• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2455-2475
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• 2021

Patient Navigation Program (PNP) is considered as an important implementation of health care systems that can assist in patient's treatment. Due to the feasibility of PNP implementation, a systematic reuse is needed for a wide adoption of PNP computerized system. SPL is one of the promising systematic reuse approaches for creating a reusable architecture to enabled reuse in several similar applications of PNP systems which has its own variations with other applications. However, stakeholder decision making which result from the imprecise, uncertain, and subjective nature of architecture selection based on quality attributes (QA) further hinders the development of the product line architecture. Therefore, this study aims to propose a quality-driven approach using Multi-Criteria Decision Analysis (MCDA) techniques for Software Product Line Architecture (SPLA) to have an objective selection based on the QA of stakeholders in the domain of PNP. There are two steps proposed to this approach. First, a clear representation of quality is proposed by extending feature model (FM) with QA feature to determine the QA in the early phase of architecture selection. Second, MCDA techniques were applied for architecture selection based on objective preference for certain QA in the domain of PNP. The result of the proposed approach is the implementation of the PNP system with SPLA that had been selected using MCDA techniques. Evaluation for the approach is done by checking the approach's applicability in a case study and stakeholder validation. Evaluation on ease of use and usefulness of the approach with selected stakeholders have shown positive responses. The evaluation results proved that the proposed approach assisted in the implementation of PNP systems.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.742-744
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• 2004

본 논문은 복잡한 배경에서의 얼굴 검출에 있어서 다중 특징 추출 데이터로 학습한 계단식 분류기에 의한 방법을 제안한다 얼굴 검출에서 얼굴의 패턴은 상당히 다양한 영상 표현으로 나타나기 때문에 하나의 특징 추출 방법은 사람의 얼굴을 모델링 하기에는 부족하다. 따라서 여기서는 얼굴의 전체적인 지역적인 특징을 나타내는 Subregion과, 얼굴의 주파수 특성에 따라 좀 더 세밀하고 다양한 속성들을 나타내는 Haar 웨이블릿 변환을 이용하여 다중으로 특징을 추출하여 효과적인 모델링을 시도하였다. 특징을 추출한 얼굴과 비얼굴의 패턴(pattern)을 구분하기 위해서 패턴들의 통계적인 특성을 이용하여 각 추출방법에 맞게 학습된 Bayesian 분류기를 직렬로 연결하여 사용하였으며 비얼굴은 얼굴과 유사한 비얼굴(face-like nonface) 패턴들을 사용하여 모델링 하였다. 제안한 얼굴 검출 방식의 성능은 MIT-CMU 시험 영상들을 이용하여 평가하였다. 그 결과 한 가지 특징 추출을 사용하는 것 보다 두 가지 특징 추출을 병행한 계단식 구성이 더 정확한 검출 결과를 나타내었다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.31-38
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• 2013

The evolution of the Web from Web 1.0 to Web 2.0 has brought up new platforms as SNSs(Social Network Service) that are used by users to articulate and manage their relationships. SNSs are an online phenomenon which has become extremely popular. A SNS essentially consists of a representation of each user, his/her social links, and a variety of additional services. SNSs are increasingly attracting the attention of academic and industry researchers. What makes SNS unique is that they have a relationship with friends. The friend recommendation is one important feature of social networking services. People tend to trust the opinions of friends they know rather than the opinions of strangers. In this paper, we propose an efficient data processing method for social data. We study previous researches about social score in social network service. Our ESS(Efficient Social Score) is computed by both friendship weight and score of a document that was tagged by a user's friends. Our experimental results also confirm that our method has good performance.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.33-36
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• 2000

To create a more realistic soccer game derived from TV images, we are developing an image synthesis system that generates 3D image sequence from TV images. We propose the method for the team and the pose recognition of players in TV images. The representation includes camera calibration method, team recognition method and pose recognition method. To find the location of a player on the field, a field model is constructed and a player's field position is transformed by 4-feature points. To recognize the team information of players, we compute RGB mean values and standard deviations of a player in TV images. Finally, to recognize pose of a player, this system computes the velocity and the ratio of player(height/width). Experimental results are included to evaluate the performance of the team and the pose recognition.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.157-160
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• 2000

This paper proposes a color-based image retrieval method using color adjacency and gradient. In proposed method, both the adjacency of different colors and gradient of a color in homogeneous region are considered as features of an image. The gradient, defined as the maximum distance along the direction with largest change of color, is computed for each pixel to determine whether the center color is similar or different to the neighboring colors. Therefore the problems caused by uniform quantization, which is popularly used at most existing retrieval, can be avoided. And furthermore, the storage of the feature is reduced by the proposed binary representation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.543-546
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• 2003

Representation and quantification of fuzziness are required for the uncertain system modelling and controller design. Conventional results show that entropy of fuzzy sets represent the fuzziness of fuzzy sets. In this literature, the relations of fuzzy enropy, distance measure and similarity measure are discussed, and distance measure is proposed. With the help of relations of fuzzy entropy, distance measure and similarity measure, fuzzy entropy is proposed by the distance measure. Finally, proposed entropy is applied to measure the fault signal of induction machine.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.42-45
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• 2003

This paper describes a new iris recognition method using shift-invariant subbands. First an iris image is preprocessed to compensate the variation of the iris image. Then, the preprocessed iris image is decomposed into multiple subbands using a shift invariant wavelet transform. The best subband among them, which have rich information for various iris pattern and robust to noises, is selected for iris recognition. The quantized pixels of the best subband yield the feature representation. Experimentally, we show that the proposed method produced superb performance in iris recognition.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.836-839
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• 2002

This paper describes the selective Boolean operations on non-manifold geometric models whose union and subtraction operations are communicative. These operations guarantee the same resulting shape in spite of change of the order of Boolean operations, and the integrity of the model for omission of some features. In addition, a B-rep model for a modified modeling history is obtained in a short time, as no boundary evaluation is necessary. These features enable easy implementation of multi-resolution representation of B-rep models.

• English Language & Literature Teaching
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• v.10 no.2
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• pp.67-87
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• 2004

The purpose of this paper is to show how the coda of a syllable and word-final clusters are represented in the English syllable structure. Previous theories on the syllable assume that there is only one segment in the coda position. And, as we know, the theories that license only one segment in the coda make it difficult to syllabicate the word-final cluster appropriately when more than two segments in the word-final cluster are encountered. I considered three approaches: the previous syllable structure (Selkirk, 1982; Borowsky 1989), sonority sequencing (Giegerich, 1992; Roca, 1999) and feature analysis (Goldsmith, 1990), But, all the considered methods don't give us a satisfactory explanation regarding word-final clusters. Finally, I will suggest a modified syllable representation as an alternative by placing two different appendixes under the Phonological Word which forms a constituent above the syllable node. From this it is possible to explain the former problematic word-final clusters including morphological information asan inflectional suffix in the structure.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.290-291
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• 2008

The most popular speech feature used in speech recognition today is the Mel-Frequency Cepstral Coefficients (MFCC) algorithm, which could reflect the perception characteristics of the human ear more accurately than other parameters. This paper adopts MFCC and its first order difference, which could reflect the dynamic character of speech signal, as synthetical parametric representation. Furthermore, we quote Dynamic Time Warping (DTW) algorithm to search match paths in the pattern recognition process. We use the software "GoldWave" to record English digitals in the lab environments and the simulation results indicate the algorithm has higher recognition accuracy than others using LPCC, etc. as character parameters in the experiment for Digital Isolated Word Recognition (DIWR) system.