• 대한전자공학회논문지SP
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• 제41권5호
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• pp.269-274
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• 2004

지상파 디지털 TV 신호를 등화하기 위한 이중모드 블라인드 판정귀환 등화기(dual-mode blind decision feedback equalizer)를 제안한다. 제안한 이중모드 판정귀환 등화기는 채널 상태에 따라 판정의거 모드 또는 블라인드 모드에서 동작한다. 등화기의 탭 계수 갱신에 사용될 오차 신호를 판정의거 모드 또는 블라인드 동작 모드에서 발생시킴으로써 탭 계수 갱신의 신뢰도를 높일 뿐만 아니라, 채널의 왜곡 정도에 따라 등화기의 동작이 판정의거 모드와 블라인드 모드 간을 자동 전환함으로써 채널 특성의 변화를 추적할 수 있다. 모의실험을 통해 다양한 정적 및 다이내믹 다중경로 채널 하에서 8-VSB(vestigial sideband) 변조된 디지털 TV 신호에 적용하여 제안한 등화 기법과 종래의 방법에 의한 성능을 평균 자승 오차(mean square error: MSE)와 심벌 오율(symbol error rate: SER) 관점에서 비교, 제안한 방법의 유용성을 확인하였다.

• 전기전자학회논문지
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• 제19권3호
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• pp.400-406
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• 2015

본 논문에서는 IEEE 802.11p WAVE 모뎀을 위한 다이버시티 모뎀 구조를 제안하고 설계하였으며, 이를 실차에 장착하여 성능테스트를 수행하였다. 제안한 구조는 듀얼채널과 다이버시티 기능을 선택적으로 수행할 수 있으며, 선택적 안테나 다이버시티와 Maximum Ratio Combining (MRC) 다이버시티 기능 중하나를 선택하여 수신할 수 있다. 개발된 구조는 HDL로 설계되어 Xillinx Kintex7보드를 이용하여 실도로에서 실차에 장착하여 테스트를 수행하여 성능을 검증하였다. 실험결과 개발된 다이버시티 모뎀은 단일 채널 모뎀에 비하여 안정적인 통신 성공률을 유지할 수 있으며, 전송거리도 안테나 후면 수신시 최소 100%이상 향상됨을 확인하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제17권3호
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• pp.205-233
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• 2008

This study suggests the dynamic value chain model, that will be able to not only show changing processes to organization's significant capital by integrating an individual, implicit, and explicit knowledge which affect organizational decision making, but also distinguish the key driver for raising organizational competitive power because it makes possible to analyze sensitivity of performance along with decision making alternatives and policy changes from dynamic view by connecting knowledge management capability, knowledge management activity, and relations with organizational performance with specific strategic map. Recently, a lot of organizations show interest in measuring and evaluating their performance synthetically. In organizations taking knowledge management, they introduce effective value chain model like a dynamic balanced scorecard (DBSC), and therefore they can reflect their knowledge management condition as well as show their changes by checking performance of established vision and strategy periodically. Furthermore, they can ask for their inner members' understanding and participation by communicating with and inspiring their members with awareness that members are one of their group, present a base of benchmarking, and offer significant information for later decision making. The BSC has been a successful framework for measuring an organization's performance in various perspectives through translating an organization's vision and strategy into an interrelated set of key performance indicators and specific actions. The BSC, while having significant strengths over traditional performance measurement methods, however, has its own limitations, due to its static nature, such as overlooking two-way causation between performance indicators and neglecting the impact of delayed feedback flowing from the adoption of new strategies or policy changes. To overcome these limitations, this study employs SD, a methodology for understanding complex systems where dynamic feedback among the interrelated system components significantly impact on the system outcomes. The SD simulation model in the form of DBSC would serve as a useful strategic teaming tool for facilitating an organization's communication process through various scenario analyses as well as predicting the dynamic behavior pattern of their key performance measures over a future time frame. For the demonstration purpose, this study applied the DBSC model to Prototype of Korea manufacturing and service firm.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.278-282
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• 2001

