• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.73-78
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• 2016

In wireless sensor networks, sensors have capabilities of sensing and wireless communication, computing power and collect data such as sound, movement, vibration. Sensors need to communicate wirelessly to send their sensing data to other sensors or the base station and so they are vulnerable to many attacks like garbage packet injection that cannot be prevented by using traditional cryptographic mechanisms. To defend against such attacks, a behavior-based attack detection is used in which some specialized monitoring nodes overhear the communications of their neighbors(normal nodes) to detect illegitimate behaviors. It is desirable that the total sensing area of normal nodes covered by monitoring nodes is as large as possible. The previous researches have focused on selecting the monitoring nodes so as to maximize the number of normal nodes(node coverage), which does not guarantee that the area sensed by the selected normal nodes is maximized. In this study, we have developed an algorithm for selecting the monitoring nodes needed to cover the maximum sensing area. We also have compared experimentally the covered sensing areas computed by our algorithm and the node coverage algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.494-501
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• 1999

In this research, ANN modeling method of SMES unit is developed for stability analysis, and the optimal site is selected to maximize stabilization effect of SMES unit. The ANN is trained by learning data which is obtained through the application of complex test function into the traditional mathematical mode. In order to verify the validity of proposed modeling method, fault data of sample power system is applied to both the traditional and the ANN models. When the response of traditional and proposed models are compared, the average error for the active and reactive power are 2.51[%], and 0.24[%], respectively. From the comparison, the relevance of proposed method is validated. For the transient stability analysis, an application method of the proposed model is presented, and the transient stability performance index, which describes system stabilization effect of SMES at disturbance, is also suggested, and optimal site selection method of SMES is presented. In the viewpoint of the voltage stability, system stabilization criterion of local bus is presented from P­V curve, and then optimal site which can maximize the voltage stabilization of the whole power system, is decided from the proposed voltage stability performance index.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.551-560
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• 2004

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms (GAs). The proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series), A comparative analysis reveals that the proposed SOFPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literatures.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.1
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• pp.103-110
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• 1998

The modeling of load characteristics is a difficult problem because of uncertainty of load. This research uses artificial neural networks which can approximate nonlinear problem to represent load characteristics. After the selection of typical load, active and reactive power for the variation of voltage and frequency is obtained from experiments. We constructed and learned ANN based on these data for component load identification. The learned ANN identified load characteristics for other voltage and/or frequency variation. In addition, the results of component load identification are presented to demonstrate the potentiality of the proposed method.method.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.231-236
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• 2012

For real-time wireless sensor network applications, it is essential to provide different levels of quality of service (QoS) such as reliability, low latency, and fault-tolerant traffic control. To meet these requirements, an (m,k)-firm based real-time routing protocol has been proposed in our prior work, including a novel local transmission status indicator called local DBP (L_DBP). In this paper, a fault recovery scheme for (m,k)-firm real-time streams is proposed to improve the performance of our prior work, by contributing a delay-aware forwarding candidates selection algorithm for providing restricted redundancy of packets on multipath with bounded delay in case of transmission failure. Each node can utilize the evaluated stream DBP (G_DBP) and L_DBP values as well as the deadline information of packets to dynamically define the forwarding candidate set. Simulation results show that for real-time service, it is possible to achieve both reliability and timeliness in the fault recovery process, which consequently avoids dynamic failure and guarantees meeting the end-to-end QoS requirement.

• Journal of Communications and Networks
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• v.13 no.5
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• pp.421-427
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• 2011

Problems encountered in IEEE 802.11 medium access control (MAC) design are interferences from neighboring or hidden nodes and collision from simultaneous transmissions within the same contention floors. This paper presents the selective decoding schemes in MAC protocol for multiple input multiple output ad-hoc networks. It is able to mitigate interferences by using a developed minimum mean-squared error technique. This interference mitigation combined with the maximum likelihood decoding schemes for the Alamouti coding enables the receiver to decode and differentiate the desired data streams from co-channel data streams. As a result, it allows a pair of simultaneous transmissions to the same or different nodes which yields the network utilization increase. Moreover, the presented three decoding schemes and time line operations are optimally selected corresponding to the transmission demand of neighboring nodes to avoid collision. The selection is determined by the number of request to send (RTS) packets and the type of clear to send packets. Both theoretical channel capacity and simulation results show that the proposed selective decoding scheme MAC protocol outperforms the mitigation interference using multiple antennas and the parallel RTS processing protocols for the cases of (1) single data stream and (2) two independent data streams which are simultaneously transmitted by two independent transmitters.

