• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.1-5
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• 2015

Recently, RF energy harvesting technology is a promising technology for small-size IoT(Internet of Things) devices such as sensor to resolve battery scarcity problem. When applied to existing cognitive radio networks, this technology can be expected to increase network throughput through the increase of cognitive user's operating time. This paper proposes a optimal channel-selection policy for RF energy harvesting CR networks model where cognitive users in harvesting zone harvest ambient RF energy from transmission by nearby active primary users and the others in non-harvesting zone choose the channel and communicate with their receiver. We consider that primary users and secondary users are distributed as Poisson point processes and contact with their intended receivers at fixed distances. Finally we can derive the optimal frame duration, transmission power and density of secondary user from the proposed model that can maximize the secondary users's throughput under the given several conditions and suggest future directions of research.

• The Magazine for Energy Service Companies
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• s.37
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• pp.92-93
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• 2005

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1255-1261
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• 2016

Recently, the energy harvesting technology in which energy is collected from the wireless signal which is transmitted by mobile communication devices, has been considered as a novel way to improve the life time of wireless sensors by mitigating the lack of power supply problem. In this paper, we consider the optimal sensing time and power allocation problem for cognitive radio systems, where the energy efficiency of secondary user is maximized while the constraint are satisfied, using the optimization technique. Based on the derived optimal solutions, we also have proposed an iterative resource allocation algorithm in which the optimal power and sensing time allocation can be found without excessive computations. The simulation results confirm that the proposed scheme achieves the optimal performance and it outperforms the conventional resource allocation schemes in terms of energy efficiency while the constraints are guaranteed to be satisfied.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.1-6
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• 2017

Recent researches on radio frequency energy harvesting networks(RF-EHNs) with limited energy resource like battery have been focusing on the development of a new scheme that can effectively extend the whole lifetime of a network to semipermanent. In order for considerable increase both in the amount of energy obtained from radio frequency energy harvesting and its charging effectiveness, it is very important to design a network that supports energy harvesting and data transfer simultaneously with the full consideration of various characteristics affecting the performance of a RF-EHN. In this paper, we proposes an interference-based charging aware routing protocol(ICARP) that utilizes interference information and charging time to maximize the amount of energy harvesting and to minimize the end-to-end delay from a source to the given destination node. To accomplish the research objectives, this paper gives a design of ICARP adopting new network metrics such as interference information and charging time to minimize end-to-end delay in energy harvesting wireless networks. The proposed method enables a RF-EHN to reduce the number of packet losses and retransmissions significantly for better energy consumption. Finally, simulation results show that the network performance in the aspects of packet transmission rate and end-to-end delay has enhanced with the comparison of existing routing protocols.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.141-145
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• 2017

Spectrum sensing is a critical functionality of Cognitive Radio(CR) systems and the CR systems can be applied to RF energy harvesting systems to improve an energy harvesting rate. There are number of spectrum sensing techniques. One of techniques is energy detection. Energy detection is the simplest detection method and is the most commonly used. But, energy detection has a hidden terminal problem in real wireless communication, because of secondary user (SU) can be affected by frequency fading and shadowing. Cooperative spectrum sensing can solve this problem using spatial diversity of SUs. But it has a problem of increasing data by processing multiple secondary. So, we propose the system model using adaptive spectrum sensing algorithm and system model is simulated. This algorithm chooses sensing method between single energy sensing and cooperative energy according to the received signal's Signal to Noise Ratio (SNR) from Primary User (PU). The simulation result shows that adaptive spectrum sensing has an efficiency and improvement in CR systems.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.350-355
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• 1998

감정을 표현하는 음성 합성 시스템을 구현하기 위해서는 감정음성에 대한 분석이 필요하다. 본 논문에선,s 평상, 화남, 기쁨, 슬픔의 네 가지 감정에 대한 음성 데이터에 대해 음절 세그먼트, 라벨링을 행한 감정 음성 데이터베이스를 구축하였고, 감정표현이 음성에 영향을 미치는 요인에대하여, 운율, 음운적인 요소로 나누어 분석하였다. 또한 기본 주파수, 에너지, 음절지속시간에 대한 분석과 감정 음성의기본 주파수, 에너지, 음절지속시간, 스펙트럼 포락의 인지 정도를 측정하기 위하여 평상 음성에 감정 음성의 운율 요소를 적용하는 음성을 합성하여 ABX 방법으로 평가하였다. 그 결과, 기본 주파수의변화가 73.3%, 음절지속시간은 43.3% 로 올바른 감정으로 인지되었으며, 특히 슬픈 감정에서 음절지속시간은 76.6%가 올바르게 감정을 나타내는 것으로 인지되었다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.3
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• pp.8-13
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• 2012

In this paper, we investigate cooperative spectrum sensing scheme for sensor network-aided cognitive radio systems with energy harvesting capability. In the proposed model, each sensor node harvests ambient energy from environment such as solar, wind, mechanical vibration, or thermoelectric effect. We propose adaptive cooperative spectrum sensing scheme in which each sensor node adaptively carries out energy detection depending on the residual energy in its energy storage and then conveys the sensing result to the fusion center. From simulation results, we show that the proposed scheme minimizes the false alarm probability for given target detection probability by adjusting the number of samples for energy detector.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.236-244
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• 2016

Theoretical review of the PR activities was initiated using Lasswell's (1948) SMCRE model to evaluate the indicators of the collaborative programs with NGO and the outcome of the activities promoting energy-saving programs. The indicators were then set based on a case study by Nho Younhwoo (2012). This paper aims to develop evaluation indicators for the activities promoting energy-saving programs and evaluate how energy consumers recognize the reputations of PR agencies (sender), PR content (message), PR media outlets (channel), and the degree to which such PR activities induce energy-saving behaviors.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.45-49
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• 2015

In this paper, we proposed not specturm sensing but also save energy without consume energy of secondary network that spectrum sensing of cognitive applied energy harvesting scheme. Algorithms of sensing and harvesting is determine active or idle of primary network, compares the amount of energy that is harvested by energy harvesting scheme with the threshold. If secondary network to send a message and primary network is active, by changing frequency to use the spectrum. Further, if secondary network have no message, continues energy harvest. Therefore, spectrum sensing applied energy harvesting scheme, energy of secondary network is remove waste and charge energy, efficiency and utilization of cognitive network can be increase.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.424-434
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• 2020

This paper describes an algorithm that calculates Absolute Sound Level (ASL) for contents platform. ASL is a single volume representing individual sound sources and is a concept designed to integrate and utilize the sound level units in digital sound source and physical domain from a speaker in practical areas. For this concept to be used in content platforms and others, it is necessary to automatically derive the ASL without having to go through a hearing of mastering engineers. The key parameters of which a person recognizes the representative sound level of an individual single sound source are the areas of "frequency, maximum energy, energy variation coefficient, and perceived energy distribution," and the ASL was calculated through the normalizing of the weights.