• Korean Journal of Artificial Intelligence
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• v.6 no.1
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• pp.1-10
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• 2018

Compressed Air is an important energy source used in most factories nowadays. The automation trend using air compressor has been gradually increasing with the interest of the 4th industry in recent years. With the air compressor system, it is possible to construct the device at low cost and easily achieve automation and energy saving. In addition, With trend of FA, miniaturation and light weight manufacturing trend expand their use in the electronics, medical, and food sectors. Research method is to design the technology for the remote control of the following information as USN base. Development of flexible sensing module from real time observation module for fusion of IT technology in compressed air systems, design and manufacture of flexible sensing module, and realiability assessment. Design of real-time integrated management system for observation data of compressed air system - Ability to process observation data measured in real time into pre-processing and analysis data. This study expects unconventionally decreasing effect of energy cost that takes up 60~70% of air compressor layout and operation and maintenance management cost through USN(Ubiquitous Sensor Network) technology by using optimum operational condition from real time observation module. In addition, by preventing maintenance cost from malfunction of air compressor beforehand, maintenance cost is anticipated to cut back.

• Convergence Security Journal
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• v.15 no.1
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• pp.83-89
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• 2015

In the wide area surveillance system including many CCTVs, application for remote realtime monitoring is designed and implemented. The applications using Xcode provide secure administrator interface from headquarters. Through the efficient and intuitive interface, it delivers real-time context reports and inference results. For the user convenience, it includes push alarm of events, SNS, Media streaming service for real-time monitoring uses Wirecast and Wowza media server. Wowza stream engine provides URL accommodating development specification. Mobile devices can receive real-time stream data. Performance evaluation in the processing is provided.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.118-123
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• 2009

In this paper, we propose packet selection and significance based interval allocation algorithm for real-time streaming service. In real-time streaming of inter-frame (and layer) coded video, minimizing packet loss does not imply maximizing QoS. It is true that packet loss adversely affects the QoS but one single packet can have more impact than several other packets. We exploit the fact that the significance of each packet loss is different from the frame type it belongs to and its position within GoP. Using packet dependency and PSNR degradation value imposed on the video from the corresponding packet loss, we find each packet's significance value. Based on the packet significance, the proposed algorithm determines which packets to send and when to send them. The proposed algorithm is tested using publicly available MPEG-4 video traces. Our scheduling algorithm brings significant improvement on user perceivable QoS. We foresee that the proposed algorithm manifests itself in last mile connection of the network where intervals between successive packets from the source and to the destination are well preserved.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.277-285
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• 2011

Real-time multimedia streaming over the Internet is rapidly increasing with the popularity of user-created contents, Web 2.0 trends, and P2P (peer-to-peer) delivery support. While many homes today are broadband-enabled, the quality of experience (QoE) of a user is still limited due to frequent interruption of media playout. The vulnerability of TCP (transmission control protocol), the popular transport-layer protocol for streaming in practice, to the packet losses, retransmissions, and timeouts makes it hard to deliver a timely and persistent flow of packets for online multimedia contents. This paper presents TCP-real-time online multimedia environment (ROME), a novel transport-layer framework that allows the establishment and coordination of multiple many-to-one TCP connections. Between one client with multiple home addresses and multiple co-located or distributed servers, TCP-ROME increases the total throughput by aggregating the resources of multiple TCP connections. It also overcomes the bandwidth fluctuations of network bottlenecks by dynamically coordinating the streams of contents from multiple servers and by adapting the streaming rate of all connections to match the bandwidth requirement of the target video.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.11
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• pp.1055-1060
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• 2006

High temperature superconducting(HTS) power cable is expected to be used for power transmission lines supplying electric power for densely populated cities in the near future. Since HTS power cable is capable of the high current density delivery with low power loss, the cable size can be compact comparing with the conventional cable whose capacity is same. In this paper, the authors propose the real time simulation method which puts a teal HTS wire into the simulated 22.9 kV utility grid system using Real Time Digital Simulator (RTDS). For the simulation analysis, test sample of HTS wire was actually manufactured. And the transient phenomenon of the HTS wire was analyzed in the simulated utility power grid. This simulation method is the world first trial in order to obtain much better data for installation of HTS power device into utility network.

