• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.307-316
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• 2016

A multiple radar system is comprised of early warning radar for fast detection of a target and air defense radar for precision intercept. For this reason, target take-over process is required between the two radars. The target take-over should be performed at an appropriate time by consideration of stable tracking and effective fire control. In this paper, operation characteristics of multiple radar system are analyzed and target take-over time determination method using estimation of target tracking performance is proposed for high-velocity targets. The proposed method is validated with ballistic target defense scenarios in the developed integrated simulator.

• Journal of the Society of Disaster Information
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• v.10 no.1
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• pp.105-115
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• 2014

In this research, we developed video analytic algorithms to detect water-level automatically and a system for proactive alarming using intelligent CCTV cameras. We applied these algorithms and a system to test-beds and verified for practical use. We made camera-selection policies and operation plans to keep the detection accuracy high and to optimize the suitability for the ever-changing weather condition, while the environmental factors such as camera shaking and weather condition can affect to detection accuracy. The estimation result of algorithms showed 90% detection accuracy for all CCTV camera types. For water level detection, NIR camera performed great. NIR camera performed over 95% accuracy in day or night, suitable in natural weather condition such as shaking condition, fog, and low light, needs similar installment skills with common cameras, and spends only 15% high cost. As a result, we practically tested water level detection algorithms and operation system based on intelligent CCTV camera. Furthermore, we expect the positive evidences when it is applied for public use.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.29-37
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• 2007

In this paper, we propose a new real-time ground motion monitoring system using MMA data which can be gathered more earlier than generic seismic data transmission method. Proposed system receives maximum, minimum and average data based on 20sps which is sent from station on every second continuously. And it calculates a PGA as a quantity of ground motion then visualizes that data to monitor the ground motion around whole country. To verify PGA data from MMA data, we checked Mu-dan-jang earthquake data of China on 2002/6/29. The proposed system was inspected by using log file of Oh-dae-san earthquake data on 2007/1/20. As results of experiment, the proposed system is proven to detect the event(earthquake) faster then existing method and to produce a useful quantitative information.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.262-267
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• 2008

Recently, landslides frequently occur on natural slope and/or man-made cut slope during periods of intense rainfall. With a rapidly increasing population on or near steep terrain, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide monitoring systems have been developed throughout the world. In this paper, a simple landslide detection system that enables people to escape the endangered area is introduced. The system is focused on the debris flows which happen frequently during periods of intense rainfall. The system is based on the wireless sensor network (WSN) that is composed of wireless sensor nodes, gateway, and remote server system. Wireless sensor nodes and gateway are deployed by commercially available Microstrain G-Link products. Five wireless sensor nodes and one gateway are installed at the test slope for detecting ground movement. The acceleration and inclination data of test slope can be obtained, which provides a potential to detect landslide. In addition, thresholds to determine whether the test slope is stable or not are suggested by a series of numerical simulations, using geotechnical analysis software package. It is obtained that the alarm should be issued if the x-direction displacement of sensor node is greater than 20mili-meters and the inclination of sensor node is greater than 3 degrees. It is expected that the landslide detection method using wireless senor network can provide early warning where landslides are prone to occur.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.334-334
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• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.268-275
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• 2005

Early predictions of crop yields call provide information to producers to take advantages of opportunities into market places, to assess national food security, and to provide early food shortage warning. The objectives of this study were to identify the most useful parameters for estimating yields and to compare two model selection methods for finding the 'best' model developed by multiple linear regression. This research was conducted in two 65ha corn/soybean rotation fields located in east central South Dakota. Data used to develop models were small temporal variability information (STVI: elevation, apparent electrical conductivity $(EC_a)$, slope), large temporal variability information (LTVI : inorganic N, Olsen P, soil moisture), and remote sensing information (green, red, and NIR bands and normalized difference vegetation index (NDVI), green normalized difference vegetation index (GDVI)). Second order Akaike's Information Criterion (AICc) and Stepwise multiple regression were used to develop the best-fitting equations in each system (information groups). The models with $\Delta_i\leq2$ were selected and 22 and 37 models were selected at Moody and Brookings, respectively. Based on the results, the most useful variables to estimate corn yield were different in each field. Elevation and $EC_a$ were consistently the most useful variables in both fields and most of the systems. Model selection was different in each field. Different number of variables were selected in different fields. These results might be contributed to different landscapes and management histories of the study fields. The most common variables selected by AICc and Stepwise were different. In validation, Stepwise was slightly better than AICc at Moody and at Brookings AICc was slightly better than Stepwise. Results suggest that the Alec approach can be used to identify the most useful information and select the 'best' yield models for production fields.

