• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.70-72
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• 1993

This paper presents an expert system that sheds loads considering priority in the localized SCADA power systems during an emergency states. The proposed algorithm uses neural networks to detect local load shedding location and heuristic rules to determine load shedding amounts. The proposed expert system is demonatrated at one of the model system which incorporates two localized SCADA power system. It is operated under workstation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.34 no.1
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• pp.1-5
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• 1998

This study presents intelligent deburring system which can transfer the exper's skill to deburring robot through neural network. The expert's skill is expressed as associate mapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring process can be extracted via the visual sense of the human, we employ vision system for the perception and identification of the changing burr. From the demonstration of human experts, force data are measured and fitted impedance model. Finally the characteristics of the burr and coressponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.

• The Korean Journal of Applied Statistics
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• v.3 no.1
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• pp.1-9
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• 1990

Engineering approach of statistics processing is defined for the statistical expert system. First, the engineering approach requirement are conceptualized by using an artificial intelligence in statistics, with the extensions being additional statistical knowlege engineering such as software engineering, optinal relationships, and the generalization abstraction. The methodology produces statistical expert system designes that are not only accurate representations of reality but also enough to accommodate future processing requirements. It also representions of knowledge that must be constructed, using the extended engineering processing model conceptualization and proposed engineering approach of the problem.

• Smart Media Journal
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• v.12 no.1
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• pp.54-61
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• 2023

Pricing, as one of the most important aspects of a business, should be taken seriously. Whatever affects a company's pricing system tends to affect its profits and losses as well. Currently, many manufacturing companies fix product prices manually by members of an organization's management team. However, due to the imperfect nature of humans, an extremely low or high price may be fixed, which is detrimental to the company in either case. This paper proposes the development of a fuzzy-based price expert system (Expert Fuzzy Price (EFP)) for manufacturing companies. This system will be able to recommend appropriate prices for products in manufacturing companies based on four major pricing strategic goals, namely: Product Demand, Price Skimming, Competition Price, and Target population.

• Journal of Korean Academy of Nursing
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• v.45 no.3
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• pp.429-438
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• 2015

Purpose: This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). Methods: This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. Results: We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. Conclusion: KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

• Nuclear Engineering and Technology
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• v.46 no.5
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• pp.619-632
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• 2014

The Best Estimate Plus Uncertainty (BEPU) method has been widely used to evaluate the uncertainty of a best-estimate thermal hydraulic system code against a figure of merit. This uncertainty is typically evaluated based on the physical model's uncertainties determined by expert judgment. This paper introduces the application of data assimilation methodology to determine the uncertainty bands of the physical models, e.g., the mean value and standard deviation of the parameters, based upon the statistical approach rather than expert judgment. Data assimilation suggests a mathematical methodology for the best estimate bias and the uncertainties of the physical models which optimize the system response following the calibration of model parameters and responses. The mathematical approaches include deterministic and probabilistic methods of data assimilation to solve both linear and nonlinear problems with the a posteriori distribution of parameters derived based on Bayes' theorem. The inverse problem was solved analytically to obtain the mean value and standard deviation of the parameters assuming Gaussian distributions for the parameters and responses, and a sampling method was utilized to illustrate the non-Gaussian a posteriori distributions of parameters. SPACE is used to demonstrate the data assimilation method by determining the bias and the uncertainty bands of the physical models employing Bennett's heated tube test data and Becker's post critical heat flux experimental data. Based on the results of the data assimilation process, the major sources of the modeling uncertainties were identified for further model development.

• The KIPS Transactions:PartA
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• v.11A no.3
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• pp.217-226
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• 2004

This paper describes an experiment of concrete and specific group work learning system based on the traditional Jigsaw group work learning model. Jigsaw model has two groups of students such as random group and expert group so that a course can make progress on explaining and lecturing all members of class after each student can be a member of expert group of course topic. We design and implement Web-based training system to support collaboration and Interaction among students of a course based on Jigsaw model The Web- based learning system makes each group going up to the expert level of a course subject by supporting various study menu and provides equal opportunity of improving social abilities such as leadership, communication skill, trust, and trouble-settling by taking part in collaboration activities.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.31-38
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• 2022

This paper applies an expert independent unsupervised neural network learning-based multivariate time series data analysis model, MSCRED(Multi-Scale Convolutional Recurrent Encoder-Decoder), and to overcome the limitation, because the MCRED is based on Auto-encoder model, that train data must not to be contaminated, by using learning data sampling technique, called Subset Sampling Validation. By using the vibration data of power plant equipment that has been labeled, the classification performance of MSCRED is evaluated with the Anomaly Score in many cases, 1) the abnormal data is mixed with the training data 2) when the abnormal data is removed from the training data in case 1. Through this, this paper presents an expert-independent anomaly diagnosis framework that is strong against error data, and presents a concise and accurate solution in various fields of multivariate time series data.

• Journal of The Korea Institute of Healthcare Architecture
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• v.16 no.4
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• pp.7-14
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• 2010

The planning and design of healthcare architecture generally requires the participation and consultation of skilled experts since it has more complex space program than any other buildings. Therefore, the computer-based expert systems for the planning of healthcare architecture have been tried continuously. The recent development of BIM technologies and object-oriented CAAD systems is leading these attempts to realize gradually. Thus, this study attempts to verify whether the new evaluation model and system of the spatial layout, which are based on the validation of space program that developed in earlier studies, are applicable to real examples of design competition. Through this simulation, this study tries to find the possibility of expert systems for the planning of healthcare architecture and act as basic data for the development of new system for the integrated design environment based on BIM technologies in the near future.

• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.245-251
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• 2013

In this paper, the expert system to reduce the amount of food waste is proposed. The method of material flow analysis (MFA) is applied. Proper handling of waste beyond the terms of the need for proactive research been mentioned before, but actually cause the waste generator research focuses on consumer behavior and the business community to analyze the flow of materials within the study are insufficient. In this paper, the type of food consumption and food waste, look at the relationship between the occurrence of secondary schools in the diet is provided for students to examine the preferences of the target model diet expert system was reconfigured. Preference for leaving the food in the diet leads to the important information that is Each diet recipes that make up the target material flow analysis (MFA) was constructed to perform all the database. This database is currently being generated from the rain while cooking diet edible plants and materials to reflect the self-esteem following the recommended diet is used to create. Reducing food waste is actually being used currently in research knowledge to the knowledge base was constructed. Future Home Smart System was developed in conjunction with the system to the user, by providing guidelines for the utilization can be expected.