• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.283-290
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• 2020

The purpose of this study was to evaluate the usefulness of the triglyceride and glucose(TyG) index to predict the risk of hyperuricemia in Korean adults. This study included 14,266 men and 9,033 women over 20 years old who underwent health screenings from 2017 to 2019 at a general hospital in Seoul. To confirm the risk of hyperuricemia and predictive ability of the TyG index, logistic regression analysis and ROC curves were obtained. The accuracy of the TyG index for predicting hyperuricemia was 0.68, 0.61 for men and 0.67 for women(respectively p<0.001). The risk of hyperuricemia in the TyG index was 1.69 times higher in the fourth quartile than in the first quartile, 2.03 times higher in men and 2.07 times higher in women(respectively p<0.05). Thus the TyG index was not of high diagnostic usefulness as a screening test for hyperuricemia, but it was related to the TyG index and hyperuricemia.

• Journal of Korean Society of Disaster and Security
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• v.16 no.3
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• pp.35-43
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• 2023

This study introduces a study on the adjustment methods of the Life Safety Index. The Life Safety Index is a service provided by the Life Safety Prevention Service System. It comprehensively evaluates individuals' levels of safety in their daily lives, continually monitors their safety status, and presents a comprehensive index to prevent safety accidents in advance. Previous studies have developed the Life Safety Index using evaluation criteria (items) for assessing life safety prevention services, incorporating both the AHP (Analytic Hierarchy Process) and Likert Scale techniques. In this study, we build upon this existing Life Safety Index and explore methods for applying adjustment factors based on individuals' characteristics to enhance its accuracy and customization. We develop adjustment factors using existing national statistics to provide personalized services tailored to individual profiles. Therefore, this paper proposes a method for providing customized services by applying adjustment factors to the Life Safety Index, contributing to the development and application of life safety index adjustment methodologies.

• Journal of the Ergonomics Society of Korea
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• v.21 no.3
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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.

• Proceedings of the KIEE Conference
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• 1998.07b
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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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• v.15 no.6
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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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• v.23 no.3
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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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.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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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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• v.16 no.1
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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.

• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.80-89
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• 2009

A fast and efficient search algorithm to determine an optimal number of clusters in clustering algorithms is presented. The method is based on cluster validity index which is a measure for clustering optimality. As the clustering procedure progresses and reaches an optimal cluster configuration, the cluster validity index is expected to be minimized or maximized. In this Paper, a fast non-exhaustive search method for finding the optimal number of clusters is designed and shown to work well in clustering. The proposed algorithm is implemented with the k-mean++ algorithm as underlying clustering techniques using CB and PBM as a cluster validity index. Experimental results show that the proposed method provides the computation time efficiency without loss of accuracy on several artificial and real-life data sets.