• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.440-448
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• 2021

This paper presents problems of network technology in smart grid and implements a blockchain-based LoRa multi-hop network to solve them. Since some smart grid applications are operated in harsh environments, it is difficult to establish communication infrastructure. We propose a LoRa network with multi-hop using the Flooding routing protocol. Smart grid environment composes an independent network using various power grid protocols depending on the application. Since this has a problem that an independent infrastructure must be established for each network, a single gateway device supports multiple power grid protocols to implement a method for network integration. Lastly, the author applied Hyperledger-based blockchain to the LoRa network to ensure the integrity of data in a smart grid environment, and strengthened security by physically distributing it. After constructing the three suggestions on the actual test bed, we confirmed that the network operates normally through experiments.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.1-8
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• 2012

In this paper, we consider an efficient protocol for the multi-hop relay transmission on a sensor network which can be utilized in a ubiquitous environment. More specifically, we propose an efficient relaying protocol for the distance and position recognition on the proposed sensor network which performs with the differentially bi-orthogonal chirp spread spectrum (DBO-CSS) in the industrial, scientific and medical (ISM) bands. For an efficient networking access, we design and implement four different packet structures, zone information packet, hop information packet, tag information packet, and application serial packet. Additionally, we also propose an efficient position recognition algorithm. Finally, for verification of our proposed protocol's efficiency, we build the testbed system which consists of $15m{\times}15m$ multi-cell and 10 hops in the network.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.401-410
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• 2014

This paper presents a high-efficiency concurrent dual-band Class-E power amplifier(PA) that is based on a multi-harmonic matching network(MHMN). The proposed MHMN controls the impedance at 1.3 GHz, 2.1 GHz, and their second and third harmonics, respectively, by using transmission lines only rather than switches or lumped components. The dual-band Class-E PA is implemented using Avago ATF-50189 GaAs p-HEMT. The PA exhibits a measured output power of 27.1 dBm and 25.7 dBm, a power gain of 6.1 dB and 4.7 dB, and a drain efficiency of 71.2 % and 60.1 % at 1.3 GHz and 2.1 GHz, respectively.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.113-122
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• 2011

Social Network Service(SNS) has become a hot trend as a web service which helps users construct social relationships in the web and enables online communication. The information about user activities and behaviors obtained from the SNSs is expected to be an useful knowledge source for other services such as recommendation services. Most of previous researches on SNS rely on analyzing overall network topology and surveying the activities in a one-dimensional aspect. This paper propose a system for measuring multi-dimensional interaction through the activities in a SNS. The proposed system delivers an unified profile (consisting of profile and multi-dimension interaction) model from user-activities in Twitter.com. At the experimental section, some meaningful perspectives on a set of the unified profiles are described.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2843-2852
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• 2013

In the nested mobile network environment, the mobile node selects one of multiple mobile routers. The MR(Mobile Router) by existing top-down or bottom-up methods may not be the optimal MR if the numbers of mobile nodes and routers are substantially increased, and the scale of the network is increased drastically. Since an inappropriate MR decision causes handover or binding renewal to mobile nodes, determining of the optimal MR is important for efficiency. In this paper, we propose an algorithm that decides on the optimal MR using MR QoS(Quality of Service) information, and we describe how to understand the various structured MLP(Multi-Layered Perceptron) based on the algorithm. In conclusion, we prove the ability of the suggested neural network for a nesting mobile network through the performance analysis of each learned MLP.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.59-70
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• 2022

Water distribution systems (WDSs) are a representative infrastructure injecting chlorine to disinfect the pathogenic microorganisms and supplying water from sources to consumers. Also, WDSs prescribe to maintain the usual standard (0.1-4.0 mg/L) of residual chlorine. However, the user's usage pattern, water age, network shape, and type affect the hydraulic features (i.e. nodal pressure, pipe velocity) and water quality features (i.e., the residual chlorine concentration). Therefore, this study developed an optimization approach for optimizing WDSs considering water quality-hydraulic factors using Multi-objective Harmony Search (MOHS). The design cost and the system resilience were applied as the design objective functions, and the nodal pressure and the concentration of residual chlorine are used as constraints. The derived optimal designs through this approach were analyzed according to network characteristics such as the network shapes and type. These optimal designs can meet the safety of economic and water quality aspects to increase user acceptance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4259-4271
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• 2016

With the increased popularity of IEEE 802.11 WLAN, the density of the WLAN devices per access point has also increased, resulting in throughput performance degradation. One of the solutions to the problem is improving the protocol efficiency by a using multi-round contention scheme. This paper first discusses how to estimate the number of contending stations in a WLAN network by using minimum elapsed backoff counter values that can be easily monitored by each station. An approximate closed form expression is derived for the number of active contending stations using the smallest backoff counter value in the network. We then apply this result to adapt the number of contending rounds according to the network loading level to enhance the throughput performance of a multi-round contention scheme. Through simulation, we show that the accuracy of the estimation algorithm depends on the contention parameters of W and the number of backoff counter observing samples, and found a reasonable value for each parameter. We clearly show that our adaptive multi-round contention scheme outperforms the standard contention scheme that uses a fixed number of rounds.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.9
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• pp.50-55
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• 2011

This research is to apply the adaptive control of neuron networks for the real-time attitude control of Multi-articulated robot. Multi-articulated robot is expressed with a complicated mathematical model on account of the mechanic, electric non-linearity which each articulation of mechanism has, and includes an unstable factor in time of attitude control. If such a complex expression is included in control operation, it leads to the disadvantage that operation time is lengthened. Thus, if the rapid change of the load or the disturbance is given, it is difficult to fulfill the control of desired performance. In this research we used the response property curve of the robot instead of the activation function of neural network algorithms, so the adaptive control system of neural networks constructed without the information of modeling can perform a real-time control. The proposed adaptive control algorithm generated control signs corresponding to the non-linearity of Multi-articulated robot, which could generate desired motion in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.149-156
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• 2011

This paper reveals a distance estimation algorithm based on multi-code ultrasonic and wireless sensor network. For measuring the distances among the sensor nodes, each ultrasonic transmitter transmits multi-code ultrasonic signal simultaneously. Receivers use cross correlation method to separate the coded signals. The information of measured distances is broadcasted to each sensor node by wireless sensor network. The wireless sensor network measures the distance among the sensor nodes using the received signal strength of the broadcasting. The multi-code ultrasonic have a limitation of measurable distance. And the received signal strength is affected from an environment. This paper measures a distance using ultrasonic and a received signal strength in short range. These measured data are applied to the least square estimation algorithm. By the expansion of the fitting curve, a distance measurement in long range using the received signal strength is compensated. The coupled system reduce the error to an acceptable level.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.176-190
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• 2018

This paper presents a novel convolutional neural network based multi-feature fusion learning method for non-rigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.