• 한국통신학회논문지
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• 제30권3B호
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• pp.53-64
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• 2005

Rapid growth of digitalization in telecommunication and broadcasting and remarkable enhancement in broadband and high speed transmission capability of media raised a problem of integrating communication and broadcasting. In order to implement this, the government has selected construction of Broadband Convergence Network (BcN) as a main new growth engine of the country. The BcN will be realized based on FTTH and Broadband Home Network (BHN) will be implemented through this solution. Transfer rate and bandwidth required for the BcN to be constructed aiming at integration of communication and broadcasting will be specified and the performance of basic transmission media, the plastic optical fiber, will be discussed in order to present its appropriateness.

• 한국정보통신학회논문지
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• 제7권5호
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• pp.1013-1018
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• 2003

본 논문은 이차여자 유도발전기시스템의 파력발전시스템에의 적용에 관한 연구내용을 요약한다. 불규칙적인 파력 입력에 따라 변화하는 발전기의 출력을 슬립주파수에 맞추어 컴퓨터로 이차전류를 제어하여 출력전압과 출력전류를 안정화시키고자 하였다. 본 논문에서 제안한 방법을 확인하기 위하여 실험실 레벨의 파력 시뮬레이터를 제작한 후 이차여자 유도발전기를 구동하였다. 파력과 같은 불규칙입력 발전시스템에 대한 이차여자 유도발전 시스템의 유효성을 실험적으로 확인하였다.

• 정보교육학회논문지
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• 제1권2호
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• pp.45-56
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• 1997

A design of Advisory Tutoring Agent(ATA) is proposed to help a student on the basis of a student-oriented discovery learning, The agents adaptively build a student model and interact with a student as well as each other to give a piece of advice at a proper time. The appropriateness of advice depends on the agents' reasoning sod interaction performed based on the student model. domain knowledge, teaching strategy, and user-friendly interface. The design has been applied to a simple English learning environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.4098-4116
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• 2020

Mobile devices such as smartphones are very attractive targets for augmented reality (AR) services, but their limited resources make it difficult to increase the number of objects to be recognized. When the recognition process is scaled to a large number of objects, it typically requires significant computation time and memory. Therefore, most large-scale mobile AR systems rely on a server to outsource recognition process to a high-performance PC, but this limits the scenarios available in the AR services. As a part of realizing large-scale standalone mobile AR, this paper presents a solution to the problem of accuracy, memory, and speed for large-scale object recognition. To this end, we design our own basic feature and realize spatial locality, selective feature extraction, rough pose estimation, and selective feature matching. Experiments are performed to verify the appropriateness of the proposed method for realizing large-scale standalone mobile AR in terms of efficiency and accuracy.

• 전자공학회논문지
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• 제51권2호
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• pp.190-196
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• 2014

본 논문에서는 밸런싱 로봇의 동역학적 모델의 해석으로부터 기울기와 조향이 독립되어 있어 서로 영향을 받지 않는 것을 증명하고, 다변수 시스템에 적합한 제어기로써 두 개의 최적 LQR 제어기 구조를 갖는 제어시스템을 제안하였다. 또한 제안한 제어시스템의 성능을 입증하기 위하여 밸런싱 로봇의 자세제어에 적용하여 모의실험과 실험을 수행하였고, PID 제어기와의 비교평가를 통하여 그 우수성을 검증하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.70-72
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• 2005

It is very difficult to control a motor and apply a mathematical algorithm using regular micro controller. However we can embody a program using the graphic language faster and easier than using another language and conveniently compose the plate based on a PC through the DAQ board included AD and DA converter. In addition, The controllable system is made due to GUI program. I verified appropriateness of variable of a speed and determining a speed of BLDC motor which is normally used through this program.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 한국지능정보시스템학회
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• pp.329-337
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• 2007

Case-based reasoning (CBR) methods are applied to various target problems on the supposition that previous cases are sufficiently similar to current target problems, and the results of previous similar cases support the same result consistently. However, these assumptions are not applicable for some target cases. There are some target cases that have no sufficiently similar cases, or if they have, the results of these previous cases are inconsistent. That is, the appropriateness of CBR is different for each target case, even though they are problems in the same domain. Thus, applying CBR to whole datasets in a domain is not reasonable. This paper presents a new hybrid datamining technique called two-step filtering CBR and Rule Induction (TSFCR), which dynamically selects either CBR or RI for each target case, taking into consideration similarities and consistencies of previous cases. We apply this method to three medical diagnosis datasets and one credit analysis dataset in order to demonstrate that TSFCR outperforms the genuine CBR and RI.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2555-2557
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• 2005

It is very difficult to control a motor and apply a mathematical algorism using regular micro controller. However we can embody a program using the graphic language faster and easier than using another language and conveniently compose the plate based on a PC through the DAQ board included AD and DA converter. In addition, The controllable system is made due to GUI program. I verified appropriateness PI control and determining a speed of BLDC motor which is nomally used through this program.

• 한국문헌정보학회지
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• 제33권2호
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• pp.5-22
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• 1999

본 연구는 인쇄본 백과사전의 평가요소를 추출하고 이를 분석함으로써 이상적인 백과사전을 선택할 수 있는 능력을 제고시키는데 목적을 둔다. 분석방법은 평가내용을 목적과 범위, 권위, 접근성, 기술형식, 형태, 특징과 가격 등의 여섯 가지 범주로 나누고 각 범주 아래에서 세부적인 평가요소를 추출하여 분석하였다. 분석은 단순히 평가요소를 제시하는 것이 아니라 각 평가요소별로 이론적 당위성을 제시하는데 중점을 두었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권12호
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• pp.3266-3285
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• 2023

With the popularity of online learning, intelligent tutoring systems are starting to become mainstream for assisting online question practice. Surrounded by abundant learning resources, some students struggle to select the proper questions. Personalized question recommendation is crucial for supporting students in choosing the proper questions to improve their learning performance. However, traditional question recommendation methods (i.e., collaborative filtering (CF) and cognitive diagnosis model (CDM)) cannot meet students' needs well. The CDM-based question recommendation ignores students' requirements and similarities, resulting in inaccuracies in the recommendation. Even CF examines student similarities, it disregards their knowledge proficiency and struggles when generating questions of appropriate difficulty. To solve these issues, we first design an enhanced cognitive diagnosis process that integrates students' affection into traditional CDM by employing the non-compensatory bidimensional item response model (NCB-IRM) to enhance the representation of individual personality. Subsequently, we propose an affection-enhanced personalized question recommendation (AE-PQR) method for online learning. It introduces NCB-IRM to CF, considering both individual and common characteristics of students' responses to maintain rationality and accuracy for personalized question recommendation. Experimental results show that our proposed method improves the accuracy of diagnosed student cognition and the appropriateness of recommended questions.