49 research outputs found
Overcoming Challenges to Teamwork in Patient-Centered Medical Homes: A Qualitative Study
There is emerging consensus that enhanced inter-professional teamwork is necessary for the effective and efficient delivery of primary care, but there is less practical information specific to primary care available to guide practices on how to better work as teams. The purpose of this study was to describe how primary care practices have overcome challenges to providing team-based primary care and the implications for care delivery and policy
On the Approximability and Hardness of the Minimum Connected Dominating Set with Routing Cost Constraint
In the problem of minimum connected dominating set with routing cost
constraint, we are given a graph , and the goal is to find the
smallest connected dominating set of such that, for any two
non-adjacent vertices and in , the number of internal nodes on the
shortest path between and in the subgraph of induced by is at most times that in . For general graphs, the only
known previous approximability result is an -approximation algorithm
() for by Ding et al. For any constant , we
give an -approximation
algorithm. When , we give an -approximation
algorithm. Finally, we prove that, when , unless , for any constant , the problem admits no
polynomial-time -approximation algorithm, improving
upon the bound by Du et al. (albeit under a stronger hardness
assumption)
2-[2-(Hydroxymethyl)phenyl]-1-phenylethanol
The title compound, C15H16O2, has a dihedral angle of 19.10 (5)° between the mean planes of the two benzene rings. There is an intramolecular O—H⋯O hydrogen bond and the C—C—C—C torsion angle across the bridge between the two rings is 173.13 (14)°. The molecules form intermolecular O—H⋯O hydrogen-bonded chains extending along the a axis. C—H⋯π contacts are also observed between molecules within the chains
Hardness and approximation for the geodetic set problem in some graph classes
In this paper, we study the computational complexity of finding the
\emph{geodetic number} of graphs. A set of vertices of a graph is a
\emph{geodetic set} if any vertex of lies in some shortest path between
some pair of vertices from . The \textsc{Minimum Geodetic Set (MGS)} problem
is to find a geodetic set with minimum cardinality. In this paper, we prove
that solving the \textsc{MGS} problem is NP-hard on planar graphs with a
maximum degree six and line graphs. We also show that unless , there is
no polynomial time algorithm to solve the \textsc{MGS} problem with
sublogarithmic approximation factor (in terms of the number of vertices) even
on graphs with diameter . On the positive side, we give an
-approximation algorithm for the \textsc{MGS}
problem on general graphs of order . We also give a -approximation
algorithm for the \textsc{MGS} problem on the family of solid grid graphs which
is a subclass of planar graphs
On the Approximability of the Minimum Rainbow Subgraph Problem and Other Related Problems
In this paper, we study the approximability of the minimum rainbow subgraph (MRS) problem and other related problems. The input to the problem is an n-vertex undirected graph, with each edge colored with one of p colors. The goal is to find a subgraph on a minimum number of vertices which has one induced edge of each color. The problem is known to be NP-hard, and has an upper bound of O(root n) and a lower bound of Omega(log n) on its approximation ratio. We define a new problem called the densest colored k-subgraph problem, which has the same input as the MRS problem along with a parameter k. The goal is to output a subgraph on k vertices, which has the maximum number of edges of distinct colors. We give an O(n(1/3))-approximation algorithm for it, and then, using that algorithm, give an O(n(1/3) log n)-approximation algorithm for the MRS problem. We observe that the Min-Rep problem (the minimization variant of the famous Label Cover problem) is indeed a special case of the MRS problem. This also implies a combinatorial O(n(1/3) log n)-approximation algorithm for the Min-Rep problem. Previously, Charikar et al. (Algorithmica 61(1):190-206, 2011) showed an ingenious LP-rounding based algorithm with an approximation ratio of O(n(1/3) log(2/3) n) for Min-Rep. It is quasi-NP-hard to approximate the Min-Rep problem to within a factor of 2(log1-is an element of n) (Kortsarz in Algorithmica 30(3): 432-450, 2001). The same hardness result now applies to the MRS problem. We also give approximation preserving reductions between various problems related to the MRS problem for which the best known approximation ratio is O(n(c)) where n is the size of the input and c is a fixed constant less than one
Polarimetric SAR decomposition parameter subset selection and their optimal dynamic range evaluation for urban area classification using Random Forest
