• Tribology and Lubricants
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• v.10 no.4
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• pp.13-26
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• 1994

Effects of resin contents, number of carbonization, graphitization, sliding speed, and oxidation on friction and wear behavior of carbon/carbon composite materials were investigated. Friction and wear tests were carried out under various sliding conditions. An experimental setup was designed and built in the laboratory. Stainless steel disks were used as the counterface material. Friction coefficient, emperature, and wear factor were measured with a data acquisition system. Wear surfaces were observed by the scanning electron microscope. It has been shown that the average friction coefficient was increased with the sliding speed in the range of 1.43~6.10 m/s, but it as decreased in the range of 6.10~17.35 m/s. Specimens prepared by different numbers of carbonization. showed variations in friction coefficient and friction coefficient of the graphitized specimen was the highest. Friction coefficients depended on contribution of the plowing and adhesive components. As the number of carbonization was increased, wear factor was reduced. Wear factor of the graphitized specimens dropped further. In the case of graphitized specimens, sliding speed had a large influence on wear behavior. When the tribological experiments were conducted in nitrogen atmosphere, the wear factor was decreased to two thirds of the wear factor obtained in air. It is obvious that the difference was affected by oxidation. Results of friction and wear tests were applied to a neural network system based on the backpropagation algorithm. A neural network may be a valuable tool for prediction of tribological behavior of the carbon/carbon composite material if ample data are present.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.286-297
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• 2011

A novel converged optical network unit (ONU)-base station (BS) architecture has been contemplated for next-generation optical-wireless networks. It has been demonstrated through high quality studies that data traffic carried by both wired and wireless networks exhibit self-similar and long range dependent characteristics; attributes that classical teletraffic theory based on simplistic Poisson models fail to capture. Therefore, in order to apprehend the proposed converged architecture and to reinforce the provisioning of tightly bound quality of service (QoS) parameters to end-users, we substantiate the analysis of the QoS behavior of the ONU-BS under self-similar and long range dependent traffic conditions using custom queuing which is a common queuing discipline. This paper extends our previous work on priority queuing and brings novelty in terms of presenting performance analysis of the converged ONU-BS under realistic traffic load conditions. Further, the presented analysis can be used as a network planning and optimization tool to select the most robust and appropriate queuing discipline for the ONU-BS relevant to the QoS requirements of different applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7A
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• pp.669-677
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• 2011

Superframe in IEEE 802.15.4 Standard is subdivided into an active period and an inactive period to reduce energy consumption. But communication nodes use same data transmission range in an active period, thus communication nodes spend a lot of energy to send data another nodes. In this paper, we proposed reduce energy consumption algorithm that nodes use different transmission power. Cordinator split transmission area into four group and transmit becon message to nodes. Nodes adjust transmission power according to becon message and wates lowe energy than normal nodes. We proposed energy-efficient cross layer protocol that have different PAN (Personal Area Network) by four range group.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1453-1458
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• 2009

Sensor network for the human approach in a difficult area and a wide range of surveillance and the boundaries for the purpose and mission is the utilization significantly. In this paper we searched important nodes from the surveillance reconnaissance sensor network based on the virtual data. we generated data within the sensor's measurement range in the data transmitted from sensor nodes, and used PCA(Principle Component Analysis) for searching key node. If the important sensor node searched, and we can have easy management and establishing security measures when security problems is happened about nodes. This is for the sensor network in terms of effectiveness and cost-effectively and is directly connected with life span.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1310-1319
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• 2016

Face detection is the first step in a wide range of face applications. However, detecting faces in the wild is still a challenging task due to the wide range of variations in pose, scale, and occlusions. Recently, many deep learning methods have been proposed for face detection. However, further improvements are required in the wild. Another important issue to be considered in the face detection is the computational complexity. Current state-of-the-art deep learning methods require a large number of patches to deal with varying scales and the arbitrary image sizes, which result in an increased computational complexity. To reduce the complexity while achieving better detection accuracy, we propose a fully convolutional network-based face detection that can take arbitrarily-sized input and produce feature maps (heat maps) corresponding to the input image size. To deal with the various face scales, a multi-scale network architecture that utilizes the facial components when learning the feature maps is proposed. On top of it, we design multi-task learning technique to improve detection performance. Extensive experiments have been conducted on the FDDB dataset. The experimental results show that the proposed method outperforms state-of-the-art methods with the accuracy of 82.33% at 517 false alarms, while improving computational efficiency significantly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.430-435
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• 2007

