• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 C
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• pp.1982-1984
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• 2004

Stator coil of rotating machinery has shown different characteristics according to impregnated with coil or not. And this is major determinant of equipment's life. In this paper, PD characteristics is studied as a classification scheme between two specimens. Processing of the coil impregnation is very important thing because that influences on thermal and electrical characteristics of the coil. And then PD is occurring at the coil and causing insulation degradation. For processing statistical processing, PD data acquired from PD detector using PDASDA(partial discharge acquisition, storage and display system). And also these statistical distribution and parameter are applied to classify PD sources by neural networks. As a result of, Neural Networks have a good discrimination rate for classification PD sources.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권3호
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• pp.264-271
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• 2017

Purpose: Field operation data contains missing values or outliers due to various causes of the data collection process, so caution is required when utilizing RAM analysis results by field operation data. The purpose of this study is to present a method to minimize the RAM analysis error of the field data to improve the accuracy. Methods: Statistical methods are presented for processing of the outliers and the missing values of the field operating data, and after analyzing the RAM, the differences between before and after applying the technique are discussed. Results: The availability is estimated to be lower by 6.8 to 23.5% than that before processing, and it is judged that the processing of the missing values and outliers greatly affect the RAM analysis result. Conclusion: RAM analysis of OO weapon system was performed and suggestions for improvement of RAM analysis were presented through comparison with the new and current method. Data analysis results without appropriate treatment of error values may result in incorrect conclusions leading to inappropriate decisions and actions.

• 한국산업정보학회논문지
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• 제28권5호
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• pp.89-108
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• 2023

본 연구는 공식발표 통계지표의 적시성 확보를 위해 기존 Nowcasting 방법론을 살펴보고 실시간 경기 현황 분석이 가능한 Real-time nowcasting 모형을 운용하기 위한 대안 데이터와 그 수집 체계를 점검한다. 공공영역과 민간영역에서 경기지표를 예측할 수 있는 고빈도 실시간 데이터를 탐색하고, 나아가 데이터의 수집, 가공, 모형화를 위한 클라우드 기반의 구축과정을 제안한다. 더불어 Real-time nowcasting 모형 추정 및 데이터 관리에 있어 고려해야 할 요소를 확인함으로써 적시성 및 안정성을 갖춘 공식 통계지표의 예측 프로세스를 제시한다.

• Journal of Information Processing Systems
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• 제19권1호
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• pp.1-16
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• 2023

Synthetic data generation is generally used in performance evaluation and function tests in data-intensive applications, as well as in various areas of data analytics, such as privacy-preserving data publishing (PPDP) and statistical disclosure limit/control. A significant amount of research has been conducted on tools and languages for data generation. However, existing tools and languages have been developed for specific purposes and are unsuitable for other domains. In this article, we propose a regular expression-based data generation language (DGL) for flexible big data generation. To achieve a general-purpose and powerful DGL, we enhanced the standard regular expressions to support the data domain, type/format inference, sequence and random generation, probability distributions, and resource reference. To efficiently implement the proposed language, we propose caching techniques for both the intermediate and database queries. We evaluated the proposed improvement experimentally.

• 제어로봇시스템학회논문지
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• 제12권4호
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• pp.353-357
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• 2006

The vehicle detection method using pulse radar has the advantage of maintenance in comparison with loop detection method. We propose the pulse radar signal processing algorithm in which we devide the trace. data from pulse radar into segments by using SSC concept, and then construct the sectors in accordance with period and amplitude of segments, and finally decide the vehicle detection probability by applying the SSC parameters of each sectors into the discriminant function. We also improve the signal processing time by reducing the quantities of processing data and processing routines.

• Communications for Statistical Applications and Methods
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• 제30권5호
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• pp.501-516
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• 2023

Knowledge distillation (KD) refers to extracting knowledge from a large and complex model (teacher) and transferring it to a relatively small model (student). This can be done by training the teacher model to obtain the activation function values of the hidden or the output layers and then retraining the student model using the same training data with the obtained values. Recently, relational KD (RKD) has been proposed to extract knowledge about relative differences in training data. This method improved the performance of the student model compared to conventional KDs. In this paper, we propose a new method for RKD by introducing a new loss function for RKD. The proposed loss function is defined using the area difference between the teacher model and the student model in a specific hidden layer, and it is shown that the model can be successfully compressed, and the generalization performance of the model can be improved. We demonstrate that the accuracy of the model applying the method proposed in the study of model compression of audio data is up to 1.8% higher than that of the existing method. For the study of model generalization, we demonstrate that the model has up to 0.5% better performance in accuracy when introducing the RKD method to self-KD using image data.

