• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2008년도 춘계 종합학술대회 논문집
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• pp.892-896
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• 2008

도로, 철도 및 운하 등을 비롯한 각종 건설공사를 위해서는 건설공사의 기본설계과정에서 건설예정지에 대한 지형측량을 실시하고 이를 기초로 종 횡단면도의 제작이 필수적인 요소이다. 본 연구에서는 건설예정지에 대한 프로파일 제작에 있어 NGIS구축사업에 의해 제작된 수치지형도의 지형정보를 이용하여 정밀 3차원지형모델을 구축하고, 이로부터 자동 프로파일을 생성하여 종 횡단면도로 활용할 수 있는 방안을 제안하고자 하였다. 이를 위해 수치지형도로부터 표고 및 주요시설물의 레이어를 각각 추출하고 이를 이용하여 정밀 3차원 지형모델을 구축하는 한편, 3차원 지형모델로부터 자동 프로파일을 생성하여 종횡단면도를 제작하였다. 그리고 생성된 프로파일의 경로에 대하여 지형측량을 실시하여 상호 분석함으로써 자동 생성된 프로파일의 정확도가 현지측량 정확도와 허용정확도를 만족시킬 수 있는지의 여부를 검토하였다. 본 연구의 결과는 건설공사를 위해 실시되는 기본설계과정에서 설계기간의 단축, 설계비용의 감소와 설계업무의 효율화를 꾀할 수 있는 새로운 개념의 프로파일 생성기법으로 제안할 수 있을 것으로 사료된다.

• 한국자동차공학회논문집
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• 제12권5호
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• pp.162-170
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• 2004

In these days, a vehicle simulator is developed by using a VR(Virtual Reality) system. A VR system must provide a vehicle simulator with a natural interaction, a sufficient immersion and realistic images. To achieve this, it is important to provide a fast and uniform rendering performance regardless of the complexity of virtual worlds or the level of simulation. In this paper, modeling methods which offer an improved rendering performance for complex VR applications as 3D road model have been implemented and verified. The key idea of the methods is to reduce a load of VR system by means of LOD(Level of Detail), alpha blending texture mapping, texture mip-mapping and bilboard. Hence, in 3D road model where a simulation is complex or a scene is very large, the methods can provide uniform and acceptable frame rates. The VR system which is constructed with the methods has been experimented under the various application environments. It is confirmed that the proposed methods are effective and adequate to the VR system which associates with a vehicle simulator.

• Bulletin of the Korean Chemical Society
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• 제32권1호
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• pp.251-262
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• 2011

Human ether-a-go-go related gene (hERG) potassium channel blockade, an undesirable side effect which might cause sudden cardiac death, is one of the major concerns facing the pharmaceutical industry. The purpose of this study is to develop an in silico QSAR model which uncovers the structural parameters of T-type calcium channel blockers to reduce hERG blockade. Comparative molecular similarity indices analysis (CoMSIA) was conducted on a series of piperazine and benzimidazole derivatives bearing methyl 5-(ethyl(methyl)amino)-2-isopropyl-2-phenylpentanoate moieties, which was synthesized by our group. Three different alignment methods were applied to obtain a reliable model: ligand based alignment, pharmacophore based alignment, and receptor guided alignment. The CoMSIA model with receptor guided alignment yielded the best results : $r^2$ = 0.955, $q^2$ = 0.781, $r^2_{pred}$ = 0.758. The generated CoMSIA contour maps using electrostatic, hydrophobic, H-bond donor, and acceptor fields explain well the structural requirements for hERG nonblockers and also correlate with the lipophilic potential map of the hERG channel pore.

• 한국전자통신학회논문지
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• 제15권1호
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• pp.107-114
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• 2020

본 논문에서는 하둡 플랫폼에서 비용 효율적 빅데이터 분석을 수행하기 위한 클러스터 규모의 설정 방안을 연구한다. 의료기관의 경우 진료기록의 병원 외부 저장이 가능해짐에 따라 클라우드 기반 빅데이터 분석 요구가 증가하고 있다. 본 논문에서는 대중적으로 많이 사용되고 있는 클라우드 서비스인 아마존 EMR 프레임워크를 분석하고, 비용 효율적으로 하둡을 운용하기 위해 클러스터의 규모를 산정하기 위한 모델을 제시한다. 그리고, 다양한 조건에서의 실험을 통해 맵리듀스의 실행에 영향을 미치는 요인을 분석한다. 이를 통해 비용 대비 처리시간이 가장 효율적인 클러스터를 설정함으로써 빅데이터 분석시 효율성을 증대시킬 수 있다.