• Journal of the Korean Society for Marine Environment & Energy
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• v.16 no.2
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• pp.138-142
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• 2013

As an early warning system to reduce the damage of aquacultured mollusks due to low salinity water, we investigated the possibility of a biomonitoring system measuring the shell valve movement (SVM) of Pacific oyster (Crassostrea gigas) by using the Hall element sensor. In high salinity water of 27 psu, SVMs of Pacific oyster showed spikes which mean a relatively fast closing condition after opened condition of average 10-15 mm, and then the SVM showed back to opening condition slower than closing speed. In water salinity of 20-27 psu, the SVMs were similar to that of 27 psu. However, below 17 psu, it showed abnormal valve movements such as spending more time for shell closure. In 10 psu, we could not detected SVMs due to closed condition during experiment periods. Thus, if we quickly detect abnormal environmental variations like low salinity using bio-monitoring of SVM, it may be contribute to increased productivity by dramatically reducing damages in aquaculture.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.407-414
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• 2014

The Internet is a highly distributed and complex system consisting of billion devices and has become the field of various kinds of conflicts during the last two decades. As a matter of fact, various actors utilise the Internet for illicit purposes, such as for performing distributed denial of service attacks (DDoS) and for spreading various types of aggressive malware. Despite the fact that numerous services provide information regarding the threat level of the Internet, they are mostly based on information acquired by their sensors or on offline statistical sampling of various security applications (antivirus software, intrusion detection systems, etc.). This paper introduces proactive threat observatory system (PROTOS), an open-source early warning system that does not require a commercial license and is capable of estimating the threat level across the Internet. The proposed system utilises both a global and a local approach, and is thus able to determine whether a specific host is under an imminent threat, as well as to provide an estimation of the malicious activity across the Internet. Apart from these obvious advantages, PROTOS supports a large-scale installation and can be extended even further to improve the effectiveness by incorporating prediction and forecasting techniques.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.125-137
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• 2024

Background: The Korea Risk Information Surveillance System (K-RISS) was developed to enable the early detection of food and drug safety-related issues. Its goal is to deliver real-time risk indicators generated from ongoing food and drug risk monitoring. However, the existing K-RISS system suffers under several limitations. Objectives: This study aims to augment K-RISS with more detailed indicators and establish a severity standard that takes into account structural changes in the daily time series of K-RISS values. Methods: First, a Delphi survey was conducted to derive the required weights. Second, a control chart, commonly used in statistical process controls, was utilized to detect outliers and establish caution, attention, and serious levels for K-RISS values. Furthermore, Bai and Perron's method was employed to determine structural changes in K-RISS time series. Results: The study incorporated 'closeness to life' and 'sustainability' indicators into K-RISS. It obtained the necessary weights through a survey of experts for integrating variables, combining indicators by data source, and aggregating sub K-RISS values. We defined caution, attention, and serious levels for both average and maximum values of daily K-RISS. Furthermore, when structural changes were detected, leading to significant variations in daily K-RISS values according to different periods, the study systematically verified these changes and derived respective severity levels for each period. Conclusions: This study enhances the existing K-RISS system and introduces more advanced indicators. K-RISS is now more comprehensively equipped to serve as a risk warning index. The study has paved the way for an objective determination of whether the food safety risk index surpasses predefined thresholds through the application of severity levels.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.317-325
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• 2015

An adequate downscaling of synoptic forecasts is a prerequisite for improved agrometeorological service to rural areas in South Korea where complex terrains and small farms are common. In this study, geospatial schemes based on topoclimatology were used to scale down the Korea Meteorological Administration (KMA) temperature forecasts to the local scale (~30 m) across a rural catchment. Then, using these schemes, local temperatures were estimated at 14 validation sites at 0600 and 1500 LST in 2013/2014 and were compared with the observations. The estimation errors were substantially reduced for both 0600 and 1500 LST temperatures when compared against the uncorrected KMA products. The improvement was most notable at low lying locations for the 0600 temperature and at the locations on west- and south-facing slopes for the 1500 LST temperature. Using the downscaled real-time temperature data, a pilot service has started to provide the field-specific weather information tailored to meet the requirements of small-scale farms. For example, the service system makes a daily outlook on the phenology of crop species grown in a given field using the field-specific temperature data. When the temperature forecast is given for next morning, a frost risk index is calculated according to a known relationship of phenology and frost injury. If the calculated index is higher than a pre-defined threshold, a warning is issued and delivered to the grower's cellular phone with relevant countermeasures to help protect crops against frost damage.