鲁棒性和有效性.结论 实验结果表明提出的分布式MAS框架下SAR图像分割方法,能够提高分割精度.该方法适用于中高分辨率单极化的SAR图像,且具有很好的抗噪性.     

Computational complexity and solution algorithms for flowshop scheduling problems with the learning effect

In this paper, we analyze the two-machine flowshop problem with the makespan minimization and the learning effect, which computational complexity was not determined yet. First, we show that an optimal solution of this problem does not have to be the ‘permutation’ schedule if the learning effect is taken into consideration. Furthermore, it is proved that the permutation and non-permutation versions of this problem are NP-hard even if the learning effect, in a form of a step learning curve, characterizes only one machine. However, if both machines have learning ability and the learning curves are stepwise then the permutation version of this problem is strongly NP-hard. Furthermore, we prove the makespan minimization problem in m-machine permutation proportional flowshop environment remains polynomially solvable with identical job processing times on each machine even if they are described by arbitrary functions (learning curves) dependent on a job position in a sequence. Finally, approximation algorithms for the general problem are proposed and analyzed.