• Geophysics and Geophysical Exploration
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• v.19 no.1
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• pp.11-19
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• 2016

Two representative residual static methods of traveltime decomposition and stack-power maximization are discussed in terms of application to land seismic data. For the model data with synthetic shot/receiver statics (time shift) applied and random noises added, continuities of reflection event are much improved by stack-power maximization method, resulting the derived time-shifts approximately equal to the synthetic statics. Optimal parameters (maximum allowable shift, correlation window, iteration number) for residual statics are effectively chosen with diagnostic displays of CSP (common shot point) stack and CRP (common receiver point) stack as well as CMP gather. In addition to removal of long-wavelength time shift by refraction statics, prior to residual statics, processing steps of f-k filter, predictive deconvolution and time variant spectral whitening are employed to attenuate noises and thereby to minimize the error during the correlation process. The reflectors including horizontal layer of reservoir are more clearly shown in the variable-density section through repicking the velocities after residual statics and inverse NMO correction.

• Progress in Medical Physics
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• v.24 no.3
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• pp.176-182
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• 2013

Through this research, we measure the data for several SUVs such as SUVLBM, SUVBW, and SUVBSA using volume of interest in order to enhance the diagnostic level in whole-body image for healthy examinees via F-18 FDG PET/CT. Maximum value, mean value, standard deviation, and threshold value for each SUVs are shown. The measurement of SUVs are carried out with 31 examinees who have taken whole-body examination with F-18 FDG PET/CT from July, 2012 to August, 2012. To secure the preciseness of measurement, we selected 26 healthy examinees as a subject of measurement according to diagnostic view of a nuclear-medical doctor. We see from the measurement of SUVs of PET/CT that the value of SUVBW is hightest and followed by SUVLBM and SUVBSA in turn regardless of the use of contrast media. By comparing the SUVLBM-maximum data for the group used contrast media with those for the group used no contrast media, there found a trend that the measured values increase when the contrast media are used. Among them, liver, aorta, lumbar-5, and Cerebellum exhibit significant difference (p<0.05). We conclude that our data for SUVs would be basic references in overall image interpretation, and hope that the research using VOI would be active.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.8
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• pp.5534-5540
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• 2015

This In the railway signaling system, applications of axle counter in addition to track circuit goes on increasing for detecting train position. Consequently, this paper compares sensor methods of axle counter with between geo-magnetism method and proximity sensor method. And it presents differences and results, to improve reliabilities of train detection and axle counting. Also, this article presents an applied result which is based on field experience, with regard to installation, considering attachment condition of sensor part for accurate axle counting. This study acquires expandability that is able to perform not only axle counting function but also various other functions (direction detection of train, speed detection of train, and so on). It was a result of a change of design in order to judge phase difference of sensors, to improve reliability of axle counting. Furthermore, it does not subordinate to characteristics (type, weight of train). And it is confirmed that the omission of axle counting was not occurred in 350km/h. This was the result of Lab test after the construction of transfer equipment of trial axle and Test Bed for axle counting. Both of them are self-productions. Through this, it prepares foundation which is able to apply not only to train detection but also to speed of passing trains, formation number of trains, detector locking condition - when the train passes the section of switch point, and level crossing devices. Furthermore, it would be judged to contribute safety train operation if proximity sensor method applies to the whole railway signaling system from now on.

• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1283-1291
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• 2005

One of the problems in boosting Java performance using a Just-in-Time (JIT) compiler is removing redundant array bound checks. In conventional static compilers, many powerful algorithms have been developed, yet they are not directly applicable to JIT compilation where the compilation time is part of the whole running time. In the current JIT compilers, we tan use either a naive algorithm that is not powerful enough or an aggressive algorithm which requires the transformation into a static single assignment (SSA) form of programs (and back to the original form after optimization), thus causing too much overhead not appropriate for JIT compilation This paper proposes a new algorithm based on an inequality graph which can eliminate array bounds check codes aggressively without resorting to the SSA form. When we actually perform this type of optimization, there are many constraints in code motion caused by the precise exception rule in Java specification, which would cause the algorithm to miss many opportunities for eliminating away bound checks. We also propose a new method to overcome these constraints.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.1
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• pp.9-18
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• 2016

