• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.7
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• pp.9-16
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• 2008

For the efficient routing on a Sensor Network, one may consider a deployment problem to interconnect the sensor nodes optimally. There is an analogous theoretic problem: the Steiner Tree problem of finding the tree that interconnects given points on a plane optimally. One may use the approximation algorithm for the problem to find out the deployment that interconnects the sensor nodes almost optimally. However, the Steiner Tree problem is to interconnect mathematical set of points on a Euclidean plane, and so involves particular cases that do not occur on Sensor Networks. Thus the approach of using the algorithm does not make a proper way of analysis. Differently from the randomly given locations of mathematical points on a Euclidean plane, the locations of sensors on Sensor Networks are assumed to be physically dispersed over some moderate distance with each other. By designing an approximation algorithm for the Sensor Networks in terms of that physical property, one may produce the execution time and the approximation ratio to the optimality that are appropriate for the problem of interconnecting Sensor Networks.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.5 no.1
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• pp.11-21
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• 1994

The vocal pitch is controlled by the tension, mass, and length of the vocal fold. It is well known that cricothyroid approximation raises the vocal pitch by simulating the contraction of the cricothyroid muscle, and there were so many reports that have noted a relationship between cricothyroid distance and pitch control, but there does not seem to be any single generally accepted theory to account for this connection. It is generally known that the strap muscles are active during low and falling Fo, and the suprahyoid muscles are active during high and raising Fo. These findings can be related to a general picture of the motion of the larynx during changes in Fo, the cricothyroid joint would tend to lengthen the vocal folds, as the larynx moves up and forward, and relax them as it moves back and down. In this study, we suggest that the relationship between anterior cricothyroid distance and fundamental frequency of the larynx was so complex according to the level of larynx and vertebral curvature. The higher the level of larynx, the wider the cricothyoid distance, but there is more greater fundamental frequency even though more wide cricothyroid distance. This phono-menon seems to be due to the multifactors, especially the vertical tension of the conus elasticus or the change of cricothyroid articulation. It is generally known that the crocothyoid and vocal is muscles are very closely related to pitch elevation, but sternohyoid muscle seems to be more closely related to pitch lowering. By this electromyographic studies, the sternohyoid muscle have dual activity to pitch control, increased activity during the low fundamental frequency and falling pitch, but also increased activity during the higher fundamental frequency and raising pitch at least in this study.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.288-296
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• 2004

This paper proposes a new mesh simplification algorithm using differential error metric. Many simplification algorithms make use of a distance error metric, but it is hard to measure an accurate geometric error for the high-curvature region even though it has a small distance error measured in distance error metric. This paper proposes a new differential error metric that results in unifying a distance metric and its first and second order differentials, which become tangent vector and curvature metric. Since discrete surfaces may be considered as piecewise linear approximation of unknown smooth surfaces, theses differentials can be estimated and we can construct new concept of differential error metric for discrete surfaces with them. For our simplification algorithm based on iterative edge collapses, this differential error metric can assign the new vertex position maintaining the geometry of an original appearance. In this paper, we clearly show that our simplified results have better quality and smaller geometry error than others.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.3
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• pp.250-257
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• 2017

It is desirable to have a way to predict the pressure drag due to various appendages attached to stern. As a mathematical model for these, a sphere and a singularity behind it, both in the uniform flow can be considered. We may use the Butler's sphere theorem to find the Stokes' stream function when the resulting flow is axisymmetric, and then the extended Lagally's theorem to get the force upon the sphere due to the singularity. Assuming the separation distance between the sphere and the singularity is small, the leading order approximation for the force is obtained and it is found out that if the separation distance and the square root of the strength of the dipole are of the same order, the effect of the image of the dipole with respect to the sphere is the most important.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.367-371
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• 2015

In this paper, a novel localization method for a monocular camera is proposed by using a feature-based probabilistic map. The localization of a camera is generally estimated from 3D-to-2D correspondences between a 3D map and an image plane through the PnP algorithm. In the computer vision communities, an accurate 3D map is generated by optimization using a large number of image dataset for camera pose estimation. In robotics communities, a camera pose is estimated by probabilistic approaches with lack of feature. Thus, it needs an extra system because the camera system cannot estimate a full state of the robot pose. Therefore, we propose an accurate localization method for a monocular camera using a probabilistic approach in the case of an insufficient image dataset without any extra system. In our system, features from a probabilistic map are projected into an image plane using linear approximation. By minimizing Mahalanobis distance between the projected features from the probabilistic map and extracted features from a query image, the accurate pose of the monocular camera is estimated from an initial pose obtained by the PnP algorithm. The proposed algorithm is demonstrated through simulations in a 3D space.

