• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.157-161
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• 2009

In recent years, there is a remarkable progress in ICTs (Information and Communication Technologies), and then many attempts to apply ICTs to other industries are being made. In the field of disaster managements, ICTs such as RFID (Radio Frequency IDentification) and USN (Ubiquitous Sensor Network) are used to provide safe environments. Actually, various types of early warning systems using USN are now widely used to monitor natural disasters such as floods, landslides and earthquakes, and also to detect human-caused disasters such as fires, explosions and collapses. These early warning systems issue alarms rapidly when a disaster is detected or an event exceeds prescribed thresholds, and furthermore deliver alarm messages to disaster managers and citizens. In general, these systems consist of a number of various sensors and measure real-time stream data, which requires an efficient and rapid data processing technique. In this study, an event-driven architecture (EDA) is presented to collect event effectively and to provide an alert rapidly. A publish/subscribe event processing method to process simple event is introduced. Additionally, a complex event processing (CEP) technique is introduced to process complex data from various sensors and to provide prompt and reasonable decision supports when many disasters happen simultaneously. A basic concept of CEP technique is presented and the advantages of the technique in disaster management are also discussed. Then, how the main processing methods of CEP such as aggregation, correlation, and filtering can be applied to disaster management is considered. Finally, an example of flood forecasting and early alarm system in which CEP is incorporated is presented It is found that the CEP based on the EDA will provide an efficient early warning method when disaster happens.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.1
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• pp.44-47
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• 2016

Real-time PCR was applied to early warning of red tide. For early warning of red tide at $10cells\;mL^{-1}$, Cochlodinium polykrikoides specific real-time PCR was used as a complement of microscopy that has a lower detection sensitivity. C. polykrikoides appeared extensively in Tongyeong, Namhae waters at low densities in the end of June, and early warning of C. polyrkrikoides blooms was issued on 2 August 2015.

• Journal of Climate Change Research
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• v.8 no.2
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• pp.171-175
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• 2017

The purpose of the farmstead-specific early warning service system for weather risk management is to develop custom-made risk management recommendations for individual farms threatened by climate change and its variability. This system quantifies weather conditions into a "weather risk index" that is customized to crop and its growth stage. When the risk reaches the stage where it can cause any damage to the crops, the system is activated and the corresponding warning messages are delivered to the farmer's mobile phone. The messages are sent with proper recommendations that farmers can utilize to protect their crops against potential damage. Currently, the technology necessary to make the warning system more practical has been developed, including technology for forecasting real-time weather conditions, scaling down of weather data to the individual farm level and risk assessments of specific crops. Furthermore, the scientific know-how has already been integrated into a web-based warning system (http://new.agmet.kr). The system is provided to volunteer farmers with direct, one-on-one weather data and disaster warnings along with relevant recommendations. In 2016, an operational system was established in a rural catchment ($1,500km^2$) in the Seomjin river basin.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.273-280
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• 2008

Debris flow has been considered as one of the major natural hazards and possesses tens to hundreds times higher destructive potential than that of slope failure. In the past 5 years, its occurrence frequency was and is likely to increasing due to the global warming. Although various methods such as basin vegetation or structural dams can be implemented to counter measure the debris flow, these methods are not always the right answer to the problem when magnitude of debris flow is far bigger than could be defended. Land use regulations to avoid the hazard or early debris flow warning system to evacuate the expected inundated area can be more economical and practical actions for those cases. In this study, an early debris flow warning system composed of rainfall measuring device, debris flow sensing device and video camera is introduced. The system is designed to issue the warning when rainfall threshold is exceeded or debris flow is sensed by sensing device. Developed monitoring system can be used to cope promptly with the debris flow risk.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.201-207
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• 2007

In some manufacturing industries, there are many situation in which the simultaneous monitoring or control of two or more related quality characteristics is necessary. However, monitoring these two or more related quality characteristics independently can be very misleading. When several characteristics of manufactured component are to be monitored simultaneously, multivariate $x^2$ or $T^2$ control chart can be used. In this paper, establishing a early warning system(EWS) using multivariate control charts to analyze early out-of-control signals in melting process with many quality characteristics was presented. This module which we developed to control several characteristics improved efficiency and effectiveness of process control in the melting process.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.80-90
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• 2022

Currently, the domestic early warning system is issued differently for each disaster, and is operated independently by relevant organizations from central government to local governments. Representative domestic disaster warning systems include disaster broadcasting using CBS(Cell Broadcasting Service) and DMB(Digital Multimedia Broadcasting) Automatic Emergency Alert Service, DITS(Disaster Information Transform System) transmitted and displayed on TV screens, automatic response system, automated rainfall warning system, and disaster message board. However, due to the difference in the method of issuing each emergency alert at the site of an emergency disaster, the alerts are issued at different times for each media, and the delivered content is also not integrated. If these systems are integrated, it is expected that damage to people's property and lives will be minimized by sharing and integrated management of disaster information such as voice, video, and data to comprehensively judge and make decisions about disaster situations. Therefore, in this study, we present a plan for the integration of the disaster warning system along with the analysis of the operation status of the domestic early warning system.

