• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.54-60
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• 2018

The data acquired from seismic exploration can be used to detect the existence of oil and gas resources through appropriate processing and interpretation. The seismic attributes indicating the existence of resources are extracted from amplitude information, where the Q-factor representing intrinsic attenuation plays an useful role of hydrocarbon indicator. So, the accuracy of Q-factor estimation is very important to investigate the existence of resources. In this study, we calculated the Q-factor and analyzed the error rate through a numerical example. To mimic real data, random noise was added to the synthetic data. With the noise-added data, the Q-factor was estimated and the error rate was analyzed by using the spectral ratio method (SRM) and peak frequency shift method (PFSM). Both methods provided a relatively accurate Q-factor when the signal-to-noise ratio was 90 dB. However, the peak frequency shift method (PFSM) produced better results than the spectral ratio method (SRM) as the level of random noise increased.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.213-219
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• 2005

In order to move NPC's to target location at game maps, various algorithm including A* has been used. The most frequently used algorithm among them is A* with fast finding speed. But A* has the following problems. The first problem is that at randomly changing map, it is necessary to calculate all things again whenever there are any changes. And when calculation is wrong, it is not possible to search for target. The second problem is that it is difficult to move avoiding dangerous locations damaging NPC such as an obstruction. Although it is possible to avoid moving to locations with high weight by giving weight to dangerous factors. it is difficult to control in case NPC moves nearby dangerous factors. In order to solve such problems, in this thesis, the researcher applied Dynamic Programming to path-finding algorithm. As the result of its application, the researcher could confirm that the programming was suitable for changes at the map with random change and NPC's avoided the factors being dangerous to them far away. In addition. when compared to A*, there were good results.

• Journal of Advanced Navigation Technology
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• v.11 no.2
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• pp.154-162
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• 2007

This paper verifies the performance of the wireless-signal map-matching (WSMM) method that is recently proposed to mitigate the effects of non-line-of-sight (NLOS) error in positioning under wireless terrestrial network environments. The WSMM method is the new positioning technology that estimates and compensate the NLOS errors by processing the bulks of anonymous measurements at unknown locations that are collected randomly and automatically. The WSMM method would be advantageous for various configurations of future ubiquitous sensor networks since it is based on the existing network configuration for communication and it requires no additional hardware in base stations and mobile handsets. It is shown that the application of the WSMM concept to the real CDMA pilot strength measurment message (PSMM) actually mitigates the NLOS error effects and improves overall positioning accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5730-5736
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• 2013

The study was conducted to determine the effect of trunk pattern training in proprioceptive neuromuscular facilitation(PNF) and weight-shift training on the muscle activity and static balance in patients with hemiplegia due to stroke. Twenty patients with hemiplegia due to stroke were assigned to the trunk pattern training in PNF group(n=10) or weight-shift training group(n=10). Both groups were executed conventional treatment for 5 times per week for 6 weeks 30 minutes per session. Each group performed additional training for 20 minutes. Post training, compared to the weight-shift training group, trunk pattern training in PNF group showed significantly increased on muscle activity of rectus femoris, gastrocnemius and static balance(p<.05). These results support the perceived benefits of trunk pattern training in PNF to augment on the static balance and muscle activity of stroke patients. Therefore, trunk pattern training in PNF is feasible and suitable for stroke patients.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.14 no.3
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• pp.171-178
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• 1981

The growth of Sebastes alutus was studied by scale reading to check the change of growth rate at the early stage of life. Lee's phenomenon was recognized on the scale measurements except thc first ring radius. No evidence was found to support the change of growth rate at early stage. Von Bert-alanffy's growth equation was estimated with the back-calculated fork lengths, $1_t=357.8(1-e^{-0.6124(t+1.8566)}),\;and\;W_{\infty}=784.4g$

• Journal of Digital Convergence
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• v.11 no.8
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• pp.205-212
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• 2013

In this paper, we present a procedural modeling algorithms to create Korean traditional stone fence using the fractal subdivision. The main process of the algorithm is to get the next step mesh by subdividing each triangle in the previous step triangular mesh. This process is repeated recursively. Dividing each triangle into four sub-triangles after choosing a random point on each side of the triangle and moving each vertices in the normal direction with random perturbations make the bumpy appearance of stone fences. In each step we remove flat vertices which does not influence the shape of the stone. The discrete curvature determines the flatness of a vertex. New triangles whose vertices are the vertices around the removed vertex are added to make a triangular mesh.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.97-103
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• 2005

Recent development of marine magnetic gradient systems, using arrays of sensors, has made it possible to survey large contaminated areas very quickly. However, underwater Unexploded Ordnances (UXO) can be moved by water currents. Because of this mobility, the cleanup process in such situations becomes dynamic rather than static. This implies that detection should occur in near real-time for successful remediation. Therefore, there is a need for a fast interpretation method to rapidly detect signatures of underwater objects in marine magnetic data. In this paper, we present a fast method for location and characterization of underwater UXOs. The approach utilises gradient interpretation techniques (analytic signal and Euler methods) to locate the objects precisely. Then, using an iterative linear least-squares technique, we obtain the magnetization characteristics of the sources. The approach was applied to a theoretical marine magnetic anomaly, with random errors, over a known source. We demonstrate the practical utility of the method using marine magnetic gradient data from Japan.

