• IEIE Transactions on Smart Processing and Computing
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• v.2 no.3
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• pp.148-159
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• 2013

An analysis of the throughput and stability region of random access systems is currently of interest in research and industry. This study evaluated the performance of a multiuser random access channel with a retransmission gain. The channel was composed of a media access control (MAC) determined by the transmission probabilities and a multiuser communication channel characterized by the packet reception probabilities as functions of the number of packet transmissions and the collision status. The analysis began with an illustrative two-user channel, and was extended to a general multiuser channel. For the two-user channel, a sufficient condition was derived, under which the maximum throughput was achieved with a control-free MAC. For the channel with retransmission gain, the maximum steady throughput was obtained in a closed form. The condition under which the random access channel can acquire retransmission gain was also obtained. The stability region of the general random access channel was derived. These results include those of the well-known orthogonal channel, collision channel and slotted Aloha channel with packet reception as a special instance. The analytical and numerical results showed that exploiting the retransmission gain can increase the throughput significantly and expand the stability region of the random access channel. The analytical results predicted the performance in the simulations quite well.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.10 s.89
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• pp.961-968
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• 2004

In this paper, we present a set of numerical schemes to solve the Muller integral equation for the analysis of electromagnetic scattering from arbitrarily shaped three-dimensional dielectric bodies by applying the method of moments(Mon. The piecewise homogeneous dielectric structure is approximated by planar triangular patches. A set of the RWG(Rao, Wilton, Glisson) functions is used for expansion of the equivalent electric and magnetic current densities and a combination of the RWG function and its orthogonal component is used for testing. Numerical results for a dielectric sphere are presented and compared with solutions obtained using other formulations.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.147-149
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• 2005

On this study, we optimized maximizing thrust force of weight ratio and minimizing detent force of weight ratio at the TFLM(Transverse Flux Linear Motor) using design of experiments by the table of orthogonal array, characteristic function and analysis of means(ANOM), For two functions or more, the effectiveness of design change can be evaluated in accordance with change in design parameters. Also, The stator and mover weight of TFLM is reduced by up to 20 percent while its thrust force of weight ratio and detent force of weight improved. From now on, we are going to apply the required technique to design various uses and shares of the TFLM.

• Journal of the Chungcheong Mathematical Society
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• v.34 no.1
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• pp.37-53
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• 2021

In this paper we define scaled visual curvature and visual Frenet frame that can be visually accepted for discrete space curves. Scaled visual curvature is relatively simple compared to multi-scale visual curvature and easy to control the influence of noise. We adopt scaled minimizing directions of height functions on each neighborhood. Minimizing direction at a point of a curve is a direction that makes the point a local minimum. Minimizing direction can be given by a small noise around the point. To reduce this kind of influence of noise we exmine the direction whether it makes the point minimum in a neighborhood of some size. If this happens we call the direction scaled minimizing direction of C at p ∈ C in a neighborhood Br(p). Normal vector of a space curve is a second derivative of the curve but we characterize the normal vector of a curve by an integration of minimizing directions. Since integration is more robust to noise, we can find more robust definition of discrete normal vector, visual normal vector. On the other hand, the set of minimizing directions span the normal plane in the case of smooth curve. So we can find the tangent vector from minimizing directions. This lead to the definition of visual tangent vector which is orthogonal to the visual normal vector. By the cross product of visual tangent vector and visual normal vector, we can define visual binormal vector and form a Frenet frame. We examine these concepts to some discrete curve with noise and can see that the scaled visual curvature and visual Frenet frame approximate the original geometric invariants.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2172-2194
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• 2023

A variational nodal method (VNM) with unstructured-mesh is presented for solving steady-state and dynamic neutron diffusion equations. Orthogonal polynomials are employed for spatial discretization, and the stiffness confinement method (SCM) is implemented for temporal discretization. Coordinate transformation relations are derived to map unstructured triangular nodes to a standard node. Methods for constructing triangular prism space trial functions and identifying unique nodes are elaborated. Additionally, the partitioned matrix (PM) and generalized partitioned matrix (GPM) methods are proposed to accelerate the within-group and power iterations. Neutron diffusion problems with different fuel assembly geometries validate the method. With less than 5 pcm eigenvalue (k_eff) error and 1% relative power error, the accuracy is comparable to reference methods. In addition, a test case based on the kilowatt heat pipe reactor, KRUSTY, is created, simulated, and evaluated to illustrate the method's precision and geometrical flexibility. The Dodds problem with a step transient perturbation proves that the SCM allows for sufficiently accurate power predictions even with a large time-step of approximately 0.1 s. In addition, combining the PM and GPM results in a speedup ratio of 2-3.

