• 한국물환경학회지
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• 제27권1호
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• pp.30-35
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• 2011

2D pollutant transport model was applied to the simulation of contaminant transport in the channel. At first, two kinds of virtual channels having different slopes were designed. The distribution of contaminant, which flows from one of the three drainages to the main channel, was simulated by each 2D model. Concentrations of 745 nodes were converted to input data of neural network model (Multi-perceptron) for training and verification using matrix. The first three cases (Case A-1, A-2, A-3) were used for training Multi-perceptron, the other three cases (Case B-1, B-2, B-3) were used for verification. As a result, Multi-perceptron reasonably divided the cases into the three characteristics which have different contaminant distributions due to the different input point of water pollution source. It can be a useful methodology for the water quality monitoring and backtracking.

• Smart Structures and Systems
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• 제6권5_6호
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• pp.545-559
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• 2010

This paper presents the results of a pilot study and verification of a concept of a novel methodology for damage detection and assessment of water distribution system. The unique feature of the proposed noninvasive methodology is the use of accelerometers installed on the pipe surface, instead of pressure sensors that are traditionally installed invasively. Experimental observations show that a sharp change in pressure is always accompanied by a sharp change of pipe surface acceleration at the corresponding locations along the pipe length. Therefore, water pressure-monitoring can be transformed into acceleration-monitoring of the pipe surface. The latter is a significantly more economical alternative due to the use of less expensive sensors such as MEMS (Micro-Electro-Mechanical Systems) or other acceleration sensors. In this scenario, monitoring is made for Maximum Pipe Acceleration Gradient (MPAG) rather than Maximum Water Head Gradient (MWHG). This paper presents the results of a small-scale laboratory experiment that serves as the proof of concept of the proposed technology. The ultimate goal of this study is to improve upon the existing SCADA (Supervisory Control And Data Acquisition) by integrating the proposed non-invasive monitoring techniques to ultimately develop the next generation SCADA system for water distribution systems.

• 물과 미래
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• 제27권1호
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• pp.111-121
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• 1994

본 연구의 목적은 한정된 자료원을 각 용수 수요점 별로 용수공급 우선 순위에 따라서 최적배분하기 위한 Network 모형을 구성하는 것이다. 본 모형의 해법은 OKA(Out of Kilter Algorithm)를 사용하였다. 모형에 대한 이론적 방법론과 프로그램을 검증하고 적용하기 위하여 금강유역을 선정했다. 대청댐 방유량과 금강 유역의 용수수요량을 사용하여, 각 수요점의 용수공급 우선 순위를 1~ 4개의 경우로 설정하고 수자원의 최적배분을 시행하였다. 모형을 적용한 결과, 물리적인 시스템을 타당성 있게 표현할 수 있었고, 높은 우선 순위로 조정된 수요점에서는 물 부족량을 줄일 수 있었다. 본 모형의 해법은 Revised Simplex 알고리즘에 의해 검증하였다.

• 산업공학
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• 제24권3호
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• pp.187-195
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• 2011

The automatic radiopharmaceutical module consists of several 2-way valves, couple of syringes, gas supply unit, heating(cooling) unit and sensors to control the chemical reagents as well as to help the chemical reaction. In order to control the actuators of radiopharmaceutical module, the process is tabulated using spread sheet as like excel. Unlike the common program, a trivial error is too critical to allowed in the process because the error can lead to leak the radioactive reagent and to cause the synthesis equipment failure during synthesizing. Hence, the synthesis process has been validated using graphic simulation while the operator checks the whole process visually and undergoes trial and error. The verification of the synthesis process takes a long time and has a difficulty in finding the error. This study presents a methodology to verify the process algebraically while the radiopharmaceutical module is converted to the network model. The proposed method is validated using actual synthesis process.

• 한국컴퓨터정보학회논문지
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• 제23권4호
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• pp.147-153
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• 2018

In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

• 한국군사과학기술학회지
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• 제9권4호
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• pp.61-70
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• 2006

This paper is to describe LYNX-ESM Simulation System to simulate for EW operating environment analysis and system performance verification of LYNX-ESM system using Discrete Event Simulation(DEVS) Methodology. This system consists of 3 PC with TCP/IP network. Each PC is loaded with Modeling & Simulation program based DEVS. Each connected program conducts EW simulation. As a result, we analyze the operating environment of the maritime EW threat, simulate the EW threat discrimination and geolocation capability, and estimate the LYNX-ESM system effectiveness before real LYNX-ESM system development.

