• 한국융합학회논문지
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• 제11권12호
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• pp.283-290
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• 2020

본 연구는 한국 성인을 대상으로 고요산혈증 위험을 예측하기 위한 중성지방-혈당 지수(triglyceride and glucose index, TyG index)의 유용성을 평가하였다. 서울지역 종합병원에서 2017년부터 2019년까지 건강진단을 실시한 20세 이상 남성 14,266명, 여성 9,033명을 대상으로 하였다. TyG 지수에 따른 고요산혈증 발생 위험도는 로지스틱 회귀분석을 실시하였으며, TyG 지수의 고요산혈증 위험 예측능력을 확인하기 위해 ROC 곡선을 구하였다. 고요산혈증을 예측하기 위한 TyG 지수의 정확도는 0.68이며, 남성 0.61, 여성 0.67이었다(각각 p<0.001). TyG 지수의 고요산혈증 발생 위험은 1사분위수보다 4사분위수에서 1.69배 높았으며, 남성은 2.03배, 여성은 2.07배 높았다(각각 p<0.05). 따라서 TyG 지수는 고요산혈증의 선별검사로서 진단적 유용성은 높지 않았으나, TyG 지수와 고요산혈증간에는 관련이 있었다.

• 한국방재안전학회논문집
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• 제16권3호
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• pp.35-43
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• 2023

본 논문은 생활안전지수 보정 방안에 대한 연구를 소개한다. 생활안전지수는 생활안전 예방서비스 시스템에서 제공되는 서비스로써, 개인의 일상생활 안전수준을 종합적으로 평가하여 개개인의 안전상태를 수시로 파악하고, 안전사고를 사전에 예방하기 위해 종합지수 형태로 나타낸다. 이전의 선행 연구에서는 생활안전 예방서비스를 평가하기 위한 평가 기준(항목)을 기반으로 하여 AHP(Analysis Hierarchy Process)와 Likert Scale 기법을 혼용하여 개발되었다. 이에 본 연구에서는 이러한 기존의 생활안전지수를 기반으로, 개인의 특성에 따른 보정 인자를 생활안전지수에 적용하는 방안을 탐구하고자 한다. 기존의 국가 통계를 활용한 보정 인자를 개발하여 개인 프로파일에 맞는 개별화된 서비스를 제공하는 방법을 제시한다. 따라서 본 논문은 생활안전지수 개발 및 보정 방법론에 대한 응용을 통해 사용자 맞춤형 서비스를 제공하는 방법에 대하여 제안하고자 한다.

• 대한인간공학회지
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• 제21권3호
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• pp.47-58
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• 2002

The similarity of shape of shape of interface between human cognitive map and real product is the important factor to determine the human performance. Nevertheless, the degree of similarity between these has not been defined quantitatively in recent studies. Therefore, in this study, the cognitive map and the mental workload were measured by SMM(Sketch Map Method) and RNASA-TLX(Revision of NASA-Task Load Index). And the numerical expression of the accuracy point was suggested for the quantitative calculation of relative positional similarity between cognitive map and real product. In the experiment, nine subjects were participated and two kinds of vehicles were used. Mental workload was mental workload was measured immediately after the road test. The result of analysis on the relationship between accuracy and mental workload shows that the negative correlation exists on each vehicle, and the lower score of mental workloads id measured on the vehicle that has the higher score of accuracy between two vehicles.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.555-559
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• 1998

The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis have been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, We proposed an optimal pattern classifier by neural network to improve the accuracy of chromosome classification. The proposed pattern classifier was built up of two-step multi-layer neural network(TMANN). We reconstructed chromosome image to improve the chromosome classification accuracy and extracted four morphological features parameters such as centromeric index (C.I.), relative length ratio(R.L.), relative area ratio(R.A.) and chromosome length(C.L.). These Parameters employed as input in neural network by preprocessing twenty human chromosome images. The experiment results shown that the chromosome classification error was reduced much more than that of the other classification methods.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1503-1516
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• 2019

In this paper, to improve the accuracy of long sentence similarity calculation, we proposed a sentence similarity calculation method based on a system similarity function. The algorithm uses word2vector as the system elements to calculate the sentence similarity. The higher accuracy of our algorithm is derived from two characteristics: one is the negative effect of penalty item, and the other is that sentence similar function (SSF) based on word2vector similar elements doesn't satisfy the exchange rule. In later studies, we found the time complexity of our algorithm depends on the process of calculating similar elements, so we build an index of potentially similar elements when training the word vector process. Finally, the experimental results show that our algorithm has higher accuracy than the word mover's distance (WMD), and has the least query time of three calculation methods of SSF.

