• 정보과학회 논문지
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• 제43권9호
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• pp.963-973
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• 2016

대용량 미디어 온톨로지를 이용하여 의미 있는 지능형 서비스를 제공하기 위해 기존의 Axiom 추론뿐만 아니라 다양한 추론을 활용하는 지식 확장이 요구되고 있다. 특히 시공간 정보는 인공지능 응용분야에서 중요하게 활용될 수 있고, 시공간 정보의 표현과 추론에 대한 중요도는 지속적으로 증가하고 있다. 따라서 본 논문에서는 공간 정보를 추론에 활용하기 위해서 공공 주소체계에 대한 LOD를 대용량 미디어 온톨로지에 추가하고, 이러한 대용량 데이터 처리를 위해 인메모리 기반의 분산 처리 프레임워크를 활용하는 공간 추론을 포함하는 RDFS 추론 시스템을 제안한다. 또한 추론을 통해 확장된 데이터를 포함하는 대용량 온톨로지 데이터를 대상으로 하는 분산 병렬 시공간 SPARQL 질의 처리 방법에 대해서 설명한다. 제안하는 시스템의 성능을 측정하기 온톨로지 추론과 질의 처리 벤치 마킹을 위한 LUBM과 BSBM 데이터셋을 대상으로 실험을 진행했다.

• Wind and Structures
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• 제14권3호
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• pp.221-238
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• 2011

The estimated response of large-scale engineering structures to severe wind loads is prone to modelling uncertainties that can only ultimately be assessed by full-scale testing. To this end ambient vibration data from full-scale monitoring of the historic Clifton Suspension Bridge has been analysed using a combination of a frequency domain system identification method and a more elaborate stochastic identification technique. There is evidence of incipient coupling action between the first vertical and torsional modes in strong winds, providing unique full-scale data and making this an interesting case study. Flutter derivative estimation, which has rarely previously been attempted on full-scale data, was performed to provide deeper insight into the bridge aerodynamic behaviour, identifying trends towards flutter at higher wind speeds. It is shown that, as for other early suspension bridges with bluff cross-sections, single-degree-of-freedom flutter could potentially occur at wind speeds somewhat below requirements for modern designs. The analysis also demonstrates the viability of system identification techniques for extracting valuable results from full-scale data.

• 천문학회지
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• 제46권1호
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• pp.33-40
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• 2013

We investigate the dependence of the extended X-ray emission from the halos of optically luminous early-type galaxies on the small-scale (the nearest neighbor distance) and large-scale (the average density inside the 20 nearest galaxies) environments. We cross-match the 3rd Data Release of the Second XMMNewton Serendipitous Source Catalog (2XMMi-DR3) to a volume-limited sample of the Sloan Digital Sky Survey (SDSS) Data Release 7 with $M_r$ < -19.5 and 0.020 < z < 0.085, and find 20 early-type galaxies that have extended X-ray detections. The X-ray luminosity of the galaxies is found to have a tighter correlation with the optical and near infrared luminosities when the galaxy is situated in the low large-scale density region than in the high large-scale density region. Furthermore, the X-ray to optical (r-band) luminosity ratio, $L_X/L_r$, shows a clear correlation with the distance to the nearest neighbor and with large-scale density environment only where the galaxies in pair interact hydrodynamically with seperations of $r_p$ < $r_{vir}$. These findings indicate that the galaxies in the high local density region have other mechanisms that are responsible for their halo X-ray luminosities than the current presence of a close encounter, or alternatively, in the high local density region the cooling time of the heated gas halo is longer than the typical time between the subsequent encounters.

• Ocean Systems Engineering
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• 제4권4호
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• pp.309-325
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• 2014

Geotextile tubes are basically a huge sack filled with sand or dredged soil. Geotextile tubes are made of permeable woven or non-woven synthetic fibers (i.e., polyester or PET and polypropylene or PP). The geotextile tubes' performances in strength, dewatering, retaining solid particles and stacked stability have been studied extensively in the past. However, only little research has been done in the observation of the deformation behavior of geotextile tubes. In this paper, a large-scale apparatus for geotextile tube experiment is introduced. The apparatus is equipped with a slurry mixing station, pumping and delivery station, an observation station and a data station. For this study the large-scale apparatus was utilized in the studies regarding the stresses on the geotextile and the deformation behavior of the geotextile tube. Model tests were conducted using a custom-made woven geotextile tubes. Load cells placed at the inner belly of the geotextile tube to monitor the total soil pressure. Strain gauges were also placed on the outer skin of the tube to measure the geotextile strain. The pressure and strain sensors are attached to a data logger that sends the collected data to a desktop computer. The experiment results showed that the maximum geotextile strain occurs at the sides of the tube and the soil pressure distribution varies at each geotextile tube section.