In this paper, we propose an intelligent deployment of sensor network for reliable communication. The proposed method determines optimal transmission range based on the wireless channel characteristics, and searches the optimal number of sensor nodes, and optimal locations with SOFM. We calculate PRR against a distance uses the log-normal path loss model, and decide the communication range of sensor node from PRR. In order to verify the effectiveness of the proposed method, we performed simulations on the searching for intelligent deployment and checking for link condition of sensor network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.61-80
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• 2018

Location information of individual nodes is important in the implementation of necessary network functions. While extensive studies focus on localization techniques in 2D space, few approaches have been proposed for 3D positioning, which brings the location closer to the reality with more complex calculation consumptions for high accuracy. In this paper, an effective range-free localization scheme is proposed for 3D space localization, and the sensitivity of parameters is evaluated. Firstly, we present an improved algorithm (MDV-Hop), that the average distance per hop of the anchor nodes is calculated by root-mean-square error (RMSE), and is dynamically corrected in groups with the weighted RMSE based on group hops. For more improvement in accuracy, we expand particle swarm optimization (PSO) of intelligent optimization algorithms to MDV-Hop localization algorithm, called PMDV-hop, in which the parameters (inertia weight and trust coefficient) in PSO are calculated dynamically. Secondly, the effect of various localization parameters affecting the PMDV-hop performance is also present. The simulation results show that PMDV-hop performs better in positioning accuracy with limited energy.

• Journal of KIISE
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• v.45 no.3
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• pp.303-310
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• 2018

LoRaWAN(Long Range Wide Area Network) is a standard for low-power, long-range, low-speed communication as announced in the LoRa Alliance. LoRaWAN addresses the physical layer and medium access control layer and the technology used in the physical layer is referred to as LoRa. LoRa can be used for remote monitoring and remote control in maritime conditions. However, unlike land, marine environment is not only difficult to construct an infrastructure for service provision, but also difficult to analyze LoRa performance in maritime. In this study, we construct an infrastructure using cloud platform and analyze LoRa link performance in maritime conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.677-686
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• 2012

In the presence of a high power cellular network, picocells are added to a Macro-cell layout aiming to enhance total system throughput from cell-splitting. While because of the different transmission power between macrocell and picocell, and co-channel interference challenges between the existing macrocell and the new low power node-picocell, these problems result in no substantive improvement to total system effective throughput. Some works have investigated on these problems. Pico Cell Range Expansion (CRE) technique tries to employ some methods (such as adding a bias for Pico cell RSRP) to drive to offload some UEs to camp on picocells. In this work, we propose two solution schemes (including cell selection method, channel allocation and serving process) and combine new adaptive frequency partitioning reuse scheme to improve the total system throughput. In the simulation, we evaluate the performances of heterogeneous networks for downlink transmission in terms of channel utilization per cell (pico and macro), call blocking probability, outage probability and effective throughput. The simulation results show that the call blocking probability and outage probability are reduced remarkably and the throughput is increased effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.713-718
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• 2012

Lumber spine range of motion has been used to measure of physical and functional impairment by various tools from a ruler to 3D kinematic devices. However, pre-existing tools have problems in either movement or accuracy and reliability limitations. Accurate devices are limited by fixed space whereas simple devices are limited in measuring complex movements with less accuracy. In order to solve the location, movement and accuracy limitations at once, we have developed a novice measurement device equipped with accelerometer sensor and gyroscope sensor for getting three-dimensional information of motion. Furthermore, Kalman filter was applied to the algorithm to improve accuracy. In addition, RF wireless communication was added for the user to conveniently check measured data in real time. Finally, the measurement method was improved by considering the movement by a reference point. An experiment was conducted to test the accuracy and reliability of the device by conducting a test-retest reliability test. Further modification will be conducted to used the device in various joints range of motion in clinical settings in the future.