• 인터넷정보학회논문지
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• 제3권3호
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• pp.39-53
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• 2002

도메인 모델은 객체 모델 개발과 소프트웨어 설계에 관한 결정에 큰 영향을 끼치고 있어, 오늘날 많은 객체 지향적 시스템과 컴포넌트 기반의 소프트웨어 개발 시 도메인 모델을 만들고 있다. 그러나 UML과 객체 지향적 방법론에서는 재사용을 위한 개발과 재사용을 수반한 개발의 지원이 부족하여 매번 새로이 모델을 개발하고 있으며 프로젝트 개발 기간 지연과 불충분한 모델 생성을 초래하고있다. 이러한 문제는 UML 표기의 확장과 재사용 처리방법을 통해 해결될 수 있다. 본 연구에서는 도메인 모델의 재사용을 위하여 UML 기반의 도메인 모델 템플리트를 설계하고 분석정보의 재사용을 위한 도메인 모델 개발 방법을 제안하였다. 아울러 제안된 표현을 인터넷 응용에 적용하여 도메인 모델과 도메인 템플리트를 생성할 수 있었다.

• ETRI Journal
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• 제33권5호
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• pp.712-719
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• 2011

In this paper, we study the problem of domain adaptation for structural support vector machines (SVMs). We consider a number of domain adaptation approaches for structural SVMs and evaluate them on named entity recognition, part-of-speech tagging, and sentiment classification problems. Finally, we show that a prior model for structural SVMs outperforms other domain adaptation approaches in most cases. Moreover, the training time for this prior model is reduced compared to other domain adaptation methods with improvements in performance.

• Journal of Information Processing Systems
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• 제9권2호
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• pp.259-270
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• 2013

A speaker's intentions can be represented by domain actions (domain-independent speech act and domain-dependent concept sequence pairs). Therefore, it is essential that domain actions be determined when implementing dialogue systems because a dialogue system should determine users' intentions from their utterances and should create counterpart intentions to the users' intentions. In this paper, a neural network model is proposed for classifying a user's domain actions and planning a system's domain actions. An integrated neural network model is proposed for simultaneously determining user and system domain actions using the same framework. The proposed model performed better than previous non-integrated models in an experiment using a goal-oriented dialogue corpus. This result shows that the proposed integration method contributes to improving domain action determination performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.914-934
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• 2016

In the mobile distributed environment, an entity may move across domains with great frequency. How to utilize the trust information in the previous domains and quickly establish trust relationships with others in the current domain remains a challenging issue. The classic trust models do not support cross-domain and the existing cross-domain trust models are not in a fully distributed way. This paper improves the outstanding Certified Reputation (CR) model and proposes a Lightweight Cross-domain Trust (LCT) model for the mobile distributed environment in a fully distributed way. The trust certifications, in which the trust ratings contain various trust aspects with different interest preference weights, are collected and provided by the trustees. Furthermore, three factors are comprehensively considered to ease the issue of collusion attacks and make the trust certifications more accurate. Finally, a cross-domain scenario is deployed and implemented, and the comprehensive experiments and analysis are conducted. The results demonstrate that our LCT model obviously outperforms the Bayesian Network (BN) model and the CR model in our cross-domain scenario, and significantly improves the successful interaction rates of the honest entities without increasing the risks of interacting with the malicious entities.

• 한국음향학회지
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• 제15권1호
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• pp.23-33
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• 1996

본 논문에서는 bispectra를 위한 고전적 주영역 (classical principal domain)이 2계 Volterra 모델의 출력을 결정짓는데 사용되면 그 출력은 완전하지 못하게 될 것임을 지적한다. 이러한 불완전함은 DFT의 주기적 특성과 관련이 있다. 이런 이유로, 본 논문의 목적은 비선형 시스템의 응답의 추정을 향상기키는 Volterra 커널을 위한 확장된 주영역 (extended principal domain)을 제안하는데 있다. 확장된 주영역을 정의 내리기 위하여, 2차원 DFT와 Volterra 모델의 2계 요소와 정사각형 필터와의 관계를 사용하여 이산 시간 영역 Volterra 모델에서 새로운 이산 주파수 영역의 Volterra 모델을 유도하였다. 확장된 영역이 모델의 출력에 미치는 영향을 DFT의 주기성 측면에서 해석을 하였다. 컴퓨터 모의 실험을 통하여, Volterra 모델링에서 확장된 주영역의 영향을 살펴보았다. 모의 실험 결과에 의하면, Volterra 모델의 출력을 계산하는 과정과 Volterra 모델의 계수를 추정하는데 있어서 매우 중요한 역할을 함을 알 수 있었다.

