• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.315-320
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• 1997

Rule minimization technique adapted from rough set theory was applied to remove redundant knowledge which is not necessary to make a knowledge base. New algorithm to diagnose fault using Improved Fuzzy Cognitive Maps(I-FCMs), and Fuzzy Associative Memory(FAM) is proposed. I-FCM[22] is superior to gathering knowledge from many experts and descries dynamic behaviors of systems very well. I-FCM is not only a knowledge base, but also a inference engine. FAM has learning capability like neural network[12]. Rule minimization and composition of I-FCM and FAM make it possible to construct compact knowledge base and breaks the border between inference engine and knowledge base.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.342-348
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• 2004

As the advent of the Internet, B2B negotiation process on the Internet has been given attention from both researchers and practitioners. However, literature still shows that only structured conditions have been explicitly considered, despite the fact that unstructured conditions should be rendered as well. In this sense, this paper proposes a new negotiation support mechanism to incorporate causal relationships between structured and unstructured conditions in the process of B2B negotiation. Fuzzy cognitive map was used as a main source of causal knowledge as well causal inference engine. A prototype named CAKES-NEGO was developed to perform experiments with an illustrative example. Results revealed the robustness of our proposed negotiation support mechanism.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.41-44
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• 1999

본 논문에서는 PC 응용을 위한 고음질의 한국어 text-to-speech(TTS) 합성 시스템을 개발하였다. 개발된 시스템의 합성방식으로는 음의 고저 조절, 인접음 사이의 연결 처리 및 음색제어 등에서 기존의 PSOLA 방식에 비해 장점을 가지는 정현파 모델 기반의 방식을 채택하였고, 자연스러운 운율 모델링을 위하여 통계적 기법중의 하나인 Classification and regression tree(CART) 방법을 사용하였다. 또한 음소 경계의 불연속성 문제를 줄이기 위한 합성단위로 초성-중성 및 종성 단위를 사용하였고, 다양한 음색표현이 가능하도록 음색제어 기능을 갖추었다. 그리고, 표준 Speech Application Program Interface(SAPI)를 준용한 TTS engine 형태로 구현함으로써 PC 상에서의 응용 프로그램 개발 편의성을 높였다. 합성음의 청취평가 결과 음질의 우수성 및 음색제어 기능의 유효성을 확인할 수 있었다.

• Journal of Industrial Convergence
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• v.18 no.1
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• pp.17-23
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• 2020

This study developed augmented reality contents for assembly of automobile engine parts for blended learning and confirmed the usefulness of educational effects through questionnaire.The curriculum for automobile engine assembly was designed and the shape, location, and assembly order of parts to be assembled according to each curriculum were developed as augmented reality contents. The AR simulations are combined with learner-centered collaborative activities so that students are actively involved in knowledge acquisition. The teachers' role, therefore, shifts. Rather than delivering direct instruction, they take on the role of facilitator, allowing them to personalize learning according to student performance, learning preferences and learning goals. As the responsibility of knowledge acquisition shifts to the students, higher level skills such as complex problem solving, social skills, process skills, systems skills and cognitive abilities are deepened and reinforced.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.100-111
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• 2009

Cognitive radio is an advanced technology for efficient utilization of under-utilized spectrum via spectrum sensing. CR users should move from current allocating channel to empty channel to avoid the interference to the primary user if the primary user is allocating that channel. Thus, CR system cannot support the CR user's QoS(Quaiity of Service). In this paper, we propose dynamic frequency selection method based on Genetic Algorithm with power control. It is to find the optimization channel for satisfying various CR user's needs with the power control method to minimize the CR user's interference to the primary user. And, we propose the Genetic Algorithm(GA) which determines the best configuration for CR communication systems. The computer simulation results show that the proposed method guaranteed the primary user's decodability and the optimized solution for various channel status.

• Korean Journal of Cognitive Science
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• v.13 no.1
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• pp.1-11
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• 2002

In this paper, a test was performed to determine whether words in Anchor Text were appropriate as key words. As a result of the test. there were proper words of high weighting factor, while some others did not even appear in the text. therefore, were not appropriate as key words. In order to resolve this problem. a new method was proposed to extract key words. Using the proposed method, inappropriate key words can be removed so that new key words be set, and then, ranking becomes possible with the TFIDF value as a weighting factor of the key word. It was verified that the new method has higher accuracy compared to the previous methods.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.5
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• pp.55-72
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• 2016

This study aims at providing a methodology for retaining international technology competitiveness, marketable industry, and sustainable promising technology in a field of new growth engine industry such as national unmanned aerial vehicle industry. We draw a result by analysing with tools such as KrKwic, Excel, NetMiner, presenting methods of a Social Network Analysis, sub-group analysis, and cognitive map analysis based on patent data in a field of unmanned aerial vehicle industry. As a result, some future promising technologies are prospected as what worths concentrated investment, such as 'pilot control tech', 'identification of friend or foe tech'.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.70-77
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• 1998

Although many methods of knowledge acquisition has been developed in the exper systems field, such a need form causal knowledge acquisition hs not been stressed relatively. In this respect, this paper is aimed at suggesting a causal knowledge acquisition process, and then investigate the causal knowledge-based inference process. A vehicle for causal knowledge acquisition is FCM (Fuzzy Cognitive Map), a fuzzy signed digraph with causal relationships between concept variables found in a specific application domain. Although FCM has a plenty of generic properties for causal knowledge acquisition, it needs some theoretical improvement for acquiring a more refined causal knowledge. In this sense, we refine fuzzy implications of FCM by proposing fuzzy causal relationship and fuzzy partially causal relationship. To test the validity of our proposed approach, we prototyped a causal knowledge-driven inference engine named CAKES and then experimented with some illustrative examples.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.800-812
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• 2018

In this study, we reviewed recent trends for enhancing human cognitive accessibility to social VR platform. We also proposed a practical method to predict VR sickness and improve the cognitive accessibility. In doing so, we investigated subtle changes in human body sway unconsciously made before, during, and after being exposed to extreme VR experience. The scientific assumption that VR sickness would be correlated with the subtle changes in body sway was validated. We found that participants who showed sensitive changes in the body sway before VR experience, felt more severe VR sickness than others. The findings can be practically applied in predicting susceptibility to VR sickness prior to VR experiences.