• 한국정보통신학회논문지
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• 제7권8호
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• pp.1831-1839
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• 2003

본 논문은 능동 네트워크를 동작하게 해주는 핵심 모듈인 Enode 노드 운영체제 구조 및 세부 기능들의 내용을 정의한다. 본 논문에서 제안하는 Enode 노드 운영체제는 능동 네트워크 환경에 적합하도록 설계하였다. 또한 "실행 환경"(Execution Environment : EE)에서 편리하게 사용할 수 있도록 인터페이스를 설계하였다. 본 논문에서 제안하는 Enode 노드 운영체제는 도메인을 중심으로 핵심적인 기능 설계에 주력하였다. Enode 운영체제는 Linux 운영체제 상에서 설계되었다. 또한 본 논문에서 제안하는 Enode 노드 운영체제의 인터페이스에 대한 실험을 수행하였다.

• 한국정밀공학회지
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• 제23권8호
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• pp.89-99
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• 2006

In this paper a new shape reconstruction method that allows us to construct surface models from very large sets of points is presented. In this method the global domain of interest is divided into smaller domains where the problem can be solved locally. These local solutions of subdivided domains are blended together according to weighting coefficients to obtain a global solution using partition of unity function. The suggested approach gives us considerable flexibility in the choice of local shape functions which depend on the local shape complexity and desired accuracy. At each domain, a quadratic polynomial function is created that fits the points in the domain. If the approximation is not accurate enough, other higher order functions including cubic polynomial function and RBF(Radial Basis Function) are used. This adaptive selection of local shape functions offers robust and efficient solution to a great variety of shape reconstruction problems.

• 한국지능시스템학회논문지
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• 제16권6호
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• pp.766-771
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• 2006

In this paper, we focus on the building domain ontology from corpus by extracting concepts and properties relationships based on linguistic patterns. The pharmacy field is selected as an experiment domain and we present an algorithm to extract hierarchical structure for terminology based on the noun/suffix patterns of terminology in domain texts. In order to show usefulness of our domain ontology, we compare a typical keyword based retrieval method with an ontology based retrieval mettled which uses related information in an ontology for a related feedback. As a result, our method shows the improvement of precision by 4.97% without losing recall.

• 한국정밀공학회지
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• 제13권12호
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• pp.63-69
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• 1996

As the significance of quality in the sense of customer satisfaction is growing, the management of quality becomes one of the main interests in the manufacturing systems research. This paper presents the concept of quality-driven CIM(Computer Integrated Manufacturing) system which is composed of a business process domain and a quality domain. In the business process domain, business functions are integrated by conventional design and manufacturing databases on the one hand, and an integrated quality system is interlinked to them via several quality modules on the other hand. Quality information model connects the business process domain with the quality domain where various types of quality data are stored in the form of quality database. This framework helps a manufacturing enterprise to implement the quality-driven CIM system to achieve its final objective "customer satisfaction".ion".uot;.

• 지구물리와물리탐사
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• 제14권3호
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• pp.214-219
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• 2011

본 논문에서는 시간영역에서 분리된 잔여 파동장을 이용하여 주파수영역 파형역산을 수행하였다. 시간영역 잔여 파동장들을 절대값의 크기에 따라 정렬하여 분류하고, 이를 여러 개의 그룹으로 분리하였다. 분리된 잔여 파동장들은 각 그룹별로 목적함수의 경사 방향을 정규화한 후 평균하기 때문에 통상적인 잔여 파동장에서 작은 크기를 가지는 파동장들을 상대적으로 강조하는 효과가 있고, 이는 파형역산 시 심부구조의 이미지 향상에 도움을 준다. 파형역산은 시간영역에서 분리된 잔여 파동장을 이용하여 주파수영역에서 수행되며, 목적함수의 경사방향은 구조보정에서 많이 쓰이는 역전파 기법을 적용하여 계산된다. 본 연구에서 제안한 알고리듬의 타당성을 확인하기 위하여 SEG/EAGE 암염 모델과 Marmousi 모델을 이용하여 파형역산을 수행하였다. 역산 결과를 통해 제안된 알고리즘이 일반적인 주파수영역 파형역산에 비해 심부구조에 대하여 향상된 결과를 제시함을 확인하였다.

