• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.611-614
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• 2009

Understanding the severity of the typhoon-induced storm-surge helps in planning reaction and in preventing further disaster. Natural disasters due to the storm-surge are predictable from accurate observations and forecasts from numerical simulations. What we can do is to make intelligent effort to minimize the loss due to the disaster to the most extent with the technology of early warning, forecast and prevention activity. In this paper, we propose the design of GIS-based Web Service System to visualize the time-varying storm-surge's height and wind field data effectively with 3 different kinds of resolution for predict and prevent storm-surge disasters. This system is one of the efforts to provide the storm-surge forecast service to general public and share two-way more helpful information to coastal resident through the Internet.

• Journal of KIISE:Computing Practices and Letters
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• 제14권9호
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• pp.841-849
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• 2008

Natural disaster such as inundation due to the typhoon induced storm-surge has inflicted severe losses on the coastal area. The problem of global warming and sea surface rising has issued and thus influences the increase of frequency and potential power of storm-surge. What we can do is to make intelligent effort to predict and prevent the losses through the early warning and prevention activity from the accurate prediction and forecasting about the time-varying storm-surge height and its arriving time resulted from the numerical simulation with sea observations. In this paper, we developed the web service based GIS-Enabled storm-surge visualization system to predict and prevent the storm-surge disasters. Moreover. for more accurate topography around coastal area and fine-grid storm-surge numerical model, we have accomplished GIS-based coastal mapping through LiDAR measurement.

• Journal of Ecology and Environment
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• 제38권1호
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• pp.119-122
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• 2015

It is very useful and important to see the status and change of necessary parts in a short period through selecting and observing the bioindicator continually to forecast and prepare the future. Especially, living things are so closely related to the environment that the indicator between the environment and living things shows close interrelationship. Also, the indicator related to environment provides information about representative or decisive environmental phenomenon and is used to simplify complicated facts. Considering wide range of background and application including various indicators such as the change-, destruction-, pollution-, and restoration of habitats, climate change, and species diversity, the closest category includes "environmental indicator," "ecological indicator," and "biodiversity indicator." The selection and use of bioindicator is complicated and difficult. The necessary conditions for the indicator selection are flexible and greatly depend on the goals of investigation such as the indicator for biological diversity investigation of specific area, the indicator for habitat destruction, the indicator for climate change, and the indicator for polluted area. It should meet many various conditions to select a good indicator. In this study, eleven selection standards are established based on domestic and overseas studies on bioindicator selection: species with clear classification and ecology, species distributed in geographically widespread area, species that show clear habitat characteristics, species that can provide early warning for a change, species that are easy and economically benefited for the investigation, species that have many independent individual groups and that is not greatly affected by the size of individual groups, species that is thought to represent the response of other species, species that represent the ecology change caused by the pressure of human influence, species for which researches on climate change have been done, species that is easy to observe, appears for a long time and forms a group with many individuals, and species that are important socially, economically, and culturally.

• The Journal of Bigdata
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• 제1권1호
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• pp.85-94
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• 2016

Traditional Anti-Money Laundering (AML) software applications monitor bank customer transactions on a daily basis using customer historical information and account profile data to provide a "whole picture" to bank management. With the advent of Big Data, these applications could be benefited from size, variety, and speed of unstructured data, which have not been used in AML applications before. This study analyses the weaknesses of a bank's current AML systems and proposes an AML systems taking advantage of Big Data. For example, early warning of AML risk can be improved by exposing identities and uncovering hidden relationships through predictive and entity analytics on real-time and outside data such as SNS data.

• Journal of Information Technology Services
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• 제15권4호
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• pp.25-39
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• 2016

The drone is an unmanned aerial vehicle which has no human pilot. Drones can be classified into military drones, commercial drones, and personal drones by usage. Also, drones can be classified from large-sized to nano-sized drone by size and autonomous, remote controlled drone by control type. Especially, military drones can be classified into low-altitude drones, medium-altitude, and high-altitude drones by altitude. Recently, the drone industry is one of the fast growing industries in the world. As drone technologies have become more advanced and cost-effective, Korean government has set its goal to become a top-level country in drone business. However, the government's strict regulation for drone operations is one of the biggest hurdles for the development of the related technologies in Korea and other countries. For example, critical problems for drone delivery can be classified into technical issues and institutional issues. Technical issues include durability, conditional awareness, grasp and release mechanisms, collision avoidance systems, drone operating system. Institutional issues include pilot and operator licensing, privacy rules, noise guidelines, security rules, education for drone police. This study analyzes the trends of the drone industry from the viewpoint of technology and regulation. Also, we define the business areas of drone utilization. Especially, the drone business types or models for public sector are proposed. Drone services or functions promoting public interests need to be aligned with the business reference model of Korean government. To define ten types of drone uses for public sector, we combine the business types of government with the future uses of drones that are proposed by futurists and business analysts. Future uses of drones can be divided into three sectors or services. First, drone services for public or military sectors include early warning systems, emergency services, news reporting, police drones, library drones, healthcare drones, travel drones. Second, drone services for commercial or industrial services include parcel delivery drones, gaming drones, sporting drones, farming and agriculture drones, ranching drones, robotic arm drones. Third, drone services for household sector include smart home drones.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제4권1호
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• pp.7-12
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• 2003

