• Journal of Information Technology Services
• /
• v.22 no.5
• /
• pp.71-86
• /
• 2023

Recently, various geographic information systems have been used based on spatial information of geographic information systems. Accordingly, it is essential to produce a large-scale map as a small-scale map for various uses of spatial information. However, maps currently being produced have inconsistencies between data due to production timing and limitations in expression, and productivity efficiency is greatly reduced due to errors in products or overlapping processes. In order to improve this, various efforts are being made, such as publishing research and reports for automating domestic mapping, but because there is no specific result, it relies on editors to make maps. This is mainly done by hand, so the time required for mapping is excessive, and quality control for each producer is different. In order to solve these problems, technology that can be automatically produced through computer programs is needed. Research has been conducted to apply the rule base to geometric generalization. The algorithm tolerance setting applied to rule-based modeling is a factor that greatly affects the result, and the level of the result changes accordingly. In this paper, we tried to study the effectiveness of mapping according to tolerance setting. To this end, the utility was verified by comparing it with a manually produced map. In addition, the original data and reduction rate were analyzed by applying generalization algorithms and tolerance values. Although there are some differences by region, it was confirmed that the complexity decreased on average. Through this, it is expected to contribute to the use of spatial information-based services by improving tolerances suitable for small-scale mapping regulations in order to secure spatial information data that guarantees consistency and accuracy.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1998.10a
• /
• pp.407-410
• /
• 1998

Configuration is a set of building block processes, a series of selection and combining parts or components which composes a whole thing. A whole thing could be such a configurable object as manufacturing product, network system, financial portfolio, system development plan, project team, etc. Configuration problem could happen during any phase of product life cycle: design, production, sales, installation, and maintenance. Configuration has long been one of cost and time consuming work, because only high salaried technical experts on product and components can do configuration. Rework for error adjustments of configurations at later process causes far much cost and time, so accurate configuration is required. Under the on-line electronic commerce environment, configuration problem solving becomes more important, because component-based sales should be done automatically on the merchant web site. Automated product search, order placement, order fulfillment and payment make that manual configuration is no longer feasible. Automated configuration means that all the constraints among components should be checked and confirmed by configuration engine automatically. In addition, technical constraints and customer preferences like price range and a specific function required should be considered. This paper gives an brief overview of configuration problems: characteristics, representation paradigms, and solving algorithms and introduce CRSP(Constraint and Rule Satisfaction Problem) method. CRSP method adopts both constraint and rule for configuration domain knowledge representation. A survey and analysis on web sites adopting configuration functions are provided. Future directions of configuration for EC is discussed in the three aspects: methodology itself, companies adopting configuration function, and electronic commerce industry.

• Korea-Australia Rheology Journal
• /
• v.16 no.4
• /
• pp.169-173
• /
• 2004

The control of the rheological properties of a fluid during processing is important and can determine the efficiency of the production in addition to the performance of the final product. The vast majority of process fluids are viscoelastic, hence an instrument that measures both the viscous and elastic properties of the material during processing would be of great practical use. However, most in-line instruments commercially available to date are only capable of measuring viscosity at a single shear rate. An in-line rheometer that measures both the viscous and elastic properties of fluids over a wide range of shear rates simultaneously has been described in a previous publication (Glasscock et at., 2003) in which the results of measurements on flowing sunflower oil were presented. Before this instrument can be used in an industrial situation, it must be demonstrated that the generated results are the same as, or bear some fixed relationship to, the results obtained by conventional off-line rheometers. To this end, the present investigation describes the measurements of a standard reference fluid, polyisobutylene dissolved in 2,6,10,14-tetramethylpentadecane, labelled SRM2490 by the National Institute of Standards and Technology (NIST) in the USA. The results obtained using the in-line rheometer show remarkably good correlation for viscosity, using a modified Cox­Merz rule, with the results supplied with the reference material from NIST.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.10 no.4
• /
• pp.315-323
• /
• 2000

In this paper, we propose a method of constructing neural networks using bio-inpired emergent and evolutionary concepts. This method is algorithm that is based on the characteristics of the biological DNA and growth of plants, Here is, we propose a constructing method to make a DNA coding method for production rule of L-system. L-system is based on so-called the parallel rewriting nechanism. The DNA coding method has no limitation in expressing the produlation the rule of L-system. Evolutionary algotithms motivated by Darwinaian natural selection are population based searching methods and the high performance of which is highly dependent on the representation of solution space. In order to verify the effectiveness of our scheme, we apply it one step ahead prediction of Mackey-Glass time series, Sunspot data and KOSPI data.

