• Journal of Gifted/Talented Education
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• v.11 no.1
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• pp.43-65
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• 2001

The contents of scribbling made by scientifically gifted students, what is called Sojabo, were analyzed in order to investigate their interests and goals in the future. The scientifically gifted students were those who attended a senior high school of science in Taejeon Metropolitan City. The scribbling shown on a bulletin board in a bookroom were gathered for seven years. The results showed that the gifted students interested in school work and university entrance. And they showed goal-oriented behaviors to achieve self-actualization. They were stressed under competition among friends. They showed difficulties in making good relationship with their teachers. However, they could be characterized as invulnerable students.

• Knowledge Management Research
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• v.15 no.4
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• pp.35-56
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• 2014

This study examined the effect of perceived risk, an under-explored area in the knowledge sharing literature. We proposed that employee perceptions of risk relate positively with their knowledge sharing behaviors (donating and collecting), and examined the mediating role of impression management strategies in the hypothesized relationships. We also explored the moderating effect of leader-member exchange (LMX) in the relationship between perceived risk and impression management strategies. Valid and reliable self-report and supervisory evaluation measures were collected from a sample of 251 railroad employees in safety-sensitive positions. The results indicate that perceived risk was not significantly associated with knowledge sharing, but rather the risk perception impacts were indirect through impression management strategies such as exemplification and supplication. The study also found that LMX has no moderating effect on the perceived risk and impression management strategies. In discussing these results, we present significant insights in terms of subjective risk judgment as a potential mechanism which can encourage organizational politics.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.95-102
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• 1999

The web-based group collaborative systems are emerging as enterprise-wide information systems. Since data in group collaborative systems are apt to be shared among multiple concurrent users and modified simutaneously by them, the web-based group collaborative systems must support synchronous collaboration in order to provide users with synchronized and consistent views of shared data. This paper proposes an active web server which can facilitate synchronous collaboration in web-based group collaborative systems. To accomplish such a goal, the active web server manages dependency relationships between shared data and web browsers referencing them and actively propagates changing details of the shared data to all web browsers referencing them. And, this paper examines usefullness and effectiveness of the active web server to apply it to the ball-bearing design example of concurrent engineering design systems. The prototype system of the active web server is developed on a commercial Object-oriented Database Management System (ODBMS) called OBJECTSTORE using the C++ programming language.

• Journal of Korean Society for Quality Management
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• v.28 no.4
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• pp.47-66
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• 2000

In recent, keeping and developing relationships with current customers is a key service business goal, and service recovery efforts is to be the essence of service business strategy. But many researchers have neglected to focus on that issue. So this research is intended to explore service quality factors that include service recovery efforts and grip those difference among service operations systems. Service operations systems are divided into three categories. Our study results suggest that customer oriented firms need to develop a comprehensive service recovery system and must include service recovery as a service quality factor.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.187-192
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• 2015

Detecting human in images is a challenging task owing to their variable appearance and the wide range of poses the they can adopt. The first need is a robust feature set that allows the human form to be discriminated cleanly, even in cluttered background under difficult illumination. A large number of vision application rely on matching keypoints across images. These days, the deployment of vision algorithms on smart phones and embedded device with low memory and computation complexity has even upped the ante: the goal is to make descriptors faster compute, more compact while remaining robust scale, rotation and noise. In this paper we focus on improving the speed of pedestrian(walking person) detection using Histogram of Oriented Gradient(HOG) descriptors provide excellent performance and tracking using kalman filter.

• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.28-39
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• 2007

The issue of customer-centric enterprise focusing on realizing customer needs has recently received considerable attention in the corporate world. However, little research has yet been reported on developing Information Systems (IS) supporting the customer-centric enterprises. This research proposes an integrated approach of IS development that supports organizations aiming to become customer-centric enterprises using various customer profiles. In this paper, we propose an integrated approach unifying goal modeling, business process modeling, and information systems modeling. The approach is expected to be seamlessly linked with the object-oriented systems development approach. Finally, we apply this approach to the real case of a securities company in Japan.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.111-115
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• 2017

목적 지향적 대화 시스템(Goal-oriented dialogue system)은 텍스트나 음성을 통해 특정한 목적을 수행할 수 있는 시스템이다. 최근 RNN(recurrent neural networks)을 기반으로 대화 데이터를 end-to-end learning 방식으로 학습하여 대화 시스템을 구축하는데에 활용한 연구가 있다. End-to-end 방식의 학습은 도메인에 대한 지식 없이 학습 데이터 자체만으로 대화 시스템 구축을 위한 학습이 가능하다는 장점이 있지만 도메인 지식을 학습하기 위해서는 많은 양의 데이터가 필요하다는 단점이 존재한다. 이에 본 논문에서는 도메인 특정 지식을 결합하여 end-to-end learning 방식의 학습이 가능한 Hybrid Code Network 구조를 기반으로 한국어로 구성된 식당 예약에 관련한 대화 데이터셋을 이용하여 식당 예약을 목적으로하는 대화 시스템을 구축하는 방법을 제안한다. 실험 결과 본 시스템은 응답 별 정확도 95%와 대화 별 정확도 63%의 성능을 나타냈다.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.288-293
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• 2011

To resolve ambiguities in speech act classification, various machine learning models have been proposed over the past 10 years. In this paper, we review these machine learning models and present the results of experimental comparison of three representative models, namely the decision tree, the support vector machine (SVM), and the maximum entropy model (MEM). In experiments with a goal-oriented dialogue corpus in the schedule management domain, we found that the MEM has lighter hardware requirements, whereas the SVM has better performance characteristics.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.596-599
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• 2018

본 논문은 일정 등록을 위한 대화 시스템 개발에 대한 연구를 수행하였다. 기계는 사용자가 요구하는 일정 등록, 일정 수정 및 일정 삭제 등 다양한 목적에 따라 이에 맞는 API를 호출하게 된다. DSCT 6가 제안한 방법을 활용하여 호출되는 API의 종류에 따라 사람과 기계와의 대화를 task 라 불리는 여러 종류의 소규모 목적 대화로 분류하였다. 그 후 분류된 목적 task를 위해 Memory Network 개발에 대한 연구를 수행하였다. 첫 번째로 분류된 task에 대한 실행 결과 75%, 두 번째 task 88%, 세 번째 task 89%, 마지막 모든 task를 합쳤을 때 90%의 성능을 확인할 수 있었다.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.147-150
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• 2018

목적 지향 대화 시스템은 자연어 이해, 대화 관리자, 자연어 생성과 같은 세분화 모델들의 결합으로 이루어져있어 하위 모델에 대한 오류 전파에 취약하다. 이러한 문제점을 해결하기 위해 자연어 이해 모델과 대화 관리자를 하나의 네트워크로 구성하고 오류에 강건한 심층 Q 네트워크를 제안한다. 본 논문에서는 대화의 전체 흐름을 파악 할 수 있는 순환 신경망인 LSTM에 심층 Q 네트워크 적용한 심층 순환 Q 네트워크 기반 목적 지향 대화 시스템을 제안한다. 실험 결과, 제안한 심층 순환 Q 네트워크는 LSTM, 심층 Q 네트워크보다 각각 정밀도 1.0%p, 6.7%p 높은 성능을 보였다.