The discovery of tacit knowledge from domain experts is one of the most exciting challenges in today\`s knowledge management. The nature of decision knowledge in determining the quality a firm\`s short-term liquidity is full of abstraction, ambiguity, and incompleteness, and presents a typical tacit knowledge extraction problem. In dealing with knowledge discovery of this nature, we propose a scheme that integrates both knowledge elicitation and knowledge discovery in the knowledge engineering processes. The knowledge elicitation component applies the Verbal Protocol Analysis to establish industrial cases as the basic knowledge data set. The knowledge discovery component then applies fuzzy clustering to the data set to build a fuzzy knowledge based system, which consists of a set of fuzzy rules representing the decision knowledge, and membership functions of each decision factor for verifying linguistic expression in the rules. The experimental results confirm that the proposed scheme can effectively discover the expert\`s tacit knowledge, and works as a feedback mechanism for human experts to fine-tune the conversion processes of converting tacit knowledge into implicit knowledge.

• 대한안전경영과학회지
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• 제6권2호
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• pp.211-229
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• 2004

The basis of cyber trading has been sufficiently developed with innovative advancement of Internet Technology and the tendency of stock market investment has changed from long-term investment, which estimates the value of enterprises, to short-term investment, which focuses on getting short-term stock trading margin. Hence, this research shows a Short-term Stock Price Forecasting System on Learning Agent System using DTA(Decision Tree Algorithm) ; it collects real-time information of interest and favorite issues using Agent Technology through the Internet, and forms a decision tree, and creates a Rule-Base Database. Through this procedure the Short-term Stock Price Forecasting System provides customers with the prediction of the fluctuation of stock prices for each issue in near future and a point of sales and purchases. A Human being has the limitation of analytic ability and so through taking a look into and analyzing the fluctuation of stock prices, the Agent enables man to trace out the external factors of fluctuation of stock market on real-time. Therefore, we can check out the ups and downs of several issues at the same time and figure out the relationship and interrelation among many issues using the Agent. The SPFA (Stock Price Forecasting System) has such basic four phases as Data Collection, Data Processing, Learning, and Forecasting and Feedback.

• Perspectives in Nursing Science
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• 제5권1호
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• pp.17-31
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• 2008

Purpose: The purpose of this study was to evaluate the usability of a prototype personal digital assistant (PDA)-based decision support system for the management of obesity through usability testing with end-users (Advanced Practice Nurses [APNs]) prior to its implementation in clinical settings. Methods: This descriptive study used observational and think aloud techniques to address the research question: what usability problems are perceived by end-users? Five APNs were provided with the scenarios and the list of tasks to evaluate the application. Their verbalizations were recorded through Morae usabil ity software. Data analysis was based on the data captured through Morae, transcriptions, notes, and the end-user survey. Results: End-users completed all the required tasks without encountering a severe usability problem, and agreed that the system was easy to use. clear, concise, and useful. Usability issues that were unrecognized by the developer or usability experts were identified by APNs. The usability problems were categorized according to positive characteristics, negative characteristics, and recommendations. The usability issues were discussed with the project team members, and solutions were suggested to improve the user interface of the PDA-based decision support system before the final implementation. Conclusions: This approach had an important impact on making the system easier to use and more useful from the perspective of design and content. The results of this evaluation provided iterative feedback regarding the design and implementation of the PDA-based decision support system for the management of obesity.

• 에너지공학
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• 제8권4호
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• pp.612-620
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• 1999

환경영향평가는 전과정평가(Life Cycle Assessment : LCA)의 인벤토리 분석과정에서 규명된 환경부하의 값으로 표현하고 상대적인 중용도를 측정하는 단계이다. 이러한 가중치를 측정하므로서 개별제품 또는 기술에 대한 환경부하의 영향을 평가하는데 이용될 수 있다. 본 연구에서는 환경영향평가에 대한 분석에서 환경부하의 상대적인 중요도 혹은 가중치를 산출하기 위하여 일반적으로 이용되는 계층적 의사결정모형(Hierarchical decision model)의 한계인 요인들간의 독립성을 극복할 수 있는 즉, 의사결정요인간 상호영향력을 가지는 네트워크 구조(Network decision model)에서도 사용될 수 있는 의사 결정모형( Analytic Network Process : ANP)을 도입한다. ANP로부터 얻어지는 각 의사결정요인의 가중치는 환경부하의 수준을 결정하는데 용이하게 이용할 수 있다.

