• 한국조경학회지
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• 제16권3호
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• pp.47-58
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• 1989

^x Residential satisfaction by apartment housing type and by location was examined in Seoul Korea for a sample of 303 housewives disaggregated into four housing subgroups. These group differ in their personal characteristic by housing type and location. They showed significant differences in their levels of satisfaction and in their perception and evaluation of several community, neighborhood and housing unit attributes. A regression model of satisfaction for entire sample explain about 45% of the variation, but this conceals the compositional and the contextual differences between groups. Seperate regression for the four groups explain an average of 63% of the variation in residential satisfaction. Residents of high-rise and low-rise apartments both of center and periphery location differ significantly both from each other. Results show that certain dwelling, neighborhood and community context elicit dissatisfaction across the full sample. The objective contextual factor of housing type prove significant in most compositional subsamples, indicating that sources of residential satisfaction are not same in everywhere.

• 한국정보시스템학회지:정보시스템연구
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• 제16권4호
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• pp.51-73
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• 2007

Ubiquitous computing is enhancing computer use by making many computers available throughout the physical environment, but making them effectively invisible to the user. To facilitate the successful adoption and diffusion of ubiquitous computing, it is necessary to figure out the factors affecting the use of U-service. Though the research related to ubiquitous computing has been vigorously conducted from the aspect of system and service provider, there have been very few studies that focus on the user's perspective. Therefore, this study attempts to figure out major factors which are dedicated to the development of ubiquitous computing and u-service, and that ultimately influence the u-business outcome. This study derived the factors that characterize u-service, such as ubiquity, contextual offer, reliability, invisibility, and confidentiality, which are then combined in the TAM model and carry out the path analysis. The research findings indicate that ubiquity affects both the perceived usefulness and perceived ease of use. The reliability and confidentiality were found to affect the perceived usefulness, whereas the contextual offer and invisibility turned out to influence the perceived ease of use. Finally, the relationship among the perceived usefulness, perceived ease of use, and the attitude toward using are identical with the previous research findings related to the technology acceptance model(TAM).

• 한국IT서비스학회지
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• 제15권4호
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• pp.125-151
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• 2016

In recent years, O2O (Online to Offline) services get a lot of attention to improve the trust in online shopping and minimize the inconvenience and the cost burden in offline shopping as the number of consumers, who do not show concern about the purchase platform like online or offline, increases. Even though the services have been getting the spotlight as a strong business platform for next generation commerce, there have been only a few studies on the O2O services. The purpose of this research is to investigate the factors which affect the consumer's intention to use location-based O2O services. The study is based on VAM (Value-based Adoption Model) which is able to analyze those factors from the aspects of benefit and sacrifice. We used the partial least squares (PLS) method for empirical analysis, and the result shows that contextual offers, instant connectivity, webrooming and economic efficiency, which fall under the benefit, affect perceived value positively while annoyance and face consciousness, which fall under the sacrifice, do not affect perceived value significantly. In addition, contextual offers and instant connectivity affect trust positively. Location accuracy, which falls under the benefit of location-based O2O service, do not significantly affect perceived value and trust while security risk affects trust and use intention negatively. It appears that trust affects perceived value and use intention positively.

• 한국언어정보학회:학술대회논문집
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• 한국언어정보학회 1985년도 Proceedings of 84 Matsuyama Workshop on Formal Grammar
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• pp.23-29
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• 1985

• 한국유전체학회:학술대회논문집
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• 한국유전체학회 2005년도 The 14th Korea Genome Conference
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• pp.52-52
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• 2005

• 제어로봇시스템학회논문지
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• 제16권1호
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• pp.33-39
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• 2010

The interaction of emotion is an important factor in Human-Robot Interaction(HRI). This requires a contextual appraisal of emotion extracting the emotional information according to the events happened from past to present. In this paper an emotion appraisal system based on the cognitive context is presented. Firstly, a conventional emotion appraisal model is simplified to model a contextual emotion appraisal which defines the types of emotion appraisal, the target of the emotion induced from analyzing emotional verbs, and the transition of emotions in the context. We employ a language based cognitive system and its sentential memory and object descriptor to define the type and target of emotion and to evaluate the emotion varying with the process of time with the a priori emotional evaluation of targets. In a experimentation, we simulate the proposed emotion appraisal system with a scenario and show the feasibility of the system to HRI.

• 대한원격탐사학회지
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• 제17권4호
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• pp.335-344
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• 2001

Texture is extensively studied in a variety of image processing applications such as image segmentation and classification because it is an important property to perceive regions and surfaces. This paper focused on the analysis and synthesis of textured single and multiband images using Markov Random Field model considering the existent spatial correlation. Especially, for multiband images, the cross-channel correlation existing between bands as well as the spatial correlation within band should be considered in the model. Although a local interaction is assumed between the specified neighboring pixels in MRF models, during the maximization process, short-term correlations among neighboring pixels develop into long-term correlations. This result in exhibiting phase transition. In this research, the role of temperature to obtain the most probable state during the sampling procedure in discrete Markov Random Fields and the stopping rule were also studied.