• 대한임베디드공학회논문지
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• 제19권2호
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• pp.73-81
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• 2024

Recently, mobile manipulators have been utilized in agriculture industry for weed removal and harvest automation. This paper proposes a domain adaptive fruit detection method for harvest automation, by utilizing OWL-ViT model which is an open-vocabulary object detection model. The vision-language model can detect objects based on text prompt, and therefore, it can be extended to detect objects of undefined categories. In the development of deep learning models for real-world problems, constructing a large-scale labeled dataset is a time-consuming task and heavily relies on human effort. To reduce the labor-intensive workload, we utilized a large-scale public dataset as a source domain data and employed a domain adaptation method. Adversarial learning was conducted between a domain discriminator and feature extractor to reduce the gap between the distribution of feature vectors from the source domain and our target domain data. We collected a target domain dataset in a real-like environment and conducted experiments to demonstrate the effectiveness of the proposed method. In experiments, the domain adaptation method improved the AP50 metric from 38.88% to 78.59% for detecting objects within the range of 2m, and we achieved 81.7% of manipulation success rate.

• 한국초등과학교육학회지:초등과학교육
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• 제24권1호
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• pp.86-101
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• 2005

In this study, a brain-basrd model for science teaching and learning was developed based on the natural processes which human acquire knowledge about a natural object or on event, the major domains of science educational objectives of the national curriculum, and the human brain's organizational patterns and functions. In the model, each educational objective domain is related to the brain regions as follows: The affective domain is related to the limbic system, especially amygdala of human brain which is involved in emotions, the psychomotor domain is related to the occipital lobes of human brain which perform visual processing, temporal lobes which perform functions of language generating and understandng, and parietal lobes which receive and process sensory information and execute motor activities of body, and the cognitive domain is related to the frontal and prefrontal lobes which are involved in think-ing, planning, judging, and problem solving. The model is a kind of procedural model which proceed fiom affective domain to psychomotor domain, and to cognitive domain of science educational objective system, and emphasize the order of each step and authentic assessment at each step. The model has both properties of circularity and network of activities. At classrooms, the model can be used as various forms according to subjects and student characteristics. STS themes can be appropriately covered by the model.

• 터널과지하공간
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• 제15권5호
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• pp.352-358
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• 2005

콘크리트 비파괴 검사를 위하여 배면공동모형과 교량공동모형에 대하여 시간영역 탐사와 주파수영역 탐사를 실시하였다. 시간영역 탐사는 초동주시 역산법을 이용하여 토모그래피를 작성하여 공동의 여부를 해석하였다. 주파수영역 탐사는 시간영역 기록을 푸리에 변환에 의한 주파수영역에서의 최대 주파수를 분석하여 해석하였다.

• 한국영재학회:학술대회논문집
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• 한국영재학회 2005년도 춘계학술대회
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• pp.173-180
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• 2005

The purpose of this study was to identify common and domain-specific cognitive characteristics of gifted students based on a hierarchical structural model of human abilities. This study is based on the premise that abilities identified by tests can appear as observable characteristics in test or school situations. Abilities proposed by major models of intelligence were reviewed in terms of their power to explain cognitive characteristics of gifted students. However, due to the lack of their explanatory power and disagreement on common and domain-specific cognitive abilities, a new hierarchical structural model was conceptualized in a unique way based on interrelationships between abilities proposed by the models. The newly established model hypothesizes a cognitive mechanism that accounts for how domain-specific knowledge is formed, as well as which abilities are common and domain-specific, how they are related functionally, and how they account for common and domain-specific cognitive characteristics of gifted students. The cognitive mechanism has important implications for our understanding of the chronically controversial concepts, 'intelligence' and 'knowledge.' Clearer definitions of what intelligence is (g or multiple), what knowledge is, and how knowledge develops ('genetic or environmental,' 'rationalistic or empiricist') may result from this model.

• 대한기계학회논문집A
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• 제22권2호
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• pp.458-466
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• 1998

In this work, a frequency domain method is tested numerically and experimentally to improve nonlinear model parameters using the frequency response function at the nonlinear element connected point of structure. This method extends the force-state mapping technique, which fits the nonlinear element forces with time domain response data, into frequency domain manipulations. The force-state mapping method in the time domain has limitations when applying to complex real structures because it needd a time domain lumped parameter model. On the other hand, the frequency domain method is relatively easily applicable to a complex real structure having nonlinear elements since it uses the frequency response function of each substurcture. Since this mehtod is performed in frequency domain, the number of equations required to identify the unknown parameters can be easily increased as many as it needed, just by not only varying excitation amplitude bot also selecting excitation frequency domain method has some advantages over the classical force-state mapping technique in the number of data points needed in curve fit and the sensitivity to response noise.