• Journal of Korea Multimedia Society
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• v.15 no.2
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• pp.242-249
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• 2012

Recently, value added location based service and convergence monitoring and control system is growing. The cases include increasing usage of smart-phone for taking picture, wireless network, GPS and digital map. Especially, Smart-phone is appropriate for using image information and location information. However it is possible to be exploited for forgery and manipulation. So we experimented on transferring modified data on the smart-phone as image and location information in EXIF and researched the technology for data verification. In addition, we have designed security monitoring and control prototype considering axis-address matching analysis used geocoding, watermarking verification, encryption.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.671-674
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• 2007

USN (Ubuquitous Sensor Network) identifies that networks are able to gather information from various kinds of sensors with RF. In the USN, it is important that sensor nodes deliver stable data by overcoming limited transmission distance and by setting optimum routes. In this paper, we propose a method to overcome the limited distance of sensor nodes using Wireless Mesh Networks. With this method, environmental monitoring system for u-farm support stable data transmission by applying MAP of Wireless Mesh Networks.

• Journal of the Korean Society of Systems Engineering
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• v.11 no.2
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• pp.41-49
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• 2015

Industrial safety is one of the crucial agenda for Government as well as Manufacturing Industry. To cope with the needs, a great deal of policies and technical implementation have been proposed and implemented. With a great increasing attention on the Industry 4.0 and Smart Factory, industrial safety has received as a crucial agenda by the manufacturing industry in particular. Up until now, almost all of them have been made from the environmental aspects, rather than operator or workers. In this paper, we present our research results how to increase the workers' safety via smart factory technology, such as IoT and CPS. Our approach has been to see the problem from SE perspectives, to draw the real issues from the various stakeholders, and define how to solve the problem based on the emerging technologies. The developed systems can give conceptual framework for the 'smart' industrial safety system by providing solution architecture for how to monitor the location of workers, and moving equipments, and generate solutions how to avoid safety problems between them if detected.

• Progress in Superconductivity and Cryogenics
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• v.11 no.3
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• pp.26-30
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• 2009

Korea Superconducting Tokamak Advanced Research(KSTAR) device is composed of 30 superconducting magnets, magnet structure, vacuum vessel, cryostat, current feeder system, and etc. KSTAR device is operated in the cryogenic temperature and high magnetic field. We install about 800 sensors - temperature sensors, stain gages, displacement gages, hall sensors - to monitor the thermal, mechanical, electrical status of KSTAR during operation. As a tremendous numbers of sensors should be installed for monitoring the KSTAR device, the method of effective installation was developed. The sensor test was successfully carried out to check its reliability and its reproduction in the cryogenic temperature. The sensor signal is processed by PXI-based DAQ system and communicated with central control system via machine network and is shown by Operator Interface(OPI) display in the main control room. In order to safely operate the device, any violations of mechanical & superconductive characteristic of the device components were informed to its operation system & operator. If the monitored values exceed the pre-set values, the protective action should be taken against the possible damage. In this paper, the system composition, operation criteria, operation result were presented.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.89-101
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• 2008

The most used tool for quality control is control chart in manufacturing industry. But it has limitations at current situation where most of manufacturing facilities are automated and several manufacturing processes have interdependent relationship such as CCM assembly line. To Solve problems, we propose quality management system based on data mining that are consisted of monitoring system where it monitors flows of processes at single window and feature extraction system where it predicts the yield of final product and identifies which processes have impact on the quality of final product. The quality management system uses decision tree, neural network, self-organizing map for data mining. We hope that the proposed system can help manufacturing process to produce stable quality of products and provides engineers useful information such as the predicted yield for current status, identification of causal processes for lots of abnormality.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.824-830
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• 2010

PLC_Zigbee system, implemented in a previous study, uses ZigBee Node based on PLC (Power Line Communication). The weak point of the system is that the long distance powerline communication and PLC is impossible to use in the areas where the powerline is not installed. In this paper, we added CDMA (Code Division Multiple Access) module using a data transfer method of SMS (Short Message Service) and XBee of WSN (Wireless Sensor Network) module to the previous system, and got around the restriction of place and environment of PLC system through the interfacing of each communication media. We, thus, implemented a wide range of real monitoring system.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.946-951
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• 2004

