• 산업공학
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• 제22권2호
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• pp.126-134
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• 2009

As product quality and yield are essential factors in semiconductor manufacturing, monitoring the main manufacturing steps is a critical task. For the purpose, FDC(Fault detection and classification) is used for diagnosing fault states in the processes by monitoring data stream collected by equipment sensors. This paper proposes an FDC model based on decision tree which provides if-then classification rules for causal analysis of the processing results. Unlike previous decision tree approaches, we reflect the structural aspect of the data stream to FDC. For this, we segment the data stream into multiple subregions, define structural features for each subregion, and select the features which have high relevance to results of the process and low redundancy to other features. As the result, we can construct simple, but highly accurate FDC model. Experiments using the data stream collected from etching process show that the proposed method is able to classify normal/abnormal states with high accuracy.

• 한국정보과학회논문지:데이타베이스
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• 제34권6호
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• pp.483-492
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• 2007

최근 센서 네트워크의 발달로 실세계의 많은 데이타가 시간 속성을 갖고 실시간으로 수집되고 있다. 기존의 시계열 데이타 예측 기법은 모델 갱신 없이 예측을 수행하였다. 그러나 스트림 데이타는 매우 빠르게 수집이 되고 시간이 지남에 따라 데이타의 특성이 변경될 수 있으므로 기존의 시계열 예측 기법을 적용하는 것은 적절하지 않다. 따라서 이 논문에서는 슬라이딩 윈도우와 점진적인 회귀분석을 이용한 스트림 데이타 예측 기법을 제안한다. 이 기법은 스트림 데이타를 다중 회귀 모델에 입력하기 위해 차원 분열을 통해 여러 개의 속성으로 분열(Fractal)하고, 변화되는 데이타의 분포를 반영하기 위해 슬라이딩 윈도우 기법을 사용하여 점진적으로 회귀 모델을 갱신한다. 또한 고정 크기 큐를 이용하여 최근의 데이타로만 모델을 유지한다. 이전 데이타의 유지 없이 최소 정보를 갖는 행렬을 통해 모델을 갱신하므로 낮은 공간 복잡도를 갖고 점진적으로 모델을 갱신함으로써 에러율의 증가를 방지한다. 제안된 기법의 타당성은 RME(Relative Mean Error)와 RMSE(Root Mean Square Error)를 이용하여 측정하였고, 실험 결과 다른 기법에 비해 우수하였다.

• International Journal of Contents
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• 제11권1호
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• pp.69-72
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• 2015

Generally, existing parallel main-memory spatial index structures to avoid the trade-off between query freshness and CPU cost uses light-weight locking techniques. However, still, the lock based methods have some limits such as thrashing which is a well-known problem in lock based methods. In this paper, we propose a distributed index structure for moving objects exploiting the parallelism in multiple machines. The proposed index is a lock free multi-version concurrency technique based on the D-Stream model of Spark Stream. The proposed method exploits the multiversion nature of D-Stream of Spark Streaming.

• 농촌계획
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• 제25권1호
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• pp.21-38
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• 2019

Korean agricultural industry has weakened as demand for domestic agricultural products has declined due to accelerating market liberalization, aging and shrinking of rural population, and stagnating rural households' incomes. On the other hand, as the forth industrial revolution unfolds in earnest, tremendous changes are expected, and those changes won't be confined to certain industries but would shaken the world we know of entirely. Smart farm, which is one example of the fourth industrial revolution, is increasingly being recognized as a new growth engine for the future as smart farm and the science and technology behind it, not the size of arable land, will determine competitiveness of the agricultural industry and drive agricultural productivity and managerial efficiency. In consideration that John W. Kingdon's Multiple Streams Framework has recently been presented as an important theoretical model in the policy field, this study analyzed problem stream, policy stream, and political stream in the process of forming the smart farm policy, and looked into what role the government played as policy entrepreneur in policy window. The smart farm policy was put on policy agenda by the government and was approved when the government announced the Smart Farm Plan together with relevant ministries at the 5th Economy-Related Ministers' Meeting held in April 2018. This suggests that change of the government is the most critical factor in political stream, and explicitly indicates the importance of politics in formation of an agricultural policy. In addition, actual outcome of the policy and how policy alternatives that will enhance people's understanding will support it seem to be the key to success. It also shows that it is important that policy alternatives be determined based on sufficient discussion amongst stakeholders.

• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.1076-1080
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• 2015

An inventory control system was developed for a distribution system consisting of a single multiproduct warehouse serving a set of customers and purchasing products from multiple vendors. Purchase orders requesting multiple products are delivered to the warehouse in a process. The receipt of customer orders by the warehouse proceeded in order intervals and in order quantities that are subject to random fluctuations. The objective of warehouse operation is to minimize the total cost while maintaining inventory levels within the warehouse capacity by adjusting the purchase order intervals and quantities. An adaptive model predictive control algorithm was developed using a periodic square wave model to represent the material flows. The adaptive concept incorporated a stabilized minimum variance control-type input calculation coupled with input/output stream parameter predictions. The effectiveness of the scheme was demonstrated using simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1385-1402
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• 2019

Quickly picking up some valuable information from massive manufacturing event stream usually faces with the problem of long detection time, high memory consumption and low detection efficiency due to its stream characteristics of large volume, high velocity, many variety and small value. Aiming to solve the problem above for the current complex event processing methods because of not sharing detection during the detecting process for massive manufacturing event streams, an efficient complex event processing method based on multipattern sharing is presented in this paper. The achievement of this paper lies that a multipattern sharing technology is successfully used to realize the quick detection of complex event for massive manufacturing event streams. Specially, in our scheme, we firstly use pattern sharing technology to merge all the same prefix, suffix, or subpattern that existed in single pattern complex event detection models into a multiple pattern complex event detection model, then we use the new detection model to realize the quick detection for complex events from massive manufacturing event streams, as a result, our scheme can effectively solve the problems above by reducing lots of redundant building, storing, searching and calculating operations with pattern sharing technology. At the end of this paper, we use some simulation experiments to prove that our proposed multiple pattern processing scheme outperforms some general processing methods in current as a whole.

