• 경영과정보연구
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• 제22권
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• pp.211-229
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• 2007

The ISO/TS16949 APQP goal of defect prevention and decrease of spread waste, is the customer satisfaction which leads a continuous improvement and profit creation. The quality expense where the most is caused by but with increase of production initial quality problem occurrence is increasing to is actuality. Like this confirmation amendment. with the problem which is forecast in the place development at the initial stage which it does completeness it does not confront not to be able, production phase to be imminent, the problem accumulates and it talks the development shedding of which occurs. In opposition, prediction confrontation. is forecast in development early stage to and it is a structure which does not occur a problem to production early stage. Like this development is a possibility of accomplishing competitive company from production phase. Which attains an goal of, chance cause it leads a APQP activity (common cause) with special cause prevention & detection the connection characteristic of the focus technique against a interaction is important. And the customer requirement satisfaction and must convert a APQP goal of attainment at the key characteristics action step. (1) The Prevention - with Design FMEA application prevention of the present design management/detection, (2) the Detection (prevention/detection) - with Process FMEA application prevention of the present process control/detection, (3) Special Cause - statistical process control (SPC) 4M cause spread removal, (4) Common Cause - statistical process control (SPC) the nothing zero defect which leads the continuous improvement back of spread with application it will be able to attain with application.

• 한국전자파학회논문지
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• 제18권1호
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• pp.96-104
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• 2007

현재 국제적으로 수풀 손실 예측 모델이나 측정 데이터가 매우 부족하다. 본 논문에서는 2005년과 2006년, 2년에 걸쳐 $1{\sim}6\;GHz$ 대역 국내 수풀 및 가로 환경에 많이 분포하는 소나무(pine tree), 히말라야시다(hymalaya cedar),플라타너스나무(plane tree), 메타나무(dawn-redwood tree)등의 수풀에 대한 수풀 손실 특성 측정 수행 결과로부터, ITU-R P.833에서 제시하고 있는 RET(radiative energy transfer) 모델 파라미터를 도출하였으며, 모델 보정을 시도하였다. 본 연구 결과는 2005년, 2006년 ITU-R SG WP 3J 회의에서 권고서에 반영되었다.

• 한국대기환경학회지
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• 제32권2호
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• pp.193-207
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• 2016

This study discusses the present status of mercury emission and distribution from major anthropogenic sources in Korea and the future trend of mercury emission by activity changes and application of BATs. Atmospheric mercury emission from major anthropogenic sources based on Annex D of Minamata convention was estimated to around 4.89 tonne in 2012. Emission ratios of cement clinker production, coal-fired power plant, waste incineration and non-ferrous metal smelting were 68.68%, 24.75%, 6.29% and 0.28%, respectively. High mercury emission regions were characterized by the presence of cement clinker production facilities and coal-fired power plants. Prediction of future activities was carried out by linear regression of the previous year data. The (total) mercury emission was estimated to decrease up to 48% Under the scenario of BATs to be applied and the change of future activities. Emissions from coal-fired powerplants and cement clinkers were expected to decrease significantly.

• Steel and Composite Structures
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• 제25권6호
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• pp.671-684
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• 2017

Elastic-plastic shear buckling behaviors of the web-post in a Castellated Steel Beam (CSB) with hexagonal web openings under vertical shear force were investigated further using Finite Element Model (FEM) based on a sub-model, which took the upper part of the web-post under horizontal shear force to represent the whole web-post under vertical shear force. A simplified design method for the web-post elastic-plastic shear buckling strength was proposed based on simulation results of the sub-model. Proper boundary conditions were applied to the sub-model to assure that its behaviors were identical to those of the whole web-post. The equation to calculate the thin plate elastic shear buckling strength was adopted as the basic form to build the design equation for elastic-plastic buckling strength of the sub-model. Parameters that might affect the elastic-plastic shear buckling strength of the whole web-post were studied. After obtaining the vertical shear buckling strength of a sub-model through FEM, the shear buckling coefficient k can be obtained through the back analysis. A practical calculation method for k was proposed through curving fitting the parameter study results. The elastic-plastic shear buckling strength of the web-post calculated using the proposed shear buckling coefficient k agreed well with that obtained from the FEM and test results. And it was more precise than those obtained from EC3 based on the strut model.

• 대한원격탐사학회지
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• 제26권1호
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• pp.47-57
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• 2010

본 연구의 목적은 2006년 태풍 에위니아, 빌리스, 개미와 집중호우로 인해 많은 산사태가 발생한 진부면 지역을 대상으로 항공사진을 이용한 산사태 탐지 및 인공신경망과 GIS를 이용한 산사태 취약성을 분석하는데 있다. 산사태 위치는 산사태 발생 전후의 항공사진을 판독 후 현장에서 확인하였다. 취약성 분석을 위해 지형, 지질, 토양, 임상, 선구조, 토지이용도 등의 자료는 공간 데이터베이스로 구축하였다. 산사태와 관련 요인들간의 상대적 가중치는 인공신경망의 역전파 알고리즘을 이용하여 결정하였다. 그 결과 경사방향과 경사는 다른 요인들 보다 1.2~1.5배 높게 나타났다. 이 가중치를 이용하여 취약성도를 작성 후 분석에 사용하지 않은 산사태 위치와 비교하여 검증하였다. 그 결과 예측 정확도는 81.44%로 나타났다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.424-424
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• 2018

