• Spatial Information Research
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• 제15권2호
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• pp.123-134
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• 2007

지적공부 등록요소의 확대와 3차원 지적정보체계 구축을 통한 국민의 안정적인 소유권 보호 등을 위해서는 지적도에 건물경계선의 등록이 필요하다. 본 연구에서는 타켓 TS 측량방법과 무타켓 TS 측량 방법의 정확도 및 효율성에 대한 비교를 통하여 무타켓 TS 측량에 의한 건물경계선 등록의 효율성을 제시하고자 하였다. 연구결과, 타켓 TS 측량과 무타켓 TS 측량성과의 RMS오차가 X좌표는 ${\pm}0.056m$, Y좌표는 ${\pm}0.043m$로 산출되어 무타켓 TS 측량성과의 높은 정확도를 확인할 수 있었다. 그리고 무타켓 TS 측량이 타켓 TS 측량에 비해 인원 및 관측시간 소요 면에서 효율적임을 알 수 있었다.

• 보건행정학회지
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• 제28권2호
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• pp.186-193
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• 2018

Background: The aim of our study was to review the findings of health insurance fraud investigations and to evaluate their impacts on medical costs for target and non-target organizations. An interrupted time series study design using generalized estimation equations was used to evaluate changes in cost following fraud investigations. Methods: We used National Health Insurance claims data from 2009 to 2015, which included 20,625 medical institutions (1,614 target organizations and 19,011 non-target organizations). Outcome variable included cost change after fraud investigation. Results: Following the initiation of fraud investigations, we found statistically significant reductions in cost level for target organizations (-1.40%, p<0.001). In addition, a reduction in cost trend change per month was found for both target organizations and non-target organizations after fraud investigation (target organizations, -0.33%; non-target organizations of same region, -0.19%; non-target organizations of other regions, -0.17%). Conclusion: This study suggested that fraud investigations are associated with cost reduction in target organization. We also found similar effects of fraud investigations on health expenditure for non-target organizations located in the same region and in different regions. Our finding suggests that fraud investigations are important in controlling the growth of health expenditure. To maximize the effects of fraud investigation on the growth of health expenditure, more organizations needed to be considered as target organizations.

• 제어로봇시스템학회논문지
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• 제19권4호
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• pp.306-314
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• 2013

Automatic tracking in cluttered environment requires the initiation and maintenance of tracks, and track existence probability of true track is kept by Markov Chain Two model of target existence propagation. Unlike Markov Chain One model for target existence propagation, Markov Chain Two model is made up three hypotheses about target existence event which are that the target exist and is detectable, the target exists and is non-detectable through occlusion, and the target does not exist and is non-detectable according to non-existing target. In this paper we present multi-scan single target tracking algorithm based on the target existence, which call the Integrated Track Splitting algorithm with Markov Chain Two model in imaging sensor.

• Molecules and Cells
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• 제39권5호
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• pp.375-381
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• 2016

MicroRNAs (miRNAs) are small non-coding RNAs (~22 nucleotides) regulating gene expression at the post-transcriptional level. By directing the RNA-induced silencing complex (RISC) to bind specific target mRNAs, miRNA can repress target genes and affect various biological phenotypes. Functional miRNA target recognition is known to majorly attribute specificity to consecutive pairing with seed region (position 2-8) of miRNA. Recent advances in a transcriptome-wide method of mapping miRNA binding sites (Ago HITS-CLIP) elucidated that a large portion of miRNA-target interactions in vivo are mediated not only through the canonical "seed sites" but also via non-canonical sites (~15-80%), setting the stage to expand and determine their properties. Here we focus on recent findings from transcriptome-wide non-canonical miRNA-target interactions, specifically regarding "nucleation bulges" and "seed-like motifs". We also discuss insights from Ago HITS-CLIP data alongside structural and biochemical studies, which highlight putative mechanisms of miRNA target recognition, and the biological significance of these non-canonical sites mediating marginal repression.

• 한국전문물리치료학회지
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• 제15권3호
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• pp.44-52
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• 2008

The purpose of this study was to investigate the effects of different objects and target location of dominant hand on the non-dominant hand movement kinematics in a bimanual reaching task. Fifteen right-handed volunteers were asked to reach from same starting point to the different target point of right and left hand with grasping the objects of different size. Independent variables were 1) three different object types (small mug cup, name pen, and PET bottle), and 2) three different target locations (shorter distance, same distance, and longer distance than the non-dominant hand) of the dominant hand. Dependent variables were movement time (MT), movement distance (MD), movement mean velocity ($MV_{mean}$), and movement peak velocity ($MV_{peak}$) of the non-dominant hand. Repeated measures two-way analysis of variance (ANOVA) was used to test for differences in the non-dominant hand movement kinematics during bimanual reaching. The results of this study were as follows: 1) MT of the non-dominant hand was increased significantly when traveling with grasping the mug cup and reaching the far target location, and was decreased significantly when traveling with grasping the PET bottle and reaching the near target location of the dominant hand. 2) MD of the non-dominant hand was significantly increased during reaching the far target location, and significantly decreased during reaching the near target location with dominant hand. 3) $MV_{mean}$ of the non-dominant hand was increased significantly when traveling with grasping the PET bottle, and was decreased significantly when traveling with grasping the mug cup of the dominant hand. Therefore, it can be concluded that the changes of the ipsilateral hand movement have influence on coupling of the contralateral hand movement in bimanual reaching.

