• Annual Conference of KIPS
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• 2004.11a
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• pp.797-800
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• 2004

유비쿼터스 컴퓨팅 환경은 공통적으로 재사용 가능하고, 확장성이 강력한 컨텍스트 모델이 필요하다. 본 논문에서는 엔티티(Entity), 컨텍스트 타입(Context Type), 값(Value)으로 구성된 트리플을 기반으로 한 유비쿼터스 컴퓨팅 환경의 컨텍스트를 모델을 제안하였다. 컨텍스트 정보를 주어, 동사, 목적어에 해당하는 (Entity, Context Type, Value) 트리플로 표현함으로써 재사용성과 확장성을 제공한다.

• Korean Journal of Cognitive Science
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• v.20 no.3
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• pp.243-274
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• 2009

The association, word frequency and imagery have been considered as the main factors that affect the word recognition. The present study aimed to examine the imagery effect and the interaction of the association effect while controlling the frequency effect. To explain the imagery effect, we compared the two theories (dual-coding theory, context availability model). The lexical decision task using priming paradigm was administered. The duration of prime words was manipulated as 20ms, 50ms, and 450ms in experiments 1, 2, and 3, respectively. The association and imagery of prime words were manipulated as the main factors in each of the three experiments. In experiment 1, the duration of prime words (20ms) which is expected to not activate the semantic context enough to affects the word recognition was used. As a result, only imagery effect was statically significant. In experiment 2, the duration of prime word was 50ms, which we expected to activate the semantic context without perceptual awareness. The result showed both the association and imagery effects. The interaction between the two effects was also significant. In experiment 3, to activate the semantic context with perceptual awareness, the prime words were presented for 450ms. Only association effect was statically significant in this experimental condition. The results of the three experiments suggest that the influence of the imagery was at the early stages of word recognition, while the association effect appeared rather later than the imagery. These results implied that the two theories are not contrary to each other. The dual-coding theory just concerned imagery effect which affects the early stage of word recognition, and context-availability model is more for the semantic context effect which affects rather later stage of word recognition. To explain the word recognition process more completely, some integrated model need to be developed considering not only the main 3 effects but also the stages which extends along the time course of the process.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1729-1734
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• 2011

Urban transit administers need to introduce the intelligent system to know the situations in the urban transit service area automatically. It is one of the important elements to detect of intrusion in operation room or electric rooms, etc. In this paper, we describe the definition for detection of intrusion in urban transit area, and propose the context-awareness model detect of intrusion. We expect that the definition is helpful to extract the elements that are need to construct the intrusion detecting system. The proposed model that is based on an image analysis model and a rule-based model is also helpful to design intelligent surveillance model.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.8
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• pp.394-406
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• 2008

Even though context is the most important feature in context-aware systems, the existing requirements engineering cannot support methodology for elicitation and specification of contexts. In this paper, we propose a requirements elicitation method and a requirements specification method for context-aware systems. Our requirements elicitation method is a 6-stepped, incremental, and iterative process. At the beginning steps in the process, we identify the requirements for business logic. Afterwards, we gather the requirements for context logic, model contexts, and identify subsystems. For requirements specification, we suggest a context-aware use case diagram, a context diagram for context modeling, and a context-type-use-case-dependency diagram for the traceability of use cases on the change of context types. We also introduce a case study that we apply our approaches to a real system, and a qualitative evaluation of our approaches. Our study will help stakeholders to efficiently elicit requirements for context-aware systems and to specify them clearly.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.254-263
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• 2006

Ontology-based context models are widely used in ubiquitous computing environment because they have advantages in the acquisition of conceptual context through inferencing, context sharing, and context reusing. Among the benefits, inferencing enables context-aware applications to use conceptual contexts which cannot be acquired by sensors. However, inferencing causes processing delay and thus becomes the major obstacle to the implementation of context-aware applications. The delay becomes longer as the amount of contexts increases. In this paper, we propose a context pre-fetching method to reduce the size of contexts to be processed in a working memory in attempt to speed up inferencing. For this, we extend the query-tree method to identify contexts relevant to the queries of a context-aware application. Maintaining the pre-fetched contexts optimal in a working memory, the processing delay of inference reduces without the loss of the benefits of ontology-based context model. We apply the proposed scheme to our ubiquitous computing middleware, Active Surroundings, and demonstrate the performance enhancement by experiments.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.510-523
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• 2012

The purpose of this study is to evaluate an airline service training program based on the CIPP model. Evaluation areas were divided into context, input, process, and product. We analyzed the factors which influenced program satisfaction and recommendation of the training program. Two hundred and one learners who participated in an airline service training program were selected for a survey. The results of this study are as follows. The factors which positively influenced training satisfaction were educational goals in context evaluation, interaction between learners and instructors, managing programs in process evaluation, and training performance in product evaluation. The factor which negatively influenced training satisfaction was human resources in input evaluation. On the other hand, the factors which positively influenced training recommendation were educational goal, assessing needs in context evaluation, interaction between learners and instructors, supporting programs in process evaluation, and training performance in product evaluation. The factor which negatively influenced training recommendation was assessing needs in context evaluation. The results of this study are expected to make an important contribution to the development of service training programs in airlines.

• Journal of KIISE
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• v.43 no.5
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• pp.531-540
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• 2016

Development of various sensors attached to mobile and wearable devices has led to increasing recognition of current context-based service to the user. In this study, we proposed a probabilistic model for recognizing user's food intake context, which can occur in a great variety of contexts. The model uses low-level sensor data from mobile and wrist-wearable devices that can be widely available in daily life. To cope with innate complexity and fuzziness in high-level activities like food intake, a context model represents the relevant contexts systematically based on 4 components of activity theory and 5 W's, and tree-structured Bayesian network recognizes the probabilistic state. To verify the proposed method, we collected 383 minutes of data from 4 people in a week and found that the proposed method outperforms the conventional machine learning methods in accuracy (93.21%). Also, we conducted a scenario-based test and investigated the effect contribution of individual components for recognition.

• Journal of IKEEE
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• v.11 no.4
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• pp.279-282
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• 2007

In this paper, we introduce the general way for producing context information to support context-aware applications. It can fetch raw data from the service environments, translate it to reasonable context information, and provide to multiple applications. It is designed originally for the ubiquitous computing middleware and based on the ontology processing model. Automated service applications can use this system as the form of libraries or of web services for deciding its semantic cause of action.

• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.55-62
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• 2006

After the advent of the Ubiquitous environment, the movement for effective information management is progressing vividly. According to this situation, this paper conducts individualized context structure for individual service and also suggests 5W1H and HFC modeling which apply using priority to manage vast context data. Thus this modeling will function as a base model to embody Ubiquitous environment and offer context based service.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.443-447
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• 2023

검색 증강형 언어 모델은 입력과 연관된 문서들을 검색하고 텍스트 생성 과정에 통합하여 언어 모델의 생성 능력을 강화한다. 본 논문에서는 사전 학습된 대규모 언어 모델의 추가적인 학습 없이 In-Context 검색 증강으로 한국어 언어 모델의 생성 능력을 강화하고 기존 언어 모델 대비 성능이 증가함을 보인다. 특히 다양한 크기의 사전 학습된 언어 모델을 활용하여 검색 증강 결과를 보여 모든 규모의 사전 학습 모델에서 Perplexity가 크게 개선된 결과를 확인하였다. 또한 오픈 도메인 질의응답(Open-Domain Question Answering) 과업에서도 EM-19, F1-27.8 향상된 결과를 보여 In-Context 검색 증강형 언어 모델의 성능을 입증한다.