• 한국신뢰성학회지:신뢰성응용연구
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• 제1권2호
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• pp.149-163
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• 2001

We study the normality of the maximum partial likelihood estimators for the proportional hazard model with informative censored data. The proposed models cover the cases in which the times to a primary event may be informatively or randomly censored and the times to a secondary event may be randomly censored. To estimate the parameters and to check the normality of the parameters in the model, we adopt the partial likelihood and counting process to use the martingale central limit theorem. Simulation studies are performed to examine the normality of the MPLE's for the five cases in which they depend upon the proportions of randomly censored and informative censored data.

• 이베로아메리카
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• 제14권2호
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• pp.119-145
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• 2012

This paper deals with the study of how the 'birth' of Brazil happened and how the European utopianism was represented in Brazilian Informative Literature of the sixteenth century, that is, the first literary manifestations of Brazil. There were at that time the Renaissance humanism and the scientific development that encouraged dozens of illustrious navigators for new discoveries ultra-seas, like Christopher Columbus who discovered America. Writings such as Letter to King Manuel of Pero Vaz de Caminha, had mostly an intention to inform Europeans about climates, indians and possibility to discover gold or silver. Main narrative characteristics were uncertainty and exageration, which ironically helped to attract more discoveries and explorations in the New World. Americo Vespucio's Mundus Novus inspired Thomas More to write Utopia, in which the author described through a Portuguese sailor the ideal but unrealizable society. Utopianism regarding the imaginary island of 'Brazi', well known among Europeans since long ago, may have influenced the current name of the country: 'Brazil'. On the other hand, utopianism shown in Brazilian Informative Literature worked as a justification for Europeans to explore and colonize the New World.

• 광고학연구
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• 제25권5호
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• pp.7-42
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• 2014

본 연구는 정보원의 사회적 거리감(social distance)에 따른 기업 페이스북 페이지에서의 광고 효과, 즉 메시지 태도와 온라인 구전의도(e-WOM)를 알아보았다. 또한, 사회적 거리감의 주 효과에 영향을 미치는 메시지의 노골적 설득 의도, 규범적 대인민감성(normative interpersonal influences), 정보적 대인민감성(informative interpersonal influences)의 조절 효과를 검증하고자 했다. 이를 위해 2(사회적 거리감 원/근)${\times}2$(메시지의 노골적 설득 의도 고/저)${\times}2$(규범적 대인민감성 고/저)${\times}2$(정보적 대인민감성 고/저)의 요인 설계를 하였다. 연구 결과, 사회적 거리감이 가까운 경우가 먼 경우보다 메시지 태도와 온라인 구전의도에 긍정적인 영향을 끼쳤다. 또한, 메시지의 노골적 설득 의도가 낮을 때는 사회적 거리감에 따라 메시지 태도, 온라인 구전의도 각각에 대한 차이가 크게 나타난 반면, 메시지의 노골적 설득 의도가 높을 때는 사회적 거리감에 따른 광고 효과에 큰 차이가 나타나지 않았다. 그리고 규범적 대인민감성과 사회적 거리감 각각은 광고 효과에 유의미한 영향력을 미쳤지만, 두 변인의 상호작용효과는 유의미하지 않아, 규범적 대인민감성의 조절 효과는 나타나지 않았다. 마지막으로, 정보적 대인민감성이 높을 때는 사회적 거리감에 따라 메시지 태도와 온라인 구전의도 각각에 대한 차이가 크게 나는 반면, 정보적 대인민감성이 낮을 때는 사회적 거리감에 따른 광고 효과에 유의미한 차이가 나타나지 않았다. 본 연구는 기업 페이스북 페이지의 광고 효과에 관한 다양한 변인들에 대해 탐색적으로 연구함으로써 다양한 관련 후속 연구를 위한 기반을 마련했을 뿐만 아니라 실무적 차원에서도 기업 페이스북 페이지와 관련한 보다 적극적이고 효율적인 마케팅 커뮤니케이션을 위한 기초 정보로서 다양한 전략적 시사점을 제공하고 있다.

• 응용통계연구
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• 제27권2호
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• pp.331-343
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• 2014

본 논문에서는 군집 구간중도절단된 자료에서 생존시간이 군집의 크기에 의존할 때 주변모형으로부터 가중 추정 방법과 군집 내 재추출 방법을 써서 모수를 추정하고 그 추정량의 점근적 성질을 살펴보았다. 모의실험을 통해 추정량의 편향의 크기와 신뢰구간의 포함율 측면에서 볼 때 제안한 두 추정 방법이 생존시간과 군집의 크기 간의 종속 관계를 무시한 방법보다 우수한 것으로 나타났다. 제안한 추정 방법을 림프성 사상충 자료에 적용한 결과에 따르면 서로 다른 두 치료방법이 유의하게 다르지 않았으며 나이 효과도 매우 유의하지 않은 것으로 나타났다.