The purpose of testability analysis is to estimate the difficulty of testing a stuck-at fault in logic circuits. A good testability measurement can give an early warning about the testing problem so as to provide guidance in improving the testability of a circuit. There have been researches attempting to efficiently compute the testability analysis. Conventional testability measurements, such as COP and SCOAP, can calculate the testability value of a stuck-at fault efficiently in a tree-structured circuit but may be very inaccurate for a general circuit. The inaccuracy is due to the ignorance of signal correlations for making the testability analysis linear to a circuit size. This paper proposes an efficient method for computing testability analysis, which takes into account signal correlation to obtain more accurate testability. The proposed method includes the algorithm for identifying all reconvergent fanouts in a given n circuit and the gates reachable from them, by which information related to signal correlation is gathered.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2008년도 정보통신설비 학술대회
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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.

• Journal of Convergence for Information Technology
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• 제12권2호
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• pp.37-46
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• 2022

The purpose of this study is to provide basic data onto preparing soft landing plan of future education policy by exploring direction of future education for the common good using big data and keyword network analysis. Based on the big data provided by Textom, data was collected under the keyword 'future education + common Good' and then keyword network analysis was performed. As a result of the research, it was found that 'common good', 'social', 'KAIST future warning', 'measures', 'research', 'future education', 'politics' were common keywords in the social awareness of future education for the common good. The results of this study suggest that the social awareness of future education for the common good is related to factors related to human, physical environment, social response, academic interest, education policy, education plan, and related variables, It was closely related. Based on these results, we suggested implications for the support for the preparation of a soft landing plan of future education for the common good.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2022년도 학술발표회
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• pp.305-305
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• 2022

A better approach for assessing meteorological drought occurrences is increasingly important in mitigating and adapting to the impacts of climate change, as well as strategies for developing early warning systems. The present study defines meteorological droughts as a period with an abnormal precipitation deficit based on monthly precipitation data of 18 gauging stations for the Han River watershed in the past (1974-2015). This study utilizes a Bayesian parameter estimation approach to analyze the effects of climate change on future drought (2025-2065) in the Han River Basin using the Coupled Model Intercomparison Project Phase 6 (CMIP6) with four bias-corrected general circulation models (GCMs) under the Shared Socioeconomic Pathway (SSP)2-4.5 scenario. Given that drought is defined by several dependent variables, the evaluation of this phenomenon should be based on multivariate analysis. Two main characteristics of drought (severity and duration) were extracted from precipitation anomalies in the past and near-future periods using the copula function. Three parameters of the Archimedean family copulas, Frank, Clayton, and Gumbel copula, were selected to fit with drought severity and duration. The results reveal that the lower parts and middle of the Han River basin have faced severe drought conditions in the near future. Also, the bivariate analysis using copula showed that, according to both indicators, the study area would experience droughts with greater severity and duration in the future as compared with the historical period.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2022년도 학술발표회
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• pp.146-146
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• 2022

A flash flood is one of the most hazardous natural events caused by heavy rainfall in a short period of time in mountainous areas with steep slopes. Early warning of flash flood is vital to minimize damage, but challenges remain in the enhancing accuracy and reliability of flash flood forecasts. The forecasters can easily determine whether flash flood is occurred using the flash flood guidance (FFG) comparing to rainfall volume of the same duration. In terms of this, the hydrological model that can consider the basin characteristics in real time can increase the accuracy of flash flood forecasting. Also, the predicted radar rainfall has a strength for short-lead time can be useful for flash flood forecasting. Therefore, using both hydrological models and radar rainfall forecasts can improve the accuracy of flash flood forecasts. In this study, FFG was applied to simulate some flash flood events in the Taehwa river basin by using of SURR model to consider soil moisture, and applied to the flash flood forecasting using predicted radar rainfall. The hydrometeorological data are gathered from 2011 to 2021. Furthermore, radar rainfall is forecasted up to 6-hours has been used to forecast flash flood during heavy rain in August 2021, Wulsan area. The accuracy of the predicted rainfall is evaluated and the correlation between observed and predicted rainfall is analyzed for quantitative evaluation. The results show that with a short lead time (1-3hr) the result of forecast flash flood events was very close to collected information, but with a larger lead time big difference was observed. The results obtained from this study are expected to use for set up the emergency planning to prevent the damage of flash flood.