• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.77-85
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• 2013

The efficient operation and management strategies of reservoirs in irrigation periods of drought events are an essential element for drought planning and countermeasure. Korea Rural Community Corporation has developed the real-time water level observation system of agricultural reservoirs to efficiently operate reservoirs, however, it is not possible to predict drought conditions, and only provides information of current situation. Hence, it is necessary to evaluate accurate irrigation vulnerability and efficiently reservoir operation rules using current water level. In this paper, the improvement methods of reservoir operation planning were developed with water supply vulnerability characteristic curves comparing to automatic water gauge at agricultural reservoirs. The 11 reservoirs were simulated applying the reservoir operation rules which was determined by irrigation vulnerability characteristic curves criteria and real time water level, and evaluated water supply situation in 2012 year. The analysis of results can be identified probabilistic possibility of water supply failures compared with the existing reservoir operation criteria. These results of efficient reservoir operation rules can be achieved enable irrigation planners to optimally manage available water resources for decision making, and contributed to maintain the water supply according to demand strategy for agricultural reservoirs management.

• Journal of Korean Society on Water Environment
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• v.33 no.2
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• pp.130-139
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• 2017

With the need to evaluate accuracy of real-time measurement of cyanobacterial fluorescence to determine cyanobacterial blooms, this research examined 357 paired data (2013-2016) comprising both microscopic toxic cyanobacterial cell counts and concurrent real-time cyanobacterial concentrations at 2 sites (YS1 and YS2) in Yeongsan river. The increase in real-time cyanobacterial concentration was closely associated with the exceedance of 5,000 cyanobacterial cells/ml (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.03-1.12) and 10,000 cells/ml (OR 1.08, 95% CI 1.04-1.12) at YS2 site. The area under the receiver operating characteristic (ROC) curve for the real-time cyanobacterial measurement at the YS2 site was 0.93, which indicates the measurement provides a high accurate detection of cyanobacterial blooms. On the ROC curve, the early alert levels of real-time cyanobacteria ranging $16-23{\mu}g$ chl-a/L would produce acceptable sensitivity of 79% and specificities greater than 90%. The real-time fluorescence measurement was found to be an accurate indicator of cyanobacteria and can serve as a tool for detecting toxic cyanobacterial bloom events in Youngsan river.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.324-332
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• 2010

The majority of event detection in real-time embedded sensor network systems is based on data fusion that uses noisy sensor data collected from complicated real-world environments. Current research has produced several excellent low-level mechanisms to collect sensor data and perform aggregation. However, solutions that enable these systems to provide real-time data processing using readings from heterogeneous sensors and subsequently detect complex events of interest in real-time fashion need further research. We are developing real-time event detection approaches which allow light-weight data fusion and do not require significant computing resources. Underlying the event detection framework is a collection of real-time monitoring and fusion mechanisms that are invoked upon the arrival of sensor data. The combination of these mechanisms and the framework has the potential to significantly improve the timeliness and reduce the resource requirements of embedded sensor networks. In addition to that, we discuss about a privacy that is foundation technique for trusted embedded sensor network system and explain anonymization technique to ensure privacy.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1-6
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• 1992

An autonomous mobile robot has been developed which can follow a travel map drawn on a monitor screen using a software. The robot works as an exhbition guide making announcement regrading the events to take place or introducing the products on display. This mobile robot computes the world position and heading direction through camera image, ultrasonic and infrared sensors in real time using specially designed algorithm. This mobile robot will be exhibited at '93 Tae-Jeon EXPO for an exhibition guide, and will be used in a plant or a hospital for materials handling purposes.