• 한국전자통신학회논문지
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• 제5권6호
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• pp.672-677
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• 2010

최근 대규모 센서 네트워크의 구축이 증가하면서 대규모의 센서 데이터를 효율적으로 관리하는 시스템이 요구되고 있다. 본 논문에서는 저비용, 높은 확장성 그리고 고 효율성을 지닌 클라우드 기반의 센서 데이터 관리 시스템을 제안한다. 제안된 시스템에서는 센서 데이터는 클라우드 게이트웨이를 통해 클라우드로 전송되며 이때 이상상황 검출과 이벤트 처리가 수행된다. 클라우드로 전송된 센서 데이터는 분산 컬럼 지향 데이터 베이스인 하둡 HBase에 저장되며 맵리듀스 모델 기반의 질의처리 모듈을 통해 병렬 처리된다. 처리된 결과는 REST 기반의 웹서비스를 통해 제공되므로 다양한 플랫폼의 응용프로그램과 연동이 가능하다.

• Journal of information and communication convergence engineering
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• 제15권4호
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• pp.217-226
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• 2017

Korea has the tenth largest film industry in the world; however, detailed analyses using the factors contributing to successful film commercialization have not been approached. Using big data, this paper analyzed both internal and external factors (including genre, release date, rating, and number of screenings) that contributed to the commercial success of Korea's top 10 ranking films in 2011-2015. The authors developed a WebCrawler to collect text data about each movie, implemented a Hadoop system for data storage, and classified the data using Map Reduce method. The results showed that the characteristic of "release date," followed closely by "rating" and "genre" were the most influential factors of success in the Korean film industry. The analysis in this study is considered groundwork for the development of software that can predict box-office performance.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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• pp.64-64
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• 2003

The aim of this study is to apply and verify of logistic regression at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database.13${\times}$1ure, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the logistic regression coefficient were overlaid for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 추계학술발표대회
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• pp.50-53
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• 2016

Image processing techniques play an increasingly important role in many aspects of our daily life. For example, it has been shown to improve agricultural productivity in a number of ways such as plant pest detecting or fruit grading. However, massive quantities of images generated in real-time through multi-devices such as remote sensors during monitoring plant growth lead to the challenges of big data. Meanwhile, most current image processing systems are designed for small-scale and local computation, and they do not scale well to handle big data problems with their large requirements for computational resources and storage. In this paper, we have proposed an IPABigData (Image Processing Algorithm BigData) platform which provides algorithms to support large-scale image processing in agriculture based on Hadoop framework. Hadoop provides a parallel computation model MapReduce and Hadoop distributed file system (HDFS) module. It can also handle parallel pipelines, which are frequently used in image processing. In our experiment, we show that our platform outperforms traditional system in a scenario of image segmentation.

• 디지털산업정보학회논문지
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• 제13권3호
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• pp.19-25
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• 2017

Nowadays, networked computer systems play an increasingly important role in our society and its economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason computer security has become an essential concern for network administrators. Recently, a number of Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. Therefore, probe detection has become a major security protection technology to detection potential attacks. Probe detection needs to take into account a variety of factors ant the relationship between the various factors to reduce false negative & positive error. It is necessary to develop new technology of probe detection that can find new pattern of probe. In this paper, we propose an hybrid probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) in dynamic environment such as Cloud and IoT. Also, in order to verify the proposed method, experiments about measuring detection rate in dynamic environments and possibility of countermeasure against intrusion were performed. From experimental results, decrease of false detection and the possibilities of countermeasures against intrusions were confirmed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권7호
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• pp.3470-3493
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• 2019

IEEE 802.11s-based infrastructure Wireless Mesh Networks (iWMNs) are envisaged as a promising solution to provide ubiquitous wireless Internet access. The limited network capacity is a problem mainly caused by the medium contention between mesh users and the mesh access points (MAPs), which gets worst when the mesh clients employ the Transmission Control Protocol (TCP). To mitigate this problem, we use wireless network coding (WNC) in the MAPs. The aim of this proposal is to take advantage of the network topology around the MAPs, to alleviate the contention and maximize the use of the network capacity. We evaluate WNC when is used in MAPs. We model the formation of coding opportunities and, using computer simulations, we evaluate the formation of such coding opportunities. The results show that as the users density grows, the coding opportunities increase up to 70%; however, at the same time, the coding delay increments significantly. In order to reduce such delay, we propose to adaptively adjust the time that a packet can wait to catch a coding opportunity in an MAP. We assess the performance of moving-average estimation methods to forecast this adaptive sojourn time. We show that using moving-average estimation methods can significantly decrease the coding delay since they consider the traffic density conditions.