• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.479-479
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• 2021

최근 기상이변으로 인한 자연재해 발생이 증가하고 있고, 그에 따라 도시의 재난 대응력 강화가 국내에서는 물론 국제적으로도 중요한 이슈가 되고 있다. 특히 쇠퇴지역은 재난재해 발생 시 인적·물적 피해가 일반 지역 보다 상대적으로 크며, 복구에도 많은 시간과 예산이 소요되므로 대응책 마련을 위한 도시재생지역의 정밀한 재난재해의 위험성 분석 기술이 필요하다. 이에 본 연구에서는 도시재생사업 대상지(311개)에 대한 재난재해 유형별 위험성 및 회복성을 종합적으로 분석하는 종합진단 기법을 개발하고, 이를 적용한 프로토타입 시스템을 개발하였다. 재난재해의 범위는 「재난 및 안전관리 기본법」을 준용하여 이에 도시재생사업 시행에 영향을 받아 재난재해 발생에 따른 위험정도가 변화할 가능성이 높은 자연재해 (폭우, 폭염, 폭설, 강풍, 지진)5종과 사회재난 (화재, 붕괴, 폭발) 3종 총 8종으로 정의하였다. 종합진단 기법은 기후변화에 관한 정부간 협의체(IPCC) 위험도 평가 방법을 준용하여 위험요소 (위해성·취약성·노출성)와 대비·대응요소 (회복성)로 구분하고, 전문가 자문회의를 거쳐 재난재해에 특히 취약한 쇠퇴지역의 특성을 반영할 수 있는 종합진단지수 산정식을 개발하였다. 또한 쇠퇴지역 재난재해 종합진단 시스템은 도시재생 업무를 수행하는 사용자가 신속히 정보를 분석하고 활용에 용이하도록 Web-GIS 기반으로 설계하였으며, 종합진단 기법에 의해 산정된 분석결과를 100m × 100m 격자 단위의 등급으로 가시화한다. 분석 결과는 지속적인 연구 개발을 통해 최적의 도시재생사업 의사결정 지원 서비스를 위한 기초 분석 자료로 연계하여 활용되며, 분석 DB는 클라우드 서비스 기반의 도시재생 데이터 플랫폼을 통해 공유된다.

• Spatial Information Research
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• v.19 no.4
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• pp.21-31
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• 2011

As large scaled natural or man-made disasters being increased, the demand for rapid responses for such emergent situations also has been ever-increasing. These responses need to acquire spatial information of each individual site rapidly for more effective management of the situations. Therefore, we are developing a close-range real-time aerial monitoring system based on a low altitude unmanned helicopter. This system can acquire airborne sensory data in real-time and generate rapidly geospatial information. The system consists of two main parts: aerial and ground parts. The aerial part includes an aerial platform equipped with multi-sensor(cameras, a laser scanner, a GPS receiver, an IMU) and sensor supporting modules. The ground part includes a ground vehicle, a receiving system to receive sensory data in real-time and a processing system to generate the geospatial information rapidly. Development and testing of the individual modules and subsystems have been almost completed. Integration of the modules and subsystems is now in progress. In this paper, we w ill introduce our system, explain intermediate results, and discuss expected outcome.

• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.775-788
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• 2006

Many disaster monitoring systems are constantly studied to prevent disasters such as environmental pollution, the breaking of a tunnel and a building, flooding, storm earthquake according to the progress of wireless telecommunication, the miniaturization of terminal devices, and the spread of sensor network. A disaster monitoring system can extract information of a remote place, process sensor data with rules to recognize disaster situation, and provide work for preventing disaster. However existing monitoring systems are not enough to predict and prevent disaster, because they can only process current sensor data through utilizing simple aggregation function and operators. In this paper, we design and implement a disaster prevention system to predict near future dangerous area through using outside sensor network and spatial Information. The provided prediction technique considers the change of spatial information over time with current sensor data, and indicates the place that could be dangerous in near future. The system can recognize which place would be dangerous and prepare the disaster prevention. Therefore, damage of disaster and cost of recovery would be reduced. The provided disaster prevention system and prediction technique could be applied to various disaster prevention systems and be utilized for preventing disaster and reducing damages.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.145-154
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• 2014

The road network becomes more complex and extensive. Therefore, the inconveniences are caused in accordance with the time delay of the restoration of damaged roads, demands for excessive costs on information collection, and limitations on acquisition of damage information of the roads. Recently, road centric spatial information is gathered using mobile multi sensor system for road inventory. But expensive MMS(Mobile Mapping System) equipments require high maintenance costs from beginning and takes a lot of time in the data processing. So research is needed for continuous maintenance by collecting and displaying the damaged information on a digital map using low cost mobile camera system. In this research we aim to develop the techniques for mosaic with a regular ground sample distance using successive image from oblique camera on a vehicle. For doing this, mosaic image is generated by estimating the homography of high resolution oblique image, and the ground sample distance and appropriate overlap are analyzed using high resolution aerial oblique images which contain resolution target. Based on this we have proposed the appropriate overlap and exposure interval for mobile road inventory system.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.12
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• pp.723-732
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• 2017

