Signature extraction using mutual interdependencies

Recently, mutual interdependence analysis (MIA) has been successfully used to extract representations, or “mutual features”, accounting for samples in the class. For example, a mutual feature is a face signature under varying illumination conditions or a speaker signature under varying channel conditions. A mutual feature is a linear regression that is equally correlated with all samples of the input class. Previous work discussed two equivalent definitions of this problem and a generalization of its solution called generalized MIA (GMIA). Moreover, it showed how mutual features can be computed and employed. This paper uses a parametrized version GMIA(λ) to pursue a deeper understanding of what GMIA features really represent. It defines a generative signal model that is used to interpret GMIA(λ) and visualize its difference to MIA, principal and independent component analysis. Finally, we analyze the effect of λ on the feature extraction performance of GMIA(λ) in two standard pattern recognition problems: illumination-independent face recognition and text-independent speaker verification.     

Scalable dimensioning of resilient Lambda Grids

Grids consist of the aggregation of numerous dispersed computational, storage and network resources, able to satisfy even the most demanding computing jobs. Due to the data-intensive nature of Grid jobs, there is an increasing interest in Grids using optical transport networks as this technology allows for the timely delivery of large amounts of data. Such Grids are commonly referred to as Lambda Grids.

An important aspect of Grid deployment is the allocation and activation of installed network capacity, needed to transfer data and jobs to and from remote resources. However, the exact nature of a Grid’s network traffic depends on the way arriving workload is scheduled over the various Grid sites. As Grids possibly feature high numbers of resources, jobs and users, solving the combined Grid network dimensioning and workload scheduling problem requires the use of scalable mathematical methods such as Divisible Load Theory (DLT). Lambda Grids feature additional complexity such as wavelength granularity and continuity or conversion constraints must be enforced. Additionally, Grid resources cannot be expected to be available at all times. Therefore, the extra complexity of resilience against possible resource failures must be taken into account when modelling the combined Grid network dimensioning and workload scheduling problem, enforcing the need for scalable solution methods. In this work, we tackle the Lambda Grid combined dimensioning and workload scheduling problem and incorporate single-resource failure or unavailability scenarios. We use Divisible Load Theory to tackle the scalability problem and compare non-resilient lambda Grid dimensioning to the dimensions needed to survive single-resource failures. We distinguish three failure scenarios relevant to lambda Grid deployment: computational element, network link and optical cross-connect failure. Using regular network topologies, we derive analytical bounds on the dimensioning cost. To validate these bounds, we present comparisons for the resulting Grid dimensions assuming a 2-tier Grid operation as a function of varying wavelength granularity, fiber/wavelength cost models, traffic demand asymmetry and Grid scheduling strategy for a specific set of optical transport networks.     

Generalized Prioritized Multicriteria Aggregation

After investigating prioritized multicriteria decision‐making or aggregation problems in depth, we reveal that priority relationships among criteria may be incomplete. In a complex and practical multicriteria decision‐making problem, the relationships of a pair of criteria can be multiform including priority relationships, except for independence. For such cases, we present a generalized prioritized multicriteria aggregation (GPMA) model with incomplete priority relationships in this paper. First, we elaborate GPMA problems, and describe them by using a dendriform structure after designing a top‐to‐bottom method to form priority hierarchies according to the given priority relationships. Furthermore, a common process for handling GPMA problems is proposed based on the premeditation that the weights associated with the lower‐priority criteria need to be revised according to the satisfaction of the higher‐priority criteria. At length, we develop two GPMA operators with respect to the GPMA with strictly and weakly ordered prioritizations, respectively, based on triangular norms, and we verify that both of them are aggregation functions.     

A review of automatic dimensioning and tolerancing schemes

Dimensioning and tolerancing are very important issues in product design and manufacture. This paper gives a survey and review of the current state-of-the-art solutions to the problem of finding a meaning for dimensions and tolerances. Dimensioning and tolerancing in current engineering practices and researches in these topics are also discussed.     

Statistical geometric computation on tolerances for dimensioning

Dimensions are used to specify the distances between different features in geometric models. These dimensions will often be expressed as a range of allowable dimensions. When considering a group of toleranced dimensions, these ranges can be analyzed as either a worst-case bound on allowable ranges, or as a statistical measure of expected distribution. This paper presents a new geometric model for representing statistically-based tolerance regions. Methods for tolerance estimation and allocation on a geometric model are provided by generalizing root sum square (RSS) methods for compositing and cascading over tolerance zones. This gives us a geometric interpretation of a statistical analysis. Tolerance regions are determined by probabilities of variations of dimensions falling into the region. A dependency graph over dimensions can be represented by a topological graph on which the tolerance cascading and tolerance allocation can be processed. To illustrate applications of this geometric method, we provide examples of tolerance estimation and tolerance allocation on our model. The estimation examples utilize the compositing and cascading operations provided in the analysis method. The allocation examples present an automatic tolerance allocation procedure on the tolerance model. As opposed to existing methods, our allocation method allows us to specify not only a numerical objective of the optimization, but also a statistically-based objective for the geometric shape of the tolerance.     