• 정보처리학회논문지B
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• 제17B권2호
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• pp.139-148
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• 2010

본 논문은 자동화된 분류시스템의 성능향상을 위한 것으로 오분류율이 높은 불확실성이 강한 문서들의 범주결정방식을 개선하기 위한 후처리분석 방법과 피드백 알고리즘을 제안한다. 전통적인 분류시스템에서 분류의 정확성을 결정하는 요인으로 학습방법과 분류모델, 그리고 데이터의 특성을 들 수 있다. 특성들이 일부 공유되어 있거나 다의적인 특성들이 풍부한 문서들의 분류문제는 정형화된 데이터들에서 보다 심화된 분석과정이 요구된다. 특히 단순히 최상위 항목으로 지정하는 기존의 결정방법이 분류의 정확도를 저하시키는 직접적인 요인이 되므로 학습방법의 개선과 함께 분류모델을 적용한 이후의 결과 값인 순위정보 리스트의 관계를 분석하는 작업이 필요하다. 본 연구에서는 경계범주의 자동탐색기법으로 확장된 학습체계를 제안한 이전 연구의 후속작업으로써, 최종 범주를 결정하기까지의 후처리분석 방법과 이전의 학습단계로 피드백하여 신뢰성을 높일 수 있는 알고리즘을 제안하고 있다. 실험결과에서는 제안된 범주결정방식을 적용한 후 1회의 피드백을 수행하였을 때의 결과들을 단계적이고 종합적으로 분석함으로써 본 연구의 타당성과 정확성을 보인다.

• 한국시스템다이내믹스연구
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• 제4권1호
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• pp.69-91
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• 2003

Using qualitative methods hinged on urban dynamics models, the paper addresses major issues concerned with new administrative capital construction. It tries to summarize the existing debates on new administrative capital construction and reinterpret diverse interacting factors in terms of reinforcing or balancing feedback structure. The paper suggests that understanding up on the dynamic mechanism imbedded in circular causal loop diagrams is the key to set up appropriate proposals and action plans for the new administrative capital, as they would reveal complicated linkages between the Capital Region and the rest, in addition to the urban dynamic of new administrative capital. In the same context, the paper can confirm similar features reflected in the relocation of capital functions at Canberra, Australia and Berlin, Germany. It has paid special attention to the fact that both Australian and German governments altogether stress the positive feedback loops as they have overcome unprecedented political confrontation among rival cities: Basically, they have encouraged gives-and-takes among major stake-holders. These research findings indicate that the future of new administrative capital construction depends on consensus buildings that can accommodate socio-economic and territorial changes between pros and cons. Although further researches and validations are needed, the system approach presented in this paper could assist Korean decision-makers in developing robust and responsive policy initiatives under uncertainties.

• 자동차안전학회지
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• 제14권2호
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• pp.26-38
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• 2022

This paper proposes multiple RLS and actuator performance index-based adaptive actuator fault-tolerant control and detection algorithms for longitudinal autonomous driving. The proposed algorithm computes the desired acceleration using feedback law for longitudinal autonomous driving. When actuator fault or performance degradation exists, it is designed that the desired acceleration is adjusted with the calculated feedback gains based on multiple RLS and gradient descent method for fault-tolerant control. In order to define the performance index, the error between the desired and actual accelerations is used. The window-based weighted error standard deviation is computed with the design parameters. Fault level decision algorithm that can represent three fault levels such as normal, warning, emergency levels is proposed in this study. Performance evaluation under various driving scenarios with actuator fault was conducted based on co-simulation of Matlab/Simulink and commercial software (CarMaker).