• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.59-70
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• 2021

With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context information that expresses the state of situations. However, these datasets is mostly unstructured and have difficulty in processing with simple approaches. Therefore, providing context-aware services using the datasets should be managed in simplified method. One of examples that should be considered as the unstructured datasets is a deep learning application. Processes in deep learning applications have a strong coupling in a way of abstracting dataset from the acquisition to analysis phases, it has less flexible when the target analysis model or applications are modified in functional scalability. Therefore, an abstraction model that separates the phases and process the unstructured dataset for analysis is proposed. The proposed abstraction utilizes a description name Analysis Model Description Language(AMDL) to deploy the analysis phases by each fat client is a specifically designed instance for resource-oriented tasks in edge computing environments how to handle different analysis applications and its factors using the AMDL and Fat client profiles. The experiment shows functional scalability through examples of AMDL and Fat client profiles targeting a vehicle image recognition model for vehicle access control notification service, and conducts process-by-process monitoring for collection-preprocessing-analysis of unstructured data.

• Asia pacific journal of information systems
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• v.15 no.2
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• pp.195-218
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• 2005

The emergence of ubiquitous computing environment will change the service architecture of business information systems such as Decision Support System(DSS), which will be a new application. Recent mobile DSSs allow the decision makers to be benefited from web and mobile technology. However, they seldom refer to context data, which are useful for proactive decision support. Meanwhile, ubiquitous applications so far provide restricted personalization service using context and preference of the user, that is, they do not fully make use of decision making capabilities. Hence, this paper aims to describe how the decision making capability and context-aware computing are jointly used to establish ubiquitous applications. To do so, an amended DSS paradigm: CKDDM(Context-Knowledge-Dialogue-Data-Model) is proposed in this paper. What will be considered for the future decision support systems when we regard ubiquitous computing technology as an inevitable impact that enforces the change of the way of making decisions are described. Under the CKDDM paradigm, a framework of ubiquitous decision support systems(ubiDSS) is addressed with the description of the subsystems within. To show the feasibility of ubiDSS, a prototype system, CAMA-myOpt(Context-Aware Multi Agent System-My Optimization) has been implemented as an illustrative example system.

• Journal of Distribution Science
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• v.20 no.8
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• pp.123-133
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• 2022

Purpose: As moment-based marketing messages (i.e., messages related to current moments or event), companies put significant investments to distribute TV advertising related to external moments in a retail environment. While the literature offers strong support for the value of distributions of context-based messaging to advertisers, less attention has been given to how to design those messages to effectively communicate across channels. This research adds a new dimension of analysis to the study of advertising context and its cross-channel effects on online consumer behavior. Research Design, Data and Methodology: A system-of-equations Tobit regression model was adopted using data collected from an advertising agency that consists of 1,223 TV ads aired during the Rio Olympics and NCAA, tagging from consumers, and a text analysis. Results: First, TV ads with high centrality of context lead to lower online search behavior and higher online social actions. Second, how brands can design messages more effectively was explored by using product information as a moderator that could improve the impact of context-based TV advertisements. Conclusions: Given that expenses in traditional channels are still one of the biggest channel management decisions, it is critical to understand how consumer engagement varies by design of context-based TV advertising.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.10a
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• pp.178-179
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• 2004

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.369-369
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• 2006

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.15-18
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• 2006

유비쿼터스 환경은 네트워크로 상호 연결된 디바이스들이 사용자의 상황을 인식하여 언제, 어디서나 사용자가 원하는 정보를 자동적으로 제공할 수 있는 환경을 말한다. 그러나 유비쿼터스 컴퓨팅 환경에서 시,공간의 제약 없이 정보에 접근할 수 있다는 것은 다른 환경에서보다 더 많은 보안 기술이 요구된다. 따라서 본 연구에서는 유비쿼터스 기반 하에서 개인 정보에 대해 기밀성과 무결성을 유지하면서 사용자가 원하는 정보를 자동적으로 인식할 수 있는 접근방법을 제안한다. 제안방법은 기존 RBAC에서 확장한 Context Roles를 정의하여 접근을 통제하였고 복수 정책(Multi-Policy)으로 개인 정보 및 역할 데이터 Object에 대해 제약을 두어 데이터 접근 시 상황정보에 따라 보안 등급을 지정하여 역할 정보에 대한 유출을 막는데 목적을 두었다.

• The Journal of Information Systems
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• v.5
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• pp.205-248
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• 1996

Historically, the en-users' acceptance of the expert systems(ES) have generally been used as a proxy for the ES' implementation success by both practitioners and academicians. However, with regard to bank loan decisions, most loan officers approach the acquisition of an ES with apprehension. In order to overcome this skepticism, more research should focus on the behavioral aspects relate to systems acquisition and usage. This research applied Vroom's(1964) expectancy theory in an effort to predict end-users' motivation to use an ES in a bank loan decision context. Because human behaviors and judgements are nonlinear rather than linear functions, accurately predicting human behavior is very difficult. To increase the prediction power for end-users' motivation to use an ES in a bank loan decision context, this research used an artificial neural network (ANN) model. In this research, an attempt was made to evaluate adequacy of the surrogates by analyzing differences between real bank loan officers and student surrogates in applying expectancy theory to estimate bank loan officers' motivation to use ES in a bank loan decision context.

• Journal of the Korea Computer Industry Society
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• v.2 no.2
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• pp.195-202
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• 2001

In this paper, we show a study on how to model a phoneme of which acoustic feature is changed according to both left-hand and right-hand phonemes. For this purpose, we make a comparative study on two kinds of algorithms; a unit reduction algorithm and decision tree modeling. The unit reduction algorithm uses only statistical information while the decision tree modeling uses statistical information and Korean acoustical information simultaneously. Especially, we focus on how to model context-dependent phonemes based on decision tree modeling. Finally, we show the recognition rate when context-dependent phonemes are obtained by the decision tree modeling.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.799-806
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• 2007

The prototypical smart environment to support the context-aware interactions between user and ubiquitous campus environment based on multi-agent system paradigm is proposed in this paper. In this model, the dynamic Bayesian is investigated to solicit and organize agents to produce information and presentation assembly process in order to allocate the resources for an unseen task across multiple services in a dynamic environment. The user model is used to manage varying user constraints and user preferences to achieve system's goals.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.133-140
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• 2006

유비쿼터스 컴퓨팅 기술이 발전함에 따라 상황인지는 유비쿼터스 환경을 구성하는 중요한 요소들 중의 하나로 안정되고 있다. 그러나 아직까지 모든 유비쿼터스 컴퓨팅 환경에 적용될만한 일반적인 상황모형 (generic context model)은 제시되지 못하고 있다. 따라서 본 논문의 목적은 혼합형 다단계(hybrid multi-level) 다이어그램을 이용해 보다 적합한 일반적 상황모형을 제안하는 것이다. 이를 위해 먼저 기존의 다양한 상황 모형들을 분석하고 이를 토대로 유비쿼터스 지능 공간에서의 컴퓨팅 시스템 환경에 적합한 일반적 상황모형을 제안하였다.