• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1347-1348
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• 2015

본 논문에서는 기상레이더 데이터에서 섞여있는 강수에코 및 비강수에코를 분류하기 위하여 Interval Type-2 FCM based RBFNN의 도움으로 사례 및 에코 분류기의 설계를 제안한다. 학습과 테스트 데이터는 현재 기상청에서 사용하는 UF radar data를 사용하였으며, 사례 분류기와 에코패턴 분류기의 데이터를 각각 생성한다. 전처리 과정인 사례 분류를 통하여 강수사례 혹은 비강수사례를 분류하여 강수사례일 경우 에코패턴분류를 진행하며, 비강수사례일 경우 데이터에 관측된 모든 반사도 값을 제거한다. 사례 및 에코 분류기는 Interval Type-2 FCM based RBFNN을 통하여 패턴분류를 진행하며, 패턴분류 성능을 확인한다. 또한 후반부 파라미터의 동정 시, 각 규칙에 파라미터를 전역적으로 구하는 LSE와 각 규칙에 대한 파라미터를 독립적으로 구하는 WSLE의 비교연구를 수행한다. 분류기의 성능을 확인하기 위하여 사례 분류 후 에코패턴분류의 결과는 현재 기상청에서 사용하고는 품질검사(QC) 데이터와 비교하여 평가하였다.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.75
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• pp.71-94
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• 2017

The Rotterdam Rules is the first international maritime carriage of goods Convention that acknowledge electronic records of contracts of carriage. The Rules have developed separate chapter in relation to electronic transport records' issuing, transfer, etc. This paper aims to evaluate Rotterdam Rules' contribution to the use of electronic transport records. To achieve the aims firstly this paper have examined the related articles of Rotterdam Rules, Secondly in practical aspects, this paper explores the opportunities and obstacles which could be happened in practical procedures, applicable to transport industry, shipper and holder of electronic transport records. Findings could be summarized as follows, first the Rules shows high acceptability to whom it may involved in transport industry by simplify the contents of the Rules to avoid conflict with each countries' national laws. The Rules acknowledge the functional equivalence between paper and electronic transport records in specific provisions. This could be important development to facilitate the use of electronic transport records. But the Rules have not mentioned liability limit of transport industry when the problems arise from issuing, tele-transmission, transfer of the records. And the secure of the functional equivalence between paper and electronic transport records also could be remained in uncertain regime due to different stance of each national laws.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.614-621
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• 2006

We have implemented a multiclassifier learning approach in a GA-based inductive learning environment that learns classification rules that are similar to rules used in PROSPECTOR. In the multiclassifier learning approach, a classification system is constructed with several classifiers that are obtained by running a GA-based learning system several times to improve the overall performance of a classification system. To implement the multiclassifier learning approach, we need a decision-making scheme that can draw a decision using multiple classifiers. In this paper, we introduce two decision-making schemes: one is based on combining posterior odds given by classifiers to each class and the other one is a voting scheme based on ranking assigned to each class by classifiers. We also present empirical results that evaluate the effect of the multiclassifier learning approach on the GA-based inductive teaming environment.

• Journal of the Korean Society for information Management
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• v.14 no.2
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• pp.213-234
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• 1997

A stemming algorithm for the Korean language free-text retrieval system has been designed and implemented. The algorithm contains three major parts and it operates iteratively ; firstly, stop-words are removed with a use of a stop-word list ; secondly, a basic removing procedure proceeds with a rule table 1, which contains the suffixes, the postpositional particles, and the optionally adopted symbols specifying an each stemming action ; thirdly, an extended stemming and rewriting procedures continue with a rule table 2, which are composed of th suffixes and the optionally combined symbols representing various actions depending upon the context-sensitive rules. A test was carried out to obtain an indication of how successful the algorithm was and to identify any minor changes in the algorithm for an enhanced one. As a result of it, 21.4 % compression is achieved and an error rate is 15.9%.

• International Journal of Highway Engineering
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• v.14 no.2
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• pp.157-164
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• 2012

Road signs serve guide informations for efficient traffic control and are regulated by Road Sign Regulation. But few road managers break the regulation because of civil complaint and cause driver's confusion. Also, as promote the road name guide signs and the new road signs on expressway, the driver's confusion being increased. This study analysis factors of driver's confusion, calculates limited information on road signs and specifies modes of driver's confusion caused by road signs. The traffic accident data during 3 years is calculated in order to see how much intimate connection between the road sign confusion and the traffic.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.163-173
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• 2004

Recently, location-based services are becoming very Popular in mobile environments. In this paper, we propose a new association based prefetch algorithm (called by STAP) that efficiently supports information service based on the large quantity of spatial database in mobile environments. We apply the spatial-temporal relations that are meaningful for location-based queries in mobile environments. Moreover, STAP considers user's mobility and the weight of spatial data. The relation of services is a new aspect not considered in previous cache politics. So STAP is the first prefetch algorithm considering the spatial-temporal relations and thus the cache policy begins to gain a new dimension. We evaluate the performance of STAP and prove the efficiency of STAP.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2597-2607
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• 1999

In this paper, we propose an efficient large item generation algorithm that overcomes the problem of the existing algorithm for making large items from quantitative attributes. The proposed algorithm splits dataset into variable size of intervals by min_split_support and merges the intervals according to the support of each interval. It reflects characteristic of data to generated large items and can generate finer large items than the existing algorithm. It is shown through the performance evaluation that our proposed algorithm outperforms the existing algorithm.

• Korean Journal of Logic
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• v.14 no.3
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• pp.27-59
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• 2011

This paper concerns several versions of conditionalization. In particular, I will examine the relationship between Jeffrey conditionalization and the second order conditionalization concerning updating higher order credences. In section 2, I suggest explicitly what Jeffrey conditionalization and the second order conditionalization are. I will argue in section 3 that Jeffrey conditionalization conflicts with van Fraassen's Reflection Principle while the second order conditionalization doesn't. And I will also argue in section 4 that under some situations, Jeffrey conditionalization may lead agents to Moorean absurdity while the second conditionalization may not. As a result, I will claim that Jeffrey conditionalization is better than the second order contionalization at updating our higher order credences.

• Journal of Advanced Navigation Technology
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• v.10 no.3
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• pp.219-225
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• 2006

This paper presents a method of object classification based on discrete wavelet transform (DWT) and fuzzy inference(FI). It concentrated not only on the design of fuzzy inference algorithm which is suitable for low speed uninhabited transportation such as, conveyor but also on the minimize the number of fuzzy rule. In the preprocess of feature extracting, feature parameters are extracted by using characteristics of the coefficients matrix of DWT. Such feature parameters as area, perimeter and a/p ratio are used obtained from DWT coefficients blocks. Secondly, fuzzy if - then rules that can be able to adapt the variety of surroundings are developed. In order to verify the performance of proposed scheme, In the middle of fuzzy inference, the Mamdani's and the Larsen 's implication operators are utilized. Experimental results showed that proposed scheme can be applied to the variety of surroundings.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.9-19
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• 2004

The selection of comparative standard parcels should be objective and reasonable, which is an important task in the individual land price appraisal procedure. However, the current procedure is mainly done manually by government officials. Therefore, the efficiency and objectiveness of this selection procedure is not guaranteed and questionable. In this study, we first defined the problem by analyzing the current comparative standard land parcel selection method. In addition, we devised a decision tree-based method using a machine learning algorithm that is considered to be efficient and objective compared to the current selection procedure. Finally the proposed method is then applied to the study area for evaluating the appropriateness and accuracy.