• 한국수자원학회논문집
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• 제45권12호
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• pp.1243-1258
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• 2012

본 연구에서는 지하수 양수에 따른 하천수 감소량을 예측할 수 있는 상관관계식을 지표수-지하수 통합모의 결과를 이용하여 유도하였다. 신둔천과 죽산천 두 개의 시험유역에 대해 지표수-지하수 통합모형 SWAT-MODFLOW을 적용하여 다양한 양수조건에 따른 하천수 감소량 자료를 모의 생성하였으며, 생성된 자료를 바탕으로 다중회귀분석을 실시하여 지하수 양수량, 하천과 양수정 이격거리, 대수층 및 하천바닥의 수리특성, 강수량 등의 함수인 하천수 감소량 산정 식을 유도, 제시하였다. 개발된 상관관계식은 하천인근 지하수 양수에 따른 하천수 영향을 평가하는데 간편하게 적용될 수 있으며, 지하수 양수량 중 하천수에 해당하는 부분인 하천수 기여도를 산정하는데 활용될 수 있을 것으로 기대된다.

• 환경영향평가
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• 제23권3호
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• pp.187-196
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• 2014

The objective of this study is to evaluate and analyze Osu stream watershed water environment system. The data were collected from January 2009 to December 2011 including water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and discharge. The data were used for principle component analysis and factor analysis. The results are as followes. The primary factors obtained from both the principal component analysis and the factor analysis were BOD, COD, TOC, SS and T-P. Once principal component analysis and factor analysis have been performed with the collected data and then the results will be applied to both simple regression model and multiple regression model. The regression model was developed into case 1 using concentrations of water quality parameters and case 2 using delivery loads. The value of the coefficient of determination on case 1 fell between 0.629 and 0.866; this was lower than case 2 value which fell between 0.946 and 0.998. Therefore, case 2 model would be a reliable choice.The coefficient of determination between the estimated figure using data which was developed to the regression model in 2012 and the actual measurement value was over 0.6, overall. It can be safely deduced that the correlation value between the two findings was high. The same model can be applied to get TOC concentrations in future.

• 한국환경과학회지
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• 제24권6호
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• pp.743-753
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• 2015

In this study, it is an object to develop a regression model for the estimation of TOC (total organic carbon) concentration using investigated data for three years from 2010 to 2012 in the Gam Stream unit watershed, and applied in 2009 to verify the applicability of the regression model. TOC and $COD_{Mn}$ (chemical oxygen demand) were appeared to be derived the highest correlation. TOC was significantly correlated with 5 variables including BOD (biological oxygen demand), discharge, SS (suspended solids), Chl-a (chlorophyll a) and TP (total phosphorus) of p<0.01. As a result of PCA (principal component analysis) and FA (factor analysis), COD, TOC, SS, discharge, BOD and TP have been classified as a first factor. TOCe concentration was estimated using the model developed as an independent variable $BOD_5$ and $COD_{Mn}$. R squared value between TOC and measurement TOC is 0.745 and 0.822, respectively. The independent variable were added step by step while removing lower importance variable. Based on the developed optimal model, R squared value between measurement value and estimation value for TOC was 0.852. It was found that multiple independent variables might be a better the estimation of TOC concentration using the regression model equation(in a given sites).

• 대한토목학회논문집
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• 제14권4호
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• pp.875-886
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• 1994

본 연구는 유역의 지형인자를 고려한 강우의 수리학적 단기유출 해석 시스템을 개발한 것이다. 강우 유출의 기본 개념은 Kinematic Wave 이론에 의거하였으며, 그 수치해는 특성곡선 추적법에 의하여 산출된다. 개발된 강우유출해석 시스템은 한개의 하도를 중심으로 좌우 2개의 등가사면을 지니는 단위 등가조도 모델이 복수개의 하도망을 따라 결합된 복합 등가조도 유역 모델로 구성되며, 등가조도유역 모델은 유역의 하천차수이론에 근거하여 규정됨으로써 유역이 지니는 확률적 지형인자를 모델 파라메타에 함축시키는 특성을 지닌다. 모델 파라메타의 민감도분석과 IHP 대표유역인 보청천 유역의 지형 및 수문자료를 이용한 모델 보정과 검정을 통하여 제안 시스템의 현장 적용성과 재현가능성이 확인되었다. 본 연구의 성과에 의하여 해석대상 등가유역의 시공간상 임의 위치에서 수리량의 시간변동 예측 및 유역의 개발에 따른 단기적 수질변동 해석에 요구되는 수리량의 해석이 가능하게 되었다.