• ETRI Journal
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• 제34권6호
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• pp.892-899
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• 2012

We analyze a wideband spectrum in a cognitive radio (CR) network by employing the optimal adaptive multiband sensing-time joint detection framework. This framework detects a wideband M-ary quadrature amplitude modulation (M-QAM) primary signal over multiple nonoverlapping narrowband Gaussian channels, using the energy detection technique so as to maximize the throughput in CR networks while limiting interference with the primary network. The signal detection problem is formulated as an optimization problem to maximize the aggregate achievable secondary throughput capacity by jointly optimizing the sensing duration and individual detection thresholds under the overall interference imposed on the primary network. It is shown that the detection problems can be solved as convex optimization problems if certain practical constraints are applied. Simulation results show that the framework under consideration achieves much better performance for M-QAM than for binary phase-shift keying or any real modulation scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권6호
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• pp.3029-3045
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• 2017

The main processes of a cognitive radio system include spectrum sensing, spectrum decision, spectrum sharing, and spectrum conversion. Experimental results show that these stages introduce a time delay that affects the spectrum sensing accuracy, reducing its efficiency. To reduce the time delay, the frequency spectrum prediction was proposed to alleviate the burden on the spectrum sensing. In this paper, the deep recurrent neural network (DRNN) was proposed to predict the spectrum of multiple time slots, since the existing methods only predict the spectrum of one time slot. The continuous state of a channel is divided into a many time slots, forming a time series of the channel state. Since there are more hidden layers in the DRNN than in the RNN, the DRNN has fading memory in its bottom layer as well as in the past input. In addition, the extended Kalman filter was used to train the DRNN, which overcomes the problem of slow convergence and the vanishing gradient of the gradient descent method. The spectrum prediction based on the DRNN was verified with a WiFi signal, and the error of the prediction was analyzed. The simulation results proved that the multiple slot spectrum prediction improved the spectrum efficiency and reduced the energy consumption of spectrum sensing.

• 한국지능시스템학회논문지
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• 제13권4호
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• pp.491-498
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• 2003

The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using FCM(Fuzzy Cognitive Maps) that can detect intrusion by the DoS attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The SPuF(Syn flooding Preventer using Fussy cognitive maps) model captures and analyzes the packet informations to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance comparison, the "KDD′99 Competition Data Set" made by MIT Lincoln Labs was used. The result of simulating the "KDD′99 Competition Data Set" in the SPuF model shows that the probe detection rates were over 97 percentages.

• 한국산업정보학회논문지
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• 제21권5호
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• pp.55-72
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• 2016

본 연구는 국내 무인항공기산업과 같은 신성장동력산업의 국제적 기술 경쟁력 확보와 시장성 확보 및 산업성장이 가능한 미래유망 기술을 도출하는 방법론을 제시하는 것이다. 이에 본 연구는 KrKwic, Excel, NetMiner등의 분석 툴을 활용하여 무인항공기산업 분야의 특허데이터를 대상으로 동시출현 단어를 활용한 소셜네트워크분석과 하위그룹분석, 인지지도분석 방법을 제시하였다. 그 결과, '비행조정 기술', '피아식별 기술' 등은 향후 유망한 기술로 선정하여 집중 투자할 필요성이 큰 기술이라 볼 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5335-5353
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• 2019

The definition of the bandwidth efficiency (BE) of cognitive cooperative network (CCN) is the ratio between a number of the licensed slot(s) or sub-channel(s) used by the unlicensed users to transmit a single data packet from the unlicensed transmitter to unlicensed destination, and from unlicensed relay(s) to unlicensed destination. This paper analyzes and improves the BE in the underlay CCN with a new reactive relay selection under interference and power constraints. In other words, this paper studies how unlicensed cooperative users use the licensed network slot(s) or sub-channel(s) efficiently. To this end, a reactive relay selection method named as Relay Automatic Repeat Request (RARQ) is proposed and utilized with a CCN under interference and power constraints. It is shown that the BE of CCN is higher than that of cooperative transmission (CT) due to the interference and power constraint. Furthermore, the BE of CCN is affected by the distance of the interference links which are between the unlicensed transmitter to the licensed destination and unlicensed relay to the licensed destination. In addition, the BE for multiple relays selection over a CCN under interference and power constraints is also analyzed and studied, and it is shown that the BE of CCN decreases as the number of relays increases.