• ETRI Journal
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• 제23권3호
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• pp.129-137
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• 2001

A random sampling or systematic sampling method is commonly used to assess the accuracy of classification results. In remote sensing, with these sampling methods, much time and tedious work are required to acquire sufficient ground truth data. So, a more effective sampling method that can represent the characteristics of the population is required. In this study, fractal analysis is adopted as an index for reference sampling. The fractal dimensions of the whole study area and the sub-regions are calculated to select sub-regions that have the most similar dimensionality to that of the whole area. Then the whole area's classification accuracy is compared with those of sub-regions, and it is verified that the accuracies of selected sub-regions are similar to that of whole area. A new kind of reference sampling method using the above procedure is proposed. The results show that it is possible to reduce sampling area and sample size, while keeping the same level of accuracy as the existing methods.

• 전기학회논문지
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• 제66권8호
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• pp.1257-1264
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• 2017

In video content watching service, when a user requests video content, the content server has to transmit the entire video to the client for watching. This transmission delay increases as the size of video content increases. In order to solve the transmission delay problem, a prefetching technique can be used in which a video content to be watched by a user is predicted and transmitted to a client before the user requests it. In this paper, we propose a prefetching system considering multiple indices for video content. In the proposed method, video content to be prefetched is selected by comprehensively analyzing the order relation index indicating the order of viewing the videos of the users, the similarity index between the video contents, and the popularity index reflecting the viewing frequency of the video content. Experimental results show that the maximum accuracy is achieved when prefetching uses only the order relation index for movie contents.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 춘계 학술발표회 초청강연 및 논문집
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• pp.987-997
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• 2008

Successful design, construction and maintenance of geotechnical structure in soft ground and marine clay demands prediction, control, stability estimation and monitoring of settlement with high accuracy. It is important to predict and to estimate the compression index of soil for predicting of ground settlement. Lab. and field tests have been and are indispensable tools to achieve this goal. In this paper, Artificial Neural Networks (ANNs) model with Levenberg-Marquardt Algorithm and field database were used to predict compression index of soil in Korea. Based on soil property database obtained from more than 1800 consolidation tests from soils samples, the ANNs model were proposed in this study to estimate the compression index, using multiple soil properties. The compression index from the proposed ANN models including multiple soil parameters were then compared with those from the existing empirical equations.

• Journal of Power Electronics
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• 제16권1호
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• pp.319-328
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• 2016

In this study, we first briefly introduce the effect of circulating current control on the modulation signal of a modular multilevel converter (MMC). The maximum modulation index is also theoretically derived. According to the optimal modulation index analysis and the model in the continuous domain, different DC-side output impedance equivalent models of MMC with/without compensating component are derived. The DC-side impedance of MMC inverter station can be regarded as a series xR + yL + zC branch in both cases. The compensating component of the maximum modulation index is also related to the DC equivalent impedance with circulating current control. The frequency characteristic of impedance for MMC, which is observed from its DC side, is analyzed. Finally, this study investigates the prediction of the DC voltage ripple transfer between two-terminal MMC high-voltage direct current systems under unbalanced conditions. The rationality and accuracy of the impedance model are verified through MATLAB/Simulink simulations and experimental results.

• 한국콘텐츠학회논문지
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• 제9권9호
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• pp.80-89
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• 2009

클러스터링 알고리즘에서 최적의 클러스터 수를 결정하기 위한 효율적인 고속 탐색 알고리즘을 소개한다. 제안하는 방법은 클러스터링 적합도의 척도로 사용되는 클러스터 타당성 평가기준을 토대로 한다. 데이터 집합에 클러스터링 프로세스를 진행하여 최적의 클러스터 형상에 도달하게 되면 클러스터 타당성 평가기준은 최대 혹은 최소값을 가질 것으로 기대한다. 본 논문에서는 최적의 클러스터 개수를 찾기 위한 고속의 비소모적 탐색 방법을 설계하고 실제 클러스터링과 접목한다. 제안하는 알고리즘은 k-means++ 클러스터링 알고리즘에 적용하였고, 클러스터 타당성 평가기준으로써 CB 및 PBM 타당성 평가기준 방법을 사용하였다. 몇몇의 가상 데이터 집합과 실제 데이터 집합에 실험한 결과, 제안하는 방법은 정확도의 손실 없이 계산 효율을 획기적으로 증가시킴을 보여주었다.