• Journal of applied mathematics & informatics
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• v.41 no.4
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.1-7
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• 2018

In the two-dimensional (2D) modeling of electrical method, the potential in the space domain is reconstructed with the calculated potentials in the wavenumber domain using inverse Fourier transform. The inverse Fourier integral is numerically evaluated using the transformed potential at different wavenumbers. In order to improve the precision of the integration, either the logarithmic or exponential approximation has been used depending on the size of wavenumber. Two numerical methods have been generally used to evaluate the integral; interval integration and Gaussian quadrature. However, both methods do not consider the distance from the current source. Thus the resulting potential in the space domain shows some error. Especially when the distance from the current source is very small or large, the error increases abruptly and the evaluated potential becomes extremely unstable. In this study, we developed a new method to calculate the integral accurately by introducing the distance from the current source to the rescaled Gauss abscissa and weight. The numerical tests for homogeneous half-space model show that the developed method can yield the error level lower than 0.4 percent over the various distances from the current source.

• Journal of Periodontal and Implant Science
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• v.51 no.3
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• pp.189-198
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• 2021

Purpose: This study was conducted to determine how the distance of the near insertion points in a vertical mattress suture from the wound margin influences the pattern of primary closure in an in vitro experimental model. Methods: Pairs of 180 porcine gingival and alveolar mucosa samples were harvested from 90 pig jaws and fixed to a specially designed model. A vertical mattress suture was performed with the near insertion point at 3 different distances from the wound margin (1-, 3-, and 5-mm) on both the gingival and mucosal samples (6 groups; n=30 for each group). The margin discrepancy and the presence of epithelium between the wound margins were measured on histologic slides. Results: The margin discrepancy decreased significantly as the near insertion point became closer to the wound margin both in mucosal tissue (0.241±0.169 mm, 0.945±0.497 mm, and 1.306±0.773 mm for the 1-, 3-, and 5-mm groups, respectively) and in gingival tissue (0.373±0.304 mm, 0.698±0.431 mm, and 0.713±0.691 mm, respectively). The frequency of complications of wound margin adaptation reduced as the distance of the near insertion point from the wound margin decreased both in the mucosal and gingival tissues. Conclusions: Placing the near insertion point close to the wound margin enhances the precision of wound margin approximation/adaptation using a vertical mattress suture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2567-2586
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• 2012

Localization of sensor nodes is a key technology in Wireless Sensor Networks(WSNs). Trilateration is an important position determination strategy. To further improve the localization accuracy, a novel Trilateration based on Point In Triangle testing Localization (TPITL)algorithm is proposed in the paper. Unlike the traditional trilateration localization algorithm which randomly selects three neighbor anchors, the proposed TPITL algorithm selects three special neighbor anchors of the unknown node for trilateration. The three anchors construct the smallest anchor triangle which encloses the unknown node. To choose the optimized anchors, we propose Point In Triangle testing based on Distance(PITD) method, which applies the estimated distances for trilateration to reduce the PIT testing errors. Simulation results show that the PIT testing errors of PITD are much lower than Approximation PIT(APIT) method and the proposed TPITL algorithm significantly improves the localization accuracy.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.26-29
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• 2002

Radial Basis Function (RBF) networks is known as efficient method in classification problems and function approximation. The basis function of RBF networks is usual adopted normal distribution like the Gaussian function. The output of the Gaussian function has the maximum at the center and decrease as increase the distance from the center. For learning of neural network, the method treating the limited area of input space is sometimes more useful than the method treating the whole of input space. The q-normal distribution is the set of probability density function include the Gaussian function. In this paper, we introduce the RBF networks with the basis function of q-normal distribution and actually approximate a function using the RBF networks.