• KIISE Transactions on Computing Practices
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• v.21 no.12
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• pp.774-779
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• 2015

In this paper, we present the design and implementation of a large-scale qualitative spatial reasoner using Apache Spark, an in-memory high speed cluster computing environment, which is effective for sequencing and iterating component reasoning jobs. The proposed reasoner can not only check the integrity of a large-scale spatial knowledge base representing topological and directional relationships between spatial objects, but also expand the given knowledge base by deriving new facts in highly efficient ways. In general, qualitative reasoning on topological and directional relationships between spatial objects includes a number of composition operations on every possible pair of disjunctive relations. The proposed reasoner enhances computational efficiency by determining the minimal set of disjunctive relations for spatial reasoning and then reducing the size of the composition table to include only that set. Additionally, in order to improve performance, the proposed reasoner is designed to minimize disk I/Os during distributed reasoning jobs, which are performed on a Hadoop cluster system. In experiments with both artificial and real spatial knowledge bases, the proposed Spark-based spatial reasoner showed higher performance than the existing MapReduce-based one.

• Geomechanics and Engineering
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• v.20 no.1
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• pp.19-28
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• 2020

The spatial variability of geotechnical properties can lead to the uncertainty of settlement for frozen soil foundation around the oil pipeline, and it can affect the stability of permafrost foundation. In this paper, the elastic modulus, cohesion, angle of internal friction and poisson ratio are taken as four independent random fields. A stochastic analysis model for the uncertain settlement characteristic of frozen soil foundation around an oil pipeline is presented. The accuracy of the stochastic analysis model is verified by measured data. Considering the different combinations for the coefficient of variation and scale of fluctuation, the influences of spatial variability of geotechnical properties on uncertain settlement are estimated. The results show that the stochastic effects between elastic modulus, cohesion, angle of internal friction and poisson ratio are obviously different. The deformation parameters have a greater influence on stochastic settlement than the strength parameters. The overall variability of settlement reduces with the increase of horizontal scale of fluctuation and vertical scale of fluctuation. These results can improve our understanding of the influences of spatial variability of geotechnical properties on uncertain settlement and provide a theoretical basis for the reliability analysis of pipeline engineering in permafrost regions.

• Journal of the Korean Geographical Society
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• v.41 no.3 s.114
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• pp.319-330
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• 2006

The objective of this research is to achieve an objectivity of site decision after extracting site decision factors on a large-scale discount store(LSDS) and utilize any hidden information using the association rules mining through huge database. To catch this objective, we collect a census, economic, and environmental dataset related with locating of LSDS. And then, we construct a spatial data on the research area. These data is used for the extraction of a spatial association rules. To verify whether the extracted rules are suitability or not, we use the sales of some LSDS. As the result of test, the more sales, the more factors of the extracted rules relate with the sales it coincides. Consequently, the spatial association rules mining is efficient method which support the ideal site decision of LSDS.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.37-43
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• 2022

Drones, one of the 4th industrial technologies that are expanding from military use to industrial use, are being actively used in the search missions of the National Police Agency and finding missing persons, thereby reducing interest in a wide area and the input of large-scale search personnel. However, legal review of police drone operation is continuously required, and the importance of advanced system for related operations and analysis of captured images in connection with search techniques is increasing at the same time. In this study, in order to facilitate recording, preservation, and monitoring in the concept of precise search and monitoring, it is possible to achieve high efficiency and secure golden time when precise search is performed by constructing spatial information based on photo rather than image data-based search. Therefore, we intend to propose a spatial information construction technique that reduces the resulting data volume by adjusting the unnecessary spatial information completion rate according to the size of the subject. Through this, the scope of use of drone search missions for large-scale areas is advanced and it is intended to be used as basic data for building a drone operation manual for police searches.

• Journal of the Korean housing association
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• v.10 no.2
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• pp.175-183
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• 1999

This study aims at modeling the compositional method in the architectural space and shape. The composition of space is composed of the position and the area in space. Therefore these elements are established to the functional program applied at the behavioral data. The element of spatial structure is position and scale in space, and the composition of spatial shape is developed repitionally to the combination of build-up method. The functional program is being expertised and the scale in building being lager, the importance of functional program is increased. Applied at data of the functional program at spatial structure, the process is developed to the method of combination. The purpose of this study is approached at the degree of application in modeling on the compositional method in architectural space and shape, which is a fundamental aspect on the quantitative analysis of architectural space.

• Journal of the Korean housing association
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• v.3 no.2
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• pp.13-19
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• 1992

The purpose of this study is to grasp spatial effects of colours in interior design. The visual feeling in the 1/10 living room scale models that are different in the colour combination of ceilings, walls and floors is judged using a semantic scale of the fifteen adjectives. The major findings are as follows; 1) As a result of factor analysis, three dimensions, "evaluation", "activity" and "warmness" are extracted. Dimension 1, "evaluation", is most greatly affected by the chroma and hue of the room colour, dimension 2, "activity", by the hue and value, by the difference in hue and value of ceilings, walls and floors, dimensions 3, "warmness", by mainly the hue of the rooms. 2) Concerning the spatial effects of colour, the subjects felt higher vlaue with relevance to the hue of GY, Y, low chroma and high value. The room colours other than walls is felt more comfortable in similar colour, especially hue and value.re comfortable in similar colour, especially hue and value.

• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.872-880
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• 2007

For effective management of sediment-related diffuse pollution, it is of utmost importance to estimate spatial variation of sediment transport processes within a catchment. A mathematical model can play a critical role in estimating sediment transport processes at the catchment scale provided that the model structure is appropriate for representing major sediment transport processes of the catchment of interest. This paper introduces a distributed catchment model River Basin Water Quality Simulator (RBWQS) and presents some results of its application to a small rural catchment in Korea. The model has been calibrated and validated for a wet period using hourly hydrographs and sediment concentrations observed at the catchment outlet. Based on the model simulation results, the spatial variation of sediment transport processes across the catchment and the effects of paddy fields and small reservoirs on hydrology and sediment transport have been analyzed at the catchment scale.

• Korean Journal of Agricultural Science
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• v.30 no.2
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• pp.139-147
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• 2003

The main purpose of this study is to obtain forest scenic beauty management informations toward forest working systems in pinus densiflora forest stands, etc. To get these information, visual preference and spatial image analysis methods are used. 25 different alternatives were simulated to visualize on basis of actual forest working methods with taken photos from May to July, 2003. The options were illustrated as photos produced by computer software. Respondents' ratings for 25 landscape scenes were obtained by interview survey method. Each alternatives were evaluated by forest major student group with total 103 respondents after reliability test. Visual preference evaluation was used 10 point rating scale. Spatial images of 12 alternatives were measured by 12 semantic differential scale. In general, the respondents preferred refreshing and ordering forest stand after forest working to natural forest stand before forest working. High visual preference for forest density produces 400-600 trees/ha in small diameter class forest stands. Regarding visual preference according to pavement type of trail, soil trail is ranked high. Visual preference for cutting area ranks mature forest stand and visual preference for trail slope cover type ranks shrub with grass as relatively high on the preference scale. Through the factor analysis, spatial images of 12 coniferous forest stands are classified as 'ordered opened' and 'beautiful healthy'. Results indicate how to conduct forest working systems for forest scenic beauty management.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.504-511
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• 2010

After facing the fact such as fossil-fuel depletion, global warming, the Kyoto Protocol coming into force of mandatory reductions of carbon dioxide, the world is actively promoting the spread of the solar, wind, tidal, geothermal and other clean renewable energy technology development. Among them, wind power is the only alternative energy to secure a comparable price competition with fossil fuels because cheaper price power generation than other renewable energy when creating large-scale wind farm, thus wind power is the fastest growing industries in the world in the renewable energy field. Especially the offshore wind power is showing rapid growth as most of the wind power sector because of less changes of wind speed, no restrictions of land use, and large-scale development of offshore wind power. In this paper, the field of site selection and spatial location analysis techniques for development of large-scale offshore wind farm are discussed primarily. This paper shows overview of offshore wind power and establishment procedure for development of offshore wind farm.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.371-371
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• 2011

본 연구에서는 한강유역 내 관측기간이 충분한 기상청 지상관측소 10개소를 선정하고 CCCma(Canadian Century for Climate modeling and analysis)에서 제공하는 자료에 대한 인공신경망기법 상세화 적용을 실시하였다. 인공신경망의 학습을 위해 CGCM3.1/T63 20C3M시나리오(reference scenario)의 22개 2D변수 중 물리적으로 민감도가 높다고 판단되는 GCM_Prec, huss, ps를 입력변수로 선정하였으며 인공신경망 학습기간은 1991년~1995년, 검증기간은 1996년~2000년, 예측기간은 2011년~2100년으로 A1B, A2 B1 시나리오 등 다양한 기후변화 시나리오를 통해 예측band를 제시하고자 하였다. 하지만 공간상관을 고려하기 위하여 각 관측소에 대하여 인공신경망 학습을 하는 경우 관측소간 spatial correlation 및 spatial cluster구현이 어렵기 때문에 Spatial Rectangular Pulse모형을 이용하고자 하였으나, 강수면적에 대한 scale의 결정이 어렵다는 단점을 확인 하고 본 연구에서는 Random Cascade 모형을 이용하여 ${\beta}$를 통한 강수면적 scale(rainy area fraction)을 결정하고자 하였다. Random Cascade모형의 기법은 격자단위의 downscaling기법으로 강수대의 공간적 형상을 재현하며 스케일에 비종속적인(scale-invariant)프랙탈 특성을 이용하여 매개변수를 최소화 할 수 있는 장점을 가진 기법으로 한강유역 1Km내외 강우장을 만들어 topographic effect를 첨가하고자 한다.