• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.231-242
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• 2001

We showed in [2] that if r≤2, zero mean Gaussian of average error of the Trapezoidal rule is proportional to h/sub i//sup 2r+3/ on the interval [0,1]. In this paper, if r≥3, we show that zero mean Gaussian of average error of the Trapezoidal rule is bounded by Ch⁴/sub i/h⁴/sub j/.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.290-295
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• 1989

This paper proposes a Expert CAPP System for integrating CAD/CAM of rotational work-part by rule based approach. The CAD/CAPP integration is performed by the recognition of machined features from the 2-D CAD data (IGES) file. Selecting functions of the process planning are performed in modularized rule base by forward chaining inference, and operation sequences are determined by means of heuristic search algorithm. For CAPP/CAM integration, post-processor generates NC code from route sheet file. This system coded in OPS5 and C language on PC/AT, and EMCO CNC lathe interfaced with PC through DNC and RS-232C.

• Transactions of Materials Processing
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• v.10 no.5
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• pp.396-401
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• 2001

The concept of the mixtures can be used not only in the composites but also in the materials with precipitates and matrix. In this investigation, the finite element method of axisymmetric unit cell models and the rule of mixtures of the Voigt and the Reuss models are used to analyze the overall mechanical response of composites with homogeneously distributed particles. The calculations have been cameo out by taking the materials as i) hardening and ii) perfect plastic materials. The Plastic properties are predicted for various volume fractions of the soft and hard particles. The computational results are compared with the results of the rule of mixtures. It is found that the plastic flow curves agree well with the Voigt model when the volume fraction of the particles is high. On the other hand, the calculated flow curves exist between the Voigt model and the Reuss model when the volume fraction of the particles is low.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.113-116
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• 2002

It is required to network to make more intelligent packet processing and forwarding for increasing bandwidth and various services. Classification provides these intelligent to network which is acquired by increasing number of rules in classification rule set. In this Paper, we propose a classification algorithm efficient to scalable rule set ahead as well as Present small rule set. This algorithm has competition to existing methods by performance and advantage that it is mixed with another algorithm because il does not change original shape of rule set.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.905-912
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• 2012

We are dealing with the Bayes' rule education tool with Excel Macro and its usage example. When an event occurs, we are interested in whether it does under certain conditions or not. In this case, we use the Bayes' rule to calculate the probability. Bayes' rule is very useful in making decision based on newly obtained statistical information. We introduce an efficient self-teaching educational tool developed to help the learners understand the Bayes' rule through intermediate steps and descriptions. The concept and examples of intermediate steps such as conditional probability, multiplication rule, law of total probability, prior probability and posterior probability could be acquired through step-by-step learning. All the processes leading to result are given with diagrams and detailed descriptions. By just clicking the execution button, users could get the results in one screen.

• Journal of the Korean Geographical Society
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• v.39 no.4
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• pp.633-642
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• 2004

This study tries to generalize the stream network by constructing rule-based modelling. A study on the map generalization tends to be concentrated on development of algorithms for modification of linear features and evaluations to the limited cartographic elements. Rule-based modelling can help to improve previous algorithms by application of generalization process with the results that analyzing mapping principles and spatial distribution patterns of geographical phenomena. Rule-based modelling can be applied to generalize various cartographic elements, and make an effective on multi-scaling mapping in the digital environments. In this research, nile-based modelling for stream network is composed of generalization rule, algorithm for centerline extraction and linear features. Before generalization, drainage pattern was analyzed by the connectivity with lake to minimize logical errors. As a result, 17 streams with centerline are extracted from 108 double-lined streams. Total length of stream networks is reduced as 17% in 1:25,000 scale, and as 29% in 1:50,000. Simoo algorithm, which is developed to generalize linear features, is compared to Douglas-Peucker(D-P) algorithm. D-P made linear features rough due to the increase of data point distance and widening of external angle. But in Simoo, linear features are smoothed with the decrease of scale.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2299-2308
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• 1997

While most machine learning research has been primarily concerned with the development of systems that implement one type of learning strategy, we use a multistrategy approach which integrates rule induction learning and instance-based learning, and show how this marriage allows for overall better performance. In the rule induction learning phase, we derive an entropy function, based on Hellinger divergence, which can measure the amount of information each inductive rule contains, and show how well the Hellinger divergence measures the importance of each rule. We also propose some heuristics to reduce the computational complexity by analyzing the characteristics of the Hellinger measure. In the instance-based learning phase, we improve the current instance-based learning method in a number of ways. The system has been implemented and tested on a number of well-known machine learning data sets. The performance of the system has been compared with that of other classification learning technique.

• Korean Journal of Child Studies
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• v.21 no.1
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• pp.109-120
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• 2000

The influence of parental perspectives about community life on children's social behavior was studied with dyads of 140 children 3-6 years of age. The children's teachers rated children's behavior on rule-keeping and responsible behavior. Teacher ratings were compared with the 6 sub-factors of parents' perspectives on community life. Father's overall perspectives about community life was correlated with child's responsible behavior but not with rule-keeping behavior. However, father's autonomy and attitude towards community life was correlated to both behaviors. Age and gender differences in children's rule-keeping and responsible behaviors showed that these behaviors increased with age and girls showed more frequent rule-keeping and responsible behaviors than boys.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.129-146
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• 1997

In traditional approaches to scheduling problems, a single dispatching rule was used by all machines in a system. However, since the situation of each machine generally differs from those of other machines, it is reasonable to apply a different dispatching rule to each machine responding to its given situation. In this regard, we introduce the concept of spatial adaptation and examine its effectiveness by simulation. In the spatial adaptation, each machine in a system selects an appropriate dispatching rule in order to improve productivity while it strives to be in harmony with other machines. This study proposes an adaptive procedure which produces a reliable dispatching rule for each machine beginning with the bottleneck machine. The dispatching rule is composed of several criteria of which priorities are adaptively weighted. The weights are learned for each machine through systematic simulations. The simulations are conducted according to a Taguchi experimental design in order to find appropriate sets of criteria weights in an efficient and robust way in the context of environmental variations. The proposed method was evaluated in an application to a semiconductor wafer fabrication system. The method achieved reliable performance compared to traditional dispatching rules, and the performance quickly approached the peak after learning for only a few bottleneck machines.

• Journal of IKEEE
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• v.17 no.3
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• pp.332-338
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• 2013

BPEL is a standard executable language for specifying actions within business processes with Web services. BPEL workflow requires rule engine to describe application process in BPEL, as the requirements increase. It is needed to develop new BPEL's engine or modify BPEL's engine in order to add the functionality of rules to BPEL engines, but this method is not easy to implement and it requires very high cost. In this paper, we present an R4BPEL document, which uses the original BPEL grammar and includes a rule document. With this method, it is possible to build rule-based BPEL environment easily by adding web services with rules and R4BPEL document analyzer to the general-purpose Web services. In this paper, we campared a BPEL's document in proposed system with a BPEL's document in the existing system. And we demonstrated the simplicity of the rule-based system.