• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.413-423
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• 2022

The NHIS provides free or highly subsidized healthcare to all people by providing financial fortification. However, the financial sustainability of the scheme is threatened by numerous factors. Therefore, this work sought to provide a solution to process claims intelligently. The provided Petri net model demonstrated successful data flow among the various participant. For efficiency, scalability, and performance two main subsystems were modelled and integrated - data input and claims processing subsystems. We provided smart claims processing algorithm that has a simple and efficient error detection method. The complexity of the main algorithm is good but that of the error detection is excellent when compared to literature. Performance indicates that the model output is reachable from input and the token delivery rate is promising.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5311-5317
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• 2015

Cigarette smoke derivatives like NNK (4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone) and NNAL (4-(methylnitrosamino)-1-(3-pyridyl)-1-butan-1-ol) are well-known carcinogens. We analyzed the interaction of enzymes involved in the NER (nucleotide excision repair) pathway with ligands (NNK and NNAL). Binding was characterized for the enzymes sharing equivalent or better interaction as compared to +Ve control. The highest obtained docking energy between NNK and enzymes RAD23A, CCNH, CDK7, and CETN2 were -7.13 kcal/mol, -7.27 kcal/mol, -8.05 kcal/mol and -7.58 kcal/mol respectively. Similarly the highest obtained docking energy between NNAL and enzymes RAD23A, CCNH, CDK7, and CETN2 were -7.46 kcal/mol, -7.94 kcal/mol, -7.83 kcal/mol and -7.67 kcal/mol respectively. In order to find out the effect of NNK and NNAL on enzymes involved in the NER pathway applying protein-protein interaction and protein-complex (i.e. enzymes docked with NNK/NNAL) interaction analysis. It was found that carcinogens are well capable to reduce the normal functioning of genes like RAD23A (HR23A), CCNH, CDK7 and CETN2. In silico analysis indicated loss of functions of these genes and their corresponding enzymes, which possibly might be a cause for alteration of DNA repair pathways leading to damage buildup and finally contributing to cancer formation.

• Communications of the Korean Mathematical Society
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• v.18 no.1
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• pp.65-73
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• 2003

In this paper we seek a positive, radially symmetric and energy minimizing solution of an m-Laplacian equation, -div$($\mid${\nabla}u$\mid$^{m-2}$\mid${\nabla}u)\;=\;h(u)$. In the variational sense, the solutions are the critical points of the associated functional called the energy, $J(v)\;=\;\frac{1}{m}\;\int_{R^N}\;$\mid${\nabla}v$\mid$^m\;-\;\int_{R^N}\;H(v)dx,\;where\;H(v)\;=\;{\int_0}^v\;h(t)dt$. A positive, radially symmetric critical point of J can be obtained by solving the constrained minimization problem; minimize{$\int_{R^N}$\mid${\nabla}u$\mid$^mdx$\mid$\;\int_{R^N}\;H(u)d;=\;1$}. Moreover, the solution minimizes J(v).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5476-5496
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• 2016

Energy efficiency of resource-constrained wireless sensor networks is critical in applications such as real-time monitoring/surveillance. To improve the energy efficiency and reduce the energy consumption, the time series data can be compressed before transmission. However, most of the compression algorithms for time series data were developed only for single variate scenarios, while in practice there are often multiple sensor nodes in one application and the collected data is actually multivariate time series. In this paper, we propose to compress the time series data by the Lasso (least absolute shrinkage and selection operator) approximation. We show that, our approach can be naturally extended for compressing the multivariate time series data. Our extension is novel since it constructs an optimal projection of the original multivariates where the best energy efficiency can be realized. The two algorithms are named by ULasso (Univariate Lasso) and MLasso (Multivariate Lasso), for which we also provide practical guidance for parameter selection. Finally, empirically evaluation is implemented with several publicly available real-world data sets from different application domains. We quantify the algorithm performance by measuring the approximation error, compression ratio, and computation complexity. The results show that ULasso and MLasso are superior to or at least equivalent to compression performance of LTC and PLAMlis. Particularly, MLasso can significantly reduce the smooth multivariate time series data, without breaking the major trends and important changes of the sensor network system.

• Journal of applied mathematics & informatics
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• v.6 no.3
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• pp.771-771
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• 1999

• Bulletin of the Korean Chemical Society
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• v.24 no.6
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• pp.859-863
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• 2003

We report on the theoretical positron affinities of closed-shell atomic anions. The second-order many-body perturbation theory is applied taking the positron-electron interaction as a perturbation. The corrections for the complete basis set effects to the second order affinity are calculated based on the variational and nonvariational energy functionals of explicitly correlated geminals. It is shown that the explicitly correlated methods accelerate the convergence of the expansion significantly giving the account of the cusp behavior outside the orbital space.

• Journal of applied mathematics & informatics
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• v.6 no.3
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• pp.873-884
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• 1999

On the basis of the semi-linear material of John invoking the theory of homogenization for heterogeneous media and the theory of invariants for isotropic scalar functions an energy function is built for a transversely-isotropic medium in finite elastic deformation. The ponyting Effect for material in simple shear is reviewed for this case of transversal isotropy. It is shown that this effect is apprehended by the constructed energy function.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.122-128
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• 2010

Efficient energy management is a very important issue in wireless sensor network since wireless sensor nodes are usually battery-powered. Recently, S-MAC protocol based on low duty-cycle has been proposed to reduce energy consumption. Even though research effort has been made to evaluate performance of S-MAC by conducting various simulations, however, some important simulation parameters are not well evaluated yet. In this paper, we identify the performance of S-MAC under different amount of streams and different patterns such as data rate and traffic. Through analyzing the simulation results, we discover weakness of S-MAC as well as analyze impact of amount of streams and packet pattern.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.299-300
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• 2003

• Smart Structures and Systems
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• v.14 no.1
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• pp.1-16
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• 2014

In this work, we address the so-called sensor reachback problem for Wireless Sensor Networks, which consists in collecting the measurements acquired by a large number of sensor nodes into a sink node which has major computational and power capabilities. Focused on applications such as Structural Health Monitoring, we propose a cooperative communication protocol that exploits the spatio-temporal correlations of the sensor measurements in order to save energy when transmitting the information to the sink node in a non-stationary environment. In addition to cooperative communications, the protocol is based on two well-studied adaptive filtering techniques, Least Mean Squares and Recursive Least Squares, which trade off computational complexity and reduction in the number of transmissions to the sink node. Finally, experiments with real acceleration measurements, obtained from the Canton Tower in China, are included to show the effectiveness of the proposed method.