• Neonatal Medicine
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• v.17 no.1
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• pp.1-12
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• 2010

Graphic monitoring assists the clinician at the bedside in several ways. It can be helpful in fine-tuning or adjusting ventilator parameters. Graphic monitoring may help to determine the patient's response to pharmacologic agents. The clinician also has the ability to trend monitored events over a prolonged period of time. The neonatal patient's self respiration, synchrony to ventilator and respiratory efforts can be well recognized with graphic monitoring. Of all, it may enable detection of complications before they become clinically apparent. This article introduces the basics of real-time graphics.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.6
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• pp.373-381
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• 2012

An automatic flow and water quality monitoring system was applied to estimate pollutant loads to an urban stream during storm events in DTV (Daeduk Techno Valley), Daejeon, Korea. The monitoring system consists of rainfall gage, ultrasonic water level meter, water quality sensors for DO, temperature, pH, conductivity, turbidity and automatic water sampler for further laboratory analysis. All data are transmitted through on-line system and the monitoring system is designed to be controlled manually in the field and remotely from laboratory computer. Flow rates were verified with field measurements during storm events and showed good agreements. Automatic sampler was used to collect real time samples and analyzed for BOD, COD, TN, TP, SS and other pollutant concentrations in the laboratory. SWMM (Storm Water Management Model) urban watershed model was applied and calibrated using the observed flow and water quality data for the study area. While flow modeling results showed good agreement for all events, water quality modeling results showed variable levels of agreement. These results indicate that current options in the SWMM model to predict pollutant build up and wash-off effects are not sufficient to satisfy modeling of all the rainfall events under study and thus need further modification. This study showed the automatic monitoring system can be used to provide data to assist further refinement of modeling accuracy. This automatic stormwater monitoring and modeling system can be used to develop basin scale water quality management strategies of urban streams in storm events.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.7-18
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• 2017

Recently, the number of SNS user has rapidly increased due to smart device industry development and also the amount of generated data is exponentially increasing. In the twitter, Text data generated by user is a key issue to research because it involves events, accidents, reputations of products, and brand images. Twitter has become a channel for users to receive and exchange information. An important characteristic of Twitter is its realtime. Earthquakes, floods and suicides event among the various events should be analyzed rapidly for immediately applying to events. It is necessary to collect tweets related to the event in order to analyze the events. But it is difficult to find all tweets related to the event using normal keywords. In order to solve such a mentioned above, this paper proposes A Generation and Matching Method of Normal-Transient Dictionary for realtime topic detection. Normal dictionaries consist of general keywords(event: suicide-death-loop, death, die, hang oneself, etc) related to events. Whereas transient dictionaries consist of transient keywords(event: suicide-names and information of celebrities, information of social issues) related to events. Experimental results show that matching method using two dictionary finds more tweets related to the event than a simple keyword search.

• Water Engineering Research
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• v.5 no.4
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• pp.157-176
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• 2004

This research presents a prototype development and implementation of Decision Support System (DSS) for integrated river basin water management for the flood control. The DSS consists of Relational Database Management System, Hydrologic Data Monitoring System, Spatial Analysis Module, Spatial and Temporal Analysis for Rainfall Event Tool, Flood Forecasting Module, Real-Time Operation of Multi Reservoir System, and Dialog Module with Graphical User Interface and Graphic Display Systems. The developed DSS provides an automated process of alternative evaluation and selection within a flexible, fully integrated, interactive, centered relational database management system in a user-friendly computer environment. The river basin decision-maker for the flood control should expect that she or he could manage the flood events more effectively by fully grasping the hydrologic situation throughout the basin.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1796-1816
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• 2020

The health and safety of elderly and disabled patients who cannot live alone is an important issue. Timely detection of sudden events is necessary to protect these people, and anomaly detection in smart homes is an efficient approach to extracting such information. In the real world, there is a causal relationship between an occupant's behaviour and the order in which appliances are used in the home. Bayesian networks are appropriate tools for assessing the probability of an effect due to the occurrence of its causes, and vice versa. This paper defines different subsets of random variables on the basis of sensory data from a smart home, and it presents an anomaly detection system based on various models of Bayesian networks and drawing upon these variables. We examine different models to obtain the best network, one that has higher assessment scores and a smaller size. Experimental evaluations of real datasets show the effectiveness of the proposed method.