• Journal of the Korea Computer Graphics Society
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• v.29 no.4
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• pp.7-16
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• 2023

For decades, creating a desired locomotive motion in a goal-oriented manner has been a challenge in character animation. Data-driven methods using generative models have demonstrated efficient ways of predicting long sequences of motions without the need for explicit conditioning. While these methods produce high-quality long-term motions, they can be limited when it comes to synthesizing motion for challenging novel scenarios, such as punching a random target. A state-of-the-art solution to overcome this limitation is by using a GAN Discriminator to imitate motion data clips and incorporating reinforcement learning to compose goal-oriented motions. In this paper, our research aims to create characters performing combat sports such as boxing, using a novel reward design in conjunction with existing GAN-based approaches. We experimentally demonstrate that both the Adversarial Motion Prior [3] and Adversarial Skill Embeddings [4] methods are capable of generating viable motions for a character punching a random target, even in the absence of mocap data that specifically captures the transition between punching and locomotion. Also, with a single learned policy, multiple task controllers can be constructed through the TimeChamber framework.

• The Korean Journal of Nuclear Medicine
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• v.37 no.6
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• pp.374-381
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• 2003

Purpose: Determining an appropriate thresholding is crucial for PDG PET analysis since strong control of Type I error could fail to find pathological differences between eariy Alzheimer' disease (AD) patients and healthy normal controls. We compared the SPM results on FDG PET imaging of early AD using uncorrected p-value, random-field based corrected p-value and false discovery rate (FDR) control. Materials and Methods: Twenty-eight patients ($66{\pm}7$ years old) with early AD and 18 age-matched normal controls ($68{\pm}6$ years old) underwent FDG brain PET. To identify brain regions with hypo-metabolism in group or individual patient compared to normal controls, group images or each patient's image was compared with normal controls usingthe same fixed p-value of 0.001 on uncorrected thresholding, random-field based corrected thresholding and FDR control. Results: The number of hypo-metabolic voxels was smallest in corrected p-value method, largest in uncorrected p-value method and intermediate in FDG thresholding in group analysis. Three types of result pattern were found. The first was that corrected p-value did not yield any voxel positive but FDR gave a few significantly hypometabolic voxels (8/28, 29%). The second was that both corrected p-value and FDR did not yield any positive region but numerous positive voxels were found with the threshold of uncorrected p-values (6/28, 21%). The last was that FDR was detected as many positive voxels as uncorrected p-value method (14/28, 50%). Conclusions FDR control could identify hypo-metaboiic areas in group or individual patients with early AD. We recommend FDR control instead of uncorrected or random-field corrected thresholding method to find the areas showing hypometabolism especially in small group or individual analysis of FDG PET.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.265-265
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• 2016

호우가 홍수에 미치는 영향의 분석은 수문현상을 이해하고 수공구조물을 설계하는데 반드시 필요한 절차이다. 호우가 홍수에 미치는 영향을 분석하기 위해서 독립된 소유역부터 비독립된 대유역까지 홍수량을 계산하고 그 상관성을 이해해야 하지만 상류쪽의 소유역의 경우 관측자료의 부재가 빈번하여 이러한 전반적인 분석이 쉽지 않다. 그리고 소유역과 대유역의 홍수특성을 연관지어 분석하기 위해서는 비교가능한 홍수특성을 추출해야 하며 이러한 일관된 잣대를 사용한 홍수분석은 중요하다. 본 연구에서는 소유역의 자료부재를 보완하기 위해 자료공간확장 방법을 제안하고 이를 통하여 안동댐 유역내 총 50개 지점의 홍수 시계열자료를 생성하였다. 자료공간확장 방법으로써, 안동댐유역의 1989년부터 2009년까지의 자료의 질이 좋은 20개의 사상을 추출하였고 안동댐유역 내에 위치한 안동댐, 도산, 소천의 수위관측지점의 관측유량자료에 대해 분포형 모형인 GRM 모형의 매개변수를 시행착오법으로 동시에 보정하여 한 개셋의 최적 매개변수를 추정하였다. 이때 모의결과를 평가하기 위하여 Nash-Sutcliffe (NS) 계수를 사용하였으며 20갯 사상의 세군데 관측수위지점에 대해서 모의결과가 전반적으로 0.5 NS 계수 이상으로써 만족할 만한 결과를 얻었다. 이 추정된 매개변수는 47개의 추가적인 관심지점의 유출모의에 사용되었으며 이렇게 모의된 유출시계열 자료는 관측시계열 자료로 가정하여 사용하였다. 이렇게 공간확장되어 생성된 시계열 자료는 이동평균방법을 사용하여 홍수강도-지속시간 곡선으로 변환되었고 50개 유역의 평균강우량 시계열 자료 또한 같은 밥법을 사용하여 강우강도-지속시간 곡선으로 변환되었다. 50개 유역의 비교가능한 일관된 홍수특성을 추출하기 위해 비유량법의 유출계수를 계산하였다. 유출계수를 계산하기 위해 유역별 도달시간을 계산하였으며 이 도달시간에 해당하는 강우강도를 추출하였다. 그리고 유역별 첨두 홍수강도를 유역별 도달시간에 해당하는 강우강도로 나눠줌으로써 유역별 유출계수를 계산하였고 이 유출계수를 유역면적에 대해 도시함으로써 그 경향을 조사하였다. 조사 결과 유역면적이 $100km^2$ 이상으로써 상류에서 하류방향으로 유역이 중첩되면서 증가하는 비독립적인 유역들의 경우 유역면적이 증가함에 따라 유출계수가 작아지거나 커지는 어떠한 경향을 보였다. 하지만 유역면적이 $100km^2$ 이하로써 독립적인 소유역의 경우 유역면적이 증가함에 따라 유출계수는 무작위로 분포되었다. 이것은 비독립적인 유역의 경우에는 호우가 홍수에 어떠한 일관된 영향을 미치나 각각 독립된 소유역의 경우에는 일관된 영향을 미치지 않음으로써 지역화방법에 의한 독립된 인근 미계측유역의 유출추정은 그 신뢰성이 높지 않다는 것을 의미한다.