인공신경망(Artificial Neural Network; ANN)은 뇌에 존재하는 생물학적 신경세포와 이들의 신호처리 과정을 수학적으로 묘사하여 뇌가 나타내는 지능적 형태의 반응을 구현한 것이다. 인공신경망은 학습(training)을 통해 입력과 출력으로 구성되는 하나의 시스템을 병렬적이고 비선형적으로 구축할 수 있으며, 유연한 모델링 특성으로 인하여 시스템 예측, 패턴인식, 분류 및 공정제어 등의 다양한 분야에서 활용되고 있다. 인공신경망에 대한 최초의 이론은 Muculloch and Pitts(1943)가 제안한 Perceptron에서 시작 되었으며, 기본적인 학습기법인 오차역전파 기법(back-propagation Algorithm) 이 1980년대에 들어 수학적으로 정립된 이후 여러 분야에서 활용되기 시작하였다). 본 연구에서는 하도추적, 구체적으로는 상류단의 복수의 수위관측을 이용하여 하류단의 수위를 예측하기 위하여 인공신경망 모델을 구성하였다. 대상하도는 금강유역의 용담댐과 대청댐 사이의 본류이며, 상류단 입력자료로써 본류에 있는 수통, 호탄 관측소 관측수위와 지류인 송천 관측소 관측수위를 고려하였다. 출력 값으로는 하류단의 옥천 관측소 수위를 3시간 및 6시간의 선행시간으로 예측하도록 인공신경망 모형을 구성하였다. 인공신경망의 학습(testing), 시험(testing), 검증(validation)을 위해 2000년부터 2012년까지 13년간의 시수위자료를 이용하여 학습을 진행하였으며, 2013년부터 2014년의 2년간의 수위자료를 이용한 시험을 통해 최적의 모형을 선정하였다. 또한 선정된 최적의 모형을 이용하여 2015년부터 2016년까지의 수위예측을 수행하였다.

• Geomechanics and Engineering
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• 제19권2호
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• pp.153-165
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• 2019

A case study of monitoring and analysis of surface settlement induced by tunneling of Tabriz metro line 2 (TML2) is presented in this paper. The TML2 single tunnel has been excavated using earth pressure balanced TBM with a cutting-wheel diameter of 9.49 m since 2015. Presented measurements of surface settlements, were collected during the construction of western part of the project (between west depot and S02 station) where the tunnel was being excavated in sand and silt, below the water table and at an average axis depth of about 16 m. Settlement readings were back-analyzed using Gaussian formula, both in longitudinal and transversal directions, in order to estimate volume loss and settlement trough width factor. In addition to settlements, face support and tail grouting pressures were monitored, providing a comprehensive description of the EPB performance. Using the gap model, volume loss prediction was carried out. Also, COB empirical method for determination of the face pressure was employed in order to compare with field monitored data. Likewise, FE simulation was used in various sections employing the code Simulia ABAQUS, to investigate the efficiency of numerical modelling for the estimating of the tunneling induced-surface settlements under such a geotechnical condition. In this regard, the main aspects of a mechanized excavation were simulated. For the studied sections, numerical simulation is not capable of reproducing the high values of in-situ-measured surface settlements, applying Mohr-Coulomb constitutive law for soil. Based on results, for the mentioned case study, the range of estimated volume loss mostly varies from 0.2% to 0.7%, having an average value of 0.45%.

• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• 농촌계획
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• 제25권2호
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• pp.99-117
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• 2019

Environmental impact assessment (EIA), which predicts, evaluates, and manages the influences on natural landscape, plays a role of monitoring natural resources for systematic management of natural landscape. However, the function of verification and correction of the system is still insufficient and feed-back, one of the most important features of EIA follow-up, has not been introduced in Korea's EIA system yet. As a procedure, it is required to check if the opinions of the evaluators are properly reflected to the outcomes of the project through a reviewing process after assessing environmental impacts of a development project. In reality, despite the awareness about the importance of follow-up inspection of the conformity with, the system mainly focuses on the agreement during the planning stage of the development project and fails to continuously manage after its completion. There have been various preceding studies related to prediction, evaluation, and management of environmental impacts on natural landscape for better management. They primarily dealt with the problems in the EIA process and suggested improvement measures, including directions for institutional development, step-by-step goals, and operation methods, to address the problems which arise in the EIA follow-up process. However, suggested measures are not actively applied with the focus only put on institutional operation, there are virtually no standardized methods to predict and assess landscape changes due to the development project and to manage landscape after the project. Against this backdrop, this study aims to explore the existing methods to analyze the impacts natural landscape and to establish a system where landscape management is continued after the development project. To this end, we will suggest reducing methods according to the predicted changes in landscape for post-project management of natural landscape. Characteristics of reduction methods by project type were examined through reviewing the guide to natural landscape rating and the importance of development project impacts on natural landscape by type of reduction was evaluated through questionnaire for experts. Evaluated types of reduction are classified and presented by characteristics of each development project and content of reduction type.

• 한국컴퓨터정보학회논문지
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• 제27권1호
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• pp.157-166
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• 2022

본 연구는 철로 복합화물 운송 시 환적 작업으로 인해 발생하는 소요 시간과 비용을 줄이고 운송속도 향상이 가능한 피기백시스템의 도입 타당성을 분석하는 것을 목표로 한다. 이를 위해 국내외 문헌검토를 통해 타당성 분석방법론을 검토한다. 타당성 분석 값을 정량적으로 도출하기 위해 교통 데이터베이스를 적용하여 운송거리가 200KM이상인 주요 화물 운송 O-D 노선에 화물 운송 시뮬레이션 모델과 운송 수단별 화물 수요 예측 모델을 개발하였다. 2025년 주요 화물 운송 O-D 노선에 피기백시스템이 도입된다는 전제로 분석기간을 15년으로 설정하여 경제적 타당성을 분석한 결과 NPV 값이 양수이고 B/C값이 1.18로 도출되어 피기백시스템이 경제성이 있는 것으로 나타났다. 제안된 연구 방법은 철도운송의 경쟁력을 향상할 수 있는 교통 정책 수립에 유의미한 자료가 될 수 있다.