• 한국영어학회지:영어학
• /
• 제2권2호
• /
• pp.185-205
• /
• 2002

Within the framework of Generalized Sympathy (GS) (Jun 1999), this paper investigates the reasons why phonological rules such as Cluster Simplification, Closed Syllable ${\ae}$-Tensing, and Belfast Dentalization overapply or underapply in Class 2 affixed words in English. According to GS, a morphologically independent word can be treated as a derived word in that it is assumed to have any possible outputs as bases to resemble. As a result, a correspondence relation is triggered between a morphologically independent word being represented as Derived (D) and any possible outputs represented as Base (B), i.e., BD-Faith. In analyses of affixed words, BA-Faith is evoked, instead of BD-Faith. Furthermore, as Benua (1997) suggests, BA-Faith is classified into two correspondence relations; $BA_1$-Faith between Base and Class 1 affixed words, and $BA_2$-Faith between Base and Class 2 affixed words. When the $BA_1$-Faith takes precedence over phonological constraints three rules misapply in Class 2 affixed words. In other words, the misapplications are driven by base-identity effects.

• 산업경영시스템학회지
• /
• 제41권2호
• /
• pp.56-64
• /
• 2018

In recent years, imbalanced data is one of the most important and frequent issue for quality control in industrial field. As an example, defect rate has been drastically reduced thanks to highly developed technology and quality management, so that only few defective data can be obtained from production process. Therefore, quality classification should be performed under the condition that one class (defective dataset) is even smaller than the other class (good dataset). However, traditional multi-class classification methods are not appropriate to deal with such an imbalanced dataset, since they classify data from the difference between one class and the others that can hardly be found in imbalanced datasets. Thus, one-class classification that thoroughly learns patterns of target class is more suitable for imbalanced dataset since it only focuses on data in a target class. So far, several one-class classification methods such as one-class support vector machine, neural network and decision tree there have been suggested. One-class support vector machine and neural network can guarantee good classification rate, and decision tree can provide a set of rules that can be clearly interpreted. However, the classifiers obtained from the former two methods consist of complex mathematical functions and cannot be easily understood by users. In case of decision tree, the criterion for rule generation is ambiguous. Therefore, as an alternative, a new one-class classifier using hyper-rectangles was proposed, which performs precise classification compared to other methods and generates rules clearly understood by users as well. In this paper, we suggest an approach for improving the limitations of those previous one-class classification algorithms. Specifically, the suggested approach produces more improved one-class classifier using hyper-rectangles generated by using Gaussian function. The performance of the suggested algorithm is verified by a numerical experiment, which uses several datasets in UCI machine learning repository.

• 한국압력기기공학회 논문집
• /
• 제18권2호
• /
• pp.54-60
• /
• 2022

ASME BPVC provides stress evaluation rules for Class 2 and 3 nuclear piping. However, such rules are difficult to be applied to reinforced wall-thinned pipes during service. To resolve this issue, a new method for stress evaluation of reinforced wall-thinned pipes is proposed in this work, based on the equivalent stiffness concept. By converting a reinforced wall-thinned pipe to an equivalent straight pipe having the same stiffness, stress evaluation can be proceeded using the current ASME BPVC rules. The proposed method is applied to pipes with 4 different normal pipe size and the effects of reinforcement and wall-thinning dimensions on evaluated stresses are discussed.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
• /
• pp.376-379
• /
• 2003

In this paper we describe DCClass, a tool for fuzzy information granulation with transparency constraints. The tool is particularly suited to solve fuzzy classification problems, since it is able to automatically extract information granules with class labels. For transparency pursuits, the resulting information granules are represented in form of fuzzy Cartesian product of one-dimensional fuzzy sets. As a key feature, the proposed tool is capable to self-determining the optimal granularity level of each one-dimensional fuzzy set by exploiting class information. The resulting fun information granules can be directly translated in human-comprehensible fuzzy rules to be used for class inference. The paper reports preliminary experimental results on a medical diagnosis problem that shows the utility of the proposed tool.

• 한국정보전자통신기술학회논문지
• /
• 제4권3호
• /
• pp.217-224
• /
• 2011

본 논문에서는 동적 데이터베이스 환경에서 발생할 수 있는 개인 정보 노출 문제를 해결할 수 있는 동적 데이터 보호 기법(Dynamic Data Protection Technique)을 제안하였다. 본 논문에서 제안한 DDPT은 다중 속성 일반화 알고리즘을 이용해 MAG(Multi-Attribute Generalization) 규칙을 생성하고, 그 MAG 규칙에 따라 k-anonymity를 만족하는 EC(Equivalence Class)를 생성한다. 그리고 데이터 변경 시 MAG 규칙에 따라 EC를 재구성 하도록 하여, EC의 변경으로 인한 식별 노출을 방지할 수 있다. 또한, ${\ell}$-diversity를 만족하는 EC의 정보손실 정도를 측정하고, 임계치 이하의 EC를 선정해서 데이터의 정확성을 유지함으로써 개인 정보 보호를 향상시켰다.

