1,159 research outputs found
Symposium on participatory approaches to reservoir fisheries management: issues, challenges and policies. Dambulla, Sri Lanka, 04-06 Oct. 2004 Session I. Community-based fisheries management; experience in other countries: presentation on STREAM Vietnam’s experience
Established in early 2002, STREAM Vietnam has so far attained a number of good experiences and lessons in using participatory approaches for its work. The Country Office has been able to link to a wide range of stakeholders, and is working hard to build close relationships amongst them, so that institutional entities can better support
the livelihoods of poor aquatic resources users, and support disadvantaged groups of people to improve their living standards by themselves.
Reservoir fisheries and co-management are at early stage in Vietnam, but in certain places and industries co-management has brought about successful results by involving proactive participation of communities. Situated on the same continent and having many similarities, the interaction in agriculture and fisheries sector between Vietnam and Sri Lanka has brought the two countries closer. Being members of the STREAM family, there are great opportunities for exchange of experiences and lessons towards sustainable management of reservoir resources. (PDF has 11 pages.
Classification of hypoglycemic episodes for Type 1 diabetes mellitus based on neural networks
Hypoglycemia is dangerous for Type 1 diabetes mellitus (T1DM) patients. Based on the physiological parameters, we have developed a classification unit with hybridizing the approaches of neural networks and genetic algorithm to identify the presences of hypoglycemic episodes for TIDM patients. The proposed classification unit is built and is validated by using the real T1DM patients' data sets collected from Department of Health, Government of Western Australia. Experimental results show that the proposed neural network based classification unit can achieve more accurate results on both trained and unseen T1DM patients' data sets compared with those developed based on the commonly used classification methods for medical diagnosis including statistical regression, fuzzy regression and genetic programming
Rough Set Approach to Sunspot Classification Problem
Abstract. This paper presents an application of hierarchical learning method based rough set theory to the problem of sunspot classification from satellite images. The Modified Zurich classification scheme [3] is defined by a set of rules containing many complicated and unprecise concepts, which cannot be determined directly from solar images. The idea is to represent the domain knowledge by an ontology of concepts – a treelike structure that describes the relationship between the target concepts, intermediate concepts and attributes. We show that such on-tology can be constructed by a decision tree algorithm and demonstrate the proposed method on the data set containing sunspot extracted from satellite images of solar disk
Lattice Boltzmann for Binary Fluids with Suspended Colloids
A new description of the binary fluid problem via the lattice Boltzmann
method is presented which highlights the use of the moments in constructing two
equilibrium distribution functions. This offers a number of benefits, including
better isotropy, and a more natural route to the inclusion of multiple
relaxation times for the binary fluid problem. In addition, the implementation
of solid colloidal particles suspended in the binary mixture is addressed,
which extends the solid-fluid boundary conditions for mass and momentum to
include a single conserved compositional order parameter. A number of simple
benchmark problems involving a single particle at or near a fluid-fluid
interface are undertaken and show good agreement with available theoretical or
numerical results.Comment: 10 pages, 4 figures, ICMMES 200
Magnetic anomalies in the spin chain system, SrCuZnIrO
We report the results of ac and dc magnetization (M) and heat-capacity (C)
measurements on the solid solution, SrCuZnIrO. While the Zn
end member is known to form in a rhombohedral pseudo one-dimensional
KCdCl structure with an antiferromagnetic ordering temperature of
(T =) 19 K, the Cu end member has been reported to form in a monoclinically
distorted form with a Curie temperature of (T =) 19 K. The magnetism of the
Zn compound is found to be robust to synthetic conditions and is broadly
consistent with the behavior known in the literature. However, we find a lower
magnetic ordering temperature (T) for our Cu compound (~ 13 K), thereby
suggesting that T is sensitive to synthetic conditions. The Cu sample
appears to be in a spin-glass-like state at low temperatures, judged by a
frequency dependence of ac magnetic susceptibility and a broadening of the C
anomaly at the onset of magnetic ordering, in sharp contrast to earlier
proposals. Small applications of magnetic field, however, drive this system to
ferromagnetism as inferred from the M data. Small substitutions for Cu/Zn (x =
0.75 or 0.25) significantly depress magnetic ordering; in other words, T
varies non-monotonically with x (T ~ 6, 3 and 4 K for x = 0.25, 0.5, and
0.67 respectively). The plot of inverse susceptibility versus temperature is
non-linear in the paramagnetic state as if correlations within (or among) the
magnetic chains continuously vary with temperature. The results establishComment: 7 pages, 7 figures, Revte
Long range magnetic ordering in a spin-chain compound, CaCuMnO, with multiple bond distances
The results of ac and dc magnetization and heat capacity measurements as a
function of temperature (T = 1.8 to 300 K) are reported for a
quasi-one-dimensional compound, CaCuMnO, crystallizing in a
triclinically distorted KCdCl-type structure. The results reveal that
this compound undergoes antiferromagnetic ordering close to 5.5 K. In addition,
there is another magnetic transition below 3.6 K. Existence of two long-range
magnetic transitions is uncommon among quasi-one-dimensional systems. It is
interesting to note that both the magnetic transitions are of long-range type,
instead of spin-glass type, in spite of the fact that the Cu-O and Mn-O bond
distances are multiplied due to this crystallographic distortion. In view of
this, this compound could serve as a nice example for studying
"order-in-disorder" phenomena.Comment: Physical Review (in press
U.S. stock market interaction network as learned by the Boltzmann Machine
We study historical dynamics of joint equilibrium distribution of stock
returns in the U.S. stock market using the Boltzmann distribution model being
parametrized by external fields and pairwise couplings. Within Boltzmann
learning framework for statistical inference, we analyze historical behavior of
the parameters inferred using exact and approximate learning algorithms. Since
the model and inference methods require use of binary variables, effect of this
mapping of continuous returns to the discrete domain is studied. The presented
analysis shows that binarization preserves market correlation structure.
Properties of distributions of external fields and couplings as well as
industry sector clustering structure are studied for different historical dates
and moving window sizes. We found that a heavy positive tail in the
distribution of couplings is responsible for the sparse market clustering
structure. We also show that discrepancies between the model parameters might
be used as a precursor of financial instabilities.Comment: 15 pages, 17 figures, 1 tabl
Superconducting proximity effect in clean ferromagnetic layers
We investigate superconducting proximity effect in clean ferromagnetic layers
with rough boundaries. The subgap density of states is formed by Andreev bound
states at energies which depend on trajectory length and the ferromagnetic
exchange field. At energies above the gap, the spectrum is governed by resonant
scattering states. The resulting density of states, measurable by tunneling
spectroscopy, exhibits a rich structure, which allows to connect the
theoretical parameters from experiments.Comment: 11 pages, 5 figures (included
Two nonmagnetic impurities in the DSC and DDW state of the cuprate superconductors as a probe for the pseudogap
The quantum interference between two nonmagnetic impurities is studied
numerically in both the d-wave superconducting (DSC) and the d-density wave
(DDW) state. In all calculations we include the tunnelling through excited
states from the CuO planes to the BiO layer probed by the STM tip. Compared
to the single impurity case, a systematic study of the modulations in the
two-impurity local density of states can distinguish between the DSC or DDW
states. This is important if the origin of the pseudogap phase is caused by
preformed pairs or DDW order. Furthermore, in the DSC state the study of the
LDOS around two nonmagnetic impurities provide further tests for the potential
scattering model versus more strongly correlated models.Comment: 6 pages, 6 figure
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