This study reported a case study that showed educational usefulness of SAFMEDS (Say All Fast a Minute Every Day Shuffled) on the improvement of Fluency. The participants were 3 experts with special teacher and speech and pathology, who enrolled a graduate level course, Research in Children with Autism Spectrum Disorder. The SAFMEDS strategy was employed as a study tool for the participants to acquire fluent verbal repertoires related to the key terminologies of Skinner's (1957) analysis of verbal behavior, list 60 pairs of terms. The participants developed 60 term flash cards which presented a target term on the front of the card, and its definition on the back. During the intervention, the participants were required to see the definition and says its term. The results of this study indicated that the SAFMEDS was effective to improve participants' fluent verbal repertoires in terms of both accuracy and fluency. The results of this study would be able to contribute for education professionals to improve certain target operant's accuracy and fluency.

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.761-771
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• 2016

The GloSea5 (Global Seasonal forecasting system version 5) is provided and operated by the KMA (Korea Meteorological Administration). GloSea5 provides Forecast (FCST) and Hindcast (HCST) data and its horizontal resolution is about 60km ($0.83^{\circ}{\times}0.56^{\circ}$) in the mid-latitudes. In order to use this data in watershed-scale water management, GloSea5 needs spatial-temporal downscaling. As such, statistical downscaling was used to correct for systematic biases of variables and to improve data reliability. HCST data is provided in ensemble format, and the highest statistical correlation ($R^2=0.60$, RMSE = 88.92, NSE = 0.57) of ensemble precipitation was reported for the Yongdam Dam watershed on the #6 grid. Additionally, the original GloSea5 (600.1 mm) showed the greatest difference (-26.5%) compared to observations (816.1 mm) during the summer flood season. However, downscaled GloSea5 was shown to have only a -3.1% error rate. Most of the underestimated results corresponded to precipitation levels during the flood season and the downscaled GloSea5 showed important results of restoration in precipitation levels. Per the analysis results of spatial autocorrelation using seasonal Moran's I, the spatial distribution was shown to be statistically significant. These results can improve the uncertainty of original GloSea5 and substantiate its spatial-temporal accuracy and validity. The spatial-temporal reproducibility assessment will play a very important role as basic data for watershed-scale water management.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.500-506
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• 2005

본 논문에서는 자가 생성 지도 학습 알고리즘을 이용한 운송 컨테이너 식별자 인식 시스템을 제안한다. 일반적으로 운송 컨테이너의 식별자들은 글자의 색이 검정색 또는 흰색으로 이루어져 있는 특정이 있다. 이러한 특성을 고려하여 원 컨테이너 영상에 대해 검은색과 흰색을 제외하고는 모든 부분을 잡음으로 처리하기 위해 퍼지 추론 방법을 이용하여 식별자 영역과 바탕영역을 구별한다. 식별자 영역으로 구분 된 영역은 그대로 두고, 바탕 영역으로 구분된 영역 은 전체 영상의 평균 픽셀 값으로 대체시킨다. 그리고 Sobel 마스크를 이용하여 에지를 검출하고, 추출된 에지를 이용하여 수직 블록과 수평 블록을 검출 하여 컨테이너의 식별자 영역을 추출하고 이진화한다. 이진화 된 식별자 영역에 대해 검정색의 빈도수를 이용하여 흰바탕과 민바탕을 구분하고 4 방향 윤곽선 추적 알고리즘을 적용하여 개별 식별자를 추출 한다. 개별 식별자 인식을 위해 자가 생성 지도 학습 알고리즘을 제안하여 개별 식별자 인식에 적용한다. 제안된 자가 생성 지도 학습 알고리즘은 입력층과 은닉층 사이의 구조를 ART-l을 개선하여 적용하고 은닉층과 출력층 사이에는 일반화된 델타 학습 방법과 Delta-bar-Delta 알고리즘을 적용하여 학습 및 인식 성능을 개선한다. 실제 80 개의 컨테이너 영상을 대상으로 실험한 결과, 제안된 식별자 추출 방법이 이전의 개별 추출 방법보다 추출률이 개선되었고 FCM 기반 자가 생성 지도 학습 알고리즘보다 제안된 자가 생성 지도 학습 알고리즘이 컨테이너 식별자의 학습 및 인식에 있어서 개선된 것을 확인하였다.색 문제를 해결하고자 하는 것이 연구의 목적이다. 정보추출은 사용자의 관심사에 적합한 문서들로부터 어떤 구체적인 사실이나 관계를 정확히 추출하는 작업을 가리킨다.앞으로 e-메일, 매신저, 전자결재, 지식관리시스템, 인터넷 방송 시스템의 기반 구조 역할을 할 수 있다. 현재 오픈웨어에 적용하기 위한 P2P 기반의 지능형 BPM(Business Process Management)에 관한 연구와 X인터넷 기술을 이용한 RIA (Rich Internet Application) 기반 웹인터페이스 연구를 진행하고 있다.태도와 유아의 창의성간에는 상관이 없는 것으로 나타났고, 일반 유아의 아버지 양육태도와 유아의 창의성간의 상관에서는 아버지 양육태도의 성취-비성취 요인에서와 창의성제목의 추상성요인에서 상관이 있는 것으로 나타났다. 따라서 창의성이 높은 아동의 아버지의 양육태도는 일반 유아의 아버지와 보다 더 애정적이며 자율성이 높지만 창의성이 높은 아동의 집단내에서 창의성에 특별한 영향을 더 미치는 아버지의 양육방식은 발견되지 않았다. 반면 일반 유아의 경우 아버지의 성취지향성이 낮을 때 자녀의 창의성을 향상시킬 수 있는 것으로 나타났다. 이상에서 자녀의 창의성을 향상시키는 중요한 양육차원은 애정성이나 비성취지향성으로 나타나고 있어 정서적인 측면의 지원인 것으로 밝혀졌다.징에서 나타나는 AD-SR맥락의 반성적 탐구가 자주 나타났다. 반성적 탐구 척도 두 그룹을 비교 했을 때 CON 상호작용의 특징이 낮게 나타나는 N그룹이 양적으로 그리고 내용적으로 더 의미 있는 반성적 탐구를 했다용을 지원하는 홈페이지를 만들어 자료

