8,088 research outputs found
Bicriteria Network Design Problems
We study a general class of bicriteria network design problems. A generic
problem in this class is as follows: Given an undirected graph and two
minimization objectives (under different cost functions), with a budget
specified on the first, find a <subgraph \from a given subgraph-class that
minimizes the second objective subject to the budget on the first. We consider
three different criteria - the total edge cost, the diameter and the maximum
degree of the network. Here, we present the first polynomial-time approximation
algorithms for a large class of bicriteria network design problems for the
above mentioned criteria. The following general types of results are presented.
First, we develop a framework for bicriteria problems and their
approximations. Second, when the two criteria are the same %(note that the cost
functions continue to be different) we present a ``black box'' parametric
search technique. This black box takes in as input an (approximation) algorithm
for the unicriterion situation and generates an approximation algorithm for the
bicriteria case with only a constant factor loss in the performance guarantee.
Third, when the two criteria are the diameter and the total edge costs we use a
cluster-based approach to devise a approximation algorithms --- the solutions
output violate both the criteria by a logarithmic factor. Finally, for the
class of treewidth-bounded graphs, we provide pseudopolynomial-time algorithms
for a number of bicriteria problems using dynamic programming. We show how
these pseudopolynomial-time algorithms can be converted to fully
polynomial-time approximation schemes using a scaling technique.Comment: 24 pages 1 figur
Real-time food intake classification and energy expenditure estimation on a mobile device
© 2015 IEEE.Assessment of food intake has a wide range of applications in public health and life-style related chronic disease management. In this paper, we propose a real-time food recognition platform combined with daily activity and energy expenditure estimation. In the proposed method, food recognition is based on hierarchical classification using multiple visual cues, supported by efficient software implementation suitable for realtime mobile device execution. A Fischer Vector representation together with a set of linear classifiers are used to categorize food intake. Daily energy expenditure estimation is achieved by using the built-in inertial motion sensors of the mobile device. The performance of the vision-based food recognition algorithm is compared to the current state-of-the-art, showing improved accuracy and high computational efficiency suitable for realtime feedback. Detailed user studies have also been performed to demonstrate the practical value of the software environment
Frustrated spin ladder with alternating spin-1 and spin-1/2 rungs
We study the impact of the diagonal frustrating couplings on the quantum
phase diagram of a two-leg ladder composed of alternating spin-1 and spin-1/2
rungs. As the coupling strength is increased the system successively exhibits
two gapped paramagnetic phases (a rung-singlet and a Haldane-like
non-degenerate states) and two ferrimagnetic phases with different
ferromagnetic moments per rung. The first two states are similar to the phases
studied in the frustrated spin-1/2 ladder, whereas the magnetic phases appear
as a result of the mixed-spin structure of the model. A detailed
characterization of these phases is presented using density-matrix
renormalization-group calculations, exact diagonalizations of periodic
clusters, and an effective Hamiltonian approach inspired by the analysis of
numerical data. The present theoretical study was motivated by the recent
synthesis of the quasi-one-dimensional ferrimagnetic material
FeFe (trans-1,4-cyclohexanedicarboxylate) exhibiting a similar
ladder structure.Comment: 10 pages, 8 figure
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