ITIS is applied to the several tunnel construction sites in Korea. Tunnel construction properties which are acquired from these sites are transferred to information management server(SQL 2000 server)by client application program in real time. Access permission to DB server depends on the user's roles. Some functions which cannot be embodied in SQL Server are serviced through XML and GMS server is used for spatial data based on GIS part. This system is supposed to give engineers the advantages which are not only easy handling of the program and computerized documentation on every information during construction but also analyzing the acquired data in order to predict the structure of ground and rock mass to be excavated later and show the guideline of construction. Neung-Dong tunnel and Mu-Gua express way tunnel are now under construction and with this system they have 3D visualized map of the geology and tunnel geometry and accumulate database of construction information such as tunnel face mapping results, special notes and pictures of construction and 3D monitoring data, all matters on the stability of rock bolts and shotcrete, and so on. Ground settlement prediction program included in ITIS, based on the artificial neural network(ANN) and supported by GIS technology is applying to the subway tunnel. This prediction tool can make it possible to visualize the ground settlement according to the excavation procedures by contouring the calculated result on 3D GIS map and to assess the damage of buildings in the vicinity of construction site caused by ground settlement.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.5
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• pp.453-460
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• 2005

Since late 1970s, water quality monitoring had been performed in Korea by various agencies according to their own needs and objectives. Lacking of consistency in principles, such diverse operation has been producing difficulties in management of information on water quality parameters. These difficulties resulted from the fact that the expansion of monitoring networks had been based not on systematic methodology with considerations on scientifically established planning objectives but on personal experiences and subjective judgments in locating monitoring stations. This study aimed, therefore, to develop a selection methodology for locating monitoring stations to provide various informations on water quality to satisfy various monitoring objectives such as understanding short and long term trends of water quality, monitoring violations to water quality standards, identifying external causes and sources affecting water quality changes, supporting utilization of water resources, examining short-term variations in water quality through a concentrated investigation, estimating pollution loads from each unit watershed, supporting water quality modeling, and establishing informative systems for water resources management. Also, we applied the proposed methodology and presented an improved expansion plan for water quality monitoring networks in the Han River.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1661-1670
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• 2016

In this paper, we present a risk prediction system and customized evacuation pathfinding algorithm in fire scenarios. For the risk prediction, we apply a multi-level clustering mechanism using collected temperature at sensor nodes throughout the network in order to predict the temperature at the time that users actually evacuate. Based on the predicted temperature and its reliability, we suggest an evacuation pathfinding algorithm that finds a suitable evacuation path from a user's current location to the safest exit. Simulation results based on FDS(Fire Dynamics Simulator) of NIST for a wireless sensor network consisting of 47 stationary nodes for 1436.41 seconds show that our proposed prediction system achieves a higher accuracy by a factor of 1.48. Particularly for nodes in the most reliable group, it improves the accuracy by a factor of up to 4.21. Also, the customized evacuation pathfinding based on our prediction algorithm performs closely with that of the ground-truth temperature in terms of the ratio of safe nodes on the selected path, while outperforming the shortest-path evacuation with a factor of up to 12% in terms of a safety measure.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.837-848
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• 2018

Monitoring technology of machining has a long history since unmanned machining was introduced. Despite the long history, many researchers have presented new approaches continuously in this area. Sound based machine fault diagnosis is the process consisting of detecting automatically the damages that affect the machines by analyzing the sounds they produce during their operating time. The collected sound is corrupted by the surrounding work environment. Therefore, the most important part of the diagnosis is to find hidden elements inside the data that can represent the error pattern. This paper presents a feature extraction methodology that combines various digital signal processing and pattern recognition methods for the analysis of the sounds produced by tools. The magnitude spectrum of the sound is extracted using the Fourier analysis and the band-pass filter is applied to further characterize the data. Statistical functions are also used as input to the nonlinear classifier for the final response. The results prove that the proposed feature extraction method accurately captures the hidden patterns of the sound generated by the tool, unlike the conventional features. Therefore, it is shown that the proposed method can be applied to a sound based automatic diagnosis system.