• 동아시아경상학회지
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• 제11권2호
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• pp.91-108
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• 2023

Purpose - This research paper empirically analyzes the effect of changes in the employment environment due to the 4th industrial revolution on the turnover intention of cosmetic employers and employees and seeks the necessary measures for job instability in the industrial field. Research design, data, and methodology - A self-report questionnaire was conducted on 513 cosmetic implementers. Statistical processing of the data collected by the data analysis method was analyzed using the Statistical Package for Social Science (SPSS) WIN23.0 statistical package program through data coding and data organizing process. Results - Changes in the employment environment were found to have a significant effect on the effect of job instability (t=13.218, p<0.05). As for the effect of organizational commitment on turnover intention, the higher the organizational commitment, which is a parameter, has a negative (-) effect on turnover intention, a dependent variable (p<0.05). Conclusions - Our results are based on an analysis that allows cosmetic employers and workers to explore ways to address job insecurity. Based on the analysis results, it will help the growth of the cosmetics industry by providing basic data for the identity of the cosmetics industry and the development of the cosmetics service organization.

• Journal of Preventive Medicine and Public Health
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• 제6권1호
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• pp.81-85
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• 1973

One hundred and thirty one health articles (as 'original articles') reported in medical journals published in Korea during the period from Jan. to Dec. 1971. were selected as the study materials for tile purpose of resumption and criticism. Of a total of 131 articles, thirty-nine were not required the statistical application for the data processing and drawing their conclusions and ninty-two, 70.2%, were needed to apply. The 92 articles were divided into three groups by the types of study: 54 for experimental study, 30 for clinical case analytic study and 8 for field study. Each report was resumed and criticised under the statistical aspects in terms of data processing and the validity of the conclusions. The results of resumption of the 92 articles needed statistical application are summarized as follow; 1. Of the 54 articles of experimental studies resumed, thirty-one articles, 57.4%, were considered acceptable. Among the 38 articles classified as clnical case analytic and field studies, only 28.9 per cent were considered acceptable. In total 45.7 per cent or less than half were considered acceptable. 2. Types of errors encountered are as shown in Table 3. 3. The most frequently encountered error was that the conclusions were drawn without having made any statistical test. This type of error was found in 14 out of 35 errors presented in experimental studies, 11 of 35 in clinical case analytic studies and 5 of 9 in field studies and 30 out of 97, 38.2%, in total.

• 한국안전학회지
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• 제11권4호
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• pp.42-48
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• 1996

Since the fatigue phenomenon is characterized as a probability feature and test data cannot be easily collected number its small sample data are uncertain. Therefore, statistical evaluation methods should necessarily be introduced into data evaluation. With such a basic concept in mind, this study attempted to apply conventional statistical processing methods to the fatigue data and thereby present a new evaluation method in consideration of the fact that the fatigue test is usually performed within a limited number. That is a package evaluation method was adopted which co-realtes parameters between different levels of capacity in E-N or S-N level. So far fatigue limits have been found by means of stiarcase method. But it was also disclosed that this new method has its own disadvantage because limited frequencies are not duely considered.

• 한국멀티미디어학회논문지
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• 제20권1호
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• pp.66-73
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• 2017

Due to the recent rapid changes in society and wide spread of information devices, diverse digital information is utilized in a variety of economic and social analysis. Information related to the crime statistics by type of crime has been used as a major factor in crime. However, statistical analysis using only the structured data has the difficulty in the investigation by providing limited information to investigators and users. In this paper, structured data and unstructured data are analyzed by applying Korean Natural Language Processing (Ko-NLP) and the Latent Semantic Analysis (LSA) technique. It will provide a crime profile optimum system that can be applied to the crime profiling system or statistical analysis.