• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.782-788
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• 2003

Making deicing countermeasure plan against snow accretion on power line is a very complicated problem, which should take into account both the possibility of accidents due to snow accretion on power line and the stable operation of power system. As knowledge engineering can be a good solution to this field of problems, a prototype expert system to assist power system operators in forecasting snow accretion on power lines and making a list of all the feasible and effective deicing countermeasures has been developed. The system has been remodelled into a fuzzy expert system by adopting fuzzy rulebase and fuzzy inference method to systematically process the fuzziness included in the heuristic knowledges. Simulation results based on the past snow accretion accident data show that the proposed system is very promising.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1073-1075
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• 1998

This paper presents the method of parameter estimation of diffusion model for monitoring Demand-Side Management Program. Bass diffusion model was applied in this paper, which has different values according to parameters ; coefficients of innovation, imitation and potential adopters. Though it is very important to estimate three parameter, there are no empirical results in practice. Thus, this paper presents the method of parameter estimation in case of few data with constraints to reduce the possibility of bad estimation. The constraints are empirical results or expert's decision. Case studies show the diffusion curves of high-efficient lighting and also forecasting of the peak value for power demand considering diffusion of high-efficient lighting, the feedback and least-square parameter estimation method used in this paper enable us to evaluate the status and forecasting of the effect of DSM program.

• Journal of Korea Water Resources Association
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• v.34 no.3
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• pp.253-263
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• 2001

It is very important to select appropriate methods of collecting, predicting, and analyzing information for the development of urban water resources and the prevention of disasters. Thus, in this study an accurate data generation method is developed using Geographic Information System (GIS) and Remote Sensing (RS). The methods of development and application of an expert system are suggested to solve more efficiently the problems of water resources and quality induced by the rapid urbanization. The time-varying data in a large region, the An-Yang cheon watershed, were reasonably obtained by the application of the GIS using ARC/INFO and RS data. The ESPE (Expert System for Parameter Estimation), an expert system is developed using the CLIPS 6.0. The simulated results showed agreement with the measured data globally. These methods are expected to efficiently simulate the runoff and water quality in the rapidly varying urban area.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.707-714
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• 2022

Versatile Video Coding (VVC) is the most recent video coding standard, which had been developed by Joint Video Expert Team (JVET). It can improve significant coding performance compared to the previous standard, namely High Efficiency Video Coding (HEVC). Although VVC can achieve the powerful coding performance, it requires the tremendous computational complexity of VVC encoder. Especially, affine motion compensation (AMC) was adopted the block-based 4-parameter or 6-parameter affine prediction to overcome the limit of translational motion model while VVC require the cost of higher encoding complexity. In this paper, we proposed the early termination of AMC that determines whether the affine motion estimation for AMC is performed or not. Experimental results showed that the proposed method reduced the encoding complexity of affine motion estimation (AME) up to 16% compared to the VVC Test Model 17 (VTM17).

• Journal of Korea Water Resources Association
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• v.35 no.2
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• pp.161-171
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• 2002

It has been known that the accurate estimates of 2-dimensional water quality model parameters are difficult for non-experts due to the complexity of theoretical background and input requirement and complicated inter-relationship between model Parameters. The main goal of this study is to Provide expert system for the optimal estimation of water quality model parameters, which is based on the development of chaining mechanism according to the sensitivity analysis of model parameter interactions and GUI interface system on ArcView Avenue. The selected study area is the 35.3- km main Han river starting from Paldang Dam site to the Point of Indo bridge and the tributary inflows including pollutant data are used for the system application and validation. The estimated main model parameters are 0.367 for transverse dispersion coefficient, 0.074 for and 0.162 for. It also shows that the simulated water quality constituents such as DO and BOD based on the estimated model parameters are well agreed with the observed ones. It can be concluded that the developed GIS-based expert system for water quality model parameter estimation and graphical representation of water quality analysis is useful for the scientific water quality management.