Evaluating the Validity of Multicriteria Decision-Making

The paper provides an approach to the assessment of the validity of decisions made for complex systems using multicriteria methods. It is also proposed to evaluate the validity based on the relevant criterion, which involves not only assessment of the results obtained by the multicriteria methods but also preliminary stages related to preparation of the initial data.     

Multicriteria Decision-Making Using Fuzzy Measures

We are interested in the formulation of multicriteria decision functions based on the use of a measure over the space of criteria. Specifically, the relationship between the criteria is expressed using a monotonic set measure. We then use the Choquet integral to construct decision functions based on the measure. We look at a number of different decision functions generated from specific classes of measures.     

Multicriteria Robust Fitting of Elliptical Primitives

Geometric fitting is present in different fields of science, engineering and astronomy. In particular, ellipse shapes are some of the most commonly employed geometric features in digital image analysis and visual pattern recognition. Most geometric and algebraic methods are sensitive to noise and outlier points and so the results are not usually acceptable. In this paper, a robust geometric multicriteria method based on the mean absolute geometric error and the eccentricity to fit an ellipse to set of points is proposed. It is well known that the least mean absolute error criterion leads to robust estimations. The experimental results on different real and synthetic data have shown that the proposed algorithm is robust to outliers. Moreover, it allows us to identify outliers and remove them.     

基于参数化的系列化图形尺寸自动标注方法

为了提高系列化图形的设计效率,降低工程制图的尺寸标注的复杂度,结合二三维一体化的设计思想,研究系列化图形的尺寸标注,提出并实践了一种系列化图形的自动标注方法--依据参数化进行实体的三维造型,然后将其进行投影生成二维视图,在二维视图上进行尺寸交互标注.研究了视图与尺寸标注之间的联系,提取关键信息,利用该关键信息对后续生成的系列化图形进行尺寸标注.最后以实例展示了自动标注的过程,表明了该方法的可行性,有效性.     

On One Feature of Multicriteria Differential Games

Differential two-person zero-sum games with a vector payoff function are considered. A counterexample states that a payoff function component convolution into a linear convolution and further finding saddle point results in the interior instability of a set of such solutions. It is found that such saddle points are Geoffrion saddle points for an initial multicriteria game.     

Vague集的多目标模糊决策方法

在进行了阐述Vague集的相关概念和运算后,对多目标模糊决策进行了定义,给出多目标模糊决策的基本思路,并对已有的基于Vague集的多目标模糊决策方法进行了分析,得出现有Vague集的多目标模糊决策方法存在着缺陷,从而提出了一种新的多目标模糊决策的Vague集方法,该方法利用一个新的评分函数对方案进行排序,选出最优方案.最后给出其相关性质,证明其解决了现有方法的缺陷,并通过实例阐明本文方法的有效性和优越性.     

Multicriteria discrete optimization of large scale truss systems

The paper discusses optimization problems in civil engineering structural design. The following questions are discussed: continuous or discrete optimization, single- or multicriteria optimization, one- or multi-level optimization. The paper is illustrated with examples of the multi-criteria discrete optimization of large scale truss systems. The cross-sectional areas of truss bars are taken as design variables. Minimization of mass, labour cost and displacements are chosen as optimization criteria. Optimization constraints concern stresses, displacements and stability, as well as technological and computational requirements. The results of single- and multicriteria optimization of hall structures are presented in the form of diagrams and tables.Presented at NASO ASI Optimization of Large Structural Systems, Sept. 23 – Oct. 4, 1991, Berchtesgarden, Germany     

Hybrid Method of Multicriteria Evaluation of Decision Alternatives

In the paper we develop a hybrid decision support method in case of dependent decision criteria. It includes methods of decision theory, fuzzy sets, mathematical programming and statistics, which are adapted to different stages of the multicriteria evaluation of alternatives depending on the specific problem being solved and on the quality of the input expert information. The use of the hybrid method is illustrated by the solution of practical problems.     

Multicriteria optimization of technological processes under uncertainty conditions

The multicriteria optimization problem under uncertainty conditions is considered, which arises at the design stage of a technological process. The uncertainty stems from the inaccuracy of mathematical models and a certain uncertainty of the conditions in which the process will be implemented. The generalization is treated of well known multicriteria optimization methods in the case of the uncertainty accounting. Here, account will be taken of the possibility of the use of control variables at the operation stage to compensate for the uncertainty effect.     

An Evolutionary Approach of Multicriteria Manufacturing Cell Formation

Several approaches to designing cellular manufacturing systems exist, but they are generally based on the optimization of a single criterion, such as the minimization of the inter-cell movement or the total cost. Unfortunately, in practice, it is often necessary to take into account multiple criteria. We present an approach based on a niched pareto evolutionary algorithm which does not rely on weights or distances to a target solution. The suggested method allows several solutions to be provided, so that a choice is offered to the decision maker, according to his/her particular constraints. A new recombination operator is also presented. This approach is illustrated on a cell formation problem using two criteria: the cell workload and the traffic between cells.     

一个智能型的多目标综合评价支持系统

本文对智能型多目标综合评价支持系统的有关问题进行了研究，提出了一种基于框架的规则表示方法，这种方法综合了深层表达和表层表达的特点，能较好地表示结构化问题和非结构化问题。文章对于已经研制并实现的一个智能化系统─—大型工程多目标综合评价支持系统进行了分析。