• Journal of Korean Academy of Nursing
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• v.44 no.2
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• pp.219-227
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• 2014

Purpose: To assess whether the Modified Early Warning Score (MEWS) predicts the need for intensive care unit (ICU) transfer for patients with severe sepsis or septic shock admitted to general wards. Methods: A retrospective chart review of 100 general ward patients with severe sepsis or septic shock was implemented. Clinical information and MEWS according to point of time between ICU group and general ward group were reviewed. Data were analyzed using multivariate logistic regression and the area under the receiver operating characteristic curves with SPSS/WIN 18.0 program. Results: Thirty-eight ICU patients and sixty-two general ward patients were included. In multivariate logistic regression, MEWS (odds ratio [OR] 2.02, 95% confidence interval [CI] 1.43-2.85), lactic acid (OR 1.83, 95% CI 1.22-2.73) and diastolic blood pressure (OR 0.89, 95% CI 0.80-1.00) were predictive of ICU transfer. The sensitivity and the specificity of MEWS used with cut-off value of six were 89.5% and 67.7% for ICU transfer. Conclusion: MEWS is an effective predictor of ICU transfer. A clinical algorithm could be created to respond to high MEWS and intervene with appropriate changes in clinical management.

• Journal of the Korean Society of Hazard Mitigation
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• v.4 no.3 s.14
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• pp.9-17
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• 2004

In recent years slope failure due to heavy rainfalls or local downpours usually accompanied by typhoons has increasingly occurred in Korea. Also, the damages caused by slope failure have a tendency to be more disastrous than before. This study has been conducted to prepare an early warning system for slope failure by : (1) analyzing types and causes of slope failure, (2) examining the published evaluation criteria for slope stability, (3) estimating slope stability by considering the properties of slope-forming materials as well as the topographical and geological properties of slopes, and (4) determining the most important variables of affecting the stability of the slope under consideration. The data on the variations of slope conditions measured by an automatic in-situ measurement system and then transmitted to the central analysis system by using an internet. The most important variables can be back-calculated in the central system and compared with the values for the first and second management criteria. These management criteria should be modified and corrected continuously in the future by accumulated data and knowledge related to the early warning system for slope failure.

• Smart Structures and Systems
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• v.23 no.2
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• pp.107-122
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• 2019

As one of the most important parameters in structural health monitoring, structural frequency has many advantages, such as convenient to be measured, high precision, and insensitive to noise. In addition, frequency-change-ratio based method had been validated to have the ability to identify the damage occurrence and location. However, building a precise enough finite elemental model (FEM) for the test structure is still a huge challenge for this frequency-change-ratio based damage detection technique. In order to overcome this disadvantage and extend the application for frequencies in structural health monitoring area, a novel method was developed in this paper by combining the cross-model cross-mode (CMCM) model updating algorithm with the frequency-change-ratio based method. At first, assuming the physical parameters, including the element mass and stiffness, of the test structure had been known with a certain value, then an initial to-be-updated model with these assumed parameters was constructed according to the typical mass and stiffness distribution characteristic of shear buildings. After that, this to-be-updated model was updated using CMCM algorithm by combining with the measured frequencies of the actual structure when no damage was introduced. Thus, this updated model was regarded as a representation of the FEM model of actual structure, because their modal information were almost the same. Finally, based on this updated model, the frequency-change-ratio based method can be further proceed to realize the damage detection and localization. In order to verify the effectiveness of the developed method, a four-level shear building was numerically simulated and two actual shear structures, including a three-level shear model and an eight-story frame, were experimentally test in laboratory, and all the test results demonstrate that the developed method can identify the structural damage occurrence and location effectively, even only very limited modal frequencies of the test structure were provided.

• Smart Structures and Systems
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• v.6 no.4
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• pp.405-421
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• 2010

This paper proposes a method for early warning of hazard for pipelines. Many pipelines transport dangerous contents so that any damage incurred might lead to catastrophic consequences. However, most of these damages are usually a result of surrounding third-party activities, mainly the constructions. In order to prevent accidents and disasters, detection of potential hazards from third-party activities is indispensable. This paper focuses on recognizing the running of construction machines because they indicate the activity of the constructions. Acoustic information is applied for the recognition and a novel pipeline monitoring approach is proposed. Principal Component Analysis (PCA) is applied. The obtained Eigenvalues are regarded as the special signature and thus used for building feature vectors. One-class Support Vector Machine (SVM) is used for the classifier. The denoising ability of PCA can make it robust to noise interference, while the powerful classifying ability of SVM can provide good recognition results. Some related issues such as standardization are also studied and discussed. On-site experiments are conducted and results prove the effectiveness of the proposed early warning method. Thus the possible hazards can be prevented and the integrity of pipelines can be ensured.