• Journal of Korean Society of Rural Planning
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• v.13 no.2
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• pp.17-26
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• 2007

This study aims to develop a rational evaluation system which consists of the selection of evaluation items and the estimation of its weight for the Enhancement Program of the Quality of Life for Farmers and Fishermen and Rural Development. This system has two hierarchical steps. The first step shows the evaluation goals which are relevance, efficiency and effectiveness of the program. The second step stands for the evaluation items which have 11 sub-items such as necessity and externalization for the program, rationality of procedures, feedback and monitoring system, budgetary allocations, information activities, impacts on the program, achievements of the goals and so on. A tentative evaluation system was proposed by brainstorming and Delphi method of expert-group. Weighting values of evaluation items were calculated through pair-comparison works of expert group using stepwise matrix sheets by AHP(Analytic Hierarchy Process).

• IE interfaces
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• v.16 no.1
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• pp.103-110
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• 2003

Growth curves are widely used in forecasting the market demand. When there are only a few data points available, the estimated model parameters have a low confidence. In this case, if some expert opinions are available, it would be better for predicting future demand to adjust the model parameters using these information. This paper proposes the methodology for re-estimation of model parameters in growth curves when adjusting market potential and/or time of maximum sales. We also provide the detailed procedures for five growth curves including Bass, Logistic, Gompertz, Weibull and Cumulative Lognormal models. Applications to real data are also included.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.117-122
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• 2022

This paper proposes a method for evaluating the work of manufacturing workers using MediaPipe as a risk factor for musculoskeletal diseases. Recently, musculoskeletal disorders (MSDs) caused by repeated working attitudes in industrial sites have emerged as one of the biggest problems in the industrial health field while increasing public interest. The Korea Occupational Safety and Health Agency presents tools such as NIOSH Lifting Equations (NIOSH), OWAS (Ovako Working-posture Analysis System), Rapid Upper Limb Assessment (RULA), and Rapid Entertainment Assessment (REBA) as ways to quantitatively calculate the risk of musculoskeletal diseases that can occur due to workers' repeated working attitudes. To compensate for these shortcomings, the system proposed in this study obtains the position of the joint by estimating the posture of the worker using the posture estimation learning model of MediaPipe. The position of the joint is calculated using inverse kinetics to obtain an angle and substitute it into the REBA equation to calculate the load level of the working posture. The calculated result was compared to the expert's image-based REBA evaluation result, and if there was a result with a large error, feedback was conducted with the expert again.

• Geotechnical Engineering
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• v.10 no.3
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• pp.79-96
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• 1994

A tunnel design expert system entitled NESTED is developed using the artificial neural network. The expert system includes three neural network computer models designed for the stability assessment of underground openings and the estimation of correlation between the RMR and Q systems. The expert system consists of the three models and the computerized rock mass classification programs that could be driven under the same user interface. As the structure of the neural network, a multi -layer neural network which adopts an or ror back-propagation learning algorithm is used. To set up its knowledge base from the prior case histories, an engineering database which can control the incomplete and erroneous information by learning process is developed. A series of experiments comparing the results of the neural network with the actual field observations have demonstrated the inferring capabilities of the neural network to identify the possible failure modes and the support timing. The neural network expert system thus complements the incomplete geological data and provides suitable support recommendations for preliminary design of tunnels in rock masses.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.376-376
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• 2000

Several algorithmic models have been proposed to estimate software cost and other management parameters. In particular, early prediction of completion time is absolutely essential for proper advance planning and a version of the possible ruin of a project. However, estimation is difficult because of its similarity to export judgment approaches and for its potential as an expert assistant in support of human judgment. Especially, the nature of the Norden/Rayleigh curve used by Putnam, renders it unreliable during the initial phases of the project, in projects involving a fast manpower buildup, as is the case with most software projects. Estimating software development effort is more complexity, because of infrastructure software related to target-machines hardware and process characteristics should be considered in software development for DCS (Distributed Control System). In this paper, we propose software development effort estimation technique using adaptive neural fuzzy inference system. The methods is applied to case-based projects and discussed.