• Journal of Korean Dental Science
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• v.17 no.1
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• pp.14-35
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• 2024

The temporomandibular joint (TMJ) is one of the most unique joints in the human body that orchestrates complex movements across different orthogonal planes and multiple axes of rotation. Comprising the articular eminence of the temporal bone and the condylar process of the mandible, the TMJ integrates five major ligaments, retrodiscal tissues, nerves, and blood and lymph systems to facilitate its function. Cooperation between the contralateral TMJ and masticatory muscles is essential for coordinated serial dynamic functions. During mouth opening, the TMJ exhibits a hinge movement, followed by gliding. The health of the masticatory system, which is intricately linked to chewing, energy intake, and communication, has become increasingly crucial with advancing age, exerting an impact on oral and systemic health and overall quality of life. For individuals to lead a healthy and pain-free life, a comprehensive understanding of the basic anatomy and functional aspects of the TMJ and masticatory muscles is imperative. Temporomandibular disorders (TMDs) encompass a spectrum of diseases and disorders associated with changes in the structure, function, or physiology of the TMJ and masticatory system. Functional and pathological alterations in the TMJ and masticatory muscles can be visualized using various imaging modalities, such as cone-beam computed tomography, magnetic resonance imaging, and bone scans. An exploration of potential pathophysiological mechanisms related to the TMJ anatomy contributes to a comprehensive understanding of TMD and informs targeted treatment strategies. Hence, this narrative review presents insights into the fundamental functional anatomy of the TMJ and pathological changes that evolve with TMD progression.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2082-2102
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• 2024

Accurate segmentation of magnetic resonance (MR) images is crucial for providing doctors with effective quantitative information for diagnosis. However, the presence of weak boundaries, intensity inhomogeneity, and noise in the images poses challenges for segmentation models to achieve optimal results. While deep learning models can offer relatively accurate results, the scarcity of labeled medical imaging data increases the risk of overfitting. To tackle this issue, this paper proposes a novel fuzzy c-means (FCM) model that integrates a deep learning approach. To address the limited accuracy of traditional FCM models, which employ Euclidean distance as a distance measure, we introduce a measurement function based on the skewed normal distribution. This function enables us to capture more precise information about the distribution of the image. Additionally, we construct a regularization term based on the Kullback-Leibler (KL) divergence of high-confidence deep learning results. This regularization term helps enhance the final segmentation accuracy of the model. Moreover, we incorporate orthogonal basis functions to estimate the bias field and integrate it into the improved FCM method. This integration allows our method to simultaneously segment the image and estimate the bias field. The experimental results on both simulated and real brain MR images demonstrate the robustness of our method, highlighting its superiority over other advanced segmentation algorithms.

• Economic and Environmental Geology
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• v.49 no.4
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• pp.269-280
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• 2016

I presented three vector crustal magnetic anomaly components and six gradients by using spherical Slepian functions over the cap area of $20^{\circ}$ of radius centered on the South Pole. The Swarm mission, launched by European Space Agency(ESA) in November of 2013, was planned to put three satellites into the low-Earth orbits, two in parallel in East-West direction and one in cross-over of the higher altitude. This orbit configuration will make the gradient measurements possible in North-South direction, vertical direction, as well as E-W direction. The gravity satellites, such as GRACE and GOCE, have already implemented their gradient measurements for recovering the accurate gravity of the Earth and its temporal variation due to mass changes on the subsurface. However, the magnetic gradients have little been applied since Swarm launched. A localized magnetic modeling method is useful in taking an account for a region where data availability was limited or of interest was special. In particular, computation to get the localized solutions is much more efficient and it has an advantage of presenting high frequency anomaly features with numbers of solutions fewer than the global ones. Besides, these localized basis functions that were done by a linear transformation of the spherical harmonic functions, are orthogonal so that they can be used for power spectrum analysis by transforming the global spherical harmonic coefficients. I anticipate in scientific and technical progress in the localized modeling with the gradient measurements from Swarm and here will do discussion on the results of the localized solution to represent the three vector and six gradient anomalies over the Antarctic area from the synthetic data derived from a global solution of the spherical harmonics for the crustal magnetic anomalies of Swarm measurements.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.2
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• pp.160-165
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• 2007

Dispersion parameters for the number of piglets born alive were estimated using a repeatability and random regression model. Six sow breeds/lines were included in the analysis: Swedish Landrace, Large White and both crossbred lines between them, German Landrace and their cross with Large White. Fixed part of the model included sow genotype, mating season as month-year interaction, parity and weaning to conception interval as class effects. The age at farrowing was modelled as a quadratic regression nested within parity. The previous lactation length was fitted as a linear regression. Random regressions for parity on Legendre polynomials were included for direct additive genetic, permanent environmental, and common litter environmental effects. Orthogonal Legendre polynomials from the linear to the cubic power were fitted. In the repeatability model estimate of heritability was 0.07, permanent environmental effect as ratio was 0.04, and common litter environmental effect as ratio was 0.01. Estimates of genetic parameters with the random regression model were generally higher than in the repeatability model, except for the common litter environmental effect. Estimates of heritability ranged from 0.06 to 0.10. Permanent environmental effect as a ratio increased along a trajectory from 0.03 to 0.11. Magnitudes of common litter effect were small (around 0.01). The eigenvalues of covariance functions showed that between 7 and 8 % of genetic variability was explained by individual genetic curves of sows. This proportion was mainly covered by linear and quadratic coefficients. Results suggest that the random regression model could be used for genetic analysis of litter size.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3135-3141
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• 2013

This study derives the optimal conditions for design parameters of clinch stud with high torque resistance and bonding force by using FE simulation and Taguchi method. Maximum forming load and filled rate of material are considered as objective functions. Height and depth of groove with diameter and depth of lobe are chosen as design parameters. These control factors and the friction considered as noise factor are combined by orthogonal array. Forming load and filled rate are evaluated through the simulation. Simulation results are analyzed by using the ratio of signal to noise through Taguchi method. From these results, their optimal combination conditions are proposed. In the order of the most important parameter which affects filled rate, there are the height of lobe, the height of groove, the radius of lobe and the depth of groove.