• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.1
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• pp.145-152
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• 2004

This paper compares seat vibrations of a small passenger car and a SUV. The results also include the comparison of the human body accelerations and the ride values, such as the component ride values, and SEAT values of 12 axis accelerations obtained at the human body and seat track. The ride comfort evaluation is usually carried out by experiments of real cars which are expensive and sometimes may contain errors by passenger's postures. Simulations by computer, on the other hand, enable to solve these problems when the accuracy is proven. This paper, thus, also shows the correlation of human body vibration between experiments and computer simulations. For the computer simulation, korean dummy models are developed from the Hybrid III models by scaling the body data of Hybrid III to those of Korean men and women. From the comparison between the test data and simulation data, a nice correlation in trends was shown.

• Wind and Structures
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• v.1 no.1
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• pp.77-109
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• 1998

An evaluation and comparison of seven of the world's major building codes and standards is conducted in this study, with specific discussion of their estimations of the alongwind, acrosswind, and torsional response, where applicable, for a given building. The codes and standards highlighted by this study are those of the United States, Japan, Australia, the United Kingdom, Canada, China and Europe. In addition, the responses predicted by using the measured power spectra of the alongwind, acrosswind and torsional responses for several building shapes tested in a wind tunnel are presented and a comparison between the response predicted by wind tunnel data and that estimated by some of the standards is conducted. This study serves not only as a comparison of the response estimates by international codes and standards, but also introduces a new set of wind tunnel data for validation of wind tunnel-based empirical expressions.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.11
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• pp.910-917
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• 2003

Fluid flow in a rectangular duct for 90$^{\circ}$ bend elbow with the ratio of 1.5 between its curvature radius and width is measured by 5 W laser doppler velocity meter. The fluid flow is also computed by commercial software of STAR-CD for comparison between measured and computed velocity profiles in the duct. Reynolds numbers for the comparison are 11,643, 19,746 and 24,260. From the comparison, computation of principal velocity components in the duct predicts the experimental data somewhat satisfactorily even though those of minor velocity components and turbulent kinetic energy do not match with the experimental data quite well. K-factor for the bend elbow is computed to be average 0.086 while the equivalent ASHRAE data is 0.07.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.333-342
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• 2022

In this paper, we perform a direct comparison study of real experimental data for domain rearrangement and the Cahn-Hilliard (CH) equation on the dynamics of morphological evolution. To validate a mathematical model for physical phenomena, we take initial conditions from experimental images by using an image segmentation technique. The image segmentation algorithm is based on the Mumford-Shah functional and the Allen-Cahn (AC) equation. The segmented phase-field profile is similar to the solution of the CH equation, that is, it has hyperbolic tangent profile across interfacial transition region. We use unconditionally stable schemes to solve the governing equations. As a test problem, we take domain rearrangement of lipid bilayers. Numerical results demonstrate that comparison of the evolutions with experimental data is a good benchmark test for validating a mathematical model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1088-1097
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• 2021

Vibration data of mechanical equipment inevitably have noise. This noise adversely af ects the maintenance of mechanical equipment. Accordingly, the performance of a learning model depends on how effectively the noise of the data is removed. In this study, the noise of the data was removed using the Denoising Auto Encoder (DAE) technique which does not include the characteristic extraction process in preprocessing time series data. In addition, the performance was compared with that of the Wavelet Transform, which is widely used for machine signal processing. The performance comparison was conducted by calculating the failure detection rate. For a more accurate comparison, a classification performance evaluation criterion, the F-1 Score, was calculated. Failure data were detected using the One-Class SVM technique. The performance comparison, revealed that the DAE technique performed better than the Wavelet Transform technique in terms of failure diagnosis and error rate.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.961-966
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• 2000

It is difficult to change or remedy concrete structure after hardened. It is usual to evaluate the quality of hardened concrete using several test method. This study was performed to make fundamental data that could be used to evaluate the quality of hardened concrete. This study is to estimate mix proportion of hardened concrete. Each elements of concrete needed different estimation methods. First, the cement that handled by the most important compounds measured by XRF(X-ray fluorecence) machine with scanning Ca-K${\alpha}$. Second, the coarse aggregate that divided by maximum size measured by the area comparison method that starts from the assumption of uniform distribution. Third, the fine aggregate measured by the weight comparison method that needs several prerequsite constants which concerned cement hydration reaction. Fourth, the water content would be estimated by expert system that has data base of design data, the contents of above estimation results, the characteristics of concrete strength. As the result of the above research, some conclusions are as follows. The cement estimation method resulted by reliability of mean 96.7%, standard deviation 3.92. The area comparison method resulted by reliability of mean 95.3%, standard deviation 2.08. The weight comparison method resulted by reliability of mean 93.3%, standard deviation 3.35.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1145-1153
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• 2009

The problem of Korean registered population is that population classified by age increases as one grows older until 6 age or 7 age. This paper is to suggest an algorithm of the re-projection under 7 age on Korean registered population and to analysis of comparison with the reported population statistical data. As the result, the reprojections population is trusted in the number of 0 age on the comparison of other reported population statistical data.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.30-33
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• 2016

With the advent of big data, data mining is more increasingly utilized in various decision-making fields by extracting hidden and meaningful information from large amounts of data. Even as exponential increase of the request of unrevealing the hidden meaning behind data, it becomes more and more important to decide to select which data mining algorithm and how to use it. There are several mainly used data mining algorithms in biology and clinics highlighted; Logistic regression, Neural networks, Supportvector machine, and variety of statistical techniques. In this paper it is attempted to compare the classification performance of an exemplary algorithm J48 and REPTree of ML algorithms. It is confirmed that more accurate classification algorithm is provided by the performance comparison results. More accurate prediction is possible with the algorithm for the goal of experiment. Based on this, it is expected to be relatively difficult visually detailed classification and distinction.

• Journal of Information Technology Services
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• v.22 no.3
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• pp.29-47
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• 2023

With the recent advancement of information and communication technologies such as artificial intelligence, big data, cloud computing, and 5G, data is being produced and digitized in unprecedented amounts. As a result, data has emerged as a critical resource for the future economy, and overseas countries have been revising laws for data protection and utilization. In Korea, the 'Data 3 Act' was revised in 2020 to introduce institutional measures that classify personal information, pseudonymized information, and anonymous information for research, statistics, and preservation of public records. Among them, it is expected to increase the added value of data by combining pseudonymized personal information, and to this end, "the Expert Data Combination Agency" and "the Expert Data Agency" (hereinafter referred to as the Expert Data Processing Agency) system were introduced. In comparison to these domestic systems, we would like to analyze similar overseas systems, and it was recently confirmed that the Vermont government in the United States enacted the first "Data Broker Act" in the United States as a measure to protect personal information held by data brokers. In this study, we aim to compare and analyze the roles and functions of the "Expert Data Processing Agency" and "Data Broker," and to identify differences in designated standards, security measures, etc., in order to present ways to contribute to the activation of the data economy and enhance information protection.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.1-5
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• 2008

Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.