As the development of ICT technology, in order to solve the problem of scattered water information's availability, WINS(Water management Information Networking System) by the Ministry of Land, Infrastructure and Transport was established and has been operated since 2004. However, there has been a disadvantage of providing specialized and limited information to the water resources sector mainly and a lack of active sharing of information because of no compulsory provision of information sharing between participants. In order to solve these problems, this paper carried out system development study, to do this, the status of domestic water information was surveyed and domestic and overseas related systems were compared and analyzed. The latest ICT technology was used to realize the contents as screen, and the user interface definition was created to present a role model of integrated water management through maximizing visualization by combining GIS and realtime data and providing space-time integrated information. These prior studies reached to actual construction of the ICT-based integrated management system for water information by K-water. This system is in service to the public installed in the water information portal, "MyWater".

• Korean Journal of Poultry Science
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• v.47 no.1
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• pp.9-19
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• 2020

Avian influenza (AI) viruses are highly contagious viruses that infect many bird species and are zoonotic. Ducks are resistant to the deadly and highly pathogenic avian influenza virus (HPAIV) and remain asymptomatic to the low pathogenic avian influenza virus (LPAIV). In this study, we identified common differentially expressed genes (DEGs) after a reanalysis of previous transcriptomic data for the HPAIV and LPAIV infected duck lung cells. Microarray datasets from a previous study were reanalyzed to identify common target genes from DEGs and their biological functions. A total of 731 and 439 DEGs were identified in HPAIV- and LPAIV-infected duck lung cells, respectively. Of these, 227 genes were common to cells infected with both viruses, in which 193 genes were upregulated and 34 genes were downregulated. Functional annotation of common DEGs revealed that translation related gene ontology (GO) terms were enriched, including ribosome, protein metabolism, and gene expression. REACTOME analyses also identified pathways for protein and RNA metabolism as well as for tissue repair, including collagen biosynthesis and modification, suggesting that AIVs may evade the host defense system by suppressing host translation machinery or may be suppressed before being exported to the cytosol for translation. AIV infection also increased collagen synthesis, showing that tissue lesions by virus infection may be mediated by this pathway. Further studies should focus on these genes to clarify their roles in AIV pathogenesis and their possible use in AIV therapeutics.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.3
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• pp.7-15
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• 2019

Cloud computing markets are rapidly growing as cost savings and business innovation are being carried out through ICT worldwide. In line with this paradigm, the nation is striving to introduce cloud computing in various areas, including the public sector and defense sector, through various research. In the defense sector, DIDC was established in 2015 by integrating military, naval, air and military computing centers, and it provides cloud services in the form of IaaS to some systems in the center. In DIDC and various future cloud defense systems, It is an important issue to ensure availability in cloud defense systems in the defense sector because system failures such as network delays and system resource failures are directly linked to the results of battlefields. However, ensuring the highest levels of availability for all systems in the defense cloud can be inefficient, and the efficiency that can be gained from deploying a cloud system can be reduced. In this paper, we classify and define the level of availability of defense cloud systems step by step, and propose the strategy of introducing Erasure coding and failure acceptance systems, and disaster recovery system technology according to each level of availability acquisition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.88-95
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• 2018

Maintainability indicates how easily a system can be restored to the normal state when a system failure occurs. Systems developed to have high maintainability can be competitive due to reduced maintenance time, workforce and resources. Quantification of the maintainability is possible in many ways, but only after prototype production or with historical data. As such, the graph theory and 3D model data have been used, but there are limitations in management efficiency and early use. To solve this problem, we studied the maintainability index of weapon systems using SysML-based modeling and simulation technique. A SysML structure diagram was generated to simultaneously model the system design and maintainability of system components by reflecting the maintainability attributes acquired from the system engineering tool. Then, a SysML parametric diagram was created to quantify the maintainability through simulation linked with MATLAB. As a result, an integrated model to account for system design and maintainability simultaneously has been presented. The model can be used from early design stages to identify components with low maintainability index. The design of such components can be changed to improve maintainability and thus to reduce the risks of cost overruns and time delays due to belated design changes.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.153-163
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• 2017

The objective of this study is to enhance the model's speed of estimating weather variables (e.g., minimum/maximum temperature, sunshine hour, PRISM (Parameter-elevation Regression on Independent Slopes Model) based precipitation), which are applied to the Agrometeorological Early Warning System (http://www.agmet.kr). The current process of weather estimation is operated on high-performance multi-core CPUs that have 8 physical cores and 16 logical threads. Nonetheless, the server is not even dedicated to the handling of a single county, indicating that very high overhead is involved in calculating the 10 counties of the Seomjin River Basin. In order to reduce such overhead, several cache and parallelization techniques were used to measure the performance and to check the applicability. Results are as follows: (1) for simple calculations such as Growing Degree Days accumulation, the time required for Input and Output (I/O) is significantly greater than that for calculation, suggesting the need of a technique which reduces disk I/O bottlenecks; (2) when there are many I/O, it is advantageous to distribute them on several servers. However, each server must have a cache for input data so that it does not compete for the same resource; and (3) GPU-based parallel processing method is most suitable for models such as PRISM with large computation loads.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.