• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.3
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• pp.374-383
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• 1998

Apparel Quality was one of the most important elements to evaluate the reputations of companies and products which affect the consumer's purchasing behavior. From researches on apparel quality, there was no common concept of quality as well as no common dimensions. The purposes of this study were to identify apparel quality concept and to classify the multi-dimensional concept of apparel quality. The research was carried out in theoretical as well as empirical studies. The theoretical study was conducted to find out apparel quality concept and divide apparel quality concept into four dimensions groups. The empirical study followed the theoretical study to confirm the multi-dimensional concept of apparel quality. The empirical study was investigated that the questionnaire was administered to 634 housewives in Seoul, Kwangju, and Busan during the fall of 1996. The data were analysed by LISREL analysis. This study identified that apparel quality was characteristics of consumer's desires for apparel. The results of the theoretical study verified that apparel quality concept was organized into four different dimensions: physical attribute, physical function, instrumental performance, and expressive performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.335-342
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• 2020

ESS(Environmental Stress Screening) is an important production process to remove 'latent defects' introduced in the production of products. Recently, ESS is included in QAR(Quality Assurance Report) as an essential quality assurance requirement for products in the defense business. However, depending on the author of the QAR or the classification of the weapon system, it is often identified that the content and form are different or important elements are omitted. Therefore, this paper proposes a MIL-HDBK-344A based quantitative ESS requirement standard to secure the consistency and completeness of QAR. and to make easier to calculate PE(Precipitation Efficiency), which is an indicator for identifying the latent defects elimination effect.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.10-13
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• 2016

정부는 K-ICT 클라우드 활성화를 위해 정부 3.0 클라우드 추진 계획을 발표하고 관련 제도와 법률을 제정하여 클라우드 서비스 도입을 위한 정책을 추진하고 있다. 그러나 공공 분야의 클라우드 컴퓨팅 도입은 기존의 법률, 제도, 관행의 통제로 인해 미미한 실정이다. 공공 기관의 클라우드 컴퓨팅 도입 활성화를 위해 중요한 부분은 클라우드 컴퓨팅의 성능과 품질 등에 대한 특성을 파악하는 것이다. 클라우드 컴퓨팅의 특성을 알아야만 적격의 클라우드 컴퓨팅 사업자 선정이 가능하게 된다. 유럽 연합(European Commission)에서는 클라우드 컴퓨팅의 특성을 서비스 성능과 품질에 대한 일반특성, 기술성, 경제성으로 분류하고 있다. 그러나 클라우드 도입을 위한 설계 시 공공 기관 담당자는 클라우드 특성의 각 부문별 하위 항목에 대한 상세한 내용과 수준까지 객관적으로 평가하기 어렵다. 이러한 문제를 해결하고자 본 연구는 클라우드 컴퓨팅의 성능과 품질 및 기술 특성을 파악하여 각 특성에 대한 가중치를 구하고 우선순위 측정을 통해 사업자 선정을 위한 평가 기준으로 적용하는 기법을 제안한다.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.149-156
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• 2015

In this paper, we propose a Korean sentence symbol preprocessor for a SSML (speech synthesis markup language) supported speech synthesis system in order to improve the quality of the synthesized result. After the analysis of Korean Wikipedia documents, we propose 8 categories for the meaning of sentence symbols and 11 regular expression for the classification of each category. After the development of a Korean sentence symbol preprocess system we archived 56% of precision and 71.45% of recall ratio for 63,000 sentences.

• Korean Journal of Optics and Photonics
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• v.32 no.3
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• pp.114-119
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• 2021

A large-area graphene sheet has been successfully grown on a copper-foil substrate by chemical vapor deposition (CVD) for industrial use. To screen out unsatisfactory graphene films as quickly as possible, noninvasive optical characterization in reflection geometry is necessary. Based on the optical conductivity of graphene, developed by the single-electron tight-binding method, we have investigated the optical-reflectance contrast. Depending on the four independent control parameters of layer number, chemical potential, hopping energy, and temperature, the optical-reflectance contrast can change dramatically enough to reveal the quality of the grown graphene sheet.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.360-364
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• 2007

Interoperability between heterogeneous domains is a very important point considered in the field of scholarly information service as well information standardization. In case of the large information system, interoperability between internal information resources becomes to affect the performance of the whole system. The automatic method for understanding heterogeneous system environment will be very helpful to solve the problems like this. This paper shows that automatic method for interoperability between heterogeneous scholarly classification code structures will be effective in enhancing the information service system.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.280-283
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• 2011

인터넷 환경에서 무차별적으로 유통되는 스팸 문서로 인한 사회적 문제가 커져 가고 있는 가운데 스팸문서를 차단하기 위한 활발한 연구들이 이루어지고 있다. 이 가운데 대표적인 연구는 자질어를 이용한 기계학습 기반의 스팸 차단 기술이다. 그러나 이 방법은 미리 선택된 자질어로만 구성된 분류 모델을 사용하기 때문에 Term Spamming(단어 조작에 의한 스팸 차단 행위)에 취약하며, 스팸 차단의 성능과 학습 소요 시간이 선택된 자질어의 품질과 수에 민감하게 영향을 받는다는 문제점이 있다. 본 논문에서는 이러한 문제를 해결하기 위해 스팸 문서에서 등장하는 특수 문자의 빈도와 반복되는 단어의 특징을 이용한 스팸 탐지 방법을 제안한다. 제안 방법은 각 문서에서 등장하는 특수 문자의 비율과 최다 출현 단어의 반복 패턴을 정의하고 기계학습 알고리즘을 적용하여 스팸 분류 모델을 생성한다. 제안 방법의 성능 평가를 위해 E-mail 데이터와 블로그의 Post 데이터를 사용하여 자질어 기반의 스팸 차단 방법과 비교 실험을 진행하였다. 실험 결과 본 논문에서 제안하는 방법이 분류 정확도와 학습 소요 시간에 있어 우수한 성능을 보이는 것을 확인하였다.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.1-8
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• 2015

Security has become an issue due to the rapid increases in internet traffic data network. Especially P2P traffic data poses a great challenge to network systems administrators. Preemptive measures are necessary for network quality of service(QoS) and efficient resource management like blocking suspicious traffic data. Deep packet inspection(DPI) is the most exact way to detect an intrusion but it may pose a private security problem that requires time. We used several machine learning methods to compare the performance in classifying network traffic data accurately over time. The Random Forest method shows an excellent performance in both accuracy and time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.442-444
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• 2019

Fabric defect classification is an important issue in fabric quality control. However, automated classification is difficult because it is hard to identify various types of defects in images. classification of fabric defects mostly rely on human ability. In this paper, to solve this problem we apply Convolutional Neural Networks (CNN) for fabric defect classification. To make training CNN easier, we propose a method that is manually attentive defect regions in images. we compare the proposed method with the original image and confirm that the proposed method is effective for learning.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.1-7
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• 2015

Many people are interesting software quality. Because of, we depend on software in our life. In terms of, I think, good software is a good quality software. So, when we develop the software, we need trying to improve software quality. In this paper, we analyze software test data. We emphasize that software quality is very important in our life. We use software experimental data, in order to analyze of software quality. On the basis of ISO/IEC 9126-2, we classify the test data and we analyze the difference of error frequency according to functionality, reliability, usability, efficiency, maintainability, portability. We analyze the number of test and used time according software type. We want to search effect variable, going through testing result and measurement convergence, we know the effect variable of functionality and efficiency.