• 한국멀티미디어학회논문지
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• 제13권6호
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• pp.890-900
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• 2010

The Bayesian networks methods provide an efficient tool for performing information fusion and decision making under conditions of uncertainty. This paper proposes Bayes estimators for the system effectiveness in energy saving of the wireless sensor networks by use of the Bayesian method under the non-informative prior knowledge about means of active and sleep times based on time frames of sensor nodes in a wireless sensor network. And then, we conduct a case study on some Bayesian estimation models for the system energy saving effectiveness of a wireless sensor network, and evaluate and compare the performance of proposed Bayesian estimates of the system effectiveness in energy saving of the wireless sensor network. In the case study, we have recognized that the proposed Bayesian system energy saving effectiveness estimators are excellent to adapt in evaluation of energy efficiency using non-informative prior knowledge from previous experience with robustness according to given values of parameters.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.714-719
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• 2005

In this paper, the informative space is proposed to implant ubiquitous functions into physical spaces. We merge physical and virtual spaces through the space structurization using an RFID system, and solve the space localization and mapping problem for a robot to navigate through the distribution and synthesis of information and knowledge. To distribute knowledge flexibly and reliably to changing environment and also to develop a system which allows a robot to invoke and merge the distributed knowledge more freely, we employ a novel approach of knowledge management based on Web services. The proposed method is verified by building a physical space with two kinds of RFID tags and a virtual space with knowledge database based on Web services.

• 아태비즈니스연구
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• 제8권1호
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• pp.15-32
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• 2017

This study was designed to examine the antecedents of mobile app usage among smart phone users. An extended TAM, which included the additional factors of perceived enjoyment, perceived informative usefulness and perceived social usefulness, was applied to predict people's intention to use mobile apps. Overall, the hypothesized research model did a fairly good job explaining significant associations between the independent variables and the dependent variable. The findings had showed that perceived social usefulness, perceived enjoyment and attitude were significantly affect intention to use mobile apps. Meanwhile, perceived ease of use (PEOU) and perceived informative usefulness were not significantly effects attitude towards intention to use mobile apps. Therefore, mobile apps developers should develop mobile apps that are easier for the users to seek information. For the information available should be more precise and bringing more benefits to the users.

• 한국IT서비스학회지
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• 제11권sup호
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• pp.139-152
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• 2012

In the medical web forum, people share medical experience and information as patients and patents' families. Some people search medical information written in non-expert language and some people offer words of comport to who are suffering from diseases. Medical web forums play a role of the informative support and the emotional support. We propose the automatic classification model of articles in the medical web forum into the information support and emotional support. We extract text features of articles in web forum using text mining techniques from the perspective of linguistics and then perform supervised learning to classify texts into the information support and the emotional support types. We adopt the Support Vector Machine (SVM), Naive-Bayesian, decision tree for automatic classification. We apply the proposed model to the HealthBoards forum, which is also one of the largest and most dynamic medical web forum.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권3호
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• pp.188-196
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• 2017

Purpose: The purpose of this research is to determine optimal replacement age using non-informative prior information and Bayesian method. Methods: We propose a novel approach using Bayesian method to determine the optimal replacement age in block replacement policy by defining the prior probability with data on failure time and repair time. The Marcov Chain Monte Carlo simulation is used to investigate the asymptotic distribution of posterior parameters. Results: An optimal replacement age of block replacement policy is determined which minimizes cost and nonoperating time when no information on prior distribution of parameters is given. Conclusion: We find the posterior distribution of parameters when lack of information on prior distribution, so that the optimal replacement age which minimizes the total cost and maximizes the total values is determined.

• Genomics & Informatics
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• 제2권1호
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• pp.19-29
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• 2004

Gene expression profiles may offer more information than morphology and provide an alternative to morphology- based tumor classification systems. Informative gene selection is finding gene subsets that are able to discriminate between tumor types, and may have clear biological interpretation. Gene selection is a fundamental issue in gene expression based tumor classification. In this report, techniques for selecting informative genes are illustrated and supervised shaving introduced as a gene selection method in the place of a clustering algorithm. The supervised shaving method showed good performance in gene selection and classification, even though it is a clustering algorithm. Almost selected genes are related to leukemia disease. The expression profiles of 3051 genes were analyzed in 27 acute lymphoblastic leukemia and 11 myeloid leukemia samples. Through these examples, the supervised shaving method has been shown to produce biologically significant genes of more than $94\%$ accuracy of classification. In this report, SVM has also been shown to be a practicable method for gene expression-based classification.