• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.449-451
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• 2003

The estimation of time-series data is fundamental process in many data analysis cases. However, the unwanted measurement error is usually added to true data, so that the exact estimation depends on efficient method to eliminate the error components. The wavelet transform method nowadays is expected to improve the accuracy of estimation, because it is able to decompose and analyze the data in various resolutions. Therefore, the wavelet based Kalman filter method for the estimation of time-series data is proposed in this paper. The wavelet transform separates the data in accordance with frequency bandwidth, and the detail wavelet coefficient reflects the stochastic process of error components. This property makes it possible to obtain the covariance of measurement error. We attempt the estimation of true data through recursive Kalman filtering algorithm with the obtained covariance value. The procedure is verified with the fundamental example of Brownian walk process.

• 한국CDE학회논문집
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• 제14권6호
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• pp.364-373
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• 2009

In this paper, we suggest the method for constructing parameterized human body model which has any required body sizes from 3D scan data. Because of well developed 3D scan technology, we can get more detailed human body model data which allow to generate precise human model. In this field, there are a lot of research is performed with 3D scan data. But previous researches have some limitations to make human body model. They need too much time to perform hole-filling process or calculate parameterization of model. Even more they missed out verification process. To solve these problems, we used several methods. We first choose proper 125 3D scan data from 5th Korean body size survey of Size Korea according to age, height and weight. We also did post process, feature point setting, RBF interpolation and align, to parameterize human model. Then principal component analysis is adapted to the result of post processed data to obtain dominant shape parameters. These steps allow to reduce process time without loss of accuracy. Finally, we compare these results and statistical data of Size Korea to verify our parameterized human model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.875-878
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• 1988

In this work it is shown how the methods used in chemical engineering for the analysis and simulation of processes may be applied to the actual phosphoric acid plant. Attention has been focused on the dihydrate process for which the necessary fundamental experimental data and plant operation data are available. The results of the simulation have shown that a reasonable description of the process at hand is possible by the proposed method. However, because of the complexity of the process, of the limited basic experimental data reported in literature, and the limitations of mathematics, the model was somewhat idealized and gave a reliable representation of the influence of only a few of the variables that affect the performance of the plant.

• Journal of information and communication convergence engineering
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• 제17권4호
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• pp.267-273
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• 2019

South Korea has allowed parallel importation since 1995. Parallel importation causes competition among importers in the logistics process allowing, consumers to purchase foreign brand products at low prices. Most parallel importers base product pricing on subjective judgements. Fashion products in particular, have different sales rates depending on trends and seasons, so sales performance varies greatly depending on selling price timing and policy. The merchandiser (MD) set the price on parallel importation products by aggregating information on imported products and pricing goods. However, this customized process is very time consuming for the MD. This is because the logistics process of parallel importation's customs clearance procedures and repair works is complicated and takes a significant amount of time. In this paper, we propose an improved parallel importation logistics process based on big data, which automatically sets the price of parallel importation products.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2005년도 춘계학술대회 논문집
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• pp.184-187
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• 2005

Forging process is one of the forming process and is used widely in automobile parts and manufacture industry. Especially the gears like spur gear, helical gear, bevel gear were produced by machine tool, but recently they have been manufactured by forging process. The goal of this study is to study forming process with data obtained by comparison between forward extrusion and upsetting simulation results and formability improvement by various heat treatment conditions. By analysis data of 3D FEM by upsetting and forward extrusion forming, the forming process of clutch gear develops using data based on 3D FEM analysis. Through tensile test using specimens by various heat treatment conditions, the optimal heat treatment condition is obtained by comparison the results of tensile test.

• 한국정밀공학회지
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• 제13권10호
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• pp.130-138
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• 1996

In general, the scattler is observed in fatigue test data due to the nonhomogeneity of a material. Consequently. It is necessary to use the statistical method to describe the fatigue crack growth process precisely. Bogdanoff and Kozin suggested and developed the B-model which is the probabilistic models of cumulative damage using the Markov process in order to describe the damage process. But the B-model uses only constant probability ratior(r), so it is not consistent with the actual damage process. In this study, the r-decreasing model using a monotonic decreasing function is introduced to improve the B-model. To verify the model, thest data of fatigue crack growth of A12024-T351 and A17075-T651 are used. Compared with the empirical distribution of test data, the distribution from the r-decreasing model is satisfactory and damage process is well described from the probabilistic and physical viewpoint.