• 인지과학
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• 제2권2호
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• pp.205-220
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• 1990

물질적으로 존재하는 모든 실체는 질료인과 형상인을 갖춘 개별 물체로 실재하면서 어떤 기능을 할 \ 수도 있고,동력인과 기능인을 갖춘 비물체적 양상으로 실재하면서 기능망(functional network)으로서 형상을 가질 수도 있다.기능망은 신경망,신경기능망,심리기능망 등 차원을 다르게 하면서 상하로 연관된 계층으 이루고 있으며 심리기능망 안에서도 비언어적 기능망,언어적 기능망이 구별되어 차원적 언어기능을 가능하게 하는 것으로 볼수 있다.이러한 기능망의 실재성은 신경과학과 인공지능학의 발전에 따라 확인, 수정,보완될 수 있을 것이다.

• 컴퓨터교육학회논문지
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• 제8권6호
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• pp.33-44
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• 2005

본 연구에서는 인지수준과 동기적 측면을 동시에 고려한 마인드 툴인 의미망 프로그램이 인지수준에 따른 학업 성취도와 동기에 미치는 효과를 알아보고, 교육현장에 보다 효과적으로 활용되도록 하는데 목적을 두고 수행되었다. 연구 결과 인지수준별 동기 전략을 적용한 마인드 툴을 활용한 수업은 과도기 학생들의 생물 학업성취도를 향상시켰고, 학습 내용에 시각적인 효과를 보여줌으로써 학생들의 인지구조에 새로운 지식을 효과적으로 연결시켜 주의집중과 자신감을 높일 수 있었다. 또한 형식적 조작기 학생들 보다 과도기 학생들의 의미망 형성에 더 효과적인 것으로 나타났고, 학습내용이 구조지식으로 조직화되어 학습내용의 파지에 효과적이었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권5호
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• pp.1286-1302
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• 2012

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권11호
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• pp.3711-3730
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• 2014

Cognitive radio networks (CRNs) have emerged as a promising solution to enhance spectrum utilization by using unused or less used spectrum in radio environments. The basic idea of CRNs is to allow secondary users (SUs) access to licensed spectrum, under the condition that the interference perceived by the primary users (PUs) is minimal. In CRNs, the channel availability is uncertainty due to the existence of PUs, resulting in intermittent communication. Transmission control protocol (TCP) performance may significantly degrade in such conditions. To address the challenges, some transport protocols have been proposed for reliable transmission in CRNs. In this paper we survey the state-of-the-art transport protocols for CRNs. We firstly highlight the unique aspects of CRNs, and describe the challenges of transport protocols in terms of PU behavior, spectrum sensing, spectrum changing and TCP mechanism itself over CRNs. Then, we provide a summary and comparison of existing transport protocols for CRNs. Finally, we discuss several open issues and research challenges. To the best of our knowledge, our work is the first survey on transport protocols for CRNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권9호
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• pp.2154-2172
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• 2013

A centralized cognitive radio (CR) network is proposed and its system capacity is studied. The CR network is designed with power control and multi-user scheduling schemes to support best-effort traffics under peak interference power constraints. We provide an analytical framework to quantify its system capacity, taking into account various key factors such as interference constraints, density of primary users, cell radius, the number of CR users, and propagations effects. Furthermore, closed-form formulas are derived for its capacities when only path loss is considered in the channel model. Semi-analytical expressions for the capacities are also given when more realistic channel models that include path loss, shadowing, and small-scale fading are used. The accuracy of the proposed analytical framework is validated by Monte Carlo simulations. Illustrated with a practical example, the provided analytical framework is shown to be useful for the strategic planning of centralized CR networks.