• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.86-88
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• 2004

Personal Robot System in developing, have a module architecture, each module are connected through variety network system like ethernet, WLAN (802.11), IEEE 1394 (firewire), bluetooth, CAN, or RS-232C. In developing personal robot system. We think that the key of robot performance is interoperablity among modules. Each network protocol are well connected in the view of network system for the interoperability. So we make a bridging architecture that can routing converting, and transporting packets with matching each network's properties. Furthermore, we suggest a advanced design scheme for realtime / non-realtime and control signal (short, requiring hard-realtime) / multimedia data (large, requiring soft-realtime).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5669-5684
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• 2018

The new mobile edge network architecture has been required for an increasing amount of traffic, quality requirements, advanced driver assistance system for autonomous driving and new cloud computing demands on highway. This article proposes a hierarchical cloud computing architecture to enhance performance by using adaptive data load distribution for buses that play the role of edge computing server. A vehicular dynamic cloud is based on wireless architecture including Wireless Local Area Network and Long Term Evolution Advanced communication is used for data transmission between moving buses and cars. The main advantages of the proposed architecture include both a reduction of data loading for top layer cloud server and effective data distribution on traffic jam highway where moving vehicles require video on demand (VOD) services from server. Through the description of real environment based on NS-2 network simulation, we conducted experiments to validate the proposed new architecture. Moreover, we show the feasibility and effectiveness for the connected car media service on highway.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.47-54
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• 2022

We analyze and compare the structure of the networks of Netflix, Disney+, and OCN, which are forerunners in OTT market, on Twitter. This study employs NodeXL pro as a visualization software package for social network analysis. As a result of the comparison with values of Vertices, Connected Components, Average Geodesic Distance, Average Betweenness Centrality, and Average Closeness Centrality. Netflix has comparative advantages at Vertices, Connected Components, and Average Closeness Centrality, OCN at Average Geodesic Distance, and Disney+ at Average Betweenness Centrality. Netflix has a more appropriate social network for influencer marketing than Disney+ and OCN. Based on the analysis results, the purpose of this study is to explain the structural differences in the social networks of Netflix, Disney+, and OCN in terms of influencer marketing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.571-581
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• 2022

Wireless sensor networks use the concept of connected dominating sets that can form virtual backbones for effective routing and broadcasting. In this paper, we propose an optimization algorithm that configures a connected dominating sets in order to balance the load of nodes to increase network lifetime and to perform effective routing. The proposed optimization algorithm in this paper uses the metaheuristic method of tabu search algorithm, and is designed to balance the number of dominatees in each dominator in the constituted linked dominance set. By constructing load-balanced connected dominating sets with the proposed algorithm, it is possible to extend the network lifetime by balancing the load of the dominators. The performance of the proposed tabu search algorithm was evaluated the items related to load balancing on the wireless sensor network, and it was confirmed in the performance evaluation result that the performance was superior to the previously proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1142-1147
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• 2015

As a method to increase the scalability and efficiency of wireless sensor networks, a scheme to construct networks hierarchically has received considerable attention among researchers. Researches on the methods to construct wireless networks hierarchically have been conducted focusing on how to select nodes such that they constitute a backbone network of wireless network. Nodes comprising the backbone network should be connected themselves and can cover other remaining nodes. A problem to find the minimum number of nodes which satisfy these conditions is known as the minimum connected dominating set (MCDS) problem. The MCDS problem is NP-hard, therefore there is no efficient algorithm which guarantee the optimal solutions for this problem at present. In this paper, we propose a novel multi-start local search algorithm to solve the MCDS problem efficiently. For the performance evaluation of the proposed method, we conduct extensive experiments and report the results.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.60-65
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• 2018

In this paper, a covariance matrix and modulogram are proposed for realizing amphibian sound classification using CNN (Convolutional Neural Network). First of all, a database is established by collecting amphibians sounds including endangered species in natural environment. In order to apply the database to CNN, it is necessary to standardize acoustic signals with different lengths. To standardize the acoustic signals, covariance matrix that gives distribution information and modulogram that contains the information about change over time are extracted and used as input to CNN. The experiment is conducted by varying the number of a convolutional layer and a fully-connected layer. For performance assessment, several conventional methods are considered representing various feature extraction and classification approaches. From the results, it is confirmed that convolutional layer has a greater impact on performance than the fully-connected layer. Also, the performance based on CNN shows attaining the highest recognition rate with 99.07 % among the considered methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.930-938
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• 2007

Captions which appear in images include information that relates to the images. In order to obtain the information carried by captions, the methods for text extraction from images have been developed. However, most existing methods can be applied to captions with fixed height of stroke's width. We propose a method which can be applied to various caption size. Our method is based on connected components. And then the edge pixels are detected and grouped into connected components. We analyze the properties of connected components and build a neural network which discriminates connected components which include captions from ones which do not. Experimental data is collected from broadcast programs such as news, documentaries, and show programs which include various height caption. Experimental result is evaluated by two criteria : recall and precision. Recall is the ratio of the identified captions in all the captions in images and the precision is the ratio of the captions in the objects identified as captions. The experiment shows that the proposed method can efficiently extract captions various in size.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.487-494
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• 2006

By development of the superhigh speed network and the Networked appliance, a home network environment was equipped quickly around the cyber apartment. The home network environment provides the abundant family life style which numerous appliance and tools are connected with the network. Recently it is caused by with appearance of the Networked appliance which is connected with the network, the service demand is augmented to hacking, wrong operation, breakdown, crime prevention in home automation, fire, and break-in. This paper planned and proposed the integrated crisis management service model in the environment of home network and Networked appliance. Namely, it classifies the Networked appliance crisis management service and it defines a crisis management message with the XML. The message where the crisis situation occurs is notified and controlled in wireless PDA or the hand phone or the specific authorization.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.516-518
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• 2000

This paper presents a methodology for effective control of fuel cell devices connected to the electric utility distribution network. A controller is designed for a fuel cell power plant to assist the conventional generators to damp out oscillations, which is possible by utilizing the fast response characteristic of fuel cells. Computer model of the controller is proposed and its effectiveness is proved by a sample test. Fuel cell devices can be used to improve power system stability when these are connected to a distribution system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1371-1373
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• 2005

Recently, preparing the problems in connection with energy and environment, grid-connected power systems have been intensively researched in the world. In general, the output power of grid-connected inverter (GCI) contains noisy components of inverter switching frequency. Moreover, pre-existing grid voltage disturbances degrade the output power quality. The objective of this paper is to make a GCI output high quality power. A robust current control scheme using neural network is presented in thispaper. To show the feasibility of the proposed scheme, some simulation results are provided.