Search results for "BINARY"

A discursive analysis of oppositional interpretations of the agro-food system: A case study of Latvia

2015

Abstract This article critically reflects on the literature that addresses the complexity of food systems, which is often caught in application of simplistic binary oppositions of local vs. global, short vs. long, sustainable vs. intensive, etc. It then goes on to show, through a case study analysis of food-system discourses in Latvia how the binary oppositions surrounding with food systems, are actually mobilised in a specific national context. Agro-food systems are often explained through binary opposing knowledge systems that, depending on the theoretical affiliation of the author, might be called frames, narratives or discourses. These powerful instruments are used to explain, and often…

Sociolinguistics from the Periphery

2016

This leading team of scholars presents a fascinating book about change: shifting political, economic and cultural conditions; ephemeral, sometimes even seasonal, multilingualism; and altered imaginaries for minority and indigenous languages and their users. The authors refer to this network of interlinked changes as the new conditions surrounding small languages (Sámi, Corsican, Irish and Welsh) in peripheral sites. Starting from the conviction that peripheral sites can and should inform the sociolinguistics of globalisation, the book explores how new modes of reflexivity, more transactional frames for authenticity, commodification of peripheral resources, and boundary-transgression with hu…

2013

Currently, a growing number of programs become available in statistical software for multiple imputation of missing values. Among others, two algorithms are mainly implemented: Expectation Maximization (EM) and Multiple Imputation by Chained Equations (MICE). They have been shown to work well in large samples or when only small proportions of missing data are to be imputed. However, some researchers have begun to impute large proportions of missing data or to apply the method to small samples. A simulation was performed using MICE on datasets with 50, 100 or 200 cases and four or eleven variables. A varying proportion of data (3% - 63%) was set as missing completely at random and subsequent…

Fast Algorithms for Pseudoarboricity

2015

The densest subgraph problem, which asks for a subgraph with the maximum edges-to-vertices ratio d∗, is solvable in polynomial time. We discuss algorithms for this problem and the computation of a graph orientation with the lowest maximum indegree, which is equal to ⌈d∗⌉. This value also equals the pseudoarboricity of the graph. We show that it can be computed in O(|E| √ log log d∗) time, and that better estimates can be given for graph classes where d∗ satisfies certain asymptotic bounds. These runtimes are achieved by accelerating a binary search with an approximation scheme, and a runtime analysis of Dinitz’s algorithm on flow networks where all arcs, except the source and sink arcs, hav…

A new compact formulation for the discrete p-dispersion problem

2017

Abstract This paper addresses the discrete p -dispersion problem (PDP) which is about selecting  p facilities from a given set of candidates in such a way that the minimum distance between selected facilities is maximized. We propose a new compact formulation for this problem. In addition, we discuss two simple enhancements of the new formulation: Simple bounds on the optimal distance can be exploited to reduce the size and to increase the tightness of the model at a relatively low cost of additional computation time. Moreover, the new formulation can be further strengthened by adding valid inequalities. We present a computational study carried out over a set of large-scale test instances i…

Optimal standalone data center renewable power supply using an offline optimization approach

2022

Abstract Because of the increasing energy consumption of data centers and their C O 2 emissions, the ANR DATAZERO2 project aims to design autonomous data centers running solely on local renewable energy coupled with storage devices to overcome the intermittency issue. In order to optimize the use of renewable energy and storage devices, a MILP solver is usually in charge of assigning the power to be supplied to the data center. However, in order to reduce the computation time and make the approach scalable, it would be more appropriate to use a polynomial time algorithm. This paper aims at showing and proving that it is possible to provide an optimal power profile via a deterministic algori…

Genetic analysis of early lamb survival in extensively reared lambs

2005

In sheep production, lamb survival is an important economic trait (Conington et al., 2004). Therefore, this trait has been studied by many scientists, especially in countries with an extensive husbandry system. In the United Kingdom, the number of lambs dying before weaning has been estimated ranging from 5 to 40% (Eales et al., 1983).

On the Non-uniform Redundancy in Grammatical Evolution

2016

This paper investigates the redundancy of representation in grammatical evolution (GE) for binary trees. We analyze the entire GE solution space by creating all binary genotypes of predefined length and map them to phenotype trees, which are then characterized by their size, depth and shape. We find that the GE representation is strongly non-uniformly redundant. There are huge differences in the number of genotypes that encode one particular phenotype. Thus, it is difficult for GE to solve problems where the optimal tree solutions are underrepresented. In general, the GE mapping process is biased towards short tree structures, which implies high GE performance if the optimal solution requir…

Cluster-based active learning for compact image classification

2010

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer…

A distance metric on binary trees using lattice-theoretic measures

1990

A so called height function which is a strictly antitone supervaluation is defined on binary trees. Via lattice-theoretic results and using the height function, we can define a distance metric on binary trees of size n which can be computed in expected time O(n 3/2 )