• Journal of KIBIM
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• v.8 no.3
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• pp.12-19
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• 2018

The research aims to find implications of machine learning and urban big data as a way to construct the flexible transportation network system of smart city by responding the urban context changes. This research deals with a problem that existing a bus headway model is difficult to respond urban situations in real-time. Therefore, utilizing the urban big data and machine learning prototyping tool in weathers, traffics, and bus statues, this research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data is gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is implemented by the machine learning tool (RapidMiner Studio) and conducted several tests for bus delays prediction according to specific circumstances. As a result, possibilities of transportation system are discussed for promoting the urban efficiency and the citizens' convenience by responding to urban conditions.

• Progress in Superconductivity and Cryogenics
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• v.8 no.3
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• pp.54-58
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• 2006

In this paper, authors developed a real-time simulation algorithm for the power device application of HTS(High Temperature Superconducting) wire by using Real Time Digital Simulator(RTDS). At present, in order to extend the power capacity of some area where has a serious problem of power quality. especially metropolitan complex city, there are so many problems such as right of way for power line routes. space for downtown substations. and the environmental protection, etc. HTS technology can be useful to overcome this problem. Recently, according to the advanced HTS technology, the power application is being researched well. Simulation is required for safety before installation of HTS power cable, a fabrication model used at the power system simulation. This paper describes a real time digital simulation method for the application of HTS wire to power device. For the simulation analysis, test sample of HTS wire was actually manufactured. And the transient phenomenon of the HTS wire was analysed in the simulated utility power grid. This simulation method is the world first trial in order to obtain much better information for installation of HTS power device into a utility network.

• Korean Journal of Hazardous Materials
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• v.3 no.1
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• pp.28-36
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• 2015

In early 2011, the Fukushima nuclear power plant had greater damage due to earthquake in Japan, and the awareness of safety has increased. In particular, special response systems should be required to handle disaster situations in plant sites which are likely to occur for large disasters. In this study, a program is designed to set up optimum escape routes, by a smart phone application, when a disaster situation occurs. This program could get information of the cumulative damage from sensors and display the escape route of the smallest damage in real-time on the screen. Utilizing our application in real-time evacuation has advantage in reducing cumulative damage. The optimal evacuation route, focusing on horizontal path, is calculated based on getting the data of fire, detected radioactivity and hazardous gas. Thus, using our application provides information of optimal evacuation to people who even can not hear sensor alarms or do not know geography, without requiring additional costs except fixed sensors or server network deployment cost. As a result, being informed of real-time escape route, the user could behave rapidly with suitable response to individual situation resulting in improved evacuation than simply reacting to existing warning alarms.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1273-1281
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• 1993

Estimation of daily and seasonal evaportranspiration is essential for water resource planning irrigation feasibility study, and real-time irrigation water management . This paper is to evaluate the applicability of neural networks to the estimation of evapotranspiration . A neural network was developed to forecast daily evapotranspiration of the rice crop. It is a three-layer network with input, hidden , and output layers. Back-propagation algorithm with delta learning rule was used to train the neural network. Training neural network wasconducted usign daily actural evapotranspiration of rice crop and daily climatic data such as mean temperature, sunshine hours, solar radiation, relative humidity , and pan evaporation . During the training, neural network parameters were calibrated. The trained network was applied to a set of field data not used in the training . The created response of the neural network was in good agreement with desired values. Evaluating the neural networ performance indicates that neural network may be applied to the estimation of evapotranspiration of the rice crop.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.3
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• pp.333-343
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• 2009

Tactical Information Communication Network(TICN) is a concept-type integrated Military Communication system that enables precise command control and decision making by unifying the diversified military communication network and conveying diverse range of battle field information on real-time, at right place at right time. TICN is designed to advance into high speed, large capacity, long distance wireless relay transmission. To support mobility in battlefield environments, the application of Ad-hoc networking technology to its wireless communication has been examined. Ad-hoc network is consist of mobile nodes and nodes in the network depends on the cooperation of other nodes for forwarding of packets. In this context, some non-cooperating nodes may delay forwarding of packets or drop the packets. This may hamper the network as a whole and disrupt communication between the cooperating nodes. To solve this problem, we present a solution with a Node Weight Management Server(NWMS), which manages each node's weight according to its behavior in local area. When the NWMS detects misbehaving node, it increases the node's weight. If the node's weight exceeds a predefined threshold then the NWMS broadcasts the node's information into network to isolate the misbehaving node from the network. These mechanisms show that they are highly effective and can reliably detect a multitude of misbehaving node.