• International Journal of Precision Engineering and Manufacturing
• /
• v.5 no.1
• /
• pp.36-41
• /
• 2004

The blanking of thin sheet metal using progressive dies is an important process on production of precision electronic machine parts such as IC leadframe. This paper summarizes the results of simulating the progressive blanking process by means of LS/DYNA. In order to verify the influence of blanking order on the final lead profile and deformed configuration, simulation technique has been proposed and analyzed using a commercial FEM code, LS/DYNA. The results of FE-simulations are in good agreement with the experimental result. After then, to construct rule base in progressive blanking process, FE-simulation has been performed using a simple model. Based on this result rule base is set up and then the blanking order of inner lead is rearranged. Consequently, from the results of FE-simulation using suggested method in this paper, it is possible to predict the shift of lead to manufacture high precision lead frame in progressive blanking process. The proposed method can give more systematic and economically feasible means for designing progressive blanking process.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2000.11c
• /
• pp.715-721
• /
• 2000

In this research, rule and neuro net based boundary extraction algorithm was developed. Extracting boundary of the interest, lean tissue, is essential for the quality evaluation of the beef based on color machine vision. Major quality features of the beef are size, marveling state of the lean tissue, color of the fat, and thickness of back fat. To evaluate the beef quality, extracting of loin parts from the sectional image of beef rib is crucial and the first step. Since its boundary is not clear and very difficult to trace, neural network model was developed to isolate loin parts from the entire image input. At the stage of training network, normalized color image data was used. Model reference of boundary was determined by binary feature extraction algorithm using R(red) channel. And 100 sub-images(selected from maximum extended boundary rectangle 11${\times}$11 masks) were used as training data set. Each mask has information on the curvature of boundary. The basic rule in boundary extraction is the adaptation of the known curvature of the boundary. The structured model reference and neural net based boundary extraction algorithm was developed and implemented to the beef image and results were analyzed.

• Korean journal of communication and information
• /
• v.56
• /
• pp.117-131
• /
• 2011

This study critically reviews the justifications for the restriction of cable local channel's news commentary function in terms of the fundamental principle of journalism. By doing so, it tries to find some problems and ways to solve them. Broadcasting Law and Korea Communications Commission's Rule inhibiting the news commentary of cable local channel on specific issues conflict with the basis of journalism which is particularly represented in Broadcasting Law. The law and rule tend to solidify public opinion for vested rights of local worthies. In addition, they are likely to degenerate cable local channel to the tools for promoting local government. Therefore, this article proposes the revision of the law and rule towards permitting the news commentary of cable local channel. At the same time, it suggests a new broadcasting policy for inducing cable local channel to increase manpower resources and production investment.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.4
• /
• pp.112-119
• /
• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• Industrial Engineering and Management Systems
• /
• v.2 no.1
• /
• pp.9-27
• /
• 2003

In a wafer fabrication factory, the completion time of an order is affected by many factors related to the specifics of the order and the status of the system, so is difficult to predict precisely. The level of influence of each factor on the order completion time may also depend on the production system characteristics, such as the rules for releasing and dispatching. This paper presents a method to identify those factors that significantly impact upon the order completion time under various combinations of scheduling rules. Computer simulations and statistical analyses were used to develop effective due date assignment models for improving the due date related performances. The first step of this research was to select the releasing and dispatching rules from those that were cited so frequently in related wafer fabrication factory researches. Simulation and statistical analyses were combined to identify the critical factors for predicting order completion time under various combinations of scheduling rules. In each combination of scheduling rules, two efficient due date assignment models were established by using the regression method for accurately predicting the order due date. Two due date assignment models, called the significant factor prediction model (SFM) and the key factor prediction model (KFM), are proposed to empirically compare the due date assignment rules widely used in practice. The simulation results indicate that SFM and KFM are superior to the other due date assignment rules. The releasing rule, dispatching rule and due date assignment rule have significant impacts on the due date related performances, with larger improvements coming from due date assignment and dispatching rules than from releasing rules.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.55 no.6
• /
• pp.946-953
• /
• 2022

Using the management strategy evaluation methods and data on the Korea chub mackerel Scomber japonicus where the state-space logistic production model is used as the operation and the estimation model respectivley, we examined the effects of both Dorn's rule, α and the buffer value for ABC (allowable biological catch), which are used by the Korea fishery managers for decision rules. We set scenarios that have different pairs of buffer and α values, which include those currently used in the management in Korea. Under each sceanario, we projected the fish population biomass until year 2050, during which ABC is determined in each year with the decision rule. We used three kinds of performance measures: (i) whether the biomass in 2050 is overfished; (ii) the average of annual yields over the simulation period; and (iii) the variability of annual yields over the period. We found that the current practice (buffer=0.9, and α = 0.05) resulted in the best performance in terms of avoiding the "overfished" status. However, the current practice failed to reach the maximum average of the annual yields and led to larger uncertainty in the annual yields.