• 한국중재학회지:중재연구
• /
• 제22권2호
• /
• pp.159-176
• /
• 2012

The Korean Commercial Arbitration Board (KCAB) recently revised its International Arbitration Rules in a way that reflects its efforts to advance its procedures, leading directly to improved competitiveness as an arbitration institute. Apart from certain limitations, the KCAB's international arbitration rule revision introduced several new arbitration mechanisms, including fast-track arbitration and an empowered administrative office. The International Chamber of Commerce (ICC) released a revised set of arbitration rules (ICC Arbitration Rules), which have been said to be probably the most consulted-on arbitration rules ever. Even though the changes codify existing ICC court practice and add to the 1998 rules only provisions felt necessary in light of input from the users of arbitration, some of the changes will have huge implications for future aspects of arbitration mechanisms, especially those of KCAB. Although it remains to be seen what impact the ICC Arbitration Rules will have in practice, the new rules have been well received by the arbitration community and represent a modern set of provisions consistent with the current needs of the users of international arbitration. That is why, here in the Korean arbitration environment, further research is needed on the possibilities of introducing several elements of the revised ICC Arbitration Rules to improve the speed and cost efficiency of international arbitration.

• 대한음성학회지:말소리
• /
• 제21_24호
• /
• pp.144-175
• /
• 1992

This paper aims to discuss determining factors of Korean allophones and to formulate and classify Korean allophonic rules systematically. The relationship between allophones and coarticulation, the most. influential factor of allophonic variation, is thoroughly investigated. Other factors -- speech tempo and style, dialect, and social factors such as age, set, class etc. -- are also briefly discussed. Allophonic rules are classified into two groups -- 3) those relevant to coarticulation and 2) those irrelevant to coarticulation. Rules of the first group are further classified into four subgroups according to the directionality of the coarticulation. Each allophonic nile formulation is explained and discussed in detai1. The allophonic rules formulated and classified in this paper are 1) Devoicing of Voiced Consonants, 2) Devoicing of Vowels, 3) Nasal Approach and Lateral Approach, 4) Uvularization, 5) Palatalization, 6) Voicing of Voiceless Lax Consonants, 7) Frication, 8) Labialization, 9) Nasalization, 10) Release Withholding and Release Masking, 11) Glottalization, 12) Flap Rule, 13) Vowel Weakening, and 14) Allophones of /ㅚ, ㅟ, ㅢ/ (which are realized as diphthongs or as monophthongs depending on phonetic contexts).

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2008년도 하계종합학술대회
• /
• pp.20-21
• /
• 2008

In the IEEE 802.16 Wireless MAN standard, the best effort service class is ranked on the lowest position in priority so that only scarce resource may be available for it. Also, the best effort service is usually assisted by a MAC scheme based on reservation ALOHA without explicit acknowledgement. However, the standard only specifies the skeleton of the MAC scheme. In this paper, we propose some rules to specify the indefinite part of the MAC scheme as well as to improve the throughput and delay performance of the MAC scheme. As generic rules for demanding and granting resource, we first propose non-gated exhaustive, gated exhaustive, non-gated limited, and gated limited demand rules, and deficient and full grant rules. Secondly, we propose grant regulation rules, identified as replacement and lifetime rules, to avoid excessive grant incurred by not giving acknowledgement. Noting the residual resource is inflated by adopting a grant regulation rule, we finally propose a rule for investing the residual resource to a subscriber station. Simulation results confirm that a combination of proposed rules improves the performance of the MAC scheme.

• 응용통계연구
• /
• 제10권2호
• /
• pp.261-274
• /
• 1997

기존에 제안되어온 판별분석 기법이 대상으로 하는 대부분의 자료는 각 개체가 어느 한 특정한 집단에 전적으로 소속되어 있는 것으로 국한되어 왔다. 그러나 오늘날 (0-1)의 이치논리가 퍼지(Fuzzy) 개념과 다치논리로 확장되는 현상은 어느 한 개체를 꼭 한개의 집단에만 국한시키는 관점 역시 변화를 요구하고 있다고 본다. 이에 본 논문에서는 한 개체가 어떤 소속확률을 갖고 여러개의 집단에 소속되어 있는 상황을 고려하여 이러한 개체들로 구성된 학습표본으로부터 판별분석 규칙을 개발하는 것을 목표로 하였다. 방법론으로는 개체들의 특성벡터와 소속상태의 관계를 역추정(calibration) 모형으로 표현하고 판별대상개체의 특성벡터가 주어졌을 때 소속상태를 추정하도록 하며 이때 추정은 베이지안 방법, Metropolis 알고리즘 등을 사용하였다. 또한 제안된 판별규칙의 평가를 위한 기준을 제안하고 두개의 자료를 기존의 다른 규칙들과 함께 분석하여 결과를 비교하였다.

• 한국멀티미디어학회논문지
• /
• 제22권3호
• /
• pp.386-394
• /
• 2019

This research will describe algorithm for class diagram extraction from problem statements. Class diagram notation consist of class name, attributes, and operations. Class diagram can be extracted from the problem statement automatically by using Natural Language Processing (NLP). The extraction results heavily depends on the algorithm and preprocessing stage. The algorithm obtained from various sources with additional rules that are obtained in the implementation phase. The evaluation features using five problem statement with different domains. The application will capture the problem statement and draw the class diagram automatically by using Windows Presentation Foundation(WPF). The classification accuracy of 100% was achieved. The final algorithm achieved 92 % of average precision score.