• 한국진공학회지
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• 제19권1호
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• pp.45-51
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• 2010

마그네트론 타겟에서 일어나는 다양한 물리적 현상에 의한 결과로 인해 발생하는 타겟 표면의 온도를 측정함으로써 그 분포가 플라즈마, 혹은 증착되는 박막에 영향을 줄 수 있는 가능성을 분석하였다. 마그네트론 스퍼터링의 타겟은 크게 원형 타겟과 사각 타겟으로 구분되는데, 사각 타겟에서는 자기장에 의한 corner effect 등에 의해 전자 집중 방전 영역이 발생하고 그것에 의해 타겟 표면에서 불균일한 온도분포가 생성됨을 확인했다. 국부적으로 온도가 높게 올라가는 지역은 비스퍼터링 지역에 비해 $10{\sim}20^{\circ}C$ 정도 높았으며, 스퍼터링 공정 시 문제점 중에 하나인 particle이 발생하면 그 부분에서 온도가 $20^{\circ}C$ 정도 더 상승함을 알 수 있었다. 이런 영향은 증착되는 박막의 균일도에도 적지 않은 영향을 주었으며 세라믹 타겟의 경우, 균열의 원인이 될 수 있고, 불균일한 타겟 침식으로 타겟의 수명을 단축시키는 문제를 유발하기도 한다.

• 환경분석과 독성보건
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• 제21권4호
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• pp.304-315
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• 2018

Located in Gimhae, Hwapo is the biggest riverine wetland in the province of Gyeongsangsam-do, Korea, and is a major habitat for various species. However, it is suspected that various pollutants enter the wetlands from agricultural and industrial areas. This study identifies major organic pollutants in this wetland and their sources using high performance liquid chromatography-high resolution mass spectrometry during one summer season. Forty-five substances were selected for quantitative analysis using target screening, and other non-selected compounds were screened using suspect and non-target screening methods. The results were that 21 and 17 targeted substances were detected in July and August, respectively. Major pollutants in July and August were oxadiazon (July: 17-220 ng/L, August: 66-460 ng/L), carbendazim (July: 10-110 ng/L, August: 64-520 ng/L), caffeine (July: 33-1,100 ng/L, August: 56-580 ng/L), and niflumic acid (July: 23-75 ng/L, August: 42-290 ng/L). Sampling sites S4 in July and S2 in August were the major inflow points. Ten substances (tricyclazole, hexaconazole, diuron, fexofenadine, irbesartan, simetryn, cimetidine, valsartan, tebuconazole, and benzotriazole) and four metabolites (valsartan acid, azoxystrobin acid, TEB_M324c, and 2-aminobenzimidazole) were tentatively identified through suspect and non-target screening, respectively.

• 한국멀티미디어학회논문지
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• 제20권10호
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• pp.1637-1645
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• 2017

Target/Nontarget classification can be divided into the study of shape estimation of the target analysing reflected echo signal and of type classification of the target using acoustical features. In active sonar system, the feature vectors are extracted from the signal reflected from the target, and an classification algorithm is applied to determine whether the received signal is a target or not. However, received sonar signals can be distorted in the underwater environments, and the spatio-temporal characteristics of active sonar signals change according to the aspect of the target. In addition, it is very difficult to collect real sea-trial data for research. In this paper, target/non-target classification were performed using real sea-trial data. Feature vectors are extracted using MFCC(Mel-Frequency Cepstral Coefficients), filterbank energy in the Fourier spectrum and wavelet domain. For the performance verification, classification experiments were performed using backpropagation neural network classifiers.

• The Journal of Asian Finance, Economics and Business
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• 제6권3호
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• pp.41-53
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• 2019

Building a target capital structure is one of the most important decisions in corporate financial management. The purpose of this article is to identify the determinants of capital structure and adjustment mechanism toward the target leverage. The partial adjustment model was applied on a sample of 306 non-financial companies listed on Vietnam stock exchange market during the period of 2008-2017. By the fixed effect model estimation method, the research results have discovered the factors of growth opportunities, firm size, tangible fixed assets and firm's unique characteristics have a positive effect on the target capital structure of enterprises. Besides, profitability and dividend payment have a negative effect on the target capital structure of enterprises. Accordingly, the research results show that the average adjustment speed toward target leverage of the firms is 90.03%. Research results also demonstrate firms have higher or lower debt ratio than the target debt ratio, capital surplus or capital deficit also have an impact on the adjustment rate toward the target capital structure. The research results are consistent with the Dynamic Trade-off Theory. From this result, this article has provided policy implications for non-financial companies listed on Vietnam's stock market in building a reasonable target capital structure according to operating timeline to maximize enterprise value.

• 전기전자학회논문지
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• 제22권4호
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• pp.1044-1049
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• 2018

CNN(Convolutional Neural Networks)은 동물의 시각정보처리과정을 모델링한 신경망으로 다양한 분야에서 좋은 성능을 보여주고 있다. 본 논문에서는 CNN을 사용하여 능동소나 신호의 스펙트로그램을 분석하고, 표적과 비표적을 식별하는 연구를 수행하였다. 데이터를 표적이 포함된 비율에 따라 8클래스로 구분하고, CNN의 학습에 사용하였다. 신호의 스펙트로그램을 프레임별로 나누어 입력으로 사용한 결과, 표적신호의 위치에서만 표적신호에 해당하는 7개 클래스의 식별 결과가 순차적으로 나타나는 특성을 사용하여 표적과 비표적을 식별해낼 수 있었다.