• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.51-55
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• 2004

This paper presents a fast and stable imaging scheme using the localized nonlinear (LN) approximation of integral equation (IE) solutions for inverting electromagnetic data obtained in a crosswell survey. The medium is assumed to be cylindrically symmetric about a source borehole, and to maintain the symmetry a vertical magnetic dipole is used as a source. To find an optimum balance between data fitting and smoothness constraint, we introduce an automatic selection scheme for a Lagrange multiplier, which is sought at each iteration with a least misfit criterion. In this selection scheme, the IE algorithm is quite attractive for saving computing time because Green's functions, whose calculation is a most time-consuming part in IE methods, are repeatedly re-usable throughout the inversion process. The inversion scheme using the LN approximation has been tested to show its stability and efficiency, using both synthetic and field data. The inverted image derived from the field data, collected in a pilot experiment of water-flood monitoring in an oil field, is successfully compared with that derived by a 2.5-dimensional inversion scheme.

• Proceedings of the Korea Association of Crystal Growth Conference
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• 1999.06a
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• pp.45-49
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• 1999

When concentration of vacancies in a CZ silicon crystal is defined by molar fraction XB, the degree of super-saturation $\sigma$ is given by [XB-XBS]/XBS=XB/XBS-1=ln (XB/XBS) because XB/XBS is nearly equal to unity. Here, XBS is the saturated concentration of vacancies in a silicon crystal and XB is a little larger than XBS. According to Bragg-Williams approximation, the chemical potential of the vacancies in the crystal is given by ${\mu}$B=${\mu}$0+RT ln XB+RT ln ${\gamma}$, where R is the gas constant, T is temperature, ${\mu}$0 is an ideal chemical potential of the vacancies and ${\gamma}$ is an adjustable parameter similar to the activity of solute in a solution. Thus, $\sigma$(T) is equal to (${\mu}$B-${\mu}$BS)/RT. Driving force of nucleation of the vacancy agglomeration will be proportional to the chemical potential difference (${\mu}$B-${\mu}$BS) or $\sigma$(T), while growth of the vacancy agglomeration is proportional to diffusion of the vacancies and grad ${\mu}$B.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.9 no.3
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• pp.286-288
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• 1999

When concentration of vacancies in a CZ silicon crystal is defined by molar fraction $X_{B}$, the degree for supersaturation $\sigma$ is given by $[X_{B}-X_{BS}]/X_{BS}=X_{B}/X_{BS}-1=ln(X_{B}/X_{BS})$ because $X_{B}/X_{BS}$ is nearly equal to unity. Here, $X_{BS}$ is the saturated concentration of vacancies in a silicon crystal and $X_{B}$ is a little larger than $X_{BS}$. According to Bragg-Williams approximation, the chemical potential of the vacancies in the crystal is given by ${\mu}_{B}={\mu}^{0}+RT$ ln $X_{B}+RT$ ln ${\gamma}$, where R is the gas constant, T is temperature, ${\mu}^{0}$ is an ideal chemical potential of the vacancies and ${\gamma}$ is and adjustable parameter similar to the activity of solute in a solute in a solution. Thus, ${\sigma}(T)$ is equal to $({\mu}_{B}-{\mu}_{BS})/RT$. Driving force of nucleation for the vacancy agglomeration will be proportional to the chemical potentialdifference $({\mu}_{B}-{\mu}_{BS})/RT$ or ${\sigma}(T)$, while growth of the vacancy agglomeration is proportaional to diffusion of the vacancies and grad ${\mu}_{B}$.

• Journal of the Korean Mathematical Society
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• v.41 no.2
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• pp.345-368
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• 2004

A preconditioning algorithm is developed in this paper for the iterative solution of the linear system of equations resulting from the p-version boundary element approximation of the three dimensional integral equation with hypersingular operators. The preconditioner is derived by first making the nodal and side basis functions locally orthogonal to the element internal bases, and then by decoupling the nodal and side bases from the internal bases. Its implementation consists of solving a global problem on the wire-basket and a series of local problems defined on a single element. Moreover, the condition number of the preconditioned system is shown to be of order $O((1＋ln/p)^{7})$. This technique can be applied to discretization with triangular elements and with general basis functions.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.335-343
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• 2014

This paper considers the crucial problem of deploying wireless relays for achieving a connected wireless sensor network in indoor environments, an important aspect related to the management of the sensor network. Several algorithms have been proposed for ensuring full sensing coverage and network connectivity. These algorithms are not applicable to indoor environments because of the complexity of indoor environments, in which a radio signal can be dramatically degraded by obstacles such as walls. We first prove theoretically that the indoor relay placement problem is NP-hard. We then predict the radio coverage of a given relay deployment in indoor environments. We consider two practical scenarios; wire-connected relays and radio-connected relays. For the network with wire-connected relays, we propose an efficient greedy algorithm to compute the deployment locations of relays for achieving the required coverage percentage. This algorithm is proved to provide a $H_n$ factor approximation to the theoretical optimum, where $H_n=1+{\frac{1}{2}}+{\cdots}+{\frac{1}{n}}={\ln}(n)+1$, and n is the number of all grid points. In the network with radio-connected relays, relays have to be connected in an ad hoc mode. We then propose an algorithm based on the previous algorithm for ensuring the connectivity of relays. Experimental results demonstrate that the proposed algorithms achieve better performance than baseline algorithms.