• 한국정밀공학회지
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• 제14권11호
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• pp.147-153
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• 1997

Fault diagnosis technique in machining system which is one of engineering techniques absolutely necessary to automation of manufacturing system has been proposed. As a whole, diagnosis process is explained by two steps: sensor data acquisition and reasoning current state of system with the given sensor data. Flexible disk grinding process implemented in milling machine was employed in order to obtain empirical manufacturing process information. Resistance force data during machining were acquired using tool dynamometer known as sensor which is comparably accurate and reliable in operation. Tool status during the process was analyzed using influnece diagram assigning probability from the statistical analysis procedure.

• 정보처리학회논문지D
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• 제18D권3호
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• pp.149-156
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• 2011

최근 기업의 시스템들은 데이터 공유와 협업을 위해 통합의 필요성을 제기하고 있다. 통합을 위한 방법론으로 서비스 통합을 위한 서비스 지향 아키텍처와 서비스에 사용되는 데이터의 통합을 위한 마스터 데이터가 등장했다. 본 논문은 BP(Business Process)를 효율적으로 운용하기 위한 방안을 제시한다. 우리는 BP를 지원하기 위한 지식 저장소로 XMDR(eXtended Meta Data Registry)과 이를 운용하기 위한 데이터 허브를 구성한다. XMDR은 데이터 통합을 위한 MDM(Master Data Management)을 관리하고, 데이터 간의 이질성을 해결하고, 업무 간의 연관관계를 효율적으로 제공한다. 이것은 MDR(Meta Data Registry), 온톨로지, BR(Business Relations)으로 구성된다. MDR은 구조적 이질성을 해결하기 위한 메타 데이터간의 관계성을 기술한다. 온톨로지는 의미적 이질성과 데이터 간의 관계성을 기술한다. BR은 업무 간의 관계성을 기술한다. XMDR 데이터 허브는 마스터 데이터의 관리를 지원하고, 프로세스 간의 상호작용을 효율적으로 지원할 수 있다.

• 한국IT서비스학회지
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• 제7권1호
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• pp.103-116
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• 2008

Efficiency and objectiveness are the most critical issues in the evaluation of software projects. It is beneficial not only to software companies participated in bids, but to administrators of projects. This study attempts to find an improvement in the evaluation process by connecting the historical data of bidding companies in the software company report system with the governmental procurement system. The proposed means will eliminate unnecessary and repetitive submission step of bidding companies and provide the administrator with objective evaluation process. Also, this paper proposes an automated process for quantifying the business experience of bidding companies.

• 한국건설관리학회논문집
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• 제19권3호
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• pp.43-51
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• 2018

건축물생애주기 중 유지관리단계는 비용적인 측면에서 그리고 건축물 가치 관리적인 측면에서 매우 중요한 단계이다. 그럼에도 불구하고, 아직 체계적이고 합리적인 유지관리 프로세스가 마련되어있지 않아 정확하고 선제적인 유지관리를 통한 건축물 가치상승 및 생애주기비용 관리를 적절하게 하지 못 하는 경우가 많다. 이러한 주된 원인은 유지관리 데이터에 대한 객관적인 분석을 토대로 한 프로세스를 구축하려는 노력이 미흡한 결과이다. 본 연구의 목적은 최적의 유지관리 프로세스를 개발하기 위한 기초연구로써 합리적인 유지관리 데이터 분석을 위한 데이터 체계를 구축하고, 이를 바탕으로 정량적 데이터분석에 기반 한 유지관리 프로세스를 제안하는데 있다. 본 연구는 유지관리 전문가 면담 및 관련 실무자료 분석을 통해 기존의 데이터체계를 검토하고, 그 한계점을 도출하였고 그에 대한 해답으로써 유지관리 분야의 정량적인 데이터 분석도구인 MTBF (Mean Time Between Failure)를 활용한 공간정보 기반 유지관리 데이터분석 방법을 제시하였다. 결과적으로 이러한 분석방법을 활용한 최적의 유지관리 프로세스를 제안하고 실제 유지관리 데이터에 이를 대입하여 그 효과성을 검증하였다. 체계적인 유지관리 실행을 위한 프레임으로써 활용이 될 경우 객관적이고 합리적인 유지관리 의사결정에 도움이 될 수 있을 것으로 판단되며, 이를 바탕으로 한 시스템 개발 시 유용한 기초자료로 이용될 수 있을 것으로 기대된다.