• Journal of Life Science
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• v.26 no.2
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• pp.234-240
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• 2016

The Y-maze is widely used to test working memory in behavioral science. For this purpose, spontaneous alternation behavior is monitored, and an increased percentage of spontaneous alternation is regarded as enhanced working memory. However, in some cases, the percentage of spontaneous alternation does not accurately reflect the extent of working memory in rodents. To complement the short-comings of this measure, we developed a new method to evaluate working memory on the Y-maze. This is done by defining all spontaneous alternation cases and P_i, the probability that the rodent achieved spontaneous alternation from each alternation case. After all P_i-values acquired in each animal are summarized, the result is considered as entropy. To validate the new analytical method, mice were raised under either control or an enriched environmental condition for 10 weeks, and working memory behavior on the Y-maze was monitored. The results showed that the new analytical method successfully reproduced significance. In addition, the new method turned out to be more accurate than measurement of the percentage of spontaneous alternation, meaning that, to get higher entropy, alternation should be recorded in all arms and directions. Together, these data indicate that the new analytical method is a useful supplement to the method that compares the percentage of spontaneous alternation, and thus is a good tool with which to evaluate working memory in rodents.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1663-1676
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• 2022

Recently, a number of deep-learning based land cover segmentation studies have been introduced. Some studies denoted that the performance of land cover segmentation deteriorated due to insufficient training data. In this study, we verified the improvement of land cover segmentation performance through data augmentation. U-Net was implemented for the segmentation model. And 2020 satellite-derived landcover dataset was utilized for the study data. The pixel accuracies were 0.905 and 0.923 for U-Net trained by original and augmented data respectively. And the mean F1 scores of those models were 0.720 and 0.775 respectively, indicating the better performance of data augmentation. In addition, F1 scores for building, road, paddy field, upland field, forest, and unclassified area class were 0.770, 0.568, 0.433, 0.455, 0.964, and 0.830 for the U-Net trained by original data. It is verified that data augmentation is effective in that the F1 scores of every class were improved to 0.838, 0.660, 0.791, 0.530, 0.969, and 0.860 respectively. Although, we applied data augmentation without considering class balances, we find that data augmentation can mitigate biased segmentation performance caused by data imbalance problems from the comparisons between the performances of two models. It is expected that this study would help to prove the importance and effectiveness of data augmentation in various image processing fields.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.