• 경영과학
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• 제10권1호
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• pp.107-125
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• 1993

Modern telecommunication switching systems are SPC(Stored Program Control) machines handling voice, data and other kinds of traffic, in an environment which tends to be fully digital switching and transmission. The throughput of such systems is determined by the real time capacity of its centralized or distributed control processors and by the traffic capacity of the switching network. Designers must verify the traffic and call processing capacity of the switching system and check its performance under traffic load before it is put into service. Verification of traffic and call processing capacity of switching systems is one of the problems treated by teletraffic studies ; teletraffic studies are based on stochastic process, queueing theory, simulations and other quantitative methods of decision making. This study suggests the general methodology to evaluate the throughput and performance of the ISDN switching system. TDX-10 ISDN switching system are employed to give illustrative examples of the methodologies discussed in this study.

• 한국안전학회지
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• 제26권6호
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• pp.111-117
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• 2011

Risk-based railway safety management has been mandatory in Korea as by relevant laws and regulations enacted since the Railway Safety Act 2004. In particular, the Railway Vehicle Safety Guidance came into effect on Jan 1, 2008 specifies the details of methodology for hazard analysis, risk assessment and safety verification and validation. Fundamentals for success of the risk-based safety management are systematic hazard identification and risk assessment by use of reasonable risk assessment criteria, but the principle of risk-based safety management has not been applied in an effective way to introduction and maintenance of railway vehicle systems because definite risk assessment criteria have not been set down for each railway system or railway network. The purpose of this study is to suggest a risk matrix development principle for risk assessment of domestic urban metro vehicles by analyses of relevant rules and railway operating environment of Korea.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1330-1333
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• 2004

The methodology for modeling building energy consumption is well established for energy saving calculation in the temperate zone both for performance-based energy retrofitting contracts and measurement and verification (M&V) projects. Mostly, statistical regression models based on utility bills and outdoor dry-bulb temperature have been applied to baseline monthly and annual whole building energy use. This paper presents the application of neural networks (NN) to model landlord energy consumption of commercial buildings in Singapore. Firstly, a brief background information on NN and its application on the building energy research is provided. Secondly, five commercial buildings with various characteristics were selected for case studies. Monthly mean outdoor dry-bulb temperature ($T_0$), Relative Humidity (RH) and Global Solar Radiation (GSR) are used as network inputs and the landlord monthly energy consumption of the same period is the output. Up to three years monthly data are taken as training data. A forecast has been made for another year for all the five buildings. The performance of the NN analysis was evaluated using coefficient of variance (CV). The results show that NNs is powerful at predicting annual landlord energy consumption with high accuracy.

• 대한공간정보학회지
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• 제21권4호
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• pp.143-150
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• 2013

본 연구의 목적은 상세 레벨의 대규모 도로망 데이터를 대상으로 다양한 축척과 추상화 수준을 가진 상위 레벨의 소축척 도로 선형 사상을 유도하는 가변-축척 기반 네트워크 데이터의 생성 방안을 제시하는 것이다. 이를 위해 우선, 가변-축척 모델 구축을 위해 관련 용어의 정의와 모델 구축시의 이점과 구축 절차에 대해 살펴보았다. 둘째, 가변-축척 모델을 설계하기 위해 지도 표출을 위한 표현 레벨과 레이어 구성요소를 제시하였다. 또한 상위 LoD와 데이터 연계 방법과 인덱스 구조 생성을 위한 규칙을 정의 하였다. 마지막으로 설계된 모델의 구현과 검증을 위해 제시된 알고리즘을 실제적인 연구지역 도로망(제주도)에 적용하여 가변 축척 도로망을 유도하여 구축하고, 공간 데이터베이스(Oracle Spatial)에 저장한 후 성능 분석을 통해 모델의 효율성과 타당성을 검증하였다.