Urban area classification is important for monitoring the ever increasing urbanization and studying its environmental impact. Two NASA JPL's UAVSAR datasets of L-band (wavelength: 23 cm) were used in this study for urban area classification. The two datasets used in this study are different in terms of urban area structures, building patterns, their geometric shapes and sizes. In these datasets, some urban areas appear oriented about the radar line of sight (LOS) while some areas appear non-oriented. In this study, roll invariant polarimetric SAR decomposition parameters were used to classify these urban areas. Random Forest (RF), which is an ensemble decision tree learning technique, was used in this study. RF performs parameter subset selection as a part of its classification procedure. In this study, parameter subsets were obtained and analyzed to infer scattering mechanisms useful for urban area classification. The Cloude-Pottier alpha, the Touzi dominant scattering amplitude as, and the anisotropy A were among the top six important parameters selected for both the datasets. However, it was observed that these parameters were ranked differently for the two datasets. The urban area classification using RF was compared with the Support Vector Machine (SVM) and the Maximum Likelihood Classifier (MLC) for both the datasets. RF outperforms SVM by 4% and MLC by 12% in Dataset 1. It also outperforms SVM and MLC by 3.5% and 11% respectively in Dataset 2. (C) 2015 Elsevier B.V. All rights reserved
Coastal changes along the coast of Tadri River, Karnataka West coast of India and its implication
1162-1166Present
study of the coastal changes in Tadri, Uttara Kannada district of Karnataka,
comparing Survey of India Toposheet, Coastal Zone Management Plan of Karnataka
and traditional ground survey measurement merged with multi temporal satellite
imagery (IRS-P6, LISS III, 2011). This analysis gives the result of erosion
from year 1978 to 1996 is 7.83 km2, during this period no accretion
is noticed. Comparing data set of 1978 with 2011, area of erosion increases to
8.45km2, and accretion by 0.15 km2. And from 1996 to 2011 it is seen erosion of
3.61km2 and accretion of 3.05 km2. Erosion is observed in the northern bank of
Tadri river, the probable cause of erosion is tidal action along the earthen
embankments results in breaching and due to this flood are occurring in the
adjacent area, and an accretion is noticed at the mouth result in narrowing the
shape, due to sediments brought from upper reaches of Tadri river. The present
studies givea scenario of changes and may help authorities to prepare the
better Integrated Coastal Zone Management Plan for coastal protection and
further developments.</span
Dimensional Relationships in <i>Crassostrea madrasensis</i> (Preston) and <i>C. gryphoides</i> (Schlotheim) in Mangrove Ecosystem
559-566Mangrove
influenced estuarine habits in the tropics are favor the settlement of oysters
and their larval stages, which protect them from strong waves and speedy
currents. Shell structure in Bivalves forms an important protective system.
Description of the relationship between shell and soft body characteristics are
essential in understanding ecological variations and productivity of oyster
population. A total number of 627 oyster specimens were collected from
different locations in Goa as case study for
the tropical estuaries and studied for their allometric relationships. Data
described in the present document could be of importance in monitoring the
health of natural oyster beds. It also serves a baseline for planning
sustainable management and understanding the aquaculture potential of Crassostrea spp. in mangrove influenced
estuarine habitats
Random Forest-Based Prospectivity Modelling of Greenfield Terrains Using Sparse Deposit Data: An Example from the Tanami Region, Western Australia
Data-driven prospectivity modelling of greenfields terrains is challenging because very few deposits are available and the training data are overwhelmingly dominated by non-deposit samples. This could lead to biased estimates of model parameters. In the present study involving Random Forest (RF)-based gold prospectivity modelling of the Tanami region, a greenfields terrain in Western Australia, we apply the Synthetic Minority Over-sampling Technique to modify the initial dataset and bring the deposit-to-non-deposit ratio closer to 50:50. An optimal threshold range is determined objectively using statistical measures such as the data sensitivity, specificity, kappa and per cent correctly classified. The RF regression modelling with the modified dataset of close to 50:50 sample ratio of deposit to non-deposit delineates 4.67% of the study area as high prospectivity areas as compared to only 1.06% by the original dataset, implying that the original "sparse" dataset underestimates prospectivity