• 한국멀티미디어학회논문지
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• 제25권10호
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• pp.1375-1385
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• 2022

In this paper, we propose a semi-supervised domain adaptation solution to deal with practical face recognition (FR) scenarios where a single face image for each target identity (to be recognized) is only available in the training phase. Main goal of the proposed method is to reduce the discrepancy between the target and the source domain face images, which ultimately improves FR performances. The proposed method is based on the Domain Adatation network (DAN) using an MMD loss function to reduce the discrepancy between domains. In order to train more effectively, we develop a novel loss function learning strategy in which MMD loss and cross-entropy loss functions are adopted by using different weights according to the progress of each epoch during the learning. The proposed weight adoptation focuses on the training of the source domain in the initial learning phase to learn facial feature information such as eyes, nose, and mouth. After the initial learning is completed, the resulting feature information is used to training a deep network using the target domain images. To evaluate the effectiveness of the proposed method, FR performances were evaluated with pretrained model trained only with CASIA-webface (source images) and fine-tuned model trained only with FERET's gallery (target images) under the same FR scenarios. The experimental results showed that the proposed semi-supervised domain adaptation can be improved by 24.78% compared to the pre-trained model and 28.42% compared to the fine-tuned model. In addition, the proposed method outperformed other state-of-the-arts domain adaptation approaches by 9.41%.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1640-1641
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• 2007

In this paper, an experiment of weighted robust least squares frequency estimation for the Gaussian envelope chirp signal which is used in the time-frequency domain reflectometry system was carried out. By incorporating the forgetting factor to the frequency estimator, the weighted robust least squares filter achieved good enough frequency estimation performance for the chirp signal and it can be adopted to implement not only low cost time-frequency domain reflectometry but also real-time time-frequency domain reflectometry implementation.

• Journal of Information Processing Systems
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• 제3권2호
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• pp.73-81
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• 2007

In this paper, we introduce a domain-independent classification framework based on both k-nearest neighbor and Naive Bayesian classification algorithms. The architecture of our system is simple and modularized in that each sub-module of the system could be changed or improved efficiently. Moreover, it provides various feature selection mechanisms to be applied to optimize the general-purpose classifiers for a specific domain. As for the enhanced classification performance, our system provides conditional probability boosting (CPB) mechanism which could be used in various domains. In the mood classification domain, our optimized framework using the CPB algorithm showed 1% of improvement in precision and 2% in recall compared with the baseline.

• 한국CDE학회논문집
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• 제11권2호
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• pp.88-96
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• 2006

This paper introduces an approach to ontology-based framework for knowledge management in a product development domain. The participants in a product life cycle want to share the product knowledge without any heterogeneity. However, previous knowledge management systems do not have any conceptual specifications of their knowledge. We suggest the three levels of knowledge framework. First level is an axiom, which specifies the semantics of concepts and relations. Second level is a product development knowledge map. It defines the common domain knowledge which domain experts agree with. Third level is a specialized knowledge for domain, which includes three knowledge types; expert knowledge, engineering function and data-analysis-based knowledge. We propose an ontology-based knowledge framework based on the three levels of knowledge. The framework has a uniform representation; first order logic to increase integrity of the framework. We implement the framework using prolog and test example queries to show the effectiveness of the framework.

• Journal of Advanced Research in Ocean Engineering
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• 제2권2호
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• pp.81-85
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• 2016

Nonlinear wave loads can lead to resonant responses of offshore structures in sum or difference frequencies. In this study, the roll motion of an FPSO with a low natural frequency is simulated in the time domain. To generate the time signals of wave loads, the quadratic transfer functions of the second-order excitations are calculated in the frequency domain. The equations of motions based on the time memory functions are used to evaluate the roll responses in irregular waves. The roll damping in empirical form is accounted for in the simulation.