22,134 research outputs found
Remote Sensing and Problems of the Hydrosphere
A discussion of freshwater and marine systems is presented including areas of the classification of lakes, identification and quantification of major functional groups of phytoplankton, sources and sinks of biochemical factors, and temporal and regional variability of surface features. Atmospheric processes linked to hydrospheric process through the transfer of matter via aerosols and gases are discussed. Particle fluxes to the aquatic environment and global geochemical problems are examined
Remote Sensing and Problems of the Hydrosphere. A Focus for Future Research
The underly problems of water quality which are addressable with remote sensors are considered. The chemical, biological, geological, and physical dynamics of natural ecosystems are examined
Properties of Nucleon Resonances by means of a Genetic Algorithm
We present an optimization scheme that employs a Genetic Algorithm (GA) to
determine the properties of low-lying nucleon excitations within a realistic
photo-pion production model based upon an effective Lagrangian. We show that
with this modern optimization technique it is possible to reliably assess the
parameters of the resonances and the associated error bars as well as to
identify weaknesses in the models. To illustrate the problems the optimization
process may encounter, we provide results obtained for the nucleon resonances
(1230) and (1700). The former can be easily isolated and thus
has been studied in depth, while the latter is not as well known
experimentally.Comment: 12 pages, 10 figures, 3 tables. Minor correction
Sub-structural Niching in Estimation of Distribution Algorithms
We propose a sub-structural niching method that fully exploits the problem
decomposition capability of linkage-learning methods such as the estimation of
distribution algorithms and concentrate on maintaining diversity at the
sub-structural level. The proposed method consists of three key components: (1)
Problem decomposition and sub-structure identification, (2) sub-structure
fitness estimation, and (3) sub-structural niche preservation. The
sub-structural niching method is compared to restricted tournament selection
(RTS)--a niching method used in hierarchical Bayesian optimization
algorithm--with special emphasis on sustained preservation of multiple global
solutions of a class of boundedly-difficult, additively-separable multimodal
problems. The results show that sub-structural niching successfully maintains
multiple global optima over large number of generations and does so with
significantly less population than RTS. Additionally, the market share of each
of the niche is much closer to the expected level in sub-structural niching
when compared to RTS
Space- and Time-Efficient Algorithm for Maintaining Dense Subgraphs on One-Pass Dynamic Streams
While in many graph mining applications it is crucial to handle a stream of
updates efficiently in terms of {\em both} time and space, not much was known
about achieving such type of algorithm. In this paper we study this issue for a
problem which lies at the core of many graph mining applications called {\em
densest subgraph problem}. We develop an algorithm that achieves time- and
space-efficiency for this problem simultaneously. It is one of the first of its
kind for graph problems to the best of our knowledge.
In a graph , the "density" of a subgraph induced by a subset of
nodes is defined as , where is the set of
edges in with both endpoints in . In the densest subgraph problem, the
goal is to find a subset of nodes that maximizes the density of the
corresponding induced subgraph. For any , we present a dynamic
algorithm that, with high probability, maintains a -approximation
to the densest subgraph problem under a sequence of edge insertions and
deletions in a graph with nodes. It uses space, and has an
amortized update time of and a query time of . Here,
hides a O(\poly\log_{1+\epsilon} n) term. The approximation ratio
can be improved to at the cost of increasing the query time to
. It can be extended to a -approximation
sublinear-time algorithm and a distributed-streaming algorithm. Our algorithm
is the first streaming algorithm that can maintain the densest subgraph in {\em
one pass}. The previously best algorithm in this setting required
passes [Bahmani, Kumar and Vassilvitskii, VLDB'12]. The space required by our
algorithm is tight up to a polylogarithmic factor.Comment: A preliminary version of this paper appeared in STOC 201
Crystal structure prediction using the Minima Hopping method
A structure prediction method is presented based on the Minima Hopping
method. Optimized moves on the configurational enthalpy surface are performed
to escape local minima using variable cell shape molecular dynamics by aligning
the initial atomic and cell velocities to low curvature directions of the
current minimum. The method is applied to both silicon crystals and binary
Lennard-Jones mixtures and the results are compared to previous investigations.
It is shown that a high success rate is achieved and a reliable prediction of
unknown ground state structures is possible.Comment: 9 pages, 6 figures, novel approach in structure prediction, submitted
to the Journal of Chemical Physic
The non-metallic materials sample array
The Non-Metallic Materials Sample Array (MSA) was flown as verification flight instrumentation (VFI) on both Spacelab 1 (SL-1) and Spacelab 2 (SL-2). The basis for materials selection was either previous flight history or probable flight suitability based upon analysis. The observed changes in the optical properties of the exposed materials are, in general, quite minimal; however, this data represents the short exposure of two Space Shuttle missions, and no attempt should be made to extrapolate the long-term exposure. The MSA was in orbit for 10 days at approximately 240 km on SL-1 and for 7 days at approximately 315 km on SL-2. The array was exposed to the solar flux for only a portion of the time in orbit
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