• 제어로봇시스템학회논문지
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• 제4권4호
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• pp.551-560
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• 1998

This paper presents a neural network model representing complex hydro-thermo-dynamic characteristics of a steam generator in nuclear power plants. The key modeling processes include training data gathering process, analysis of system dynamics and determining of the neural network structure, training process, and the final process for validation of the trained model. In this paper, we suggest a training data gathering method from an unstable steam generator so that the data sufficiently represent the dynamic characteristics of the plant over a wide operating range. In addition, we define the inputs and outputs of neural network model by analyzing the system dimension, relative degree, and inputs/outputs of the plant. Several types of neural networks are applied to the modeling and training process. The trained networks are verified by using a class of test data, and their performances are discussed.

• 산업공학
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• 제12권1호
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• pp.79-93
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• 1999

As most of information systems developed are data-centric rather than process-centric, it is difficult for users to understand and manage the system from the viewpoint of work processes. To resolve the problem of the data-centric design, we propose a new method to design WFMSs(Workflow Management Systems), which are focused on processes and modified from current information engineering methods. In this research, the drawing approval and engineering change approval process of a K manufacturing company has been analyzed as a sample process. This method takes two steps, i.e., process analysis and system design. In the prosess analysis, data and processes are analyzed, and functions and tasks are derived from the processes. In the system design, a data model for the operation of WFMS is designed, and based on this data model, build-time and run-time functions of WFMS are designed.

• 한국정밀공학회지
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• 제16권3호통권96호
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• pp.9-17
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• 1999

This paper presents a method of grinding and polishing automation of precision die after CNC machining. The method employs a robot system equipped with a pneumatic spindle and a special abrasive film pad. The robot program is automatically generated off-line program form a PC and downloaded to robot controller. Position and orientation data for the program is supplied form cutter contact (CC) data of NC machining process. This eliminates separate robot teaching process. This paper aims at practical automation of die finishing process which is very time consuming and suffering from shortage of workpeople. Time loss due to changeover from one product to another is eliminated by PC off-line programming exploiting appropriate NC machining data. Dextrous 6-axis robot with rigid wrist and simple tooling enables the process applicable to larger, rather complex 3 dimensional free surfaces.

• 한국도서관정보학회지
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• 제54권3호
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• pp.321-346
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• 2023

연구데이터를 서술하는 데이터논문은 데이터를 생산한 연구자에게 연구논문과 같은 학술적 성과로 인정받을 수 있게 하고 다른 연구자가 데이터논문에서 공유한 데이터를 활용하여 기존 연구를 재현하거나 새로운 연구를 시작할 수 있도록 도움을 준다. 이러한 장점으로 데이터논문의 동료심사, 출판, 인용은 지속적으로 증가하고 있다. 데이터논문을 출판하고자 하는 학술단체는 연구논문과 다른 데이터논문의 핵심 개념, 데이터논문 심사 절차, 데이터논문 출판과 관계된 정보시스템 등을 이해하고 데이터논문에 포함할 구성요소 정의, 동료심사 절차 수립, 그리고 데이터저장소와 연계 등 세부 사항을 결정하는 것이 필요하다. 하지만, 데이터논문의 동료심사와 관련하여 다루어야 할 정보가 방대하고, 데이터논문 출판에 관한 연구 및 체계적인 정보가 부족하여 국내 학술단체는 데이터논문의 동료심사 업무에 어려움을 겪고 있다. 이러한 문제를 해결하는 데 도움이 될 수 있도록, 본 논문은 국내외 다섯 종 데이터학술지의 데이터논문 양식, 동료심사 사례를 조사·분석하여 데이터논문의 핵심 구성요소를 포함한 데이터논문 동료심사의 핵심 개념을 제안하고 프로세스를 모델링하였다. 데이터논문을 신규로 출판하거나, 기존의 연구논문과 함께 데이터논문을 심사하여 출판하고자 하는 학술단체는 본 논문에서 제시한 데이터논문의 핵심 개념과 동료심사 프로세스를 활용하여 데이터논문의 양식 개발, 체계적인 동료심사 프로세스 정립, 출판 정책 개발 등의 학술지업무에 신속하고 효과적으로 적용할 수 있을 것으로 기대된다.