• ETRI Journal
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• 제45권1호
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• pp.93-104
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• 2023

Coreference resolution is a task in discourse analysis that links several headwords used in any document object. We suggest pointer networks-based coreference resolution for Korean using multi-task learning (MTL) with an attention mechanism for a hierarchical structure. As Korean is a head-final language, the head can easily be found. Our model learns the distribution by referring to the same entity position and utilizes a pointer network to conduct coreference resolution depending on the input headword. As the input is a document, the input sequence is very long. Thus, the core idea is to learn the word- and sentence-level distributions in parallel with MTL, while using a shared representation to address the long sequence problem. The suggested technique is used to generate word representations for Korean based on contextual information using pre-trained language models for Korean. In the same experimental conditions, our model performed roughly 1.8% better on CoNLL F1 than previous research without hierarchical structure.

• 전자공학회논문지CI
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• 제41권3호
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• pp.67-77
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• 2004

최근 잡음환경에서 신뢰도 높은 음성인식을 위해 음성정보와 영상정보를 융합하는 방법이 활발히 연구되고 있다. 본 논문에서는 이절적인 정보의 융합에 적합한 신경망 모델을 기반으로 음성, 영상 및 문맥 정보 등 다양한 정보를 융합하여 잡음 환경에서 고려단어를 인식하는 음성인식 기법에 대하여 기술한다. 음성과 영상 특징을 이용한 이중 모드 신경망 BMNN(BiModal Neural Network)을 제안한다. BMM은 4개 층으로 이루어진 다층퍼셉트론의 구조를 가지며 각 층은 입력 특징의 추상화 기능을 수행한다. BMNN에서는 제 3층이 잡음에 의한 음성 정보의 손실을 보상하기 위하여 음성과 영상 특징을 통합하는 기능을 수행한다. 또한, 잡음환경에서 음성 인식률을 향상시키기 위해 사용자가 말한 단어들의 순차 패턴을 나타내는 문맥정보를 이용한 후처리 방법을 제안한다. 잡음환경에서 BMNN은 단순히 음성만을 사용한 것 보다 높은 성능을 보임으로써 그 타당성을 확인할 수 있을 뿐 아니라, 특히 문맥을 이용한 후처리를 하였을 경우 잡음 환경에서 90%이상의 인식률을 달성하였다 본 연구는 잡음환경에서 강인한 음성인식을 위해 다양한 추가 정보를 사용함으로써 성능을 향상시킬 수 있음을 제시한다.

• 지능정보연구
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• 제21권1호
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• pp.15-28
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• 2015

최근 개인 단말기의 보급과 객체간의 네트워크 연결이 확산됨에 따라 방대한 양의 상황 정보들이 수집되고 있지만 역설적으로 사용자들과 서비스 제공자들은 정보의 홍수 속에서 종종 잘못된 의사결정을 내리고 있다. 이러한 정보 과부하 문제를 해결하기 위해 추천 시스템은 좋은 대안이 될 수 있지만 전통적인 추천 시스템은 다양한 형태의 상황 정보 사용에 한계를 보이고 있다. 또한 획득 가능한 상황 정보가 다양해지고 방대해짐에 따라 이를 활용한 추천 시스템은 복잡성의 문제를 해결해야 하며 지속적으로 변화되는 사용자 선호 및 상황에 부합할 수 있도록 실시간 서비스가 가능하도록 설계되어야 한다. 따라서 본 연구에서는 상황 영역의 개념을 기반으로 한 상황 인식 추천 서비스 방법론을 제안하여 추천 시스템에서 상황정보를 활용하는 한편 복잡성 및 실시간 서비스 제공의 문제를 해결하려 한다. 먼저 적절한 해석과 구조로 상황 데이터를 사용자 프로필에 반영할 수 있도록 상황 영역 개념에 기반한 프로파일링을 제안함에 따라 기존의 상황 인식 추천 시스템이 가지고 있던 복잡성의 한계를 해결하고자 한다. 다음으로 목표 사용자의 상황 영역에 기반한 이웃 집단 탐색으로 추천 시스템의 희박성과 신규 사용자 문제를 해결하는 한편 현재의 상황 정보에 대한 해석으로 도출되는 상황 지지 점수를 기반으로 한 추천 목록을 생성하여 실시간 서비스가 가능한 방법론을 제안한다. 결론적으로 본 연구에서 제안하는 방법론은 추천 시스템의 적용 영역을 확장하는 연구가 될 것으로 기대되며 새로운 기술 출현을 고려한 유연한 모델을 제안함에 따라 마케팅 담당자나 서비스 제공자들이 쉽게 본 연구에서 제안하는 방법론을 적용할 수 있으리라 판단된다.