An efficient solver for weighted Max-SAT

We present a new branch and bound algorithm for weighted Max-SAT, called Lazy which incorporates original data structures and inference rules, as well as a lower bound of better quality. We provide experimental evidence that our solver is very competitive and outperforms some of the best performing Max-SAT and weighted Max-SAT solvers on a wide range of instances.     

Input optimization: I. Optimal realizations of mathematical models

Mathematical models are considered as input-output systems. The input is data (technological coefficients, available energy, prices) and the output is the feasible set, the set of optimal solutions, and the optimal value. We study when output is a continuous function of input and identify optimal (minimal) realizations of mathematical models. These are states of the model having the property that every stable perturbation of input results in a locally worse (higher) value of the optimal value function. In input optimization we “optimize” mathematical model rather than a specific mathematical program. This research was supported in part by the Natural Sciences and Engineering Research Council of Canada, and in part by the Gouvernement du Québec, programme de formation de chercheurs et d’action concertée.     

Variational parameter estimation for a two-dimensional numerical tidal model

It is shown that the parameters in a two-dimensional (depth-averaged) numerical tidal model can be estimated accurately by assimilation of data from tide gauges. The tidal model considered is a semi-linearized one in which kinematical non-linearities are neglected but non-linear bottom friction is included. The parameters to be estimated (bottom friction coefficient and water depth) are assumed to be position-dependent and are approximated by piecewise linear interpolations between certain nodal values. The numerical scheme consists of a two-level leapfrog method. The adjoint scheme is constructed on the assumption that a certain norm of the difference between computed and observed elevations at the tide gauges should be minimized. It is shown that a satisfactory numerical minimization can be completed using either the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton algorithm or Nash's truncated Newton algorithm. On the basis of a number of test problems, it is shown that very effective estimation of the nodal values of the parameters can be achieved provided the number of data stations is sufficiently large in relation to the number of nodes.     

Optimal estimation of eddy viscosity for a quasi-three-dimensional numerical tidal and storm surge model

It is shown that the eddy viscosity profile in a quasi-three-dimensional numerical tidal and storm surge model can be estimated by assimilation of velocity data from one or more current meters located on the same vertical line. The computational model used is a simplified version of the so-called vertical/horizontal splitting algorithm proposed by Lardner and Cekirge. We have estimated eddy viscosity both as a constant and as a variable parameter. The numerical scheme consists of a two-level leapfrog method to solve the depth-averaged equations and a generalized Crank-Nicolson scheme to compute the vertical profile of the velocity field. The cost functional in the adjoint scheme consists of two terms. The first term is a certain norm of the difference between computed and observed velocity data and the second term measures the total variation in the eddy viscosity function. The latter term is not needed when the data are exact for the model but is necessary to smooth out the instabilities associated with ‘noisy’ data. It is shown that a satisfactory minimization can be accomplished using either the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton algorithm or Nash's truncated Newton algorithm. Very effective estimation of eddy viscosity profiles is shown to be achieved even when the amount of data is quite small.     

Discriminant versus rough sets approach to vague data analysis

This paper presents a comparative study of the use of two different methods of data analysis on a common set of data. The first is a method based on rough sets theory and the second is the location model method from the field of discriminant analysis. To investigate the comparative performance of these methods, a set of real medical data has been used. The data considered are of both discrete and continuous character. During the comparison, particular attention is paid to data reduction and to the derivation of decision rules and classification functions from the reduced set.     

Algorithms for generalized halfspace range searching and other intersection searching problems

In a generalized intersection searching problem, a set S of colored geometric objects is to be preprocessed so that, given a query object q, the distinct colors of the objects of S that are intersected by q can be reported or counted efficiently. These problems generalize the well-studied standard intersection searching problems and have many applications. Unfortunately, the solutions known for the standard problems do not yield efficient solutions to the generalized problems. Recently, efficient solutions have been given for generalized problems where the input and query objects are iso-oriented (i.e., axes-parallel) or where the color classes satisfy additional properties (e.g., connectedness). In this paper, efficient algorithms are given for several generalized problems involving objects that are not necessarily iso-oriented. These problems include: generalized halfspace range searching in , for any fixed d ≥ 2, and segment intersection searching, triangle stabbing, and triangle range searching in for certain classes of line segments and triangles. The techniques used include: computing suitable sparse representations of the input, persistent data structures, and filtering search.     

Automatic peak detection in chromatography

Summary A modified derivative of chromatographic signal is proposed for detection of the appearance of a new peak. The method is shown to yield peak areas of good precision even in very noisy systems.This paper is dedicated to Dr. Leslie Ettre on his 60th birthday.     

Review of particle properties

This review of the properties of leptons, mesons, and baryons is an updating of Review of Particle Properties, Particle Data Group [Rev. Mod. Phys. 45, No. 2, Part II, Supplement (1973)]. Data are evaluated, listed, averaged, and summarized in tables.     

Fast searches in a recommendation session

In this paper, we introduce a recommendation session and propose a data structure (recommendation Patricia) which is used to accomplish fast searches in a recommendation session. The time cost for a search in each recommendation step is O(E * s²) if a recommendation Patricia is used, where E is the maximal length of words involved and s is the maximal size of each recommendation. In contradistinction, the worst-case time cost for the same goal is Ω(n) if a Patricia is used, where n is the number of words involved.     

基于数据驱动加权的模糊评价量化方法

模糊评价改变了量化打分的评价方式,使评价者能够更加客观的进行评价,因此在各行各业有着广泛的应用。但是如何将模糊评价转化为量化分值,以便对被评价者进行评价一直是不少学者研究的重点。本文提出一种将模糊评价进行量化评分的新方法,并提出了一种以评价数据来驱动各项指标权重的方法。