180,442 research outputs found
Synthesis of Attributed Feature Models From Product Descriptions: Foundations
Feature modeling is a widely used formalism to characterize a set of products
(also called configurations). As a manual elaboration is a long and arduous
task, numerous techniques have been proposed to reverse engineer feature models
from various kinds of artefacts. But none of them synthesize feature attributes
(or constraints over attributes) despite the practical relevance of attributes
for documenting the different values across a range of products. In this
report, we develop an algorithm for synthesizing attributed feature models
given a set of product descriptions. We present sound, complete, and
parametrizable techniques for computing all possible hierarchies, feature
groups, placements of feature attributes, domain values, and constraints. We
perform a complexity analysis w.r.t. number of features, attributes,
configurations, and domain size. We also evaluate the scalability of our
synthesis procedure using randomized configuration matrices. This report is a
first step that aims to describe the foundations for synthesizing attributed
feature models
Hierarchical Coding for Distributed Computing
Coding for distributed computing supports low-latency computation by
relieving the burden of straggling workers. While most existing works assume a
simple master-worker model, we consider a hierarchical computational structure
consisting of groups of workers, motivated by the need to reflect the
architectures of real-world distributed computing systems. In this work, we
propose a hierarchical coding scheme for this model, as well as analyze its
decoding cost and expected computation time. Specifically, we first provide
upper and lower bounds on the expected computing time of the proposed scheme.
We also show that our scheme enables efficient parallel decoding, thus reducing
decoding costs by orders of magnitude over non-hierarchical schemes. When
considering both decoding cost and computing time, the proposed hierarchical
coding is shown to outperform existing schemes in many practical scenarios.Comment: 7 pages, part of the paper is submitted to ISIT201
Improvements to NESTLE: Cross Section Interpolation and \u3ci\u3eN\u3c/i\u3e-Group Extension
The NESTLE program is a few-group neutron diffusion reactor core simulator code utilizing the nodal expansion method (NEM). This thesis presents two improvements made to NESTLE regarding cross-section interpolation and multigroup capability.
To quickly and accurately obtain cross sections from lattice physics input data, a new cross section interpolation routine was developed utilizing multidimensional radial basis function interpolation, also known as thin plate spline interpolation. Testing showed that, for existing NESTLE lattice physics input, accuracy was retained but not improved and processing time was longer. However, the new interpolation routine was shown allow much greater exibility in the case matrix of the the lattice physics input file. This allows for much more detailed modeling of cross section variation at the expense of computation time.
The existing capability of NESTLE to use two or four neutron energy groups in the NEM calculation was supplemented with a new routine to allow the use of an arbitrary number of neutron energy groups by calling existing, widely used linear algebra libraries. This represents a significant expansion of NESTLE\u27s capability to model a broader ranger of reactor types beyond typical light water reactors (LWRs). Testing revealed that the new NEM routines retained the accuracy and speed of the existing routines for two and four energy groups, while calculations with other numbers of energy groups had adequate accuracy and speed for practical use
Black Box White Arrow
The present paper proposes a new and systematic approach to the so-called
black box group methods in computational group theory. Instead of a single
black box, we consider categories of black boxes and their morphisms. This
makes new classes of black box problems accessible. For example, we can enrich
black box groups by actions of outer automorphisms.
As an example of application of this technique, we construct Frobenius maps
on black box groups of untwisted Lie type in odd characteristic (Section 6) and
inverse-transpose automorphisms on black box groups encrypting .
One of the advantages of our approach is that it allows us to work in black
box groups over finite fields of big characteristic. Another advantage is
explanatory power of our methods; as an example, we explain Kantor's and
Kassabov's construction of an involution in black box groups encrypting .
Due to the nature of our work we also have to discuss a few methodological
issues of the black box group theory.
The paper is further development of our text "Fifty shades of black"
[arXiv:1308.2487], and repeats parts of it, but under a weaker axioms for black
box groups.Comment: arXiv admin note: substantial text overlap with arXiv:1308.248
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