• 한국컴퓨터정보학회논문지
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• 제27권7호
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• pp.65-73
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• 2022

최근 윈도우 시스템에서는 리눅스용 윈도우즈 하위 시스템(Windows Subsystem for Linux, WSL)을 지원함에 따라 도커 컨테이너를 해당 시스템에 적용하기 위해 다양한 연구가 진행 중에 있다. 그러나 기존의 다양한 연구에서는 호스트 운영체제별로 시스템을 적용하기 위해 성능과 관련한 지표가 부족할 실정이다. 본 논문에서는 도커 컨테이너 기반의 호스트 운영체제별 성능 비교 분석을 진행하고자 한다. 성능 비교 분석을 진행하기 위해, 실험 환경에서는 동일한 스펙 환경과 데이터셋을 구성하였다. 실험 결과에서 리눅스 시스템에서의 도커 컨테이너가 윈도우즈 시스템 대비 데이터셋 1-6의 기준으로 3.9%, 62.16%, 1552.38%, 7.27%, 60.83%의 평균 지연시간 감소를 보였다.

• Communications for Statistical Applications and Methods
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• 제19권4호
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• pp.559-569
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• 2012

Compositional data consist of compositions that are non-negative vectors of proportions with the unit-sum constraint. In disciplines such as petrology and archaeometry, it is fundamental to statistically analyze this type of data. Aitchison (1983) introduced a log-contrast principal component analysis that involves logratio transformed data, as a dimension-reduction technique to understand and interpret the structure of compositional data. However, the analysis is not usable when zero values are present in the data. In this paper, we introduce 4 possible methods to reduce the dimension of compositional data with zero values. Two real data sets are analyzed using the methods and the obtained results are compared.

• 대한산업공학회지
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• 제23권4호
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• pp.755-767
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• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.

• 디지털산업정보학회논문지
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• 제12권4호
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• pp.51-58
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• 2016

In the area of hotel and tourism sector, various research are analyzed using big data. Big data is being generated by any digital devices around us all the times. All the digital process and social media exchange produces the big data. In this paper, we analyzed the de-identification method of big data to use the personal information of hotel guests. Through the analysis of these big data, hotel can provide differentiated and diverse services to hotel guests and can improve the service and support the marketing of hotels. If the hotel wants to use the information of the guest, the private data should be de-identified. There are several de-identification methods of personal information such as pseudonymisation, aggregation, data reduction, data suppression and data masking. Using the comparison of these methods, the pseudonymisation is discriminated to the suitable methods for the analysis of information for the hotel guest. Also, among the pseudonymisation methods, the t-closeness was analyzed to the secure and efficient method for the de-identification of personal information in hotel.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.1-11
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• 2006

Data mining technique is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. It has been widely used in many applications, such that pattern analysis or recognition, data analysis, image processing, market research on off-line or on-line and so on. We analyze Gyeongnam social indicator survey data by 2001 using twostep clustering technique for environment information. The twostep clustering is classified as a partitional clustering method. We can apply these twostep clustering outputs to environmental preservation and improvement.

• International Journal of Advanced Culture Technology
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• 제8권2호
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• pp.231-238
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• 2020

Generally, sequential data refers to data having continuity. Text data, which is a representative type of unstructured data, is also sequential data in that it is necessary to know the meaning of the preceding word in order to know the meaning of the following word or context. So far, many techniques for analyzing sequential data such as text data have been proposed. In this paper, four methods of 1d-CNN, LSTM, BiLSTM, and C-LSTM are introduced, focusing on neural network techniques. In addition, by using this, IMDb movie review data was classified into two classes to compare the performance of the techniques in terms of accuracy and analysis time.

• Journal of information and communication convergence engineering
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• 제20권2호
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• pp.125-130
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• 2022

In modern society, as many data are used for research or commercial purposes, the value of data is gradually increasing. In related fields, research is being actively conducted to collect valuable data, but it is difficult to collect proper data because the value of collection is determined according to the performance of existing sensors. To solve this problem, a method to effectively reduce noise has been proposed, but there is a point in which performance is degraded due to damage caused by noise. In this paper, a device capable of collecting time series data was designed to correct such data noise, and a correction technique was performed by giving an error value based on the representatively collected ultrafine dust data, and then comparing before and after Compare performance. For the correction method, Kalman, LPF, Savitzky-Golay, and Moving Average filter were used. Savitzky-Golay filter and Moving Average Filter showed excellent correction rate as an experiment. Through this, the performance of the sensor can be supplemented and it is expected that data can be effectively collected.

• 대한후두음성언어의학회지
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• 제12권1호
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• pp.17-21
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• 2001

Aims of study : The purpose of this study is to measure the chronic and daily voice burden of the professionals in their actual working places. These will be a valuable guideline for preventing and controlling the voice production of professionals. Material and method : Our study was selected to the 10 female telephone operators in the Asan Medical Center, ages ranging from 22 to 38 years old. The symptoms and acoustic analysis of both telephone operators and the controls were evaluated before and after their working. The symptoms were evaluated with questionaires, and the acoustic analysis was measured by using CSL (computerized speech laboratory) system. Results : The symptoms of the professional voice abusers are same as those symptoms in laryngeal fatigue. The acoustic analysis before their working were significantly increased in jitter and shimmer, in comparison with the data of the control. This shows that the experimental group is exposed to the chronic burden of voice production. The jitter, shimmer, and NHR after their working are significantly increased in comparison with the data of the acoustic analysis before their working. This also shows that the experimental group is exposed to the daily burden of voice production. Conclusion : The acoustic analysis of the professional voice overusers has objectively measured that there are chronic and daily overloading to the voice of operators, and these will be a valuable data for preventing and controlling the professionals that abuse their voice.

• 한국소음진동공학회논문집
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• 제22권3호
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• pp.234-243
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• 2012

In this paper, a sound quality indices for the evaluation of vehicle intake and exhaust noise were developed through a correlation analysis of objective measurement data and subjective evaluation data. At first, intake and exhaust orifice noise were measured at the wide-open throttle sweep condition. And then, acoustic transfer function between intake orifice noise and interior noise at the steady state condition was measured. Also, acoustic transfer function for exhaust system was measured as the same method. Simultaneously, subjective evaluation was carried out by the paired comparison and semantic differential method by 27 engineers. Next, the correlation analysis between the psycho-acoustic parameters derived from the measured data and the subjective evaluation was performed. The most critical factor was determined and the corresponding sound quality index for the intake and exhaust noise was obtained from the multiple factor regression method. At last, the effectiveness of the proposed index was investigated.

• Journal of Astronomy and Space Sciences
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• 제34권3호
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• pp.213-223
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• 2017

The deep space orbit determination software (DSODS) is a part of a flight dynamic subsystem (FDS) for the Korean Pathfinder Lunar Orbiter (KPLO), a lunar exploration mission expected to launch after 2018. The DSODS consists of several sub modules, of which the orbit determination (OD) module employs a weighted least squares algorithm for estimating the parameters related to the motion and the tracking system of the spacecraft, and subroutines for performance improvement and detailed analysis of the orbit solution. In this research, DSODS is demonstrated and validated at lunar orbit at an altitude of 100 km using actual Lunar Prospector tracking data. A set of a priori states are generated, and the robustness of DSODS to the a priori error is confirmed by the NASA planetary data system (PDS) orbit solutions. Furthermore, the accuracy of the orbit solutions is determined by solution comparison and overlap analysis as about tens of meters. Through these analyses, the ability of the DSODS to provide proper orbit solutions for the KPLO are proved.