In this work we address part-based object detection under variability of part shapes and spatial relations. Our approach bases on the hierarchical finite element modeling concept of Engel and Tönnies [ET09a, ET09b]. They model object parts by elastic materials, which adapt to image structures via image-derived forces. Spatial part relations are realized through additional layers of elastic mate...

Introduction: Effective out-of-hospital administration of naloxone in opioid overdoses is dependent on timely arrival naloxone. Delays emergency medical services (EMS) response time could potentially be overcome with drones to deliver efficiently the scene for bystander use. Our objective was evaluate a mathematical optimization simulation geographical placement drone bases reducing overdose.Met...

An optimization problem, formulated using a nonlinear least-squares approach, was used to estimate parameters for kinetic models of the three isoforms of the kidney-specific Na-K-2Cl (NKCC2) cotransporter. Specifically, the optimization problem estimates the magnitude of model parameters (i.e., off-binding and translocation rate constants) by minimizing the distance between model unidirectional...

We present an iterative deconvolution algorithm that minimizes a functional with a non-quadratic waveletdomain regularization term. Our approach is to introduce subband-dependent parameters into the bound optimization framework of Daubechies et al.; it is sufficiently general to cover arbitrary choices of wavelet bases (non-orthonormal or redundant). The resulting procedure alternates between t...

Although there have been many compression schemes for reducing data effectively, most schemes do not consider the reordering of data. In the case of unordered data, if the users change the data order in a given data set, the compression ratio may be improved compared to the original compression before reordering data. However, in the case of ordered data, the users need a mapping table that map...

This paper presents an efficient shape optimization technique based on stochastic response surfaces (polynomial chaos expansion) constructed using performance and local sensitivity data at heuristically selected collocation points. The cited expansion uses Hermite polynomial bases for the space of square-integrable probability density functions and provides a closed form solution of the perform...

The quantity of entities in the Linked Data is increasing rapidly. For entity search and browsing systems, filtering is very useful for users to find entities that they are interested in. Type is a kind of widely-used facet and can be easily obtained from knowledge bases, which enables to create filters by selecting at most K types of an entity collection. However, existing approaches often fai...

Random sampling i s a powerful way t o gather informat ion about a group by considering only a small part of it. W e give a paradigm f o r applying this technique to optimization problems, and demonstrate its effectiveness o n matroids. Matroids abstractly model many optimization problems that can be solved by greedy methods, such as the minimum spanning tree ( M S T ) problem. Our results have...

We show how structured data stored in les can beneet from standard database technology and in particular be queried and updated using database languages. We introduce the notion of structuring schema which consists of a grammar annotated with database programs and of a database schema. We study the translation from structured strings to databases, and the converse. We adapt optimization techniq...

This paper presents a fuzzy genetic approach to perform data classification. The method aims to obtain small fuzzy classifiers by means of optimization of fuzzy rules bases using a genetic algorithm. It is shown how a fuzzy rules base is generated from a numerical database and how its best subset is found by the genetic algorithm. The classifiers are evaluated in terms of accuracy, cardinality ...