• The Journal of Korea Robotics Society
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• v.1 no.1
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• pp.58-65
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• 2006

The emotional interface is essential technology for the robot to provide the proper service to the user. In this research, we developed emotional components for the service robot such as a neural network based facial expression recognizer, emotion expression technologies based on 3D graphical face expression and joints movements, considering a user's reaction, behavior selection technology for emotion expression. We used our humanoid robots, AMI and AMIET as the test-beds of our emotional interface. We researched on the emotional interaction between a service robot and a user by integrating the developed technologies. Emotional interface technology for the service robot, enhance the performance of friendly interaction to the service robot, to increase the diversity of the service and the value-added of the robot for human. and it elevates the market growth and also contribute to the popularization of the robot. The emotional interface technology can enhance the performance of friendly interaction of the service robot. This technology can also increase the diversity of the service and the value-added of the robot for human. and it can elevate the market growth and also contribute to the popularization of the robot.

• Journal of Korea Technology Innovation Society
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• v.7 no.1
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• pp.64-88
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• 2004

This paper aims at investigating which factors play important roles in selecting government's new core IT industries and how competitive they are. We surveyed 6 competitiveness factors and 17 IT industries for the expert group. The logit and probit models were estimated and SWOT analysis was performed. The empirical results show that government put emphasis on marketability, externality and technology, not publicity, when selecting IT new core industry. The skilled human resources turn out to be a threat factor in the government selected IT new core industries such as home-network, third generation semi-conductor. Therefore, training or education system for skilled labors is required to develop and nurture such industries. The contribution to small medium venture industry and publicity are lower in the several industries such as intelligent service robots, post PC, embodied S/W, next generation battery, which are selected by government, not by standardized data based criterion. in such industries, marketabilities, technology, skilled human resources are threats factors to such industries. Therefore every effort for enhancing the marketability and R&D investment and education system for skilled labor are necessary to develop the industries.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.465-482
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• 2015

IEEE 802.11p is a standard MAC protocol for wireless access in vehicular environments (WAVEs). If a packet collision happens when a safety message is sent out, IEEE 802.11p chooses a random back-off counter value in a fixed-size contention window. However, depending on the random choice of back-off counter value, it is still possible that less important messages are sent out first while more important messages are delayed longer until sent out. In this paper, we present a new scheme for safety message scheduling, called the enhanced message priority mechanism (EMPM). It consists of the following two components: the benefit-value algorithm, which calculates the priority of the messages depending on the speed, deceleration, and message lifetime; and the back-off counter selection algorithm, which chooses the non-uniform back-off counter value in order to reduce the collision probability and to enhance the throughput of the highly beneficial messages. Numerical results show that the EMPM can significantly improve the throughput and delay of messages with high benefits when compared with existing MAC protocols. Consequently, the EMPM can provide better QoS support for the more important and urgent messages.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.3
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• pp.91-96
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• 2008

An image scalablity function is noted as technology to embody One Source-Multi-use's Image division by the network Bandwidth and diversification of resolution of reception terminal recently. In MPEG present H.264/MPEG-4 AVC that do to standardization of SVC (Scalable Video Coding) that know go and SVC can offer space time SNR scalability. But, encoding that do scalable usually is known that encoding efficiency drops than encoding that do rain scalable during time and treatise that see. Examine technique to plan improvement of management quality as that aim to time, SNR scalability in treatise that see so and change FGS (Fine Granular Scalability) function that offer SNR scalability that do about scalability's particle size and encoding efficiency relation by SVC to foundation.