• 대한안전경영과학회지
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• 제6권3호
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• pp.237-247
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• 2004

The condition of the manufacturing process in a factory should be diagnosed and maintained efficiently because any unexpected disorder in the process will be reason to decrease the efficiency of the overall system. However, if an expert experienced in this system leaves, there will be a problem for the efficient process diagnosis and maintenance, because disorder diagnosis within the process is normally dependent on the expert's experience. This paper suggests a process diagnosis using data mining based on the collected data from the coil-spring manufacturing process. The rules are generated for the relations between the attributes of the process and the output class of the product using a decision tree after selecting the effective attributes. Using the generated rules from decision tree, the condition of the current process is diagnosed and the possible maintenance actions are identified to correct any abnormal condition. Then, the appropriate maintenance action is recommended using the decision network.

• 한국분말재료학회지
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• 제31권2호
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• pp.137-145
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• 2024

In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

• 대한공간정보학회지
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• 제19권1호
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• pp.79-86
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• 2011

최근 수치표고모델(DEM : Digital Elevation Model)을 구축하기 위한 목적으로 항공레이저측량(LiDAR : Light Detection And Ranging) 기술이 주목받고 있다. DEM은 항공레이저측량으로부터 획득된 라이다 데이터에서 지면점만 추출한 수치지면자료(DTD : Digital Terrain Data)의 정확성에 의해 그 품질이 좌우된다. 하지만 원시자료에서 수치지면자료를 추출하기 위한 자동 필터링 작업은 필터링 알고리즘의 한계 및 라이다 데이터의 고유한 특성으로 인하여 항상 오분류 영역이 발생한다. 따라서 이를 보완하기 위해서는 작업자에 의한 수동분류 작업이 반드시 필요하다. 본 연구에서는 수동 작업이 원활하게 이루어 질 수 있도록 자동 필터링 작업에서 얻어진 수치지면자료에서 오분류 될 가능성이 있는 영역을 자동으로 탐지하는 알고리즘을 제안한다. 제안된 알고리즘은 2D 격자 구조를 적용하였으며 'Slope Angle', 'Slope DeltaH', 'NNMaxDH(Nearest Neighbor Max Delta Height)'로 명명한 매개변수를 사용하였다. 실험 결과, 제안된 알고리즘은 지형형태나 라이다 데이터 평균 점밀도에 제한받지 않는 안정적인 결과를 보여주었다.

• 한국멀티미디어학회논문지
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• 제24권6호
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• pp.768-788
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• 2021

The reversible data hiding technique safely transmits secret data to the recipient from malicious attacks by third parties. In addition, this technique can completely restore the image used as a transmission medium for secret data. The reversible data hiding schemes have been proposed in various forms, and recently, the reversible data hiding schemes based on interpolation are actively researching. The reversible data hiding scheme based on the interpolation method expands the original image into the cover image and embed secret data. However, the existing interpolation-based reversible data hiding schemes did not embed secret data during the interpolation process. To improve this problem, this paper proposes embedding the first secret data during the image interpolation process and embedding the second secret data into the interpolated cover image. In the embedding process, the original image is divided into blocks without duplicates, and the maximum and minimum values are determined within each block. Three way searching based on the maximum value and two way searching based on the minimum value are performed. And, image interpolation is performed while embedding the first secret data using the PVD scheme. A stego image is created by embedding the second secret data using the maximum difference value and log function in the interpolated cover image. As a result, the proposed scheme embeds secret data twice. In particular, it is possible to embed secret data even during the interpolation process of an image that did not previously embed secret data. Experimental results show that the proposed scheme can transmit more secret data to the receiver while maintaining the image quality similar to other interpolation-based reversible data hiding schemes.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1157-1170
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• 2007

LBS must manage various context data and make the best use of this data for application service in ubiquitous environment. Conventional mobile object data management architecture did not consider process of context data. Therefore a new mobile data management framework is needed to process location context data. In this paper, we design a new context management framework for a location based application service. A suggestion framework is consisted of context collector, context manager, rule base, inference engine, and mobile object context database. It describes a form of rule base and a movement process of inference engine that are based on location based application scenario. It also presents an embodiment instance of interface which suggested framework is applied to location context interference of mobile object.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2010년도 춘계학술대회
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• pp.226-234
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• 2010

In this thesis, we present process that remove mistake of data before statistical analysis. If field data which is not simple examination about validity of data, we cannot believe analyzed statistics information. As statistical analysis information is produced based on data to be input in statistical analysis process, the data to be input should be free of error. In this paper, we study the application of statistical analysis road map that can enhance application on site by organizing basic theory and approaching on initial data exploratory phase, essential step before conducting statistical analysis. Therefore, access to statistical analysis can be enhanced and reliability on result of analysis can be secured by conducting correct statistical analysis.