• 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.

• 정보과학회 논문지
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• 제41권12호
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• pp.1126-1135
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• 2014

최근 대규모 RDF 데이터를 효과적으로 분산 저장 및 관리하기 위해 RDF 분할 기법의 연구가 진행되고 있다. 본 논문에서는 지속적으로 데이터의 추가 및 변경이 발생하는 동적 환경에서 부하 분산을 지원하는 RDF 동적 분할 기법을 제안한다. 제안하는 기법은 그래프 분할을 수행하기 위한 기준으로 질의에 의해 사용된 RDF 데이터의 사용 빈도에 따라 클러스터와 서브 클러스터 그룹을 생성한다. 생성된 클러스터와 서브 클러스터는 분산된 서버의 부하 및 저장되는 데이터 크기를 고려하여 분할을 수행한다. 이를 통해 지속적인 데이터 변경 및 추가로 인해 특정 서버에 대한 데이터 집중을 해결하고 서버들간에 효율적인 부하 분산을 수행한다. 성능평가를 통하여 분산 서버에서 제안하는 기법이 기존 분할 기법에 비해 질의 수행 시간이 크게 향상됨을 보인다.

• International Journal of Contents
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• 제16권4호
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• pp.16-25
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• 2020

The size of observation data in astronomy has been increasing exponentially with the advents of wide-field optical telescopes. This means the needs of changes to the way used for large-scale astronomy data analysis. The complexity of analysis tools and the lack of extensibility of computing environments, however, lead to the difficulty and inefficiency of dealing with the huge observation data. To address this problem, this paper proposes a workflow execution system for analyzing large-scale astronomy data efficiently. The proposed system is composed of two parts: 1) a workflow execution manager and its RESTful endpoints that can automate and control data analysis tasks based on workflow templates and 2) an elastic resource manager as an underlying mechanism that can dynamically add/remove virtualized computing resources (i.e., virtual machines) according to the analysis requests. To realize our workflow execution system, we implement it on a testbed using OpenStack IaaS (Infrastructure as a Service) toolkit and HTCondor workload manager. We also exhaustively perform a broad range of experiments with different resource allocation patterns, system loads, etc. to show the effectiveness of the proposed system. The results show that the resource allocation mechanism works properly according to the number of queued and running tasks, resulting in improving resource utilization, and the workflow execution manager can handle more than 1,000 concurrent requests within a second with reasonable average response times. We finally describe a case study of data reduction system as an example application of our workflow execution system.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1374-1376
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• 2003

NASA, NSF and USGS jointly conducted a LIDAR survey over several sites in the Antarctic Dry Valleys and its vicinity, acquiring numerous surface points by NASA's Airborne Topographic Mapper (ATM) conical laser scanning altimetry system. The data set have high blunder ratio, and the conical scanning pattern resulted large variation of the point densities. Hence, to reduce the undesirable effects due to these characteristics and process the huge number of points with reasonable time and resources, we developed a novel approach to generate large-scale and high-resolution DEMs in robust, efficient and nearly automatic manners. Based on this approach we produced DEMs and then verified them with reference data.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1233-1235
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• 2003

We are studying large-scale irrigation projects of 100,000 ha to 1,000,000 ha in the world with emphasis on their historical courses of development, geographical conditions, water managements, planting conditions and landuse changes. Recent advancement in GIS/remote sensing techniques has enabled us to proceed studies in this field in more details. Here, we describe the results of analysis on distribution of irrigation canals, three-dimensional shape of the irrigation area and planting conditions of agricultural products investigated last year in Gezira irrigation project, Sudan, using Landsat 7 ETM data and DEM supplied by USGS.

• 천문학회지
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• 제29권spc1호
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• pp.23-24
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• 1996

We reexamined CDM texture large-scale structure (LSS) formation model. We confirmed that texture model is consistent with 4-year COBE data both in an open and a critical matter density (${\Omega}_0$ = 1) universes, and then obtained normalization for density perturbation power spectrum. We next compare the power spectrum with LSS observation data. Contrary to the previous literature, we found that texture model matches with these data in an open universe no better than in an ${\Omega}_0$ = 1 universe. We also found that the model is more likely to fit